{"cells":[{"cell_type":"markdown","metadata":{"id":"YIteW5YWUfbP", "nbsphinx-toctree": {}},"source":["#A Comprehensive Toolkit for Protein-Ligand Interactions"]},{"cell_type":"markdown","metadata":{"id":"IUVrNy82Wlsm"},"source":["* **BsiteP** - predicts protein binding site\n","* **NuriKit** - generates 3D general (non-macrocyclic) ligand conformations\n","* **GDDL** - predicts protein-ligand binding poses When the protein and ligand engage in typical (non-covalent) interactions\n","* **BindingRMSD** - predicts protein-ligand binding poses RMSD\n","\n","\n","\n"]},{"cell_type":"markdown","metadata":{"id":"fpxoD9mabQvs"},"source":["#Section 0: Fetching and installing the required software"]},{"cell_type":"markdown","metadata":{"id":"-kbBIathb7T7"},"source":["Please keep in mind that Google Colab requires **a few minutes to initialize the hosted runtime** at the beginning.\n","\n","Before starting the toolkit, we need to download the necessary software. The types are as follows:\n","\n","\n","* **py3Dmol** - helps to visualize protein or ligand structures\n","* **openbabel_wheel** - helps interconversion of chemical file formats, molecular structure manipulation, and cheminformatics tasks.\n","* **rdkit** - helps representing, manipulating, and analyzing chemical structures\n","* **prolif** - helps analyze protein-ligand interactions\n","* **MDAnalysis** - allows for efficient handling of the structures of the protein and ligand\n","* **torch_*** - extends PyTorch's capabilities for operations on tensors ( * includes geometric, scatter, cluster)\n","* **DGL** - simplifies deep learning on graph-structured data, providing efficient tools for building graph neural networks\n","\n","\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"collapsed":true,"id":"PaErakUL2WiK"},"outputs":[],"source":["%%capture\n","! pip install py3Dmol\n","! pip install openbabel_wheel\n","! pip install rdkit\n","! pip install prolif\n","! pip install MDAnalysis\n","! pip install torch_geometric\n","! pip install dgl -f https://data.dgl.ai/wheels/torch-2.4/cu121/repo.html"]},{"cell_type":"markdown","metadata":{"id":"8xLPZxcYiYFg"},"source":[" Then, download the toolkit code stored in the GitHub repository"]},{"cell_type":"code","execution_count":null,"metadata":{"collapsed":true,"id":"7cto1uEPiW0z"},"outputs":[],"source":["%%capture\n","# Install BsiteP\n","! git clone https://github.com/ding-oh/BsiteP\n","# Install BindingRMSD\n","! git clone https://github.com/eightmm/BindingRMSD\n","# Install NuriKit\n","! pip install nurikit\n","# Install GDDL\n","! git clone https://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@github.com/seoklab/colab_gd_dl.git\n","%cd /content/colab_gd_dl\n","! pip install -e ."]},{"cell_type":"markdown","metadata":{"id":"foEyShgEiILz"},"source":["Now, we are ready to use the toolkit."]},{"cell_type":"markdown","metadata":{"id":"cLBhcmOUjd8f"},"source":["#Section 1: Generating 3D conformations for two ligands using \"nurikit\"\n","* 1D SMILES for ligand 1 (drug name):\n","* 1D SMILES for ligand 2 (drug name):"]},{"cell_type":"markdown","metadata":{"id":"JdF4mKKZPnOC"},"source":["#1-0. Choose whether the docking method is covalent or non-covalent#"]},{"cell_type":"markdown","metadata":{"id":"zld-_iuZ2yLh"},"source":["If you select general (non-covalent) docking in this, proceed to 1-1.\n","\n","If you select covalent docking, proceed to 1-2. This choice will also be reflected when selecting a docking tool later."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"7LBCtSCO2vXd"},"outputs":[],"source":["#@title ##Selecting docking mode (covalent or non-covalent)\n","whether_covalent_docking_or_not = \"non-covalent\" #@param [\"covalent\", \"non-covalent\"]\n","#@markdown - If the protein and ligand are connected by a covalent bond, select covalent; otherwise, non-covalent."]},{"cell_type":"markdown","metadata":{"id":"_PrS0bAyPtCj"},"source":["#1-1. For non-covalent docking#"]},{"cell_type":"markdown","metadata":{"id":"I34SeKg9lXmq"},"source":["**If you are going to use covalent docking tool (C-Dock), Please skip this section and go to 1-2, please.**\n","\n","Please provide **the SMILES format of the molecule** you want to convert into a 3D conformation. **NuriKit** will quickly generate the ligand structure. If checking the **show_ligand_3D_conformation**, you can visually inspect the 3D structure of the molecule."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"otmfQeRJ5w3u","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1736738845767,"user_tz":-540,"elapsed":332,"user":{"displayName":"­최자윤 / 학생 / 화학부","userId":"06915946716678996990"}},"outputId":"6d1e7d10-e7fd-4442-8cd1-a45825eed7de"},"outputs":[{"output_type":"stream","name":"stdout","text":["/content/iitp_demonstrate\n"]}],"source":["#@title Ligand input\n","\n","import nuri.algo\n","from pathlib import Path\n","import nuri.algo\n","from openbabel import pybel\n","import py3Dmol\n","import os\n","from rdkit import Chem\n","from rdkit.Chem import AllChem\n","\n","target_dir = f'/content/iitp_demonstrate/'\n","os.makedirs(target_dir, exist_ok=True)\n","\n","%cd '/content/iitp_demonstrate//'\n","SMILES = \"c1(c(cc2c(c1)c(ncn2)Nc1cc(c(cc1)F)Cl)OC)NC(=O)CCCN\" #@param {type:\"string\"}\n","#@markdown - Please provide the SMILES format of the ligand to be used for protein-ligand docking\n","mol = next(nuri.readstring(\"smi\", SMILES))\n","nuri.algo.generate_coords(mol)\n","Path(\"ligand_input.mol2\").write_text(nuri.to_mol2(mol))\n","\n","show_ligand_3D_conformation = True #@param {type:\"boolean\"}\n"]},{"cell_type":"markdown","metadata":{"id":"3XLlfjPbvzEo"},"source":["Hydrogens are added and charges are assigned to the generated structure."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Ky_7lpgcxwhe"},"outputs":[],"source":["mol = next(pybel.readfile(\"mol2\", \"ligand_input.mol2\"))\n","mol.addh()\n","mol.calccharges(\"gasteiger\")\n","mol.write(\"mol2\", \"ligand_charged.mol2\", overwrite=True)"]},{"cell_type":"markdown","metadata":{"id":"zJvZcp8X1lBu"},"source":["The unnecessary parts are removed from the ligand file."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"q12WqSh71kt_"},"outputs":[],"source":["wrt = []\n","write = True\n","with open('ligand_charged.mol2') as fp:\n"," for line in fp:\n"," if line == '@UNITY_ATOM_ATTR\\n':\n"," write = False\n"," if line == '@BOND\\n':\n"," write = True\n"," if write:\n"," wrt.append(line)\n","fout= open('ligand_charged.mol2', 'wt')\n","fout.writelines(wrt)\n","fout.close()"]},{"cell_type":"markdown","metadata":{"id":"c6lJup7AyJr9"},"source":["If checking the show_ligand_3D_conformation above, you can visualize the 3D structure of the molecule."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"hdwB5U-Cx1Hn","colab":{"base_uri":"https://localhost:8080/","height":451},"executionInfo":{"status":"ok","timestamp":1736738154257,"user_tz":-540,"elapsed":411,"user":{"displayName":"­최자윤 / 학생 / 화학부","userId":"06915946716678996990"}},"outputId":"81480a19-02c2-4548-fe63-7d2a80f87ebd"},"outputs":[{"output_type":"stream","name":"stdout","text":["\n","\u001b[1m\u001b[0m\n"]},{"output_type":"display_data","data":{"application/3dmoljs_load.v0":"
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약학과","userId":"17104096532647650828"}},"outputId":"27dd51b0-462a-46bf-a33b-79d009deb6fa"},"outputs":[{"output_type":"display_data","data":{"text/plain":[""],"application/javascript":["\n"," async function download(id, filename, size) {\n"," if (!google.colab.kernel.accessAllowed) {\n"," return;\n"," }\n"," const div = document.createElement('div');\n"," const label = document.createElement('label');\n"," label.textContent = `Downloading \"${filename}\": `;\n"," div.appendChild(label);\n"," const progress = document.createElement('progress');\n"," progress.max = size;\n"," div.appendChild(progress);\n"," document.body.appendChild(div);\n","\n"," const buffers = [];\n"," let downloaded = 0;\n","\n"," const channel = await google.colab.kernel.comms.open(id);\n"," // Send a message to notify the kernel that we're ready.\n"," channel.send({})\n","\n"," for await (const message of channel.messages) {\n"," // Send a message to notify the kernel that we're ready.\n"," channel.send({})\n"," if (message.buffers) {\n"," for (const buffer of message.buffers) {\n"," buffers.push(buffer);\n"," downloaded += buffer.byteLength;\n"," progress.value = downloaded;\n"," }\n"," }\n"," }\n"," const blob = new Blob(buffers, {type: 'application/binary'});\n"," const a = document.createElement('a');\n"," a.href = window.URL.createObjectURL(blob);\n"," a.download = filename;\n"," div.appendChild(a);\n"," a.click();\n"," div.remove();\n"," }\n"," "]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":[""],"application/javascript":["download(\"download_61bd0554-f291-41e7-aef2-8c5925ae2a26\", \"ligand_charged.mol2\", 5408)"]},"metadata":{}}],"source":["from google.colab import files\n","\n","output_file = 'ligand_charged.mol2'\n","files.download(output_file)"]},{"cell_type":"markdown","metadata":{"id":"296LMXlqR5Za"},"source":["# Section 2: Finding binding pockets for a given protein (EGFR) using \"BsiteP\" #\n","\n","---"]},{"cell_type":"markdown","metadata":{"id":"8BjEsY5OWNjH"},"source":["## Benchmarking results of binding site prediction method\n","------\n","We benchmarked our **binding site prediction method** on widely used binding site benchmark sets: **COACH420** and **BU48**.\n","\n","The success rate of binding site predictions are generally measured by two metrics: **DCC** and **DCA**.\n","\n","**DCC** measures if the **distance between the centers** of mass of ligand and ligand binding site residues are less than a given cutoff distance.\n","\n","**DCA** is measures if the **distance between the any heavy atoms** of a ligand and ligand binding site residues are less than a given cutoff distance.\n","\n","Thus, DCA is easier to satify than DCC.\n","\n","The plots below show that our method achived high accuracy in binding site predictions.\n","\n","With the COACH420 benchmark set, our method achieved an accuracy of **DCC > 65%** and **DCA > 90%**.\n","\n","With the BU48 benchmark set, our method achieved an accuracy of **DCC > 70%** and **DCA > 93%**.\n","\n","\n"]},{"cell_type":"markdown","metadata":{"id":"UaGqmyqIz78V"},"source":["![](https://drive.google.com/uc?export=view&id=1UOoKwkf9DqOgTAi8ATMDpt0xJ7CNWOth)\n","\n","![](https://drive.google.com/uc?export=view&id=1WONik6TYbkIK6uFB536RjEN4zqXHEkEV)\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"eXh9yVVfoByR"},"outputs":[],"source":["#@title Setting up enviroments\n","%%capture\n","import sys\n","import os\n","\n","if os.path.basename(os.getcwd()) != \"BsiteP\":\n"," bsitep_path = \"/content/BsiteP\"\n"," if os.path.exists(bsitep_path):\n"," os.chdir(bsitep_path)\n"," print(f\"Changed directory to: {os.getcwd()}\")\n"," else:\n"," print(\"Error: BsiteP directory does not exist in the current path.\")\n","else:\n"," print(f\"Already in BsiteP directory: {os.getcwd()}\")\n","\n","import torch\n","from openbabel import pybel\n","from utils.model_utils import load_model\n","from utils.pocket_utils import save_pocket_mol\n","from utils.data_utils import prepare_data\n","import glob\n","\n","from collections import OrderedDict\n","from SEResnet import SEResNet\n","\n","# Check device availability\n","device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n","\n","model = SEResNet().to(device)\n","model_path = f\"./ckpt/model0.pth\"\n","\n","state_dict = torch.load(model_path, map_location=device)\n","new_dict = OrderedDict((key[7:], value) for key, value in state_dict.items())\n","model.load_state_dict(new_dict)\n","model.to(device)\n","\n","model.eval()\n","print(f\"Model loaded successfully. - using device: {device}\")"]},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"id":"tjkyLAuRELh0","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1736738257529,"user_tz":-540,"elapsed":59847,"user":{"displayName":"­최자윤 / 학생 / 화학부","userId":"06915946716678996990"}},"outputId":"0e68d005-6273-4ea4-f43f-40850ff490fc"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"code","execution_count":null,"metadata":{"id":"1ICrvT30oBt5","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1736738271741,"user_tz":-540,"elapsed":1792,"user":{"displayName":"­최자윤 / 학생 / 화학부","userId":"06915946716678996990"}},"outputId":"647dae83-0483-4910-f56f-dbad493236a3"},"outputs":[{"output_type":"stream","name":"stdout","text":["Downloading PDB ID: 4i24\n","./example/4i24/protein.pdb\n","./example/4i24/ligand.pdb\n","PDB ID 4i24 processed and saved in directory: ./example/4i24\n"]}],"source":["import os\n","import requests\n","\n","input_path = \"./example\"\n","output_path = \"./output/example\"\n","file_format = \"pdb\"\n","\n","os.makedirs(input_path, exist_ok=True)\n","os.makedirs(output_path, exist_ok=True)\n","\n","#@markdown - We present two options. The first is to download the pdb file from RCSB PDB and the second is to upload it to mydrive. Then, the prepared files are processed and placed in 'example'\n","#@markdown - Please provide the PDB ID or your PDB file.\n","\n","Download_PDB = \"4i24\" # @param {type:\"string\"}\n","#@markdown - Download PDB file from RCSB PDB and process the downloaded pdb.\n","\n","\n","Uploaded_pdb_path = \"/content/drive/MyDrive/your_pdb_file.pdb\" # @param {type:\"string\"}\n","#@markdown - Please place your PDB file at '/content/drive/MyDrive/.\n","#@markdown - Process the uploaded pdb file from mydrive as '/example/{pdb_id}/protein.pdb'.\n","\n","Target_chain = \"ALL\" # @param {type:\"string\"}\n","#@markdown - Target Chain (ex: A, B, C ...)\n","\n","#@markdown - 시연 코드는 RCSB PDB로부터 2QEH을 받아서 사용함.\n","\n","\n","base_output_dir = \"./example\"\n","\n","def find_pdb_id(pdb_lines):\n"," for line in pdb_lines:\n"," if line.startswith(\"HEADER\"):\n"," return line[62:66].strip() # PDB ID is typically at these positions in HEADER line\n"," return None # Return None if no HEADER line with PDB ID is found\n","\n","def process_pdb_file(pdb_lines, chain, output_dir):\n"," protein_path = os.path.join(output_dir, \"protein.pdb\")\n"," ligand_path = os.path.join(output_dir, \"ligand.pdb\")\n"," with open(protein_path, 'w') as protein_file, open(ligand_path, 'w') as ligand_file:\n"," for line in pdb_lines:\n"," if line.startswith(\"ATOM\"):\n"," if chain.upper() == \"ALL\" or f\" {chain} \" in line:\n"," protein_file.write(line + \"\\n\") # Write ATOM lines for the selected chain\n"," elif line.startswith(\"HETATM\"):\n"," if not (\" DMS \" in line or \" HOH \" in line):\n"," ligand_file.write(line + \"\\n\") # Write HETATM lines excluding DMS and HOH\n"," print(protein_path)\n"," print(ligand_path)\n","\n","def handle_pdb_file(path, chain):\n"," with open(path, 'r') as file:\n"," pdb_lines = file.readlines()\n"," pdb_id = find_pdb_id(pdb_lines) or \"Unknown\"\n"," output_dir = os.path.join(base_output_dir, pdb_id)\n"," os.makedirs(output_dir, exist_ok=True)\n"," process_pdb_file(pdb_lines, chain, output_dir)\n"," print(f\"PDB processed and saved in directory: {output_dir}\")\n","\n","if Uploaded_pdb_path != \"/content/drive/MyDrive/your_pdb_file.pdb\":\n"," if os.path.exists(Uploaded_pdb_path):\n"," handle_pdb_file(Uploaded_pdb_path, Target_chain)\n"," else:\n"," print(f\"Warning: The file at '{Uploaded_pdb_path}' does not exist. Please check the path and ensure the file is correctly placed.\")\n","\n","# Download and process from PDB ID if no uploaded file is processed\n","elif Download_PDB:\n"," output_dir = os.path.join(base_output_dir, Download_PDB)\n"," os.makedirs(output_dir, exist_ok=True)\n"," protein_path = os.path.join(output_dir, \"protein.pdb\")\n"," ligand_path = os.path.join(output_dir, \"ligand.pdb\")\n"," print(f\"Downloading PDB ID: {Download_PDB}\")\n"," url = f\"https://files.rcsb.org/download/{Download_PDB}.pdb\"\n"," response = requests.get(url)\n"," if response.status_code == 200:\n"," pdb_lines = response.text.splitlines()\n"," process_pdb_file(pdb_lines, Target_chain, output_dir)\n"," print(f\"PDB ID {Download_PDB} processed and saved in directory: {output_dir}\")\n"," else:\n"," print(f\"Failed to download PDB file {Download_PDB}. Status code: {response.status_code}\")\n","else:\n"," print(\"No valid PDB file provided or found.\")\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"NXU7coJYoBrq"},"outputs":[],"source":["#@title Visualizing predicted binding site with native ligand\n","%%capture\n","\n","import os\n","from py3Dmol import view\n","\n","def read_pdb_as_string(file_path):\n"," \"\"\"Read the PDB file content as a string.\"\"\"\n"," with open(file_path, 'r') as file:\n"," return file.read()\n","\n","def visualize_molecules(protein_path, ligand_path=None, pocket_paths=None, label_residues=False):\n"," \"\"\"\n"," Visualizes the protein, ligand, and predicted pockets using Py3Dmol.\n"," Adds residue labels with residue names and numbers for the pockets if `label_residues` is True.\n"," \"\"\"\n"," try:\n"," viewer = view(width=1200, height=800)\n","\n"," # Add protein\n"," protein_data = read_pdb_as_string(protein_path)\n"," if protein_data:\n"," viewer.addModel(protein_data, 'pdb')\n"," viewer.setStyle({'model': 0}, {'cartoon': {'color': 'white'}})\n","\n"," # Add ligand\n"," if ligand_path and os.path.exists(ligand_path):\n"," ligand_data = read_pdb_as_string(ligand_path)\n"," viewer.addModel(ligand_data, 'pdb')\n"," viewer.setStyle({'model': 1}, {'stick': {'radius': 0.3, 'color': 'red'}})\n","\n"," # Add pockets and optionally label residues\n"," if pocket_paths:\n"," pocket_path = pocket_paths[0]\n"," if os.path.exists(pocket_path):\n"," pocket_data = read_pdb_as_string(pocket_path)\n"," viewer.addModel(pocket_data, 'pdb')\n"," viewer.setStyle({'model': 2 + i}, {'sphere': {'opacity': 0.4, 'color': 'blue'}})\n","\n"," if label_residues:\n"," # Extract residues and label them\n"," lines = pocket_data.splitlines()\n"," for line in lines:\n"," if line.startswith(\"ATOM\") or line.startswith(\"HETATM\"):\n"," residue_name = line[17:20].strip()\n"," residue_number = line[22:26].strip()\n"," chain_id = line[21].strip()\n"," viewer.addLabel(\n"," f\"{residue_name} {residue_number}\",\n"," {\n"," 'position': {\n"," 'x': float(line[30:38].strip()),\n"," 'y': float(line[38:46].strip()),\n"," 'z': float(line[46:54].strip())\n"," },\n"," 'backgroundColor': 'white',\n"," 'fontColor': 'black',\n"," 'fontSize': 10\n"," },\n"," {'chain': chain_id, 'resi': int(residue_number)}\n"," )\n","\n"," # Adjust view\n"," viewer.zoomTo()\n"," viewer.show()\n"," except Exception as e:\n"," print(f\"An error occurred during visualization: {e}\")"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"w0HfnxWVoBns","colab":{"base_uri":"https://localhost:8080/","height":817},"executionInfo":{"status":"ok","timestamp":1736738299223,"user_tz":-540,"elapsed":1112,"user":{"displayName":"­최자윤 / 학생 / 화학부","userId":"06915946716678996990"}},"outputId":"32ce7bf9-824e-42d5-ef8c-de327da902a9"},"outputs":[{"output_type":"display_data","data":{"application/3dmoljs_load.v0":"
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\n","
\n",""]},"metadata":{}}],"source":["visualize_molecules(protein_path)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"-oyMLZXjoBld"},"outputs":[],"source":["#@title Preparing Input Data\n","%%capture\n","input_path = \"./example\"\n","output_path = \"./output/example\"\n","file_format = \"pdb\"\n","\n","# Prepare input data\n","\n","!rm -rf /content/BsiteP/example/.ipynb_checkpoints\n","\n","input_data = prepare_data(input_path, file_format)\n","print(f\"Prepared {len(input_data)} input samples.\")\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"88R3yZWvoBd_"},"outputs":[],"source":["#@title Predicting Binding Pockets\n","%%capture\n","pocket_paths = []\n","\n","for i, data in enumerate(input_data):\n"," input_tensor, origin, step, name, mol_paths = data\n"," mol = next(pybel.readfile(file_format, mol_paths[0]))\n"," input_tensor = input_tensor.to(device)\n"," # Perform inference\n"," with torch.no_grad():\n"," output = model(input_tensor)\n","\n"," # Save predicted pockets\n"," pockets, score = save_pocket_mol(output.cpu(), origin[0], step[0], mol, dist_cutoff=1.5)\n","\n"," print(pockets)\n","\n"," # Save pocket files\n"," for j, pocket in enumerate(pockets):\n"," folder_name = os.path.join(output_path, str(name).split(\"'\")[1])\n"," os.makedirs(folder_name, exist_ok=True)\n","\n"," pocket_filename = os.path.join(folder_name, f\"pocket{j}.{file_format}\")\n"," pocket.write(file_format, pocket_filename, overwrite=True)\n"," pocket_paths.append(pocket_filename)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"I5WDYyYLo85u","cellView":"form"},"outputs":[],"source":["#@title Predicting Binding Pockets\n","\n","import pandas as pd\n","\n","\n","AA_3TO1 = {\n"," \"ALA\": \"A\", \"ARG\": \"R\", \"ASN\": \"N\", \"ASP\": \"D\", \"CYS\": \"C\",\n"," \"GLN\": \"Q\", \"GLU\": \"E\", \"GLY\": \"G\", \"HIS\": \"H\", \"ILE\": \"I\",\n"," \"LEU\": \"L\", \"LYS\": \"K\", \"MET\": \"M\", \"PHE\": \"F\", \"PRO\": \"P\",\n"," \"SER\": \"S\", \"THR\": \"T\", \"TRP\": \"W\", \"TYR\": \"Y\", \"VAL\": \"V\"\n","}\n","\n","def parse_coords(file):\n"," coords = {}\n"," try:\n"," with open(file, 'r') as f:\n"," for line in f:\n"," if line.startswith(\"ATOM\"):\n"," res = line[17:20].strip()\n"," chain = line[21].strip()\n"," res_id = int(line[22:26].strip())\n"," x, y, z = map(float, (line[30:38].strip(), line[38:46].strip(), line[46:54].strip()))\n"," if res in AA_3TO1:\n"," coords[(x, y, z)] = (res_id, chain, AA_3TO1[res])\n"," except FileNotFoundError:\n"," print(\"Failed : Model can not found any binding site.\")\n"," return coords\n","\n","def match_residues(pocket_file, protein_coords):\n"," pocket_coords = parse_coords(pocket_file)\n"," return {protein_coords[pc][0] for pc in pocket_coords if pc in protein_coords}\n","\n","def calculate_center(pocket_file):\n"," coords = []\n"," try:\n"," with open(pocket_file, 'r') as f:\n"," for line in f:\n"," if line.startswith(\"ATOM\"):\n"," x, y, z = map(float, (line[30:38].strip(), line[38:46].strip(), line[46:54].strip()))\n"," coords.append((x, y, z))\n"," if coords:\n"," x_mean = sum(c[0] for c in coords) / len(coords)\n"," y_mean = sum(c[1] for c in coords) / len(coords)\n"," z_mean = sum(c[2] for c in coords) / len(coords)\n"," return x_mean, y_mean, z_mean\n"," except FileNotFoundError:\n"," pass\n"," return None, None, None\n","\n","def parse_sequence(file):\n"," chains = {}\n"," with open(file, 'r') as f:\n"," for line in f:\n"," if line.startswith(\"ATOM\"):\n"," res = line[17:20].strip()\n"," chain = line[21].strip()\n"," res_id = int(line[22:26].strip())\n"," if res in AA_3TO1:\n"," chains.setdefault(chain, {})[res_id] = AA_3TO1[res]\n"," return chains\n","\n","def generate_seqs(chains, matches):\n"," full_seqs = {}\n"," highlight_seqs = {}\n"," for c, residues in chains.items():\n"," full_seqs[c] = ''.join(residues[rid] for rid in sorted(residues))\n"," highlight_seqs[c] = ''.join(residues[rid] if rid in matches else '-' for rid in sorted(residues))\n"," return full_seqs, highlight_seqs\n","\n","def format_split_seq(target_seq, binding_seq, interval=100):\n"," result = []\n"," for i in range(0, max(len(target_seq), len(binding_seq)), interval):\n"," target_chunk = target_seq[i:i+interval]\n"," binding_chunk = binding_seq[i:i+interval]\n"," index_line = ''.join([f\"{j:>5}\" if (j+1) % interval == 0 else \" \" for j in range(i, i+len(target_chunk))])\n"," result.append(f\"{index_line}\\n{target_chunk}\\n{binding_chunk}\")\n"," return '\\n\\n'.join(result)\n","\n","def print_pocket_table(chains, highlight_seqs):\n","\n"," pocket_data = {\n"," \"Chain\": [],\n"," \"Residue ID\": [],\n"," \"Amino Acid\": []\n"," }\n","\n"," for chain, seq in highlight_seqs.items():\n"," for idx, residue in enumerate(seq, start=1):\n"," if residue != '-':\n"," pocket_data[\"Chain\"].append(chain)\n"," pocket_data[\"Residue ID\"].append(idx)\n"," pocket_data[\"Amino Acid\"].append(residue)\n","\n"," df = pd.DataFrame(pocket_data)\n","\n"," if not df.empty:\n"," print(df)\n"," else:\n"," print(\"No pocket residues found.\")\n","\n","protein_file = os.path.join(input_path, Download_PDB, \"protein.pdb\")\n","pocket_file = f'./output/example/{Download_PDB}/pocket0.pdb'\n","\n","protein_coords = parse_coords(protein_file)\n","pocket_residues = match_residues(pocket_file, protein_coords)\n","chains = parse_sequence(protein_file)\n","full_seqs, highlight_seqs = generate_seqs(chains, pocket_residues)\n","center = calculate_center(pocket_file)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"A9Rp6pzUo83k","colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"status":"ok","timestamp":1736738337460,"user_tz":-540,"elapsed":1103,"user":{"displayName":"­최자윤 / 학생 / 화학부","userId":"06915946716678996990"}},"outputId":"a4d53a38-d7d2-402f-876f-54e9ba8ea5ef"},"outputs":[{"output_type":"display_data","data":{"application/3dmoljs_load.v0":"
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\n",""]},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Chain A:\n"," 99\n","NQALLRILKETEFKKIKVLGSGAFGTVYKGLWIPEGEKVKIPVAIKELANKEILDEAYVMASVDNPHVCRLLGICLTSTVQLIMQLMPFGCLLDYVREHK\n","------------------L-------V----------------A-K-----------------------------------L-M-LM--GC---------\n","\n"," 199\n","DNIGSQYLLNWCVQIAKGMNYLEDRRLVHRDLAARNVLVKTPQHVKITDFGLAKLLVPIKWMALESILHRIYTHQSDVWSYGVTVWELMTFGSKPYDGIP\n","----------------------------------R--L---------TD---------------------------------------------------\n","\n"," \n","ASEISSILEKGERLPQPPICTIDVYMIMVKCWMIDADSRPKFRELIIEFSKMARDPQRYLVIQGDERMHLPSPTDSNFYRALMDEEDMDDVVDAD\n","-----------------------------------------------------------------------------------------------\n","Chain B:\n"," 99\n","NQALLRILKETEFKKIKVLGSGAFGTVYKGLWIPEGEKVKIPVAIKELREATSPKANKEILDEAYVMASVDNPHVCRLLGICLTSTVQLIMQLMPFGCLL\n","------------------L-------V----------------A-K------------------------------------------L-M-LM--GC--\n","\n"," 199\n","DYVREHKDNIGSQYLLNWCVQIAKGMNYLEDRRLVHRDLAARNVLVKTPQHVKITDFGLAKLLGKVPIKWMALESILHRIYTHQSDVWSYGVTVWELMTF\n","-----------------------------------------R--L---------TD--------------------------------------------\n","\n"," 299\n","GSKPYDGIPASEISSILEKGERLPQPPICTIDVYMIMVKCWMIDADSRPKFRELIIEFSKMARDPQRYLVIQGDERMHLPSPTDSNFYRALMDEEDMDDV\n","----------------------------------------------------------------------------------------------------\n","\n"," \n","VDAD\n","----\n"]}],"source":["#@title Visualizing the protein, ligand, and pockets\n","ligand_file = os.path.join(input_path, Download_PDB, \"ligand.pdb\")\n","\n","visualize_molecules(protein_path, ligand_file, pocket_paths, label_residues=False)\n","\n","for chain in chains.keys():\n"," print(f\"Chain {chain}:\")\n"," print(format_split_seq(full_seqs[chain], highlight_seqs[chain]))"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"vA_VyW_yRVum","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1736738372778,"user_tz":-540,"elapsed":375,"user":{"displayName":"­최자윤 / 학생 / 화학부","userId":"06915946716678996990"}},"outputId":"c3bf74d0-cd62-4ab4-c378-c592a7144146"},"outputs":[{"output_type":"stream","name":"stdout","text":[" Chain Residue ID Amino Acid\n","0 A 19 L\n","1 A 27 V\n","2 A 44 A\n","3 A 46 K\n","4 A 82 L\n","5 A 84 M\n","6 A 86 L\n","7 A 87 M\n","8 A 90 G\n","9 A 91 C\n","10 A 135 R\n","11 A 138 L\n","12 A 148 T\n","13 A 149 D\n","14 B 19 L\n","15 B 27 V\n","16 B 44 A\n","17 B 46 K\n","18 B 89 L\n","19 B 91 M\n","20 B 93 L\n","21 B 94 M\n","22 B 97 G\n","23 B 98 C\n","24 B 142 R\n","25 B 145 L\n","26 B 155 T\n","27 B 156 D\n"]}],"source":["print_pocket_table(chains, highlight_seqs)"]},{"cell_type":"markdown","metadata":{"id":"87XbHDuLcqbG"},"source":["#Section 3: Conducting Protein-ligand Docking Using GDDL\n","---------\n"]},{"cell_type":"markdown","metadata":{"id":"4SXLV1KFcr1I"},"source":["The accuracy of protein-ligand docking methods are evaluted with two popular benchmark sets: **CASP-2016** and **PoseBuster**.\n","\n","Generally, ligand pose prediction is **considered accurate** if **RMSD value** of a predicted pose is **less than 2 angstrom** from the crystal structure.\n","\n","The plots below show the benchmark results of our protein-ligand docking program, **GalaxyDock-DL (GDDL)**.\n","\n","Using the CASF-2016 core set, GDDL showed a **docking accuracy of 87%**, which is comparable to existing deep-learning-based docking models.\n","\n","Using the PoseBuster set, which is newer and more comprehensive than CASP-2016, GDDL showed a **docking accuracy of 63%~78%**, which is next to the best existing model, 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)"]},{"cell_type":"markdown","metadata":{"id":"mS9XnjJ9R6-7"},"source":["#3-0. Obtaining the binding site center from Section 2"]},{"cell_type":"markdown","metadata":{"id":"4UITrLuxSivf"},"source":["Since both GDDL and C-Dock are local docking tools, the binding site center coordinates of the protein where the ligand will be docked are required. The binding site center information predicted in Section 2 is provided as input to the docking tools. f you want to specify the desired coordinates as the docking box center without using the binding site from Section 2, you can check the **put_direct_coordinates** option and enter the desired coordinates in the x, y, and z fields."]},{"cell_type":"code","source":["#@title Specifying the center coordinates of a ligand binding site\n","\n","import os\n","import shutil\n","import subprocess\n","\n","target = '4i24'\n","source_path = '/content/BsiteP/example/4i24/protein.pdb'\n","source_lig_path = '/content/BsiteP/example/4i24/ligand.pdb'\n","target_dir = '/content/iitp_demonstrate/'\n","target_file = os.path.join(target_dir, '4i24_pro.pdb')\n","lig_file = os.path.join(target_dir, '4i24_lig.pdb')\n","\n","shutil.copy(source_path, target_file)\n","shutil.copy(source_lig_path, lig_file)\n","\n","%cd /content/iitp_demonstrate/\n","\n","put_direct_coordinates = True #@param{type:\"boolean\"}\n","\n","if put_direct_coordinates:\n"," x = '-12.57260799407959' #@param {type:\"string\"}\n"," y = '41.4859619140625' #@param {type:\"string\"}\n"," z = '-3.1989645957946777' #@param {type:\"string\"}\n","else:\n"," x = center[0]\n"," y = center[1]\n"," z = center[2]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"NpgL8KEZc4jD","executionInfo":{"status":"ok","timestamp":1736742196215,"user_tz":-540,"elapsed":444,"user":{"displayName":"­최자윤 / 학생 / 화학부","userId":"06915946716678996990"}},"outputId":"8d388889-fb14-4b80-9217-b678875ed873"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["/content/iitp_demonstrate\n"]}]},{"cell_type":"markdown","metadata":{"id":"xJ_N6A5dULLK"},"source":["If you select general (non-covalent docking) in section 1, proceed to 3-1. If you select non-covalent docking, proceed to 3-2."]},{"cell_type":"markdown","metadata":{"id":"Vifx5WqCRSYM"},"source":["#3-1. Protein-ligand docking 1: EGFR(L858R)-ligand1 using \"GDDL\" Protein-ligand docking 2: EGFR(L858R, T790M)-ligand1 using \"galaxydock_dl\" Protein-ligand docking 3: EGFR(L858R, T790M)-ligand2 using \"galaxydock_dl\""]},{"cell_type":"markdown","metadata":{"id":"Kwqnx_ztVsIQ"},"source":["GDDL can be run in two versions. **The 'original' version** uses the existing GDDL parameters, which increases the likelihood of obtaining more accurate results, but it takes longer **(around 30 to 50 minutes)**. **The 'light' version** reduces the number of parameters to speed up the docking process **(about 10 minutes)**, but the results may be relatively less accurate."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"wLuNtFheR_Cv"},"outputs":[],"source":["#@title Selecting gddl_docking version\n","\n","gddl_docking_ver = \"original\" #@param [\"original\", \"light\"]"]},{"cell_type":"markdown","metadata":{"id":"i2pHAZC_Y70V"},"source":["Protein-ligad docking by GDDL in assigned gddl_docking_ver is performed."]},{"cell_type":"code","execution_count":null,"metadata":{"collapsed":true,"id":"LsQ02PDpY1DQ","colab":{"base_uri":"https://localhost:8080/"},"outputId":"fb9f352c-4895-4297-fc5a-acd23568e547","executionInfo":{"status":"ok","timestamp":1736747007592,"user_tz":-540,"elapsed":526943,"user":{"displayName":"­최자윤 / 학생 / 화학부","userId":"06915946716678996990"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[1;30;43m스트리밍 출력 내용이 길어서 마지막 5000줄이 삭제되었습니다.\u001b[0m\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 11 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 42.82 (s)\n"," 61 7.111 was replaced to 84 6.941 in same group\n"," 43 0.267 was replaced to 97 -0.014 in same group\n"," 32 5.466 was replaced to 132 5.182 in same group\n"," 12 5.543 was replaced to 178 4.074 in same group\n"," 24 7.128 was replaced to 182 7.059 in same group\n"," 24 7.059 was replaced to 184 4.640 in same group\n"," 39 6.825 was replaced to 190 6.449 in same group\n"," 76 5.429 was replaced to 199 5.386 in same group\n"," 61 6.941 was replaced to 210 5.223 in same group\n"," Bank No.: Energy\n"," Bank 1: 7.902\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.503\n"," Bank 6: -12.428\n"," Bank 7: -16.096\n"," Bank 8: -15.499\n"," Bank 9: -6.440\n"," Bank 10: -18.253\n"," Bank 11: -10.754\n"," Bank 12: -14.252\n"," Bank 13: -12.578\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 18.151\n"," Bank 17: -12.520\n"," Bank 18: -12.484\n"," Bank 19: -17.973\n"," Bank 20: -1.594\n"," Bank 21: -9.337\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -3.031\n"," Bank 25: 2.476\n"," Bank 26: -12.710\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -14.235\n"," Bank 30: -1.944\n"," Bank 31: -13.349\n"," Bank 32: -0.261\n"," Bank 33: -17.383\n"," Bank 34: -13.259\n"," Bank 35: -16.676\n"," Bank 36: -17.961\n"," Bank 37: -1.174\n"," Bank 38: -16.756\n"," Bank 39: -13.855\n"," Bank 40: -16.890\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -14.115\n"," Bank 44: -7.125\n"," Bank 45: -15.998\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -18.291\n"," Bank 49: -3.911\n"," Bank 50: -10.887\n"," Bank 51: -7.725\n"," Bank 52: -6.062\n"," Bank 53: -8.530\n"," Bank 54: -17.361\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -13.903\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.229\n"," Bank 65: -15.745\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -4.663\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -14.137\n"," Bank 77: -15.629\n"," Bank 78: -4.390\n"," Bank 79: -17.076\n"," Bank 80: -13.944\n"," Bank 81: -15.962\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -16.847\n"," Bank 85: -5.422\n"," Bank 86: -13.892\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -20.447\n"," Bank 92: -15.901\n"," Bank 93: 5.350\n"," Bank 94: -12.538\n"," Bank 95: -18.945\n"," Bank 96: -19.477\n"," Bank 97: -18.993\n"," Bank 98: -12.528\n"," Bank 99: -10.422\n"," Bank 100: -15.040\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 55\n"," D_ave / D_cut / D_min = 5.674 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 44M 53.8S\n","LCSA PLD: 1 0 13600 2.078 54 52 -17.361 -6.062 3346473 7 100 2693.797 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 7 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 40.93 (s)\n"," 52 7.248 was replaced to 1 6.962 in new group\n"," 29 5.717 was replaced to 50 5.693 in same group\n"," 16 6.861 was replaced to 56 3.978 in same group\n"," 76 5.386 was replaced to 78 4.729 in same group\n"," 38 6.693 was replaced to 83 6.571 in same group\n"," 31 6.565 was replaced to 125 6.085 in same group\n"," 12 4.074 was replaced to 126 3.675 in same group\n"," 24 4.640 was replaced to 128 4.021 in same group\n"," 1 7.072 was replaced to 195 5.223 in new group\n"," 97 -2.775 was replaced to 202 -3.055 in same group\n"," 100 4.221 was replaced to 218 4.181 in same group\n"," 100 4.181 was replaced to 220 4.078 in same group\n"," 86 6.546 was replaced to 237 5.953 in same group\n"," Bank No.: Energy\n"," Bank 1: -6.232\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.503\n"," Bank 6: -12.428\n"," Bank 7: -16.096\n"," Bank 8: -15.499\n"," Bank 9: -6.440\n"," Bank 10: -18.253\n"," Bank 11: -10.754\n"," Bank 12: -14.395\n"," Bank 13: -12.578\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -12.484\n"," Bank 19: -17.973\n"," Bank 20: -1.594\n"," Bank 21: -9.337\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -5.520\n"," Bank 25: 2.476\n"," Bank 26: -12.710\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.404\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.383\n"," Bank 34: -13.259\n"," Bank 35: -16.676\n"," Bank 36: -17.961\n"," Bank 37: -1.174\n"," Bank 38: -16.448\n"," Bank 39: -13.855\n"," Bank 40: -16.890\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -14.115\n"," Bank 44: -7.125\n"," Bank 45: -15.998\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -18.291\n"," Bank 49: -3.911\n"," Bank 50: -10.887\n"," Bank 51: -7.725\n"," Bank 52: -12.343\n"," Bank 53: -8.530\n"," Bank 54: -17.361\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -13.903\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.229\n"," Bank 65: -15.745\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -4.663\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -15.629\n"," Bank 78: -4.390\n"," Bank 79: -17.076\n"," Bank 80: -13.944\n"," Bank 81: -15.962\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -16.847\n"," Bank 85: -5.422\n"," Bank 86: -12.478\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -20.447\n"," Bank 92: -15.901\n"," Bank 93: 5.350\n"," Bank 94: -12.538\n"," Bank 95: -18.945\n"," Bank 96: -19.477\n"," Bank 97: -18.377\n"," Bank 98: -12.528\n"," Bank 99: -10.422\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 56\n"," D_ave / D_cut / D_min = 5.664 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 45M 43.5S\n","LCSA PLD: 1 0 13850 2.078 54 50 -17.361 -10.887 3404729 12 100 2743.493 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 12 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.58 (s)\n"," 12 3.675 was replaced to 54 3.385 in same group\n"," 50 7.067 was replaced to 56 5.442 in new group\n"," 24 4.021 was replaced to 133 3.881 in same group\n"," 86 5.953 was replaced to 205 5.599 in same group\n"," 5 -1.474 was replaced to 206 -2.193 in same group\n"," 91 -0.240 was replaced to 212 -1.661 in same group\n"," 84 3.857 was replaced to 224 3.818 in same group\n"," 43 -0.014 was replaced to 243 -0.794 in same group\n"," Bank No.: Energy\n"," Bank 1: -6.232\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -15.025\n"," Bank 6: -12.428\n"," Bank 7: -16.096\n"," Bank 8: -15.499\n"," Bank 9: -6.440\n"," Bank 10: -18.253\n"," Bank 11: -10.754\n"," Bank 12: -14.173\n"," Bank 13: -12.578\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -12.484\n"," Bank 19: -17.973\n"," Bank 20: -1.594\n"," Bank 21: -9.337\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -12.710\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.404\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.383\n"," Bank 34: -13.259\n"," Bank 35: -16.676\n"," Bank 36: -17.961\n"," Bank 37: -1.174\n"," Bank 38: -16.448\n"," Bank 39: -13.855\n"," Bank 40: -16.890\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.998\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -18.291\n"," Bank 49: -3.911\n"," Bank 50: -12.721\n"," Bank 51: -7.725\n"," Bank 52: -12.343\n"," Bank 53: -8.530\n"," Bank 54: -17.361\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -13.903\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.229\n"," Bank 65: -15.745\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -4.663\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -15.629\n"," Bank 78: -4.390\n"," Bank 79: -17.076\n"," Bank 80: -13.944\n"," Bank 81: -15.962\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -17.026\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.901\n"," Bank 93: 5.350\n"," Bank 94: -12.538\n"," Bank 95: -18.945\n"," Bank 96: -19.477\n"," Bank 97: -18.377\n"," Bank 98: -12.528\n"," Bank 99: -10.422\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 57\n"," D_ave / D_cut / D_min = 5.666 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 46M 34.0S\n","LCSA PLD: 1 0 14100 2.078 54 13 -17.361 -12.578 3462822 8 100 2794.034 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 8 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 40.43 (s)\n"," 10 3.307 was replaced to 60 2.947 in same group\n"," 26 3.840 was replaced to 125 1.834 in same group\n"," 5 -2.193 was replaced to 126 -2.232 in same group\n"," 50 5.442 was replaced to 135 4.718 in same group\n"," 64 1.580 was replaced to 171 1.325 in same group\n"," 38 6.571 was replaced to 204 6.083 in same group\n"," 19 0.220 was replaced to 235 -0.125 in same group\n"," Bank No.: Energy\n"," Bank 1: -6.232\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.096\n"," Bank 8: -15.499\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.173\n"," Bank 13: -12.578\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -12.484\n"," Bank 19: -18.745\n"," Bank 20: -1.594\n"," Bank 21: -9.337\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -16.850\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.404\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.383\n"," Bank 34: -13.259\n"," Bank 35: -16.676\n"," Bank 36: -17.961\n"," Bank 37: -1.174\n"," Bank 38: -14.482\n"," Bank 39: -13.855\n"," Bank 40: -16.890\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.998\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -18.291\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -12.343\n"," Bank 53: -8.530\n"," Bank 54: -17.361\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -13.903\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -16.476\n"," Bank 65: -15.745\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -4.663\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -15.629\n"," Bank 78: -4.390\n"," Bank 79: -17.076\n"," Bank 80: -13.944\n"," Bank 81: -15.962\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -17.026\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.901\n"," Bank 93: 5.350\n"," Bank 94: -12.538\n"," Bank 95: -18.945\n"," Bank 96: -19.477\n"," Bank 97: -18.377\n"," Bank 98: -12.528\n"," Bank 99: -10.422\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 58\n"," D_ave / D_cut / D_min = 5.669 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 47M 23.9S\n","LCSA PLD: 1 0 14350 2.078 54 13 -17.361 -12.578 3527691 7 100 2843.876 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 7 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 39.08 (s)\n"," 13 7.054 was replaced to 2 5.150 in new group\n"," 19 -0.125 was replaced to 51 -0.467 in same group\n"," 13 5.150 was replaced to 53 3.674 in same group\n"," 40 0.822 was replaced to 66 0.543 in same group\n"," 40 0.543 was replaced to 114 0.337 in same group\n"," 65 -1.147 was replaced to 169 -1.750 in same group\n"," 92 -0.676 was replaced to 178 -3.162 in same group\n"," 19 -0.467 was replaced to 182 -0.474 in same group\n"," 26 1.834 was replaced to 185 1.137 in same group\n"," 64 1.325 was replaced to 186 1.149 in same group\n"," 61 5.223 was replaced to 200 5.211 in same group\n"," Bank No.: Energy\n"," Bank 1: -6.232\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.096\n"," Bank 8: -15.499\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.173\n"," Bank 13: -13.727\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -12.484\n"," Bank 19: -18.843\n"," Bank 20: -1.594\n"," Bank 21: -9.337\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.109\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.404\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.383\n"," Bank 34: -13.259\n"," Bank 35: -16.676\n"," Bank 36: -17.961\n"," Bank 37: -1.174\n"," Bank 38: -14.482\n"," Bank 39: -13.855\n"," Bank 40: -14.978\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.998\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -18.291\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -12.343\n"," Bank 53: -8.530\n"," Bank 54: -17.361\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -17.464\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.457\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -4.663\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -15.629\n"," Bank 78: -4.390\n"," Bank 79: -17.076\n"," Bank 80: -13.944\n"," Bank 81: -15.962\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -17.026\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.274\n"," Bank 93: 5.350\n"," Bank 94: -12.538\n"," Bank 95: -18.945\n"," Bank 96: -19.477\n"," Bank 97: -18.377\n"," Bank 98: -12.528\n"," Bank 99: -10.422\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 59\n"," D_ave / D_cut / D_min = 5.662 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 48M 12.2S\n","LCSA PLD: 1 0 14600 2.078 54 21 -17.361 -9.337 3583215 8 100 2892.187 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 8 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.01 (s)\n"," 40 0.337 was replaced to 132 -0.291 in same group\n"," 65 -1.750 was replaced to 138 -1.920 in same group\n"," 34 4.679 was replaced to 171 4.402 in same group\n"," 94 1.812 was replaced to 175 1.681 in same group\n"," 13 3.674 was replaced to 177 3.503 in same group\n"," 65 -1.920 was replaced to 195 -4.409 in same group\n"," 77 -1.619 was replaced to 206 -2.209 in same group\n"," 77 -2.209 was replaced to 208 -3.084 in same group\n"," 39 6.449 was replaced to 229 6.242 in same group\n"," Bank No.: Energy\n"," Bank 1: -6.232\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.096\n"," Bank 8: -15.499\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.173\n"," Bank 13: -14.324\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -12.484\n"," Bank 19: -18.843\n"," Bank 20: -1.594\n"," Bank 21: -9.337\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.109\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.404\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.383\n"," Bank 34: -16.483\n"," Bank 35: -16.676\n"," Bank 36: -17.961\n"," Bank 37: -1.174\n"," Bank 38: -14.482\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.998\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -18.291\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -12.343\n"," Bank 53: -8.530\n"," Bank 54: -17.361\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -17.464\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.571\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -4.663\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -17.076\n"," Bank 80: -13.944\n"," Bank 81: -15.962\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -17.026\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.274\n"," Bank 93: 5.350\n"," Bank 94: 39.963\n"," Bank 95: -18.945\n"," Bank 96: -19.477\n"," Bank 97: -18.377\n"," Bank 98: -12.528\n"," Bank 99: -10.422\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 60\n"," D_ave / D_cut / D_min = 5.667 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 49M 2.1S\n","LCSA PLD: 1 0 14850 2.078 65 21 -19.571 -9.337 3644781 7 100 2942.142 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 7 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 39.75 (s)\n"," 7 0.747 was replaced to 88 -0.089 in same group\n"," 54 -3.860 was replaced to 110 -4.336 in same group\n"," 94 1.681 was replaced to 194 0.039 in same group\n"," 94 0.039 was replaced to 196 -0.361 in same group\n"," 61 5.211 was replaced to 199 5.027 in same group\n"," 81 1.682 was replaced to 213 -0.292 in same group\n"," Bank No.: Energy\n"," Bank 1: -6.232\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.853\n"," Bank 8: -15.499\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.173\n"," Bank 13: -14.324\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -12.484\n"," Bank 19: -18.843\n"," Bank 20: -1.594\n"," Bank 21: -9.337\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.109\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.404\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.383\n"," Bank 34: -16.483\n"," Bank 35: -16.676\n"," Bank 36: -17.961\n"," Bank 37: -1.174\n"," Bank 38: -14.482\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.998\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -18.291\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -12.343\n"," Bank 53: -8.530\n"," Bank 54: -18.240\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -16.307\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.571\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -4.663\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -17.076\n"," Bank 80: -13.944\n"," Bank 81: -10.018\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -17.026\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.274\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.477\n"," Bank 97: -18.377\n"," Bank 98: -12.528\n"," Bank 99: -10.422\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 61\n"," D_ave / D_cut / D_min = 5.669 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 49M 51.3S\n","LCSA PLD: 1 0 15100 2.078 65 21 -19.571 -9.337 3706798 5 100 2991.258 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 5 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.39 (s)\n"," 8 3.014 was replaced to 140 2.726 in same group\n"," 71 6.232 was replaced to 152 5.867 in same group\n"," 7 -0.089 was replaced to 177 -0.258 in same group\n"," 54 -4.336 was replaced to 179 -4.395 in same group\n"," 34 4.402 was replaced to 211 3.893 in same group\n"," 71 5.867 was replaced to 215 5.709 in same group\n"," 13 3.503 was replaced to 227 2.837 in same group\n"," 79 0.948 was replaced to 236 0.829 in same group\n"," Bank No.: Energy\n"," Bank 1: -6.232\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.173\n"," Bank 13: -14.917\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -12.484\n"," Bank 19: -18.843\n"," Bank 20: -1.594\n"," Bank 21: -9.337\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.109\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.404\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.383\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -17.961\n"," Bank 37: -1.174\n"," Bank 38: -14.482\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.998\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -18.291\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -12.343\n"," Bank 53: -8.530\n"," Bank 54: -18.588\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -16.307\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.571\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -13.358\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -17.907\n"," Bank 80: -13.944\n"," Bank 81: -10.018\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -17.026\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.274\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.477\n"," Bank 97: -18.377\n"," Bank 98: -12.528\n"," Bank 99: -10.422\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 62\n"," D_ave / D_cut / D_min = 5.655 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 50M 41.7S\n","LCSA PLD: 1 0 15350 2.078 65 21 -19.571 -9.337 3765570 7 100 3041.749 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 7 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.36 (s)\n"," 21 7.046 was replaced to 57 6.659 in new group\n"," 36 -0.709 was replaced to 65 -1.710 in same group\n"," 18 6.199 was replaced to 114 3.113 in same group\n"," 98 6.479 was replaced to 117 6.096 in same group\n"," 13 2.837 was replaced to 130 2.667 in same group\n"," 79 0.829 was replaced to 139 0.142 in same group\n"," 84 3.818 was replaced to 143 3.798 in same group\n"," 45 -1.150 was replaced to 204 -1.232 in same group\n"," 29 5.693 was replaced to 209 5.581 in same group\n"," Bank No.: Energy\n"," Bank 1: -6.232\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.173\n"," Bank 13: -14.767\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -16.021\n"," Bank 19: -18.843\n"," Bank 20: -1.594\n"," Bank 21: 80.859\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.109\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -13.955\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.383\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -16.235\n"," Bank 37: -1.174\n"," Bank 38: -14.482\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -16.241\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -18.291\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -12.343\n"," Bank 53: -8.530\n"," Bank 54: -18.588\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -16.307\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.571\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -13.358\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -14.724\n"," Bank 80: -13.944\n"," Bank 81: -10.018\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.274\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.477\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -10.422\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 63\n"," D_ave / D_cut / D_min = 5.628 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 51M 32.6S\n","LCSA PLD: 1 0 15600 2.078 65 99 -19.571 -10.422 3824167 9 100 3092.565 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 9 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.88 (s)\n"," 19 -0.474 was replaced to 6 -2.211 in same group\n"," 13 2.667 was replaced to 52 -0.204 in same group\n"," 18 3.113 was replaced to 54 2.684 in same group\n"," 38 6.083 was replaced to 153 5.800 in same group\n"," 61 5.027 was replaced to 197 4.236 in same group\n"," 33 1.463 was replaced to 205 1.127 in same group\n"," 1 5.223 was replaced to 213 4.952 in same group\n"," 96 -2.576 was replaced to 240 -2.656 in same group\n"," Bank No.: Energy\n"," Bank 1: -12.177\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.173\n"," Bank 13: -16.164\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -8.539\n"," Bank 19: -18.037\n"," Bank 20: -1.594\n"," Bank 21: 80.859\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.109\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -13.955\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -16.235\n"," Bank 37: -1.174\n"," Bank 38: -15.511\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -16.241\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -18.291\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -12.343\n"," Bank 53: -8.530\n"," Bank 54: -18.588\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -16.342\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.571\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -13.358\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -14.724\n"," Bank 80: -13.944\n"," Bank 81: -10.018\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.274\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -10.422\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 64\n"," D_ave / D_cut / D_min = 5.612 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 52M 24.3S\n","LCSA PLD: 1 0 15850 2.078 65 99 -19.571 -10.422 3885169 8 100 3144.316 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 8 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.38 (s)\n"," 21 6.659 was replaced to 5 5.333 in same group\n"," 19 -2.211 was replaced to 8 -2.287 in same group\n"," 1 4.952 was replaced to 53 4.236 in same group\n"," 13 -0.204 was replaced to 54 -0.600 in same group\n"," 99 7.042 was replaced to 62 6.697 in new group\n"," 18 2.684 was replaced to 183 1.190 in same group\n"," Bank No.: Energy\n"," Bank 1: -12.537\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.173\n"," Bank 13: -16.961\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -1.594\n"," Bank 21: -12.607\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.109\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -13.955\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -16.235\n"," Bank 37: -1.174\n"," Bank 38: -15.511\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -16.241\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -18.291\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -12.343\n"," Bank 53: -8.530\n"," Bank 54: -18.588\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -16.342\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.571\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -13.358\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -14.724\n"," Bank 80: -13.944\n"," Bank 81: -10.018\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.274\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: 1.017\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 65\n"," D_ave / D_cut / D_min = 5.587 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 53M 14.8S\n","LCSA PLD: 1 0 16100 2.078 65 52 -19.571 -12.343 3943195 6 100 3194.816 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 6 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.83 (s)\n"," 99 6.697 was replaced to 136 4.483 in same group\n"," 1 4.236 was replaced to 176 3.297 in same group\n"," 48 1.014 was replaced to 212 0.287 in same group\n"," 71 5.709 was replaced to 238 5.262 in same group\n"," 26 1.137 was replaced to 242 0.950 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.173\n"," Bank 13: -16.961\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -1.594\n"," Bank 21: -12.607\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -17.646\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -13.955\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -16.235\n"," Bank 37: -1.174\n"," Bank 38: -15.511\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -16.241\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -12.343\n"," Bank 53: -8.530\n"," Bank 54: -18.588\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -16.342\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.571\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -14.920\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -14.724\n"," Bank 80: -13.944\n"," Bank 81: -10.018\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.274\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -1.090\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 66\n"," D_ave / D_cut / D_min = 5.585 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 54M 5.2S\n","LCSA PLD: 1 0 16350 2.078 65 52 -19.571 -12.343 4001246 5 100 3245.166 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 5 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 42.12 (s)\n"," 99 4.483 was replaced to 65 2.717 in same group\n"," 12 3.385 was replaced to 92 3.240 in same group\n"," 52 6.962 was replaced to 103 6.856 in new group\n"," 71 5.262 was replaced to 132 4.998 in same group\n"," 61 4.236 was replaced to 197 3.972 in same group\n"," 29 5.581 was replaced to 210 5.516 in same group\n"," 36 -1.710 was replaced to 213 -3.583 in same group\n"," 21 5.333 was replaced to 239 2.966 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -16.961\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -1.594\n"," Bank 21: -11.537\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -17.646\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.568\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.783\n"," Bank 37: -1.174\n"," Bank 38: -15.511\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -16.241\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -9.401\n"," Bank 53: -8.530\n"," Bank 54: -18.588\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -9.285\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.571\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -11.043\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -14.724\n"," Bank 80: -13.944\n"," Bank 81: -10.018\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.274\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -12.246\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 67\n"," D_ave / D_cut / D_min = 5.551 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 54M 55.5S\n","LCSA PLD: 1 0 16600 2.078 65 66 -19.571 -12.305 4063511 8 100 3295.452 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 8 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 43.14 (s)\n"," 99 2.717 was replaced to 74 1.994 in same group\n"," 52 6.856 was replaced to 135 3.638 in same group\n"," 36 -3.583 was replaced to 187 -4.004 in same group\n"," 52 3.638 was replaced to 188 1.446 in same group\n"," 71 4.998 was replaced to 195 4.613 in same group\n"," 38 5.800 was replaced to 210 5.565 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -16.961\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -1.594\n"," Bank 21: -11.537\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -17.646\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.568\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -1.174\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -16.241\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.317\n"," Bank 53: -8.530\n"," Bank 54: -18.588\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -9.285\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.571\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -14.724\n"," Bank 80: -13.944\n"," Bank 81: -10.018\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.274\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -13.620\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 68\n"," D_ave / D_cut / D_min = 5.542 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 55M 45.8S\n","LCSA PLD: 1 0 16850 2.078 65 66 -19.571 -12.305 4126065 5 100 3345.813 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 5 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 42.27 (s)\n"," 54 -4.395 was replaced to 85 -4.562 in same group\n"," 99 1.994 was replaced to 188 1.556 in same group\n"," 79 0.142 was replaced to 226 -0.334 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -16.961\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -1.594\n"," Bank 21: -11.537\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -17.646\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.568\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -1.174\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -16.241\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.317\n"," Bank 53: -8.530\n"," Bank 54: -17.616\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -9.285\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.571\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -18.778\n"," Bank 80: -13.944\n"," Bank 81: -10.018\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -15.274\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -15.975\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 69\n"," D_ave / D_cut / D_min = 5.541 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 56M 35.3S\n","LCSA PLD: 1 0 17100 2.078 54 66 -17.616 -12.305 4189382 3 100 3395.251 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 3 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 42.61 (s)\n"," 54 -4.562 was replaced to 177 -4.731 in same group\n"," 92 -3.162 was replaced to 178 -3.788 in same group\n"," 79 -0.334 was replaced to 180 -0.664 in same group\n"," 26 0.950 was replaced to 215 0.680 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -16.961\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.520\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -1.594\n"," Bank 21: -11.537\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.568\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -1.174\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -16.241\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.317\n"," Bank 53: -8.530\n"," Bank 54: -18.000\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -9.285\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.571\n"," Bank 66: -12.305\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -18.321\n"," Bank 80: -13.944\n"," Bank 81: -10.018\n"," Bank 82: -11.243\n"," Bank 83: -13.821\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -16.065\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -19.047\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -15.975\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 70\n"," D_ave / D_cut / D_min = 5.543 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 57M 25.1S\n","LCSA PLD: 1 0 17350 2.078 54 66 -18.000 -12.305 4250788 4 100 3445.081 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 4 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 43.52 (s)\n"," 79 -0.664 was replaced to 59 -0.837 in same group\n"," 52 1.446 was replaced to 88 0.066 in same group\n"," 88 -2.936 was replaced to 114 -3.344 in same group\n"," 83 6.713 was replaced to 158 6.507 in same group\n"," 66 6.946 was replaced to 175 6.379 in same group\n"," 99 1.556 was replaced to 222 1.004 in same group\n"," 17 6.716 was replaced to 244 6.052 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -16.961\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -1.594\n"," Bank 21: -11.537\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.568\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -1.174\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -16.241\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.246\n"," Bank 53: -8.530\n"," Bank 54: -18.000\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -9.285\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -17.312\n"," Bank 65: -19.571\n"," Bank 66: -11.255\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -19.631\n"," Bank 80: -13.944\n"," Bank 81: -10.018\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -19.047\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.895\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 71\n"," D_ave / D_cut / D_min = 5.547 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 58M 16.0S\n","LCSA PLD: 1 0 17600 2.078 54 2 -18.000 -8.143 4321425 7 100 3495.983 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 7 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.6 (s)\n"," 52 0.066 was replaced to 54 -0.370 in same group\n"," 54 -4.731 was replaced to 68 -5.666 in same group\n"," 64 1.149 was replaced to 101 0.578 in same group\n"," 45 -1.232 was replaced to 156 -1.280 in same group\n"," 52 -0.370 was replaced to 179 -0.451 in same group\n"," 79 -0.837 was replaced to 185 -1.358 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.143\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -16.961\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -1.594\n"," Bank 21: -11.537\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.568\n"," Bank 30: -1.944\n"," Bank 31: -12.930\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -1.174\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: -3.911\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.388\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -9.285\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -9.407\n"," Bank 65: -19.571\n"," Bank 66: -11.255\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -18.341\n"," Bank 80: -13.944\n"," Bank 81: -10.018\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -19.047\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.895\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 72\n"," D_ave / D_cut / D_min = 5.542 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 59M 5.1S\n","LCSA PLD: 1 0 17850 2.078 54 2 -18.657 -8.143 4377957 5 100 3545.086 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 5 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.53 (s)\n"," 2 6.934 was replaced to 6 3.848 in new group\n"," 92 -3.788 was replaced to 130 -5.314 in same group\n"," 49 6.857 was replaced to 191 5.559 in new group\n"," 31 6.085 was replaced to 228 5.949 in same group\n"," 13 -0.600 was replaced to 247 -1.023 in same group\n"," 81 -0.292 was replaced to 249 -0.909 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -1.921\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -6.531\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -18.596\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -1.594\n"," Bank 21: -11.537\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.568\n"," Bank 30: -1.944\n"," Bank 31: -14.267\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -1.174\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: 2.398\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.388\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -9.285\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -9.407\n"," Bank 65: -19.571\n"," Bank 66: -11.255\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -18.341\n"," Bank 80: -13.944\n"," Bank 81: -12.171\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -9.604\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.895\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 73\n"," D_ave / D_cut / D_min = 5.526 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 59M 54.3S\n","LCSA PLD: 1 0 18100 2.078 54 23 -18.657 -16.139 4433681 6 100 3594.280 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 6 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.19 (s)\n"," 10 2.947 was replaced to 95 2.234 in same group\n"," 2 3.848 was replaced to 127 3.457 in same group\n"," 90 -0.907 was replaced to 189 -1.069 in same group\n"," 20 4.608 was replaced to 247 4.529 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -18.596\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -14.290\n"," Bank 21: -11.537\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.568\n"," Bank 30: -1.944\n"," Bank 31: -14.267\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -1.174\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: 2.398\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.388\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -9.144\n"," Bank 61: -9.285\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -9.407\n"," Bank 65: -19.571\n"," Bank 66: -11.255\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -18.341\n"," Bank 80: -13.944\n"," Bank 81: -12.171\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -0.102\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.895\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 74\n"," D_ave / D_cut / D_min = 5.512 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 0H 60M 43.7S\n","LCSA PLD: 1 0 18350 2.078 54 23 -18.657 -16.139 4493182 4 100 3643.704 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 4 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.53 (s)\n"," 66 6.379 was replaced to 52 5.138 in same group\n"," 60 5.550 was replaced to 92 5.210 in same group\n"," 20 4.529 was replaced to 183 3.410 in same group\n"," 90 -1.069 was replaced to 187 -2.132 in same group\n"," 61 3.972 was replaced to 233 3.375 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -18.596\n"," Bank 14: -17.096\n"," Bank 15: -3.817\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.582\n"," Bank 21: -11.537\n"," Bank 22: 8.983\n"," Bank 23: -16.139\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.568\n"," Bank 30: -1.944\n"," Bank 31: -14.267\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -1.174\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.799\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: 2.398\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.388\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -9.407\n"," Bank 65: -19.571\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -18.341\n"," Bank 80: -13.944\n"," Bank 81: -12.171\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.895\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 75\n"," D_ave / D_cut / D_min = 5.491 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 1M 33.7S\n","LCSA PLD: 1 0 18600 2.078 54 23 -18.657 -16.139 4553582 5 100 3693.724 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 5 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 39.95 (s)\n"," 23 6.734 was replaced to 10 4.266 in new group\n"," 15 6.638 was replaced to 63 4.795 in new group\n"," 40 -0.291 was replaced to 143 -0.673 in same group\n"," 20 3.410 was replaced to 178 3.191 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: -15.768\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -16.942\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -18.596\n"," Bank 14: -17.096\n"," Bank 15: -6.416\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -11.537\n"," Bank 22: 8.983\n"," Bank 23: -3.206\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.568\n"," Bank 30: -1.944\n"," Bank 31: -14.267\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -1.174\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.058\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: 2.398\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.388\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -9.407\n"," Bank 65: -19.571\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -15.190\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -18.341\n"," Bank 80: -13.944\n"," Bank 81: -12.171\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.895\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 76\n"," D_ave / D_cut / D_min = 5.445 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 2M 23.0S\n","LCSA PLD: 1 0 18850 2.078 54 30 -18.657 -1.944 4612025 4 100 3743.000 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 4 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 40.39 (s)\n"," 70 0.654 was replaced to 170 0.357 in same group\n"," 30 6.607 was replaced to 196 6.461 in new group\n"," 7 -0.258 was replaced to 203 -0.881 in same group\n"," 4 -0.571 was replaced to 236 -0.758 in same group\n"," 99 1.004 was replaced to 247 0.755 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: 23.381\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -17.026\n"," Bank 8: -15.361\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -18.596\n"," Bank 14: -17.096\n"," Bank 15: -6.416\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -11.537\n"," Bank 22: 8.983\n"," Bank 23: -3.206\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.568\n"," Bank 30: 104.432\n"," Bank 31: -14.267\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -1.174\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.058\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: 2.398\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.388\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -9.407\n"," Bank 65: -19.571\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -16.505\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -18.341\n"," Bank 80: -13.944\n"," Bank 81: -12.171\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.222\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 77\n"," D_ave / D_cut / D_min = 5.404 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 3M 12.8S\n","LCSA PLD: 1 0 19100 2.078 54 22 -18.657 8.983 4675319 5 100 3792.799 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 5 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 40.8 (s)\n"," 8 2.726 was replaced to 19 2.601 in same group\n"," 22 6.602 was replaced to 39 6.363 in new group\n"," 52 -0.451 was replaced to 98 -2.183 in same group\n"," 99 0.755 was replaced to 135 0.718 in same group\n"," 31 5.949 was replaced to 225 5.743 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: 23.381\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -17.026\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -18.596\n"," Bank 14: -17.096\n"," Bank 15: -6.416\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -11.537\n"," Bank 22: 65.013\n"," Bank 23: -3.206\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -13.952\n"," Bank 29: -15.568\n"," Bank 30: 104.432\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -1.174\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.058\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: 2.398\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -14.577\n"," Bank 64: -9.407\n"," Bank 65: -19.571\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -16.505\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -18.341\n"," Bank 80: -13.944\n"," Bank 81: -12.171\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 78\n"," D_ave / D_cut / D_min = 5.365 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 4M 3.2S\n","LCSA PLD: 1 0 19350 2.078 54 37 -18.657 -1.174 4729339 5 100 3843.178 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 5 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 42.4 (s)\n"," 37 6.566 was replaced to 13 6.370 in new group\n"," 22 6.363 was replaced to 128 5.005 in same group\n"," 40 -0.673 was replaced to 222 -0.849 in same group\n"," 13 -1.023 was replaced to 224 -2.194 in same group\n"," 28 0.394 was replaced to 227 0.015 in same group\n"," 63 -0.087 was replaced to 232 -0.285 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: 23.381\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -17.026\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -6.416\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -11.537\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -15.568\n"," Bank 30: 104.432\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -4.745\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.019\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -19.933\n"," Bank 49: 2.398\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -16.858\n"," Bank 64: -9.407\n"," Bank 65: -19.571\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -16.505\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -18.341\n"," Bank 80: -13.944\n"," Bank 81: -12.171\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 79\n"," D_ave / D_cut / D_min = 5.343 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 4M 54.8S\n","LCSA PLD: 1 0 19600 2.078 54 87 -18.657 -11.549 4791819 6 100 3894.769 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 6 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 42.66 (s)\n"," 48 0.287 was replaced to 97 -0.483 in same group\n"," 81 -0.909 was replaced to 157 -0.998 in same group\n"," 37 6.370 was replaced to 186 5.344 in same group\n"," 70 0.357 was replaced to 192 0.032 in same group\n"," 81 -0.998 was replaced to 221 -1.038 in same group\n"," 7 -0.881 was replaced to 223 -1.271 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: 23.381\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -6.416\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -11.537\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -15.568\n"," Bank 30: 104.432\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -6.621\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.019\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -16.477\n"," Bank 49: 2.398\n"," Bank 50: 9.560\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -16.858\n"," Bank 64: -9.407\n"," Bank 65: -19.571\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -18.341\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 80\n"," D_ave / D_cut / D_min = 5.338 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 5M 44.9S\n","LCSA PLD: 1 0 19850 2.078 54 87 -18.657 -11.549 4852545 5 100 3944.908 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 5 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 43.52 (s)\n"," 50 4.718 was replaced to 119 3.168 in same group\n"," Bank No.: Energy\n"," Bank 1: -13.960\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: 23.381\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -6.416\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -11.537\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -15.568\n"," Bank 30: 104.432\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -6.621\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.019\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -16.477\n"," Bank 49: 2.398\n"," Bank 50: -9.384\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.716\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -16.858\n"," Bank 64: -9.407\n"," Bank 65: -19.571\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.726\n"," Bank 78: -4.390\n"," Bank 79: -18.341\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: 5.350\n"," Bank 94: -12.657\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 81\n"," D_ave / D_cut / D_min = 5.329 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 6M 35.8S\n","LCSA PLD: 1 1 20100 2.078 54 87 -18.657 -11.549 4918205 100 100 3995.765 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 100 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.95 (s)\n"," 77 -3.084 was replaced to 62 -3.290 in same group\n"," 1 3.297 was replaced to 96 2.208 in same group\n"," 48 -0.483 was replaced to 148 -0.867 in same group\n"," 57 -1.399 was replaced to 187 -1.451 in same group\n"," 29 5.516 was replaced to 192 5.331 in same group\n"," 63 -0.285 was replaced to 232 -1.459 in same group\n"," 94 -0.361 was replaced to 249 -0.620 in same group\n"," Bank No.: Energy\n"," Bank 1: -14.693\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: 23.381\n"," Bank 5: -17.438\n"," Bank 6: -12.428\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -6.416\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -11.537\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: 104.432\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -16.676\n"," Bank 36: -18.292\n"," Bank 37: -6.621\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.019\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.080\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -9.384\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -18.551\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -19.571\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -18.341\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -13.980\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -11.549\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: 5.350\n"," Bank 94: -16.711\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 82\n"," D_ave / D_cut / D_min = 5.340 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 7M 25.0S\n","LCSA PLD: 1 1 20350 2.078 54 87 -18.657 -11.549 4984030 78 100 4045.010 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 78 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 44.21 (s)\n"," 6 4.785 was replaced to 72 4.561 in same group\n"," 87 6.539 was replaced to 104 5.836 in new group\n"," 93 6.011 was replaced to 119 5.176 in same group\n"," 1 2.208 was replaced to 168 1.789 in same group\n"," 65 -4.409 was replaced to 178 -5.023 in same group\n"," 84 3.798 was replaced to 191 3.476 in same group\n"," 35 0.507 was replaced to 205 -0.014 in same group\n"," 21 2.966 was replaced to 221 2.160 in same group\n"," 47 6.165 was replaced to 233 4.114 in same group\n"," Bank No.: Energy\n"," Bank 1: -15.626\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: 23.381\n"," Bank 5: -17.438\n"," Bank 6: -13.300\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -6.416\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -13.274\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: 104.432\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -18.140\n"," Bank 36: -18.292\n"," Bank 37: -6.621\n"," Bank 38: -14.644\n"," Bank 39: -10.748\n"," Bank 40: -15.019\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.380\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -9.384\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -18.551\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -20.055\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -9.666\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -18.341\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -14.129\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -4.529\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: -9.427\n"," Bank 94: -16.711\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 83\n"," D_ave / D_cut / D_min = 5.286 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 8M 16.6S\n","LCSA PLD: 1 1 20600 2.078 54 83 -18.657 -14.129 5043209 61 100 4096.595 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 61 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.14 (s)\n"," 83 6.507 was replaced to 54 5.822 in new group\n"," 75 6.020 was replaced to 116 5.799 in same group\n"," 93 5.176 was replaced to 118 1.138 in same group\n"," 94 -0.620 was replaced to 119 -1.336 in same group\n"," 47 4.114 was replaced to 137 3.563 in same group\n"," 21 2.160 was replaced to 152 1.394 in same group\n"," 5 -2.232 was replaced to 165 -2.808 in same group\n"," 1 1.789 was replaced to 182 1.558 in same group\n"," 39 6.242 was replaced to 197 5.685 in same group\n"," 87 5.836 was replaced to 220 5.634 in same group\n"," 75 5.799 was replaced to 240 5.601 in same group\n"," 79 -1.358 was replaced to 245 -2.389 in same group\n"," Bank No.: Energy\n"," Bank 1: -17.014\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: 23.381\n"," Bank 5: -18.273\n"," Bank 6: -13.300\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -6.416\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -15.704\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -6.850\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: 104.432\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -18.140\n"," Bank 36: -18.292\n"," Bank 37: -6.621\n"," Bank 38: -14.644\n"," Bank 39: -8.934\n"," Bank 40: -15.019\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -7.125\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -12.974\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -9.384\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -18.551\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -20.055\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.086\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -13.235\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -10.924\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -6.668\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -14.302\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: -13.682\n"," Bank 94: -16.834\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 84\n"," D_ave / D_cut / D_min = 5.221 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 9M 6.9S\n","LCSA PLD: 1 1 20850 2.078 54 25 -18.657 2.476 5102044 45 100 4146.929 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 45 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 42.91 (s)\n"," 21 1.394 was replaced to 62 1.203 in same group\n"," 50 3.168 was replaced to 96 2.154 in same group\n"," 4 -0.758 was replaced to 142 -1.114 in same group\n"," 79 -2.389 was replaced to 200 -2.734 in same group\n"," 72 -1.785 was replaced to 211 -1.797 in same group\n"," 5 -2.808 was replaced to 224 -2.851 in same group\n"," 44 5.964 was replaced to 239 5.176 in same group\n"," 44 5.176 was replaced to 241 1.360 in same group\n"," 24 3.881 was replaced to 242 3.379 in same group\n"," Bank No.: Energy\n"," Bank 1: -17.014\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: -15.047\n"," Bank 5: -18.309\n"," Bank 6: -13.300\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -6.416\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -13.922\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -9.360\n"," Bank 25: 2.476\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: 104.432\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -18.140\n"," Bank 36: -18.292\n"," Bank 37: -6.621\n"," Bank 38: -14.644\n"," Bank 39: -8.934\n"," Bank 40: -15.019\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -9.316\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -12.974\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -9.229\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -18.551\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -20.055\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.213\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -13.235\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -12.521\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -6.668\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -14.302\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -17.892\n"," Bank 93: -13.682\n"," Bank 94: -16.834\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 85\n"," D_ave / D_cut / D_min = 5.223 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 9M 59.5S\n","LCSA PLD: 1 1 21100 2.078 54 25 -18.657 2.476 5163244 27 100 4199.531 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 27 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 42.9 (s)\n"," 57 -1.451 was replaced to 62 -1.548 in same group\n"," 15 4.795 was replaced to 79 3.236 in same group\n"," 24 3.379 was replaced to 182 2.513 in same group\n"," 37 5.344 was replaced to 189 5.087 in same group\n"," 44 1.360 was replaced to 197 -0.620 in same group\n"," 92 -5.314 was replaced to 216 -5.820 in same group\n"," 25 6.470 was replaced to 233 1.542 in new group\n"," Bank No.: Energy\n"," Bank 1: -17.014\n"," Bank 2: -8.816\n"," Bank 3: -11.490\n"," Bank 4: -15.047\n"," Bank 5: -18.309\n"," Bank 6: -13.300\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -6.753\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -13.922\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -4.217\n"," Bank 25: 12.393\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: 104.432\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -18.140\n"," Bank 36: -18.292\n"," Bank 37: -6.852\n"," Bank 38: -14.644\n"," Bank 39: -8.934\n"," Bank 40: -15.019\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -11.056\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -12.974\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -9.229\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.832\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -20.055\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.213\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -13.235\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -12.521\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -6.668\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -14.302\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -18.009\n"," Bank 93: -13.682\n"," Bank 94: -16.834\n"," Bank 95: -18.945\n"," Bank 96: -19.866\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 86\n"," D_ave / D_cut / D_min = 5.196 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 10M 50.7S\n","LCSA PLD: 1 1 21350 2.078 92 30 -18.009 104.432 5222936 9 100 4250.724 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 9 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 44.51 (s)\n"," 30 6.461 was replaced to 75 6.226 in new group\n"," 96 -2.656 was replaced to 106 -3.325 in same group\n"," 15 3.236 was replaced to 177 3.010 in same group\n"," 3 6.391 was replaced to 183 6.256 in new group\n"," 57 -1.548 was replaced to 197 -1.610 in same group\n"," 4 -1.114 was replaced to 234 -1.250 in same group\n"," Bank No.: Energy\n"," Bank 1: -17.014\n"," Bank 2: -8.816\n"," Bank 3: -4.294\n"," Bank 4: -14.654\n"," Bank 5: -18.309\n"," Bank 6: -13.300\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -10.893\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -13.922\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -4.217\n"," Bank 25: 12.393\n"," Bank 26: -18.131\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: -7.625\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -18.140\n"," Bank 36: -18.292\n"," Bank 37: -6.852\n"," Bank 38: -14.644\n"," Bank 39: -8.934\n"," Bank 40: -15.019\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -11.056\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -12.974\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -9.229\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.642\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -20.055\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.213\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -13.235\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -12.521\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -6.668\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -14.302\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -18.009\n"," Bank 93: -13.682\n"," Bank 94: -16.834\n"," Bank 95: -18.945\n"," Bank 96: -18.798\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 87\n"," D_ave / D_cut / D_min = 5.184 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 11M 42.4S\n","LCSA PLD: 1 1 21600 2.078 92 3 -18.009 -4.294 5283323 6 100 4302.402 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 6 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 43.86 (s)\n"," 15 3.010 was replaced to 58 2.047 in same group\n"," 5 -2.851 was replaced to 122 -3.084 in same group\n"," 26 0.680 was replaced to 158 0.211 in same group\n"," Bank No.: Energy\n"," Bank 1: -17.014\n"," Bank 2: -8.816\n"," Bank 3: -4.294\n"," Bank 4: -14.654\n"," Bank 5: -18.232\n"," Bank 6: -13.300\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -9.588\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -13.922\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -4.217\n"," Bank 25: 12.393\n"," Bank 26: -18.077\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: -7.625\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -18.140\n"," Bank 36: -18.292\n"," Bank 37: -6.852\n"," Bank 38: -14.644\n"," Bank 39: -8.934\n"," Bank 40: -15.019\n"," Bank 41: -15.273\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -11.056\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -12.974\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -9.229\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.642\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -20.055\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.213\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -13.235\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -12.521\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -6.668\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -14.302\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -18.009\n"," Bank 93: -13.682\n"," Bank 94: -16.834\n"," Bank 95: -18.945\n"," Bank 96: -18.798\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 88\n"," D_ave / D_cut / D_min = 5.178 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 12M 33.5S\n","LCSA PLD: 1 1 21850 2.078 92 3 -18.009 -4.294 5341852 3 100 4353.469 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 3 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 43.1 (s)\n"," 41 3.756 was replaced to 18 3.184 in same group\n"," 15 2.047 was replaced to 54 1.794 in same group\n"," 83 5.822 was replaced to 128 5.246 in same group\n"," 21 1.203 was replaced to 131 0.963 in same group\n"," 15 1.794 was replaced to 180 1.730 in same group\n"," 15 1.730 was replaced to 181 1.406 in same group\n"," Bank No.: Energy\n"," Bank 1: -17.014\n"," Bank 2: -8.816\n"," Bank 3: -4.294\n"," Bank 4: -14.654\n"," Bank 5: -18.232\n"," Bank 6: -13.300\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -5.022\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -16.924\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -4.217\n"," Bank 25: 12.393\n"," Bank 26: -18.077\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: -7.625\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -18.140\n"," Bank 36: -18.292\n"," Bank 37: -6.852\n"," Bank 38: -14.644\n"," Bank 39: -8.934\n"," Bank 40: -15.019\n"," Bank 41: -9.727\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -11.056\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -12.974\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -9.229\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.642\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -20.055\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.213\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -13.235\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -12.521\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -6.698\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -14.302\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -18.009\n"," Bank 93: -13.682\n"," Bank 94: -16.834\n"," Bank 95: -18.945\n"," Bank 96: -18.798\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 89\n"," D_ave / D_cut / D_min = 5.172 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 13M 25.0S\n","LCSA PLD: 1 1 22100 2.078 92 3 -18.009 -4.294 5402476 4 100 4404.995 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 4 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 43.41 (s)\n"," 6 4.561 was replaced to 108 4.160 in same group\n"," 83 5.246 was replaced to 132 4.407 in same group\n"," 15 1.406 was replaced to 176 0.820 in same group\n"," 36 -4.004 was replaced to 194 -4.404 in same group\n"," Bank No.: Energy\n"," Bank 1: -17.014\n"," Bank 2: -8.816\n"," Bank 3: -4.294\n"," Bank 4: -14.654\n"," Bank 5: -18.232\n"," Bank 6: -11.644\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -14.556\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -17.627\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -16.924\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -4.217\n"," Bank 25: 12.393\n"," Bank 26: -18.077\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: -7.625\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -18.140\n"," Bank 36: -17.172\n"," Bank 37: -6.852\n"," Bank 38: -14.644\n"," Bank 39: -8.934\n"," Bank 40: -15.019\n"," Bank 41: -9.727\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -11.056\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -12.974\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -9.229\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.642\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -20.055\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.213\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -13.235\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -12.521\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -9.197\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -14.302\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -18.009\n"," Bank 93: -13.682\n"," Bank 94: -16.834\n"," Bank 95: -18.945\n"," Bank 96: -18.798\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.427\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 90\n"," D_ave / D_cut / D_min = 5.169 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 14M 18.7S\n","LCSA PLD: 1 1 22350 2.078 92 3 -18.009 -4.294 5469705 4 100 4458.714 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 4 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 44.54 (s)\n"," 15 0.820 was replaced to 128 0.561 in same group\n"," 15 0.561 was replaced to 129 0.453 in same group\n"," 15 0.453 was replaced to 179 -0.453 in same group\n"," 83 4.407 was replaced to 185 4.043 in same group\n"," 83 4.043 was replaced to 186 2.787 in same group\n"," 4 -1.250 was replaced to 213 -1.377 in same group\n"," 99 0.718 was replaced to 218 0.333 in same group\n"," 18 1.190 was replaced to 233 1.122 in same group\n"," 18 1.122 was replaced to 234 0.446 in same group\n"," Bank No.: Energy\n"," Bank 1: -17.014\n"," Bank 2: -8.816\n"," Bank 3: -4.294\n"," Bank 4: -14.846\n"," Bank 5: -18.232\n"," Bank 6: -11.644\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -14.387\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -13.985\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -18.696\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -16.924\n"," Bank 22: 29.302\n"," Bank 23: -3.206\n"," Bank 24: -4.217\n"," Bank 25: 12.393\n"," Bank 26: -18.077\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: -7.625\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: 3.828\n"," Bank 35: -18.140\n"," Bank 36: -17.172\n"," Bank 37: -6.852\n"," Bank 38: -14.644\n"," Bank 39: -8.934\n"," Bank 40: -15.019\n"," Bank 41: -9.727\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -11.056\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -12.974\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -9.229\n"," Bank 51: -7.725\n"," Bank 52: -19.312\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.642\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -20.055\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.213\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -13.235\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -12.521\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -8.668\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -14.302\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -18.009\n"," Bank 93: -13.682\n"," Bank 94: -16.834\n"," Bank 95: -18.945\n"," Bank 96: -18.798\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.979\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 91\n"," D_ave / D_cut / D_min = 5.176 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 15M 11.9S\n","LCSA PLD: 1 1 22600 2.078 92 3 -18.009 -4.294 5534604 5 100 4511.896 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 5 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 43.7 (s)\n"," 23 4.266 was replaced to 56 2.847 in same group\n"," 2 3.457 was replaced to 82 2.517 in same group\n"," 4 -1.377 was replaced to 126 -1.595 in same group\n"," 12 3.240 was replaced to 152 3.109 in same group\n"," 15 -0.453 was replaced to 181 -1.211 in same group\n"," 34 3.893 was replaced to 209 3.731 in same group\n"," 47 3.563 was replaced to 236 3.558 in same group\n"," 52 -2.183 was replaced to 249 -3.174 in same group\n"," Bank No.: Energy\n"," Bank 1: -17.014\n"," Bank 2: 2.579\n"," Bank 3: -4.294\n"," Bank 4: -13.591\n"," Bank 5: -18.232\n"," Bank 6: -11.644\n"," Bank 7: -17.246\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -11.180\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -13.445\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -18.696\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -16.924\n"," Bank 22: 29.302\n"," Bank 23: -13.785\n"," Bank 24: -4.217\n"," Bank 25: 12.393\n"," Bank 26: -18.077\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: -7.625\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: -19.197\n"," Bank 35: -18.140\n"," Bank 36: -17.172\n"," Bank 37: -6.852\n"," Bank 38: -14.644\n"," Bank 39: -8.934\n"," Bank 40: -15.019\n"," Bank 41: -9.727\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -11.056\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -12.909\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -9.229\n"," Bank 51: -7.725\n"," Bank 52: -20.989\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.642\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -20.055\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -17.445\n"," Bank 71: -10.848\n"," Bank 72: -19.213\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -13.235\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -12.521\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -8.668\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -14.302\n"," Bank 88: -15.776\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -18.009\n"," Bank 93: -13.682\n"," Bank 94: -16.834\n"," Bank 95: -18.945\n"," Bank 96: -18.798\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -17.979\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 92\n"," D_ave / D_cut / D_min = 5.163 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 16M 3.2S\n","LCSA PLD: 1 1 22850 2.078 92 3 -18.009 -4.294 5597596 8 100 4563.150 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 8 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 42.4 (s)\n"," 35 -0.014 was replaced to 90 -0.294 in same group\n"," 47 3.558 was replaced to 138 3.422 in same group\n"," 99 0.333 was replaced to 152 0.044 in same group\n"," 38 5.565 was replaced to 157 5.516 in same group\n"," 83 2.787 was replaced to 185 0.944 in same group\n"," 70 0.032 was replaced to 218 -0.368 in same group\n"," 7 -1.271 was replaced to 236 -1.487 in same group\n"," 88 -3.344 was replaced to 243 -3.745 in same group\n"," Bank No.: Energy\n"," Bank 1: -17.014\n"," Bank 2: 2.579\n"," Bank 3: -4.294\n"," Bank 4: -13.591\n"," Bank 5: -18.232\n"," Bank 6: -11.644\n"," Bank 7: -15.626\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -11.074\n"," Bank 11: -10.754\n"," Bank 12: -11.180\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -13.445\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -18.696\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -16.924\n"," Bank 22: 29.302\n"," Bank 23: -13.785\n"," Bank 24: -4.217\n"," Bank 25: 12.393\n"," Bank 26: -18.077\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: -7.625\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: -19.197\n"," Bank 35: -17.837\n"," Bank 36: -17.172\n"," Bank 37: -6.852\n"," Bank 38: -16.881\n"," Bank 39: -8.934\n"," Bank 40: -15.019\n"," Bank 41: -9.727\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -11.056\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.853\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -9.229\n"," Bank 51: -7.725\n"," Bank 52: -20.989\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.642\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -20.055\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -16.065\n"," Bank 71: -10.848\n"," Bank 72: -19.213\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -13.235\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -12.521\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -11.019\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -14.302\n"," Bank 88: -7.290\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -18.009\n"," Bank 93: -13.682\n"," Bank 94: -16.834\n"," Bank 95: -18.945\n"," Bank 96: -18.798\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -15.804\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 93\n"," D_ave / D_cut / D_min = 5.155 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 16M 53.8S\n","LCSA PLD: 1 1 23100 2.078 92 3 -18.009 -4.294 5664463 8 100 4613.770 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 8 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 41.26 (s)\n"," 35 -0.294 was replaced to 4 -0.633 in same group\n"," 10 2.234 was replaced to 107 1.497 in same group\n"," 83 0.944 was replaced to 136 -0.103 in same group\n"," 35 -0.633 was replaced to 181 -1.138 in same group\n"," 70 -0.368 was replaced to 190 -0.534 in same group\n"," 87 5.634 was replaced to 221 5.430 in same group\n"," 50 2.154 was replaced to 230 1.614 in same group\n"," 65 -5.023 was replaced to 240 -5.344 in same group\n"," Bank No.: Energy\n"," Bank 1: -17.014\n"," Bank 2: 2.579\n"," Bank 3: -4.294\n"," Bank 4: -13.591\n"," Bank 5: -18.232\n"," Bank 6: -11.644\n"," Bank 7: -15.626\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -9.210\n"," Bank 11: -10.754\n"," Bank 12: -11.180\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -13.445\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -18.696\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -16.924\n"," Bank 22: 29.302\n"," Bank 23: -13.785\n"," Bank 24: -4.217\n"," Bank 25: 12.393\n"," Bank 26: -18.077\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: -7.625\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: -19.197\n"," Bank 35: -18.767\n"," Bank 36: -17.172\n"," Bank 37: -6.852\n"," Bank 38: -16.881\n"," Bank 39: -8.934\n"," Bank 40: -15.019\n"," Bank 41: -9.727\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -11.056\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.853\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -8.327\n"," Bank 51: -7.725\n"," Bank 52: -20.989\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.642\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -19.106\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -16.931\n"," Bank 71: -10.848\n"," Bank 72: -19.213\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -13.235\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -12.521\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -12.325\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -14.867\n"," Bank 88: -7.290\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -18.009\n"," Bank 93: -13.682\n"," Bank 94: -16.834\n"," Bank 95: -18.945\n"," Bank 96: -18.798\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -15.804\n"," Bank 100: -11.007\n","------------------------------------------------------------\n"," CSA Run Number / Interation / SEED CYCLE = 1 / 1 / 94\n"," D_ave / D_cut / D_min = 5.154 / 2.078 / 2.078\n","------------------------------------------------------------\n","Used time for CSA cycle 0D 1H 17M 44.1S\n","LCSA PLD: 1 1 23350 2.078 92 3 -18.009 -4.294 5728191 7 100 4664.068 sec\n","------------------------------------------------------------\n"," Select Seeds....\n"," Unused seeds : 7 / 100\n","------------------------------------------------------------\n","Make new conformation\n","perturbation rate : 0.000\n","calc_ml_energy.mol2 is working!\n","Time for inference: 40.13 (s)\n"," 23 2.847 was replaced to 107 2.464 in same group\n"," 34 3.731 was replaced to 158 3.403 in same group\n"," Bank No.: Energy\n"," Bank 1: -17.014\n"," Bank 2: 2.579\n"," Bank 3: -4.294\n"," Bank 4: -13.591\n"," Bank 5: -18.232\n"," Bank 6: -11.644\n"," Bank 7: -15.626\n"," Bank 8: -15.261\n"," Bank 9: -6.440\n"," Bank 10: -9.210\n"," Bank 11: -10.754\n"," Bank 12: -11.180\n"," Bank 13: -19.119\n"," Bank 14: -17.096\n"," Bank 15: -13.445\n"," Bank 16: 0.329\n"," Bank 17: -12.729\n"," Bank 18: -18.696\n"," Bank 19: -17.639\n"," Bank 20: -12.513\n"," Bank 21: -16.924\n"," Bank 22: 29.302\n"," Bank 23: -12.384\n"," Bank 24: -4.217\n"," Bank 25: 12.393\n"," Bank 26: -18.077\n"," Bank 27: 1.413\n"," Bank 28: -2.509\n"," Bank 29: -16.706\n"," Bank 30: -7.625\n"," Bank 31: -13.290\n"," Bank 32: -0.261\n"," Bank 33: -17.803\n"," Bank 34: -19.439\n"," Bank 35: -18.767\n"," Bank 36: -17.172\n"," Bank 37: -6.852\n"," Bank 38: -16.881\n"," Bank 39: -8.934\n"," Bank 40: -15.019\n"," Bank 41: -9.727\n"," Bank 42: -10.572\n"," Bank 43: -7.233\n"," Bank 44: -11.056\n"," Bank 45: -15.396\n"," Bank 46: -2.847\n"," Bank 47: -11.853\n"," Bank 48: -12.722\n"," Bank 49: 2.398\n"," Bank 50: -8.327\n"," Bank 51: -7.725\n"," Bank 52: -20.989\n"," Bank 53: -8.530\n"," Bank 54: -18.657\n"," Bank 55: -10.692\n"," Bank 56: -13.383\n"," Bank 57: -17.642\n"," Bank 58: -12.285\n"," Bank 59: -10.040\n"," Bank 60: -5.368\n"," Bank 61: -16.728\n"," Bank 62: -9.283\n"," Bank 63: -15.991\n"," Bank 64: -9.407\n"," Bank 65: -19.106\n"," Bank 66: -10.232\n"," Bank 67: -12.252\n"," Bank 68: -9.073\n"," Bank 69: -12.832\n"," Bank 70: -16.931\n"," Bank 71: -10.848\n"," Bank 72: -19.213\n"," Bank 73: -18.355\n"," Bank 74: -11.687\n"," Bank 75: -13.235\n"," Bank 76: -8.720\n"," Bank 77: -16.693\n"," Bank 78: -4.390\n"," Bank 79: -12.521\n"," Bank 80: -13.944\n"," Bank 81: -16.000\n"," Bank 82: -11.243\n"," Bank 83: -12.325\n"," Bank 84: -15.318\n"," Bank 85: -5.422\n"," Bank 86: -12.399\n"," Bank 87: -14.867\n"," Bank 88: -7.290\n"," Bank 89: -17.945\n"," Bank 90: -8.666\n"," Bank 91: -19.070\n"," Bank 92: -18.009\n"," Bank 93: -13.682\n"," Bank 94: -16.834\n"," Bank 95: -18.945\n"," Bank 96: -18.798\n"," Bank 97: -18.377\n"," Bank 98: -9.926\n"," Bank 99: -15.804\n"," Bank 100: -11.007\n","calc_ml_energy.mol2 is working!\n","Time for inference: 24.49 (s)\n","------------------------------------------------------------\n","Total User Time = 4798.725 sec\n"," 0 dy 1 hr 19 min 58.725 sec\n","------------------------------------------------------------\n","Parameter files exist\n","Error: forrtl: warning (768): Internal file write-to-self; undefined results\n","forrtl: warning (768): Internal file write-to-self; undefined results\n","forrtl: warning (768): Internal file write-to-self; undefined results\n","forrtl: warning (768): Internal file write-to-self; undefined results\n","forrtl: warning (768): Internal file write-to-self; undefined results\n","forrtl: warning (768): Internal file write-to-self; undefined results\n","forrtl: warning (768): Internal file write-to-self; undefined results\n","forrtl: warning (768): Internal file write-to-self; undefined results\n","forrtl: warning (768): Internal file write-to-self; undefined results\n","forrtl: warning (768): Internal file write-to-self; undefined results\n","\n"]}],"source":["#@title Performing protein-ligand docking with GDDL\n","\n","if whether_covalent_docking_or_not == 'non-covalent':\n"," if gddl_docking_ver == 'original':\n"," command = f'python /content/colab_gd_dl/scripts/run_gd_dl_from_other_directory.py -d /content/colab_gd_dl/ -p /content/iitp_demonstrate/{target}_pro.pdb -l /content/iitp_demonstrate/ligand_charged.mol2 --out_dir /content/iitp_demonstrate/ -x {x} -y {y} -z {z}'\n"," process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)\n"," for line in process.stdout:\n"," print(line, end='')\n"," stderr_output = process.stderr.read()\n"," if stderr_output:\n"," print(\"Error:\", stderr_output)\n"," process.wait()\n"," if gddl_docking_ver == 'light':\n"," command = f'python /content/colab_gd_dl/scripts/run_gd_dl_from_other_directory.py -d /content/colab_gd_dl/ -p /content/iitp_demonstrate/{target}_pro.pdb -l /content/iitp_demonstrate/ligand_charged.mol2 --out_dir /content/iitp_demonstrate/ -x {x} -y {y} -z {z} --n_seed_cycle 1 --max_opt_cycle 10 --n_bank 50'\n"," process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)\n"," for line in process.stdout:\n"," print(line, end='')\n"," stderr_output = process.stderr.read()\n"," if stderr_output:\n"," print(\"Error:\", stderr_output)\n"," process.wait()"]},{"cell_type":"markdown","metadata":{"id":"-uAIePreaMZv"},"source":["GDDL outputs the top 50 protein-ligand docking poses. By selecting a ranking, you can visualize the corresponding docking pose. The output from GDDL shows the protein and ligand in rainbow and gray, respectively, while the crystal structure's protein and ligand are displayed in pink and yellow. Depending on whether the show_crystal_structure option is checked, the crystal structure may or may not be displayed."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"WekwhZsgaM4d","colab":{"base_uri":"https://localhost:8080/","height":634},"executionInfo":{"status":"ok","timestamp":1736742050891,"user_tz":-540,"elapsed":1105,"user":{"displayName":"­최자윤 / 학생 / 화학부","userId":"06915946716678996990"}},"outputId":"82c03509-7092-4970-89fe-9f78c98986ab"},"outputs":[{"output_type":"display_data","data":{"application/3dmoljs_load.v0":"
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3Dmol.js failed to load for some reason. Please check your browser console for error messages.

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\n","
\n",""]},"metadata":{}},{"output_type":"stream","name":"stdout","text":["GDDL Score: 21.537\n"]}],"source":["#@title Visualizing Protein-ligand Docking Output Files with the Crystal Structure\n","rank = 15 #@param {type:\"integer\"}\n","show_crystal_structure = True #@param {type:\"boolean\"}\n","\n","wrt = True\n","write = []\n","if whether_covalent_docking_or_not == 'non-covalent':\n"," fname = 'GalaxyDock_fb.mol2'\n","else:\n"," fname = 'reranked_fb.mol2'\n","\n","num = 0\n","with open('GalaxyDock_fb.E.info') as fp:\n"," for line in fp:\n"," num += 1\n"," if num > 3 and num == rank+3:\n"," score = line.split()[1].strip('\\n')\n"," break\n","\n","num = 0\n","with open(fname) as fp:\n"," for line in fp:\n"," if line == '@MOLECULE\\n':\n"," num += 1\n"," if num > rank:\n"," break\n"," if num == rank:\n"," write.append(line)\n","\n","fout = open('final_ligand.mol2', 'wt')\n","fout.writelines(write)\n","fout.close()\n","view = py3Dmol.view(width=800, height=600)\n","mol = next(pybel.readfile(\"mol2\", \"final_ligand.mol2\"))\n","pdb_data = mol.write(\"pdb\")\n","view.addModel(pdb_data, \"pdb\")\n","view.setStyle({'model': 0}, {\"stick\":{}})\n","view.addModel(open(f'/content/iitp_demonstrate/{target}_pro.pdb').read(), \"pdb\")\n","view.setBackgroundColor(\"white\")\n","view.addSurface(py3Dmol.VDW, {\"opacity\":0.7, 'color':'white'}, {'chain':'A'})\n","view.setStyle({'model': 1}, {'cartoon': {'color': 'spectrum'}})\n","if show_crystal_structure:\n"," view.addModel(open(f'/content/iitp_demonstrate/{target}_lig.pdb').read(), \"pdb\")\n"," view.setStyle({'model': 2}, {'stick': {'color': 'yellow'}})\n","view.addaddLabel(f\"GDDL Score: {score}\", {'position': (50, 50, 50), 'color': 'red', 'fontSize': 20, 'backgroundColor': 'white'})\n","view.zoomTo()\n","view.show()\n","\n","print(f'GDDL Score: {score}')"]},{"cell_type":"markdown","metadata":{"id":"rqV-efNnCBL7"},"source":["The following graph shows the GDDL energy score according to rank."]},{"cell_type":"code","execution_count":null,"metadata":{"cellView":"form","id":"sfGwehjdCBhS","colab":{"base_uri":"https://localhost:8080/","height":582},"executionInfo":{"status":"ok","timestamp":1735394723389,"user_tz":-540,"elapsed":3110,"user":{"displayName":"­김동우 / 학생 / 약학과","userId":"17104096532647650828"}},"outputId":"39975880-0f7a-4c7d-ba56-0a2cdda2d10b"},"outputs":[{"output_type":"display_data","data":{"text/plain":["
"],"image/png":"iVBORw0KGgoAAAANSUhEUgAAAv4AAAI1CAYAAACuSv7OAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAACJfElEQVR4nOzde1xUdfoH8M+ZKzNcddB1xmRQS0FlQCBNrbBy806llrW1m122tv2V25ahpLVtYgRarmv33bZ+tbvZb8XKvLZtRQVlhHIpIFkVMEFNxLgMl7mc3x8srOgMMwcZODCf9+vlSxzOc84zw/HMM1++5/kKoiiKICIiIiKiQU3R3wkQEREREZHvsfAnIiIiIvIDLPyJiIiIiPwAC38iIiIiIj/Awp+IiIiIyA+w8CciIiIi8gMs/ImIiIiI/AALfyIiIiIiP8DCn4iIiIjID7DwJyIaRLZt24bx48d3/iEiIuqg6u8EiIgGgn379uEXv/jFeY8rFAoEBgZi1KhRmD59OpYtW4Zhw4b1Q4aD05kzZ/Daa68hOzsblZWVsNlsCA4ORlhYGMaMGYPo6GgsXrwYRqOxv1MlIpI9Fv5ERBfA6XSioaEBJSUlKCkpwXvvvYd//OMfLER7wbFjx/Czn/0Mx48f7/L46dOncfr0aRw+fBgffvghoqKi+HoTEXmBhT8RUQ/MmzcPkyZNQmNjIz788EMcPHgQAPDDDz/g9ddfR2pqaj9nOPBt2LChs+hXqVSYM2cOxo4dC1EU8f3332P//v2oqKjo3yRdcDgcaGtrg06n6+9UiIi6YOFPRNQDV1xxBRYtWgQAuPPOOzFt2jTYbDYAwL///e8u2545cwavvPIKvv32Wxw9ehR1dXWw2WwICQnB+PHjcd111+G6666DIAidMedOLfrwww/x6aefYsuWLaioqEBQUBCuvvpqpKSkIDQ01Kuc161bhzfeeANA+xSltWvXYsmSJS63dTqduOaaa1BdXQ0AuP/++/HAAw902Wb9+vX485//DACIjIzE3r17AQDfffcd/vSnP2H//v04efIkFAoFhg4dioiICMTGxuK2227DT37yE4/55uTkdH5933334f777z9vm0OHDkGr1Z73uN1ux7vvvotdu3ahrKwM9fX1CAoKQkREBK688srz9nXkyBG8/vrr+PLLLzs/bIwYMQJTp07F7bffjrFjx3bZftWqVXjnnXcAAFOmTEFGRgY2btyInJwcnD59Gs899xxmzZoFADh16hTeeOMNZGdno6qqCna7HSNGjMDll1+OX/7ylzCZTB5fCyKi3sDCn4joAgUHByMwMBBnzpwBAAwZMqTL90+ePIlXX331vLja2lrk5uYiNzcX+/btQ3p6uttjrFy5Evn5+Z3/Pn36NLZu3YrKykr89a9/9ZhjZmZmZ9GvVCqRkZGBhQsXut1eoVDg+uuvxwsvvAAA2LFjR5fCXxRF7Nq1q/PfHR+C/v3vf2Pp0qVobm7usr+amhrU1NRg3759uPTSS70q/O12e+fXhw8fRltbGzQaTZdtzi3IgfYPWnfffTeKi4u7PF5XV4e6ujocPny4S+G/e/durFy5Eq2trV22r6ioQEVFBd555x08/fTTmD9/vss8T548iZtuugk//PDDed87cOAA7rvvPtTV1XV5vKqqCn//+9/x/vvv46WXXkJiYqKbV4GIqPew8CciugCNjY3Ytm1bZ9EPAHPnzu2yjUKhwNixY2GxWBAeHo6QkBC0traipKQEH3/8MURRxLZt23DLLbfAYrG4PE5+fj6mTZuGyZMnd5lalJeXh4KCAsTFxbnN8Q9/+EPnBw+1Wo1nnnkGs2fP9vjcFi1ahBdffBGiKKKiogLffPMNJk2a1JlPx28DlEolrr/+egDAO++801n0jxgxAsnJydDpdDh+/DjKy8tRWFjo8bgdJk6ciK+++goAsHPnTmRnZyMuLg4TJ06ExWLBZZddhqCgoPPiUlJSuhT9Y8eORVJSEjQaDUpKSlBUVNT5vcrKSqSkpKCtrQ0AEBYWhhtuuAGCIOCdd95BXV0d2trasHLlSkycOBGRkZHnHa9jutG1116L8ePHo7q6GkFBQWhsbMT//M//dBb9I0eOxNy5cxEQEIC9e/eivLwcDQ0NeOCBB/DBBx8gODjY69eGiKgnWPgTEfVAamrqefP4dTodHnjgAVxzzTVdHr/44ouxa9cuVFdXo7i4GKdOnYJKpUJiYiK+/fZbnDhxAgDw2WefuS38f/rTn2Lz5s0QBAG33347pk+fDofDAQAoLi52W/i/8MILePHFFwEAGo0Gf/zjH3HVVVd59RxHjRqFSy+9tEvx3VH479y5s3O7GTNmdI7gnz1qfuutt+Kee+7pss8ff/zRq2MDwCOPPIKf/exnnVOoGhsb8fnnn+Pzzz8HAGi1Wtx00014+OGHO+fTf/fdd8jOzu7cR1JSEp5//nmo1erOx44ePdr59V//+tfOol+hUODNN9/EuHHjAAA33HADrrvuOjidTthsNvztb3/D6tWrXeb66KOP4vbbb+/y2BtvvIHa2loAQGhoKLZt24awsDAAwF133YVrrrmm80bld955x2XXKCKi3sTCn4iol8yaNQs333zzeY/X1dVh1apV+OSTT7qN7/gA4Mott9zSeQ9AWFgYhgwZglOnTgHovpjetGkTACAgIADPP/88Lr/8ck9Po4vFixd3Fv67du1CSkoKHA4H9uzZ07lNxzQfAEhMTMSbb74JoP03DR999BFGjx6N0aNHIzY2FomJiVAqlV4d22Kx4B//+Ac2b96MTz/9tPMDQIfW1la8+eabaGxsxNNPPw0AXaZDAe33Jpxd9APtH2g6FBQUdH49ceLEzqIfAMaNG4eJEyd2/vbg7G3PFhoailtvvfW8x/fv39/59Y8//oipU6e6fa4HDhxg4U9EPsfCn4ioB+bNm4eoqCgcOHAAH3/8MQDg/fff7+zqc/aNuqtXr/ZY9APoHHl2ZeTIkV3+ffZcd1EUPe47ICDAq3n155o9ezaefPJJNDU14fjx48jLy0NLSwtOnz4NoP1DyNm/4ZgzZw7uvPPOzpH0AwcO4MCBA12ex8svv4xLLrnEq+NHR0fjhRdeQHNzM4qKilBYWIjPPvus88MI0D69aNWqVQgLCzvvQ9BFF13U7f7P3j48PPy875/9WH19vct9jBo1CirV+W+nUn670fF6EhH5Egt/IqIeOLurz+OPP463334bAPDll1/ivffe65zzbrVauxT906ZNw9q1a2EymaBUKrFkyZLzbkJ15dzC8uwPFt0ZM2YMDh8+jDNnzuCOO+7A3//+d0RERHgVC7RPX5o3bx7+8Y9/AGi/yffs6TwLFy4874bblStX4te//jX279+PI0eO4MiRI/joo49w8uRJHDt2DL///e+9uiH53DymTp2KqVOn4p577sHzzz+PP/7xj53fr6ysRFhY2Hkdjr7//nsMHTrU7X7P3r7jNyhnO/uxkJAQl/vQ6/Ue9z1s2DDccccdbvPgOgRE1BcU/Z0AEdFAt2LFii43Zr7wwgud8+8bGho6vwaAmTNnYtSoUVAqlTh8+DC+++47n+b26quvdo70//DDD1i2bNl5C2J5snjx4s6v9+7diw8//NDl94D2+fP19fUIDg5GUlISli1bht///vd4/PHHO7f59ttvvTru2rVrsW/fPpe/0QgMDOzy747XPyEhocvjL7zwQpfuQED7wmAdJk+e3CWv8vLyzn8fPHiwS65nb+uNs7evq6vDjBkzcNddd3X5c+eddyI6OhoxMTGS9k1E1BMc8SciukAhISG49dZb8dJLLwFoH33etWsXFi5cCIPBgJCQkM5pIi+++CJqa2tht9uxbdu2bqf39AaTyYQ///nPuPXWW1FfX49jx45h2bJl+Nvf/gaDweDVPiZPntzlNwcdoqOjER0d3WXb3bt3449//COmTp0Ks9mMYcOGobm5GTt27Ojcxt3I+bk+/vhj/PWvf8Xw4cMxZcoUmM1mqNVqHDlypEsr0YsuugijR48GAIwfPx5JSUmdN/h+/PHHuO6663DllVdCq9Xi3//+N/Ly8rBv3z4A7Tcgv/XWW2hra4PT6cRtt93WpauP0+kE0N4NydU8/u50dEWqq6uD3W7HLbfcgjlz5sBsNqOtrQ1HjhzBV1991dnn/+x7D4iIfIGFPxFRL7j99tvxv//7v52tLF9++WUsWLAAKpUKv/zlL/HMM88A+O9iXkD7zaMjR470egS8p8aNG4cXX3wRd955J1pbW3HkyBHceeedePPNN70uwhctWoQNGzZ0eezc0f4ONputS/edc919992S8j958mSXDw5n02q1SEtL6zL1KSMjA7/85S87p1D9+9//7rKo2tm/nTGbzcjMzOzs43/mzBm89tprXY6h0Wjw9NNPw2w2S8o7ODgYL7zwAn7961+jrq4OVqsV27Ztk7QPIqLexKk+RES9YOjQoV1WwS0vL8c///lPAMA999yDxx9/HJGRkVCr1Rg2bBhuuukmvPnmm+dNWfGVxMREPPvss50ddcrKynDPPffAarV6FX/dddd16cajVquxYMGC87a75ppr8D//8z+YPn06Ro4cCZ1OB5VKhWHDhmHmzJl48cUX8fOf/9yrY/75z3/G448/jmuvvRbjxo2DwWCASqWCXq/HxRdfjFtvvRXvv/8+pk2b1iVuyJAheOutt5CWlobp06dj6NChUKlUCA0NxcSJE89ruzl37ly8++67uPnmm2E2m6HVaqHVahEREYGbbroJ7777rtvFuzyJj4/Hzp078etf/xoTJ05EUFAQlEolQkJCMHHiRNx222147bXXcOmll/Zo/0REUgiiN+0giIiIiIhoQOOIPxERERGRH2DhT0RERETkB1j4ExERERH5ARb+RERERER+gIU/EREREZEf8Js+/mFhYWhtbeWy6EREREQ0aNTU1ECr1XZZYNEdvyn8W1tbYbPZ4XD0ffdSQQAUCgFOpwhvmqeKohNHj1YBAEaNioAgePeLGanHYczgi5FrXoxhzGCMkWtejGHMYIyRa159GeOOzWb3elu/KfyNRiMcDhFff13U58dWqRQYMiQQdXVNsNudHrdvamrC6NHtv5nIzc2DVqvzyXEYM/hi5JoXYxgzGGPkmhdjGDMYY+SaV1/GuJOYaIFSKXjeEH5U+A8kAQEB+PDDbISE6BAQEHDBnwSJiIiIiFj4y5BSqUR8fEKvfRIkIiIiImJXHyIiIiIiP8ARfxlqa2vDCy+8BL1eg1/84m4oFPwxEREREdGFYUUpQzabDU88sQYAcMstt0Or5Y+JiIiIiC4Mp/oQEREREfkBFv5ERERERH6AhT8RERERkR9g4U9ERERE5AdY+BMRERER+QEW/kREREREfoB9ImUoICAA27fvQnCwDgEBARDF/s6IiIiIiAY6Fv4ypFQqcfnlV2LIkEDU1TXBbnf2d0pERERENMCx8CciIiIikkAURRQVFWDn7r0oLC5FW1srNBotYmOiMX/ubFgscRAEob/TPA8Lfxmy2Wx4/fXXoddrceONt0IQlP2dEhEREREBqKmpxrr0TFRW1yPcPBNjpy6EPjAI1qZGlFfmY83azTCbQrA6NQVGo6m/0+2Chb8MtbW1ISXlYQDAddfdCK1W188ZEREREVFNTTVWrFwDlWEGpicvhkKpgiAAarUSGp0BoQYznLHJKDuQhRUr12BDRpqsin929SEiIiIi8kAURaxLz4TKMAMTEpdCoXQ9fq5QqjAhcSlUQ6djXXomRBl1aWHhT0RERETkQVFRAaqqGxA1ebFX20fFL0FldT2Kiwt9nJn3WPgTEREREXmwc/deGCKS3I70n0uhVMEQkYQdu/b4ODPvsfAnIiIiIvKgoKgUI8wJkmKM5gQUFJX6KCPpWPgTEREREXnQ3GyFWquXFKPW6NHS0uyjjKRj4U9ERERE5IFOp4et1SopxtZmRUCAfLozsp2nDGm1WmzZshVBQQHQarX9nQ4RERGR34uzRKO8Kh9h4WavY2oq8xFnifZhVtJwxF+GVCoVrr12DubPnw+Vip/NiIiIiPrb/LmzUVuZDafD7tX2TocdtVXZWDBvjo8z8x4LfyIiIiIiDyyWOESYglF2IMur7cv2b4XZFIKYmFgfZ+Y9Fv4yZLPZ8Pe//xWvv/46bDZbf6dDRERE5PcEQcDq1BTYa3NQkrfF7ci/02FHSd4W2E/nYnVqCgRB6ONM3eM8Ehlqa2vD/ff/CgBw9Og8aLXyuSmEiIiIyF8ZjSZsyEjDuvRM5G7PhSEiCabIBOj0wWi2NqC6Ih+1Vdkwm0KwOiMNRqOpv1PugoU/EREREZGXjEYTNm/aiOLiQuzYtQeF+9bDZmuDWq1BbEw0FixbjpiYWFmN9Hdg4U9EREREJIEgCLBY4mCxxEGlUmDIkEDU1TXBbnf2d2rd4hx/IiIiIiI/wMKfiIiIiMgPyKrwt9lsuOmmmzBx4kTMmDEDANDY2IgHHngA8fHxWLp0KSoqKvo3SSIiIiKiAUhWc/wFQcCsWbOg1+tRXl4OAPjLX/6CnJwcvPHGG1i3bh0ee+wxvPnmmz3cP6BS9f1nHaVS0eVvT87OUalUeJ2z1OMwZvDFyDUvxjBmMMbINS/GMGYwxsg1r76McUfKPcSCKIriBR+xl61atQqfffYZcnJycM899+DUqVPYtm0bNm7ciJdffhlFRUXQaDSS9jlmzBgAwOHDh32Rcq+y2+145513AAA33HADV+8lIiIiIpek1LiyryjDw8NRXFyMxsZGlJeXQxRF1NfXIzw8XPK+nE4RdXVNPsiye0qlAiEhOtTXN8Ph8O5u79mzF5wV0+qz4zBmcMXINS/GMGYwxsg1L8YwZjDGyDWvvoxxx+kUoVB4N+wv+8L/7rvvRk5ODi699FIEBwdDrVZj6NChPdqXKKJf2yw5HE7Jx2cMY3oSI9e8GMOYwRgj17wYw5jBGCPXvPoy5lxS5u7IrvA/dOgQGhoa4HA4cOjQIQQFBeHll1/G6dOn8corr2D48OFQKGR1T3Kvs9vt2LFjB4KCAjBz5rWQ2T3YRERERDQAya7wnzdvXpevX3vtNfz2t7+F3W7HFVdcgdWrV/djdn2jtbUVd975CwDA0aMnoNXq+jkjIiIiosFJFEUUFRVg5+69KCwuRVtbKzQaLWJjojF/7mxYLHGyXIW3J2RX+H/33XfnPbZv375+yISIiIiIBrOammqsS89EZXU9ws0zMXbqQugDg2BtakR5ZT7WrN0MsykEq1NTYDSa+jvdCya7wp+IiIiIqCekjN7X1FRjxco1UBlmYHryYiiUKggCoFYrodEZEGowwxmbjLIDWVixcg02ZKQN+OKfhT8RERERDXhSRu9HjDBiXXomVIYZmJC41O0+FUoVJiQuRUmeiHXpmdi8aeOAnvbDwp+IiIiIBjSpo/d33n4zqqobMC15sVf7j4pfgtztuSguLoTFEufbJ+NDbBdDRERERAOWKIpdRu8VStfj2h2j96qh07H2qUwMjbjS7bauYg0RSdixa09vpt7nWPgTERER0YBVVFSAquoGRE32fvT+xKkGBBvGSzqO0ZyAgqLSnqQoG5zqI0MajQbPPfcSAgO10Gg0/Z0OERERUZ/z9kbdnbv3whCRJGn0XqHU40y9FRdJyEet0aOlpblnT0YmWPjLkFqtxs9+dhuGDAlEXV1Tv642TERERNTXpNyoW1BUirFTF0ravy7IgDN1pyTF2NqsCAgY2GsrsfAnIiIiIp/zdgRf6o269T/+CLVWLymXYSMuxpkT3wKY53HbDjWV+YizREt81vLCwl+G7HY7PvroIwQFBWDKlMvBWzGIiIhoIPN2BP/RVY/gqafXS2qzeaL0L7C1NgHBw7zO56IxifjyXy/B6fitV1OEnA47aquysWDZcq+PIUcs/GWotbUVN9+8BABw9OgJaLUD+9dKRERE5L+kjODfe9/9sAvBuHKR9zfqFn/xBo6UfY7Jl0d6nVNbayPCQxUoO5DV7QeMDmX7t8JsCkFMTKzXx5AjDiUTERERkU9IbbVZ2xSANvV4KJRKr/avUKpgjvopDn+zA06H3asYp8OO00c/xWOPPgJ7bQ5K8ra4jXU67CjJ2wL76VysTk0Z0It3ASz8iYiIiMhHpLbadDoVCAgbh/r6eq+PMX7y9Whr/gFlB7K82r5j9P6qq2ZhQ0Yagp3fIHf7QyjNz8KZUxVo/PEkzpyqQGl+FnK3P4Rg5zfYkJEGo9HkdU5yxak+RERERCSJr1pt2m0t0AYZcfLkDwgJCfUqRqMNxIif/OQ/o/ciouKXuDye02FH2f6t7aP3GWkQBAFGowmbN21EcXEhduzag8J962GztUGt1iA2JhoLli1HTEzsgB/p78DCn4iIiIi85stWmyqNDmqVGj/WN3gdY2uzIiR0CDZkpGFdeiZyt+fCEJEEU2QCdPpgNFsbUF2Rj9qq7Pa8zhm9FwQBFkscLJY4qFSKQd1OnYU/EREREXnF1602h5vG4cyJQkmr6na02fS30fueYOFPRERERB6de6OuOxfSavPiibPw6e7nEGwY59X257bZ9KfR+55g4S9DGo0GmZnPQK/XQqPR9Hc6RERENIh5O1+/40bdacm+a7U5/KIYiI4mNNTkAEj0uP1gabPZV1j4y5Barcbdd9/LT6lERETkU1Lm60u9UffsVpux0272Kk50OhA+RI+A1gMoydsi6UZd8oyFPxEREZEfkjpfv8lqRfQV3t+oC7S32jzy7Q5JC2VdMvonnSv4Sr1Rl7rHwl+GHA4HvvzycwQH6zBpUjwAfoolIiKi3tOT+fqHv/kTLLN0ko7T01abvFHXN1j4y1BLSwuSk+cBAI4ePQGtVtp/MiIiIqLu9GS+/lcf/wl1tScRGDzc6+NcSKtN3qjb+1j4ExEREfmZnszXHzrsYpR/m42LIid5fRy22pQXFv5EREREfkbqwloAMCHxBnz5r5fgdNzr1QcGttqUH0V/J0BEREREfau52SppYS0AGBExGbCfQdmBLK+2Z6tN+WHhT0RERORndDo9bK1WSTF2WzPGjB7znxt1t8DpsLvczumwoyRvS/uNuqkpnL4jI5zqQ0RERORn4izRKK/KR1i42euYmsp8TJ0Sjztu/4XkG3VJHlj4ExEREfmZ+XNn47G1z8EZmyx5vj5v1B24WPjLkFqtxhNPpEGv10CtVvd3OkRERDTIWCxxiDAFS1pY6+z5+rxRd2DiHH8Z0mg0WL78QTzyyCPQaDT9nQ4RERENMoIgYHVqCufr+xmO+BMRERH5IaPR1KOFtWjgYuEvQw6HA0VFBxASosPo0eMB8NM1ERER9T7O1/cvLPxlqKWlBbNmJQEAjh49Aa1W188ZERER0WDF+fr+g3P8iYiIiIj8AEf8iYiIiAYJURRRVFSAnbv3orC4FG1trdBotIiNicb8ubNhscRx2o4fY+FPRERENAjU1FRjXXomKqvrEW6eibFTF0IfGARrUyPKK/OxZu3m9ht1U1N4o66fYuFPRERENMDV1FRjxco1UBlmYHryYiiUKggCoFYrodEZEGowwxmbjLIDWVixcg02sEuPX+IcfyIiIqIBTBRFrEvPhMowAxMSl7pdiVehVGFC4lKohk7HuvRMiKLYx5lSf2PhT0RERDSAFRUVoKq6AVGTF3u1fVT8ElRW16O4uNDHmZHccKqPDKnVaqSkpEKn00CtVvd3OkRERCRjO3fvhSEiye1I/7kUShUMEUnYsWsPLJY43yZHssLCX4Y0Gg1WrVrNPrpERETkUUFRKcZOXSgpxmhOQMG+9T7KiOSKU32IiIiIBrDmZivUWr2kGLVGj5aWZh9lRHLFEX8ZcjqdKC0tQ2ioHiNGRPR3OkRERCRjOp0etlYrEOx9jK3NioAAne+SIlniiL8MNTc3Y8aMKZg0aRKam/lpnIiIiNyLs0TjeFW+pJiaynzEWaJ9lBHJFQt/IiIiogFs/tzZqK3MhtNh92p7p8OO2qpsLJg3x8eZkdyw8CciIiIawCyWOESYglF2IMur7cv2b4XZFIKYmFgfZ0Zyw8KfiIiIaAATBAGrU1Ngr81BSd4WtyP/TocdJXlbYD+di9WpKRAEoY8zpf7Gm3uJiIiIBjij0YQNGWlYl56J3O25MEQkwRSZAJ0+GM3WBlRX5KO2KhtmUwhWZ6TBaDT1d8rUD1j4ExEREQ0CRqMJmzdtRHFxIXbs2oPCfeths7VBrdYgNiYaC5YtR0xMLEf6/RgLfyIiIqJBQhAEWCxxsFjioFIpuBgodcHCX4bUajXuv/83CAhQQ61W93c6RERERDQIsPCXIY1GgyefXMdP6URERH5MFEUUFRVg5+69KCwuRVtbKzQaLWJjojF/7mxYLHGctkOSsPAnIiIikpmammqsS89EZXU9ws0zMXbqQugDg2BtakR5ZT7WrN3cfqNuagpv1CWvsfCXIafTiaqqo/jxRz2Cgw39nQ4RERH1oZqaaqxYuQYqwwxMT14MhVIFQQDUaiU0OgNCDWY4Y5NRdiALK1auwQZ26SEvsY+/DDU3NyMubiJGjx6N5ubm/k6HiIiI+ogoiliXngmVYQYmJC6FQul6jFahVGFC4lKohk7HuvRMiKLYx5nSQMTCn4iIiEgmiooKUFXdgKjJi73aPip+CSqr61FcXOjjzGgwYOFPREREJBM7d++FISLJ7Uj/uRRKFQwRSdixa4+PM6PBQFaFv81mw0033YSJEydixowZAIDTp09j2bJliI2NxRVXXIGsrKx+zpKIiIjINwqKSjHCnCApxmhOQEFRqY8yosFEVjf3CoKAWbNmQa/Xo7y8HACwfft2fPHFF3jhhRfw9ttvIy0tDYsWLWL7KiIiIhowvG3N2dxshVqrl7RvtUaPlhbeE0ieyarwV6lUuOeee3D48OHOwn/06NEAALPZjLCwMOj1+h4X/YIAqFR9/0sOpVLR5W9Pzs5RqVR4nbPU4zBm8MXINS/GMGYwxsg1L8bIL6a6uhprn8pA5bEfYYiYiYsvS4ZOH4hmaxPKK77GY2mbYR4ZisceXQm9Xg97mxXnljodtU/7311v5LXbrNDpdOfVC3J6DS40Rq559WWMO1LKYkGU4W3gq1atwmeffYacnBycPn0ad9xxBw4ePAgAWL9+PRYsWCB5n2PGjAEAHD58uFdz9YWmpiYEBQUBABobGxEYGNjPGREREVFPHDt2DPf++mEow2YgOnGxy7n7TocdpV9nwXEmB2NGX4Sq+rGYkOjdzb0AUJK3FRMv+gHr1v6uN1OnAUJKjSurEX9XXn31VRw8eBCvvPIK3nvvPTzxxBO46qqrelQMO50i6uqafJBl95RKBUJCdKivb4bD4XkV3tbWVtx99z3QaFSwWm1oa/MuZ6nHYczgi5FrXoxhzGCMkWtejJFPjCiKeDjldxCDp2Fc/BI4nIDD6YAgCFCpFLDbnf9pwylgXPwSlOQ5UPbdJ2horsLYSQu6fEg4P6ad02HHiSOf4MHbf3NejSOH16C3YuSaV1/GuON0ilAovBv2l13hf+jQITQ0NMDhcODQoUMQRRGCIECn00GtVqOhoQGtra09KvxFEbDbL+zFvRAOh9Or4yuVamRmPoshQwJRV9ckOWdvj8OYwRsj17wYw5jBGCPXvBjT/zGFhQdQ+X09piUvQtf5Fe3/EEWxy+PjJy9GznufIyzQjtL9WZiQuNRjTGn+VkQYgzFhQozbnAfa69bfx5B7zLmkzN2RXeE/b968Ll9v2LABCQkJuOuuuxAYGIiHH34YQ4cO7ccMiYiIiDzrSWvOcPNMmHQHUXk0ByV5IqLil7idHlS2fyvsp3OxOiONTU/IK7Ir/L/77rvzHlu4cGE/ZNJ/RFHEqVM/wG63QqnU9Xc6RERE1AMFRaUYO1VaDWM0J+Df+z7CpmfSsS49E7nbc2GISIIpMgE6fTCarQ2orshHbVU2zKYQrM5Ig9Fo8tEzoMFGdoU/AVarFePGtXczOnr0BLRaFv9EREQDzYW05jQaTdi8aSOKiwuxY9ceFO5bD5utDWq1BrEx0ViwbDliYmI50k+SsPAnIiIi8gGdTg9bqxUI9j7G1mZFQED7gJ8gCLBY4mCxxEGlUvT43j+iDrJauZeIiIhosIizRON4Vb6kmJrKfMRZon2UEfk7Fv5EREREPjB/7mzUVmbD6bB7tb3TYUdtVTYWzJvj48zIX7HwJyIiIvIBiyUOEaZglB3I8mr7sv1bYTaFICYm1seZkb9i4U9ERETkA4IgYHVqCuy1OSjJ2+J25N/psKMkb0t7a87UFN6wSz7Dm3uJiIiIfMRoNGFDRhpbc5IssPCXIZVKhVtuuRUajQoqFX9EREREAxlbc5JcsKqUIa1Wi+eff5ltu4iIiAYJtuYkOeAcfyIiIiIiP8ARfxkSRRFNTU3QaNq/JiIiIvkQRRFFRQXYuXsvCotL0dbWCo1Gi9iYaMyfOxsWSxyn7ZAssfCXIavVitGjjQCAo0dPQKvV9XNGREREBAA1NdVYl56Jyup6hJtnYuzUhdAHBsHa1IjyynysWbu5/Ubd1BTeqEuyw8KfiIiIyAs1NdVYsXINVIYZmJ68GAqlCoIAqNVKaHQGhBrMcMYmo+xAFlasXIMN7NJDMsM5/kREREQeiKKIdemZUBlmYELiUiiUrsdOFUoVJiQuhWrodKxLz+SUXZIVFv5EREREHhQVFaCqugFRkxd7tX1U/BJUVtejuLjQx5kReY+FPxEREZEHO3fvhSEiye1I/7kUShUMEUnYsWuPjzMj8h4LfyIiIiIPCopKMcKcICnGaE5AQVGpjzIiko6FPxEREZEHzc1WqLV6STFqjR4tLc0+yohIOnb1kSGlUonk5Ouh0aigVCr7Ox0iIiK/p9PpYWu1AsHex9jarAgIYEtukg8W/jIUEBCA11//K5fzJiIikok4SzTKq/IRFm72OqamMh9xlmgfZkUkDaf6EBEREXkwf+5s1FZmw+mwe7W902FHbVU2Fsyb4+PMiLzHwp+IiIjIA4slDhGmYJQdyPJq+7L9W2E2hSAmJtbHmRF5j4W/DDU1NWHo0CAIgoCmpqb+ToeIiMjvCYKA1akpsNfmoCRvi9uRf6fDjpK8LbCfzsXq1BQIgtDHmRK5xzn+RERE5LdEUURRUQF27t6LwuJStLW1QqPRIjYmGvPnzobFEtdZvBuNJmzISMO69Ezkbs+FISIJpsgE6PTBaLY2oLoiH7VV2TCbQrA6Iw1Go6mfnx1RVyz8iYiIyC/V1FRjXXomKqvrEW6eibFTF0IfGARrUyPKK/OxZu3m9iI+NaWziDcaTdi8aSOKiwuxY9ceFO5bD5utDWq1BrEx0ViwbDliYmI50k+yxMKfiIiI/E5NTTVWrFwDlWEGpicvhkKpgiAAarUSGp0BoQYznLHJKDuQhRUr12DDWSP4giDAYomDxRIHlUrBLnw0YHCOPxEREfkVURSxLj0TKsMMTEhcCoXS9TioQqnChMSlUA2djnXpmRBFsY8zJepdLPyJiIjIrxQVFaCqugFRkxd7tX1U/BJUVtejuLjQx5kR+RYLfyIiIvIrO3fvhSEiye1I/7kUShUMEUnYsWuPjzMj8i3O8ZchpVKJn/50NtRqJZRKZX+nQ0RENKgUFJVi7NSFkmKM5gQU7Fvvo4yI+gYLfxkKCAjA229n8WYhIiIiCbxtzdncbIVaq5e0b7VGj5aWZh9lTtQ3WPgTERHRgCelNadOp4et1QoEe79/W5sVAQE63z0Boj7Awp+IiIgGNKmtOS8ZMwrVVfkICzd7f4zKfMRZon34LIh8j4W/DDU1NWHixLEAgO++OwKtliMMRETkX7ydtnNua053OlpzluSJOFLxCRpaauCMTfbqBl+nw47aqmwsWLa8N58iUZ9j4S9TVqu1v1MgIiLqFd4W8R2kTNs5efIEqqobMC3Z+9acOe/lICzQjrIDWd1+WOhQtn8rzKYQxMTE9vg1IJIDFv5ERETkM1KKeKPRJHnaTmSESXJrznDzTJh0B1F5NAcleSKi4pe4jHc67CjbvxX207lYnZHW5cMJ0UDEPv5ERETkEx1FfIMyBtOTn0VU/CKEhZsRGDIcYeFmRMUvwvTkZ9GgjMGKlWtQXX1M8oq6u/Z+hBHmeEl5Gc0J+PeR77EhIw3Bzm+Qu/0hlOZn4cypCjT+eBJnTlWgND8LudsfQrDzG2zISIPRaOqNl4SoX3HEn4iIiHpdT+ber0hZiYYWLaZLmLbz5YcvoaXNISm3jtacRqMJmzdtRHFxIXbs2oPCfeths7VBrdYgNiYaC5YtR0xMLEf6adBg4U9ERES9rqioQPLc+388/wYuif+ZpGk7Wr0BJ2qOYYRprNe5nd2aUxAEWCxxsFjioFIpuIYODWqc6kNERES9bufuvZLn3ttFHZS6CEnHMY6KwbEjeZJi2JqT/BULfxlSKBSYMeNyJCUlQaHgj4iIiAaegqJSjDAnSIpRKNWwttglxYyZMBOnqj6F0+FdXGdrznlzJB2HaDBgVSlDOp0O77+/B5988gl0OvbwJyKigae52Qq1Vi8pRq3Rw9bWLCkm1GCGWmhE2YEsr7Zna07yZyz8iYiIqNfpdHrYWqWtSTM0PAKNtWWSYo5X7ce82bNgr81BSd4WtyP/TocdJXlb2ltzpqbwhl3yS7y5l4iIiHpdnCUa5VX5CAs3ex2jDwpF3eF9cDrsklbUfejx5Rg2bDjWpWcid3suDBFJMEUmQKcPRrO1AdUV+aitym5fL4CtOcmPsfCXoaamJiQmToIgCDhw4FtotZzuQ0RE8uDtKrzz587GY2ufgzM22esi3tZ4GONGG3q0oq4gCGzNSeQBC3+Zqq2t7e8UiIiIupCyCq/FEocIU7CkIj5yZCgeXfUIHln1WI9W1GVrTqLucY4/EREReSR1Fd7jx2uwOjVF8tx7k2kkV9Ql8hGO+BMREVG3erIK77r0TGzetBEbMtIkz73nirpEvsHCn4iIyE95O1+/J6vw5m7PRXFxISyWuB4V8Zy2Q9T7WPgTERH5ISnz9XuyCq8hIgk7du3p/PDAIp6o/7HwJyIi8jMd8/VVhhmYnrwYCqUKggCo1UpodAaEGsxwxiaj7EAWVqxcgyarFdFXLJR0DKM5AQX71vvoGRBRT/DmXhlSKBSYPDkeiYmJUCj4IyIiot5z7nx9d6P4HfP1VUOn4/DhI1BLbC2t1ujR0iJtFV4i8i1WlTKk0+nwr399iry8POh07OFPRES9p2O+ftRk7+fr2xxAXe1JScextVkREMD3MCI5YeFPRETkR3oyX3/osItR/m22pOPUVOYjzhLdkxSJyEdY+BMREfmRgqJSjDAnSIqZkHgDjpX/020v/nM5HXbUVmVjwbw5PUmRiHyEhb8MWa1WxMZOQGRkJKxWa3+nQ0REg0hzsxVqrV5SzIiIyYD9DMoOZHm1fdn+rTCbQhATE9uTFInIR1j4y5Aoijh6tAqVlZUQRbG/0yEiokFEp9PD1iptUMlua8aY0WMkr8LLBbaI5EVW7TxtNhtuvfVWfPvttwgLC0NOTg5WrVqFd955p3MbQRBQVlbWj1kSERENXHGWaJRX5SMs3Ox1TE1lPqZOiccdt/9C8iq8RCQfsir8BUHArFmzoNfrUV5eDgBITU3Fgw8+CAD4+c9/DqPReAH7B1Sqvv8lh1Kp6PK3J2fnqFQqvM5Z6nEYM/hi5JoXYxgzGGPkmpenmOQFc/Ho7/8IMS65yw2+HaPz7X//97fNTocdp49+iuvu+g1GjboILz6/CUVFhXh/524UfLWhc7XfOEs0Ft71ICyW81fh9eXzYYx/xMg1r76McUfKL9YEUYZzSVatWoXPPvsMOTk5nY8VFRXhxhtvxPr165GcnCx5n2PGjAEAHD58uNfy9JWmpiYEBQUBABobGxEYGNjPGRER0WAhiiJuv/M+/OiciIlTl3rc/tt9WxCqKMH//uVFTt0hkiEpNa6sRvy7s3XrVoSEhGD27Nk93ofTKaKurqkXs/KOUqlASIgO9fXNcDg8L0/e1PTfHOvrm9HW5pvjMGbwxcg1L8YwZjDGyC0vURRRWFiAHbv2oKCoFK2tLdBqAxBnicaCeXMQGxvXWbivXPEwHnrkURTmOhAV37FyrwCVSgG73QlRFOF02FG2Pwv20zl4av1TOHPm/PsC5PYaMGbwxsg1r76MccfpFKFQePehfEAU/i0tLdi1axeSk5Oh1Wp7vB9RBOz2C3txL4TD4fTq+Gdv421MT47DmMEbI9e8GMOYwRgjh7xqaqqxLj0TldX1CDfPxJgpC6APDIK1qRHfVeYj54lN7XPvU1NgNJowfPgIrH86DevSM5HzXk738/WfTsPw4SO6zVcOrwFj/CNGrnn1Zcy5pMzdkV3hf+jQITQ0NMDhcODQoUMwmUzYu3cvGhoacOONN/Z3en1CEASMHx8FpVLBX6sSEVG3amqqsWLlGqgMMzA9uWP0HlCrldDoDAg1mOGMTUbZgSysWLkGG/5z463RaMLmTRtRXFyIHbv2oHDfethsbVCrNYiNicaCZcsRE9P9fH0iGlhkV/jPmzevy9dvvPEGsrKyMHHiRERH+8cKgHq9Hl988TWGDAlEXV1Tv/6WgoiI5EsURaxLz4TKMAMTEt3P11coVZiQuBQlee3bb960EYIgQBAEWCxxsFjioFIp+L5DNMjJrvD/7rvvznts6tSp/ZAJERGRvBUVFaCqugHTkhd7tX1U/BLkbs9FcXEhLJY43yZHRLLDBbyIiIgGqJ2798IQkdSlLWd3FEoVDBFJ2LFrj48zIyI5YuEvQ1arFdOmJWLixImwWqWtrkhERP6joKgUI8wJkmKM5gQUFJX6KCMikjPZTfWh9jmb331X1vk1ERGRK83NVqi1ekkxao0eLS3NPsqIiOSMI/5EREQDlE6nh61V2m+GbW1WBATofJQREckZC38iIqIBKs4SjeNV+ZJiairzEWfxjy55RNQVC38iIqIBav7c2aitzIbTYfdqe6fDjtqqbCyYN8fHmRGRHLHwJyIiGqAsljhEmIJRdiDLq+3L9m+F2RSCmJhYH2dGRHLEwp+IiGiAEgQBq1NTYK/NQUneFrcj/06HHSV5W2A/nYvVqSlcjZfIT7GrjwwJgoBRoyKgUAi8OBMR+SFRFFFUVICdu/eisLgUbW2t0Gi0iI2Jxvy5s2GxxHW+PxiNJmzISMO69Ezkbs+FISIJpsgE6PTBaLY2oLoiH7VV2TCbQrA6Iw1Go6mfnx0R9RcW/jKk1+tRWFjCpdOJiAYBKUU8ANTUVGNdeiYqq+sRbp6JsVMXQh8YBGtTI8or87Fm7eb2Ij41pbOINxpN2LxpI4qLC7Fj1x4U7lsPm60NarUGsTHRWLBsOWJiYjmYROTnWPgTERH5iNQivqamGitWroHKMAPTkxdDoVRBEAC1WgmNzoBQgxnO2GSUHcjCipVrsOGsEXxBEGCxxMFiiYNKpeDgERGdh3P8iYiIfKCjiG9QxmB68rOIil+EsHAzAkOGIyzcjKj4RZie/CwalDFYsXINqquPYV16JlSGGZiQuBQKpeuxOYVShQmJS6EaOh3r0jO50CMReY2Fvww1NzfjmmuuxKWXXormZq6uSEQ00IiiKLmIX5GyEpXVDYiavNirY0TFL0FldT2Kiwt7M3UiGsQ41UeGnE4nDhzY3/k1ERHJg7fz9YuKClBV3YBpyd4X8f94/g1cEv8ztx8SzqVQqmCISMKOXXtgscRdwLMiIn/Bwp+IiMgLUubr79y9F4aIJElFvF3UQamLkJST0ZyAgn3re/J0iMgPsfAnIiLyQOpNt01WK6KvWCjpGAqlGtYW71bg7aDW6NHSwimhROQdzvEnIiLqRk/m6x8+fARqrU7ScdQaPWxt0op4W5sVAQHSjkNE/osj/kRE5Le8mbPfk/n6X338J9TVnkRg8HCvcxkaHoHG2jIA872OqanMR5wl2uvtici/sfAnIiK/5O2c/dCQIMnz9YcOuxjl32bjoshJXuejDwpF3eF9cDrsXh3L6bCjtiobC5Yt9/oYROTfONVHpgwGA8LDw/s7DSKiQUlKj/33dv4TQ43eF/AAMCHxBhwr/yecDu/m7DsddtgaD2PcaAPKDmR5FVO2fyvMphDExMRKyo2I/BcLfxkKDAxEeXklfvjhBwQGBvZ3OkREg4rUOfuioMPRYycAeL9Q1oiIyYD9jKQiPnJkKDKffgr22hyU5G1x+6HB6bCjJG8L7KdzsTo1BYIgeJ0XEfk3Fv5ERORXOubse7tQVnDYSDQ1NaK+vt7rY9htzRgzeozkIt5kGokNGWkIdn6D3O0PoTQ/C2dOVaDxx5M4c6oCpflZyN3+EIKd32BDRhqMRpPXORERcY4/ERH5Fak99oePHI+GH4/i5MkfEBIS6lVMTWU+pk6Jxx23/wLr0jORuz0XhogkmCIToNMHo9nagOqKfNRWZbf3/j+riDcaTdi8aSOKiwuxY9ceFO5bD5utDWq1BrEx0ViwbDliYmI50k9EkrHwl6Hm5mb87GeLoVIp8fe/b4Vare3vlIiIZM/bVXULikoxdqr3PfYvnjgLn+5+DnUj473a/uybbntaxAuCAIslDhZLHFQqBYYMCURdXRPsdq7mTkQ9x8JfhpxOJ3JyPu/8moiIuidlVd3mZivUWr3X+x5+UQz0ej2OH/onkJjocftzb7plEU9EcsHCn4iIBjSpq+oqlUrYWq1AsHf7FwQBcdNvxUdZKSjJG42o+CUupwk5HXaU7d/aPl8/I41TcYhIdlj4ExHRgHVuhx53Ojr0lOSJOHNsC45Xfo2wcLPXx6mvq0Ly/GtR3/CNpPn6RERywsKfiIgGrJ6sqnu0dCe+P7gX4+Kuk7RQ1kOPt8/H5023RDRQsfAnIqIBS2qHHoVShVETrkNV8d9RdiCr298SdDh7zj7n6xPRQMY+/kRENGAVFJVihDlBUowpMhEhIWFcKIuI/A5H/GVKr/e+4wQRkb+S2qEHANQaPUQAGzLSJPfYJyIayFj4y1BgYCC+//4kf4VMROSBTqeX1KEHAGxtVgQE6LhQFhH5HRb+REQ0YMVZolFelS+pQ09NZT7iLNEA2GOfiPwL5/gTEdGANX/ubNRWZrudp3+uzlV1583xcWZERPLDEX8ZamlpwV13/RxqtRJ//vMbUKk0/Z0SEVGfEkURRUUF2Ll7LwqLS9HW1gqNRovYmGjMnzsbFktc52h9hCm4Rx16iIj8DQt/GXI4HPjnP/d2fq3iT4mI/EhNTTXWpWeisroe4eaZGDt1IfSBQbA2NaK8Mh9r1m5uv+k2NQVGowmrU1OwYuUalOSJXFWXiKgbLCmJiMinvB29B9qL/hUr10BlmIHpyYuhUKogCIBarYRGZ0CowQxnbDLKDmRhxco12PCfjjvs0ENE5BkLfyIi8hkpo/cjRhixLj0TKsOMbqftKJQqTEhcipI8EevSM7F500Z26CEi8gILfyIi8gmpo/d33n4zqqobMC15sVf7j4pfgtztuSguLuwy558deoiIXGNXHyIi6nWiKHYZvXc17x747+i9auh0rH0qE0MjrnS7ratYQ0QSduza05upExENWhzxJyIir3k7X7+oqEDy6P1XH/8JMYbxkvIxmhNQsG99T54KEZHfYeFPRERekTJff+fuvTBEJEkavVco9ThTb8VFEnJSa/RoaWnu2RMiIvIzLPxlKDAwEKdPN3J+KhH5lC+77TRZrYi+YqGkfHRBBpypOyUpxtZmRUCATlIMEZG/YuFPROSHfN1t5/A3f4JllrSCfNiIi3HmxLcA5nn/PCrzEWeJlnQcIiJ/xZt7iYj8TMfofYMyBtOTn0VU/CKEhZsRGDIcYeFmRMUvwvTkZ9GgjMGKlWvw0Uf/RFV1A6Imez9f3+YA6mpPSsrrojGJOFOdA6fD7tX2TocdtVXZWDBvjqTjEBH5K474y1BLSwvuv/8eaDQq/PGPL0Gl0vR3SkQkc95O2zm32447Z4/er30qE5GxP5c0X3/osItR/m02Loqc5PVzaGttRHioAmUHsrrNrUPZ/q0wm0IQExPr9TGIiPxZr434nzhxAhUVFb21O7/mcDiwffu72Lp1KxwOR3+nQ0QyV1NTjQd+81usWbsZ5T+YMHZqChLmZGDs1BSU/2DCmrWb8cBvfouamurObjtSRu9PnGpAsMRuOxMSb8Cx8n9KGr0/ffRTPPboI7DX5qAkb4vbWKfDjpK8LbCfzsXq1BQuykVE5KULGvFvaGjAs88+i507d6KhoQGCIODAgQO477774HA48Pjjj2Ps2LG9lSsREZ1D6k23kRGmPum2MyJiMmA/I3n0/qqrZiE6eiLWpWcid3suDBFJMEUmQKcPRrO1AdUV+aitym6//yAjDUajSUJWRET+rceFf319PW6++WYcOXIEoih2Pq7VaqHRaJCdnY3du3fj/vvv75VEiYioq55M29m19y+Yc9vNko7Tk247dlszxowe85/RexFR8UtcfthwOuwo27+1ffQ+Iw2CIMBoNGHzpo0oLi7Ejl17ULhvPWy2NqjVGsTGRGPBsuWIiYnlSD8RkUQ9LvxfeOEFHD58GACg0+nQ3PzfPsqXXXYZPvnkE3z22Wcs/ImIfKQni2R9+eFLaGmTNoWwp912pk6Jxx23/6JHo/eCIMBiiYPFEgeVSsH2xkREvaDHhf8///lPCIKARYsW4YYbbsBtt93W+b2LLmr/hfCxY8cuPEMiInKpJ4tkafUGnKg5hhEm76dhXjQmEV/+6yU4Hb/16lid3XaWLefoPRGRjPS48D9x4gQAYP78+eddsHW69t7NZ86c6XlmRETUrYKiUoydKm2RLOOoGBw7kofYhCu9jrnQbjscvScikoceF/7BwcE4c+YMKioqMH58124PBw4cAACEhYVdUHJERP7I29aczc1WqLV6SfseM2EmPt21EU7Hb7weve/otvPq629Jnq9PRETy0ePCPy4uDh9//DGeffZZzJ49u/Px5557Dq+88goEQUB8fHyvJOlv9Ho9jh49gSFDAtHaKsLhED0HEdGgIGVFXZ1OD1urFQj2fv+hBjPUQiO77RAR+aEeF/533XUXsrOz0dTUhG3btnWO7Dz//PMQRRFKpRJ33HFHryXqTwRBQGBgIAIDA9HW1gSAhT+RP5DamvOSMaNQXZWPsHCz18c4XrUf82bPQuVRdtshIvI3PS78ExMT8fvf/x5r165FW1tbl+9pNBo89thjmDx58gUnSETkD3rSmvNIxSdoaKmBMzZZ0k23Dz2+HMOGDWe3HSIiP3NBC3jdeOONuPLKK7Fnz57OVXsjIyMxZ84c/OQnP5G8P5vNhltvvRXffvstwsLCkJOTAwD44IMP8Mwzz6CmpgbTp0/HSy+9dCFpy15rayt+85sHodGo8PTTz0KpVPd3SkTkYz1pzZnzXg7CAu09uulWEASO3hMR+ZkeFf7Nzc149dVXAbSP/N9+++29kowgCJg1axb0ej3Ky8sBABUVFXjwwQdx++23Y9GiRSgoKLiA/QMqlaJXcpVCqVR0+duT1lYn3nrrbwCA9PQNXucs9TiMGXwxcs2LMZ5jdu/9AAZzEpSqrpfljsK7/e//TvtTqlQYFjkTJv1BVFbloPRrICq+Y3pQ15j2aTtZcNTl4vH1T0GtVnbuJz4+HvHx8VAqFQgJ0aG+vhkOh3ej93J43fozRq55MYYxgzFGrnn1ZYw7UsZnBPHsZXcliImJgd1ux/PPP4+rr766J7twa9WqVfjss8+Qk5ODF198ES+99BLy8vKg0Wh6vM8xY8YAQOeiY3LW1NSEoKAgAEBjYyMCAwP7OSMi8rXZ827EmMsewZDwSK9j6n6owOF96/GXP/0BqWvW4nBVHcIjkmCMTIRao4etzYqaiq9xqiobYyKGID3tMYwcOdJ3T4KIiPqclBq3x1N9xowZg4MHD8Jut/d0F16pqamBWq3GkiVLcObMGdx222245557erQvp1NEXV1TL2fomdSRtKam/+ZYX9+Mc26h6LXjMGbwxcg1L3+OEUURhYUF2LFrDwqKStHa2gKtNgBxlmgsmDcHsbHtrTnr6xshKAJgs3VdVVcQBKhUCtjtTpw7TiMotKhvaIJeH4Y/PLMBRUWFeH/nbhTkZnS2AI2zROPB25fDYmmftuPuGii3120gxMg1L8YwZjDGyDWvvoxxx+kUoVB4N+zf48L//vvvx/Lly/Hqq69i2rRpCA6W0E9OgrCwMDQ0NOC+++5Dfn4+nnnmGcyaNavz040Uooh+vQHN4XB6dfyzt/E2pifHYczgjZFrXv4Wc25rzjFTFnS25vyuMh85T2zqbM0ZoNOhrcUKfdC5e2kv9kVRxLm/n21rtSIgIKDz+BMnWjBxosXlTbftbYE9/4JXDq/bQIuRa16MYcxgjJFrXn0Zcy4pc3d6XPh/9NFHGDlyJAoLCzFz5kzEx8cjPDy8yzaCIOCpp56StN9Dhw6hoaEBDocDhw4d6lwLQKvVQq1uv8m1428iIrnqi9acNZX5iLNE+/BZEBHRYNLjwv+dd96BIAgQBAFNTU34/PPPXW4ntfCfN29el6/feOMN/M///A8effRRKJVKpKamYtSoUT1Nm4jI5/qyNeeCZct7M3UiIhrELqid59nzTV3dI9yTNnDffffdeY9NnToVy5fzzY2I+pcoiigqKsDO3XtRWFzaOY8+NiYa8+fOhsXSPl+/r1tzEhEReaPHhf8bb7zRm3nQWfR6PQ4ePIKwsEAolbr/zM0lov507nz9sVMXds7XL6/Mx5q1mzvn6+/cvReGiCSvRu6B9pH/cPNMmHQHe7SiLhERkTd6XPhPmTKlN/OgswiCgPDwYZ0353lzQx4R+Y7U+fpNViuir1go6RhGcwL+ve8jbHomvUcr6hIREXlyQVN9AODEiRPYu3dvl5V7Z8+e3aOVe4mI5KYn8/UPf/MnWGbpJB1HrdGjpaUZRqOJK+oSEZFPXFDhv2XLFjz11FOw2WxdHt+wYQNWr16NpUs9z1Ol87W2tiI19VFotWo89thaKJXsYkTUX3oyX/+rj/+EutqTCAwe7vVxbG1WBAS0f1gQBAEWSxwsljiXrTmJiIh6osfrBH/xxRf4/e9/D5vN9p/+0v/909bWht///vf48ssvezNXv2G32/Hqq3/CCy+84PMF0oioez2Zrz902MUo/zZb0nHYmpOIiHytx4X/a6+9BlEUIQgCrr32WqxYsQKPPPIIrr32WigUCoiiiL/85S+9mSsRUZ8rKCrFCHOCpJgJiTfgWPk/4XR498G9szXnvDk9SZGIiMgrPZ7qU1hYCEEQcN999+GBBx7o8r3Nmzfj+eefR2Fh4QUnSETUn5qbrVBr9ZJiRkRMBuxn2JqTiIhkpccj/k1NTQCA2Njz36g6HuvYhohooNLp9LC1WiXF2G3NGDN6DOy1OSjJ2+J25N/psKMkb0t7a87UFN6wS0REPtXjwj88PBxA+wq+Doej83Gn04l33nmnyzZERANVnCUax6vyJcXUVOZj6pR4bMhIQ7DzG+Rufwil+Vk4c6oCjT+exJlTFSjNz0Lu9ocQ7PwGG9iak4iI+kCPp/pMmzYN77zzDvbs2YOvv/4aEydOBACUlJTghx9+gCAImDZtWq8lSkTUH+bPnY3H1j4HZ2yyVzf4ds7XX7acrTmJiEhWelz433ffffjggw9gtVpx6tQpZGf/t4OFKIoICgrCfffd1ytJEhH1F4slDhGm4B7P12drTiIikoseT/WJiIjAa6+9hjFjxpzXznPs2LH4y1/+goiIiN7M1W/odDoUFHyLI0eOQKeTtggQEfUuQRCwOjWF8/WJiGjAu6AFvCwWC3bu3InS0lIcOXIEADB69GhER7MX9YVQKBSIiDB3jgw6nRwZJOptoiiiqKgAO3fvRWFxKdraWqHRaBEbE435c2fDYonrLN6NRhM2ZKRhXXomcrfnwhCRBFNkAnT6YDRbG1BdkY/aqmyYTSFYzfn6REQkUxdU+HeIjo5msU9EA0ZNTTXWpWeisroe4eaZGDt1IfSBQbA2NaK8Mh9r1m5uL+JTUzqLeM7XJyKiga7Hhf/f/vY37N27F0ajERkZGV2+l5KSguPHj2P27Nm49dZbLzhJf9PW1oYnn1yLgAA1Vqx4FApFr3w+IyK0F/0rVq6ByjAD05MXQ6FUQRAAtVoJjc6AUIMZzthklB3IwoqVa7p03OF8fSIiGsh6PMc/KysLeXl5GD9+/HnfmzBhAr766itkZWVdUHL+ymaz4bnnNmHDhg2w2Wz9nQ7RoCGKItalZ0JlmIEJiUvddulRKFWYkLgUqqHTsS49E6Io9nGmREREva/HhX9lZSUAuCz8L7nkki7bEBHJQVFRAaqqGxA1ebFX20fFL0FldT2Ki7kKORERDXw9nkPSsWhXTU3Ned/reOzshb2IiHzF2xt1d+7eC0NEklf9+IH2kX9DRBJ27NoDiyXOt0+CiIjIx3pc+I8cORKHDh3CCy+8gISEBIwePRoAcOTIEbz44oud2xAR+ZKUG3ULikoxdupCSfs3mhNQsG+9j7InIiLqOz0u/K+++mocOnQINTU1WLhwIS666CIAwPfffw+73Q5BEHD11Vf3WqJEROeSeqNu/Y8/Qq3VSzqGWqNHS0uzj54BERFR3+nxHP+7774bRqMRoijCbrejsrISlZWVsNvbF7cZMWIE7rrrrl5LlIjobD25UffEyZOwtTZJOo6tzYqAAC6kR0REA1+PC//Q0FC89dZbmDlzJhQKReeqvQqFAjNnzsTf//53hIWF9WKqRET/1ZMbdQWFCkfKPpd0nJrKfMRZuE4JERENfBfUIH7EiBF46aWX8OOPP3Z28DGbzQgNDe2V5PyVTqdDTs5XCA3VQ6fTgQv3Ep2vJzfqmqN+isPf7EDstJu9inM67KitysaCZcsvNF0iIqJ+1ysrQykUCvzrX/9CSUkJnE4nYmJi8POf/xwGg6E3du93FAoFoqMndC4O5GTlTwOUt912ehLTkxt1x0++Hke+3YGyA1mYkLjU4/Zl+7fCbApBTEyspOMQERHJkaTC//nnn8eLL76I0NBQfPTRR9BqtWhubsbixYtx9OjRzu1yc3Oxbds2bN26FcOHD+/1pIlI/qR02+lYGVdKTHOzVfKNuhptIEb85Cew1+agJE9EVPwSlyP/TocdZfu3wn46F6sz0s77cEJERDQQSSr8i4uLYbfbcc0110Cr1QIAtmzZgqqqqvO2/eGHH/Dyyy/jscce651M/UhbWxs2bHgGOp0G9933GygUvfKLGaI+I7XbzoaMNACQFKNUKmFrtQLB3udla7MiJHQINmSkYV16JnK358IQkQRTZAJ0+mA0WxtQXZGP2qrs9g8YGWmdH0qIiIgGOkkV5eHDhyEIAmJiYjof++c//wkAEAQBP/3pT3H99dfjD3/4Aw4ePIjPP5d2Ex21s9lsyMxMBwDcffevodWy8KeB49xuO+50dNspyROR9lQGIAiSYs4c24LjlV8jLNzsdW4dN+oajSZs3rQRxcWF2LFrDwr3rYfN1ga1WoPYmGgsWLYcMTGxHOknIqJBRVJFefr0aQDo7Nlvs9lQXFwMoH1e+hNPPIGhQ4eipaUFDz30kMtVfYlocOvotjMt2ftuO//8204o1TpcfZP3MUdLd+L7g3sxLu66Ht2oKwgCLJY4WCxxUKkUnffU2O28p4aIiAYnSe08W1paAABNTe19sIuKimCz2SAIAsaPH4+hQ4cCQOdNvSoVR6qJ/E1Puu20OvRQhsRJihk14TrYW06h7ECWVzG8UZeIiPydpMK/40bdt956C+Xl5Xj11Vc7v3fZZZd1fn3y5EkAwLBhw3ojRyIaQAqKSjHCnCApprWtFeqgSEkxpshEhISE/edG3S1wOuwut3M67CjJ29J+o25qCqfvEBGR35JU+E+fPh2iKCI3NxfJycn4+OOPO783Z86czq/z8vIAAKNGjeqlNIlooOhJtx2HvQ2CQiMpRq3RQwSwISMNwc5vkLv9IZTmZ+HMqQo0/ngSZ05VoDQ/C7nbH0Kw8xts4I26RETk5yTNxXnggQfwySef4NSpU10eX7hwISwWCwDAarViz549EAQB06dP771MiWhA0On0krvtKFUaiM42ScextVkREKDjjbpEREReklT4/+QnP8G7776LN998EyUlJQgMDMT06dOxZMmSzm1KSkqQlJQEAJg1a1bvZktEshdniUZ5Vb6kbjtajRa2xiOSjtPRoQfgjbpERETekHz3bXh4OH7729+6/X5iYiISExMvKCl/FxAQgA8/zEZIiA4BAQEQxf7OiMh78+fOxmNrn4MzNtnrbjtapRWO+kI4HfYedeghIiIizyTN8ae+oVQqER+fgEsvvRRKpbK/0yGSxGKJQ4QpWFK3nehxERg3Zjg79BAREfkQ+20SkVdEUURRUQF27t6LwuJStLW1QqPRIjYmGvPnzobFEgdBECAIAlanpmDFyjUoyRMRFb/E5Si+02FH2f6tsJ/OxZqzVu71NmZ1Rhrn7RMREUnAwl+G2tra8MILL0Gv1+AXv7gbCgV/TNS/amqqsS49E5XV9Qg3z8TYqQuhDwyCtakR5ZX5WLN2M8ymEKxOTYHRaILRaMKGjDSsS89E7vZcGCKSYIpMgE4fjGZrA6or8lFbld0ec1a3nZ7EEBERkXdYUcqQzWbDE0+sAQDccsvt0Gr5Y6L+U1NTjRUr10BlmIHpyYuhUKogCIBarYRGZ0CowQxnbDLKDmRhxco1nW0ze9Jthx16iIiIfIcVJRG5JYoi1qVnQmWYgQmJS91up1CqMCFxKUry2rffvGlj57Qfqd122KGHiIjIN3hzLxG5VVRUgKrqBkRNXuzV9lHxS1BZXY/i4kIfZ0ZERERSsfAnIrd27t4LQ0SSVy02gfaRf0NEEnbs2uPjzIiIiEgqFv5E5FZBUSlGmBMkxRjNCSgoKvVRRkRERNRTLPyJyK3mZivUWr2kGLVGj5aWZh9lRERERD3Fm3uJ/JC3Pfl1Oj1srVYg2Pt929qsCAjQ+S55IiIi6hEW/jIUEBCA7dt3IThYh4CAAIhif2dEcuZtEd9BSk/+OEs0yqvyERZu9jqfmsp8xFmiffFUiYiI6AKw8JchpVKJyy+/km0MySOpC2tJ7cl/5+0348sX34YzNtmrG3ydDjtqq7KxYNnyPnj2REREJAXn+BMNUB1FfIMyBtOTn0VU/CKEhZsRGDIcYeFmRMUvwvTkZ9GgjMGKlWtQXX2sS09+d4V8R09+1dDp2PbuTowyBaPsQJZXOZXt3wqzKQQxMbG9+VSJiIioF7DwlyGbzYY///llPP/887DZbP2dDsnQuQtreVPEr0hZiUqJPfmrahqw+Pr5sNfmoCRvC5wOu8ttnQ47SvK2wH46F6tTU7iyLhERkQyx8JehtrY2pKQ8jPvvvx9tbW39nQ7JUE8W1iorr4J+2KWSe/J/+VU+NmSkIdj5DXK3P4TS/CycOVWBxh9P4sypCpTmZyF3+0MIdn6DDRlpMBpNF/LUiIiIyEc4x59oAOrJwlp2UQelLkLScYzmBBTsWw+j0YTNmzaiuLgQO3btQeG+9bDZ2qBWaxAbE40Fy5YjJiaWI/1EREQyxsKfaAAqKCrF2KkLJcUolGpYW1xP1XHn7J78giDAYomDxRIHlUrBm8+JiIgGGE71IRqAerqwlq1N2sJa7MlPREQ0eLDwJxqAOhfWkmBoeAQaa8skxbAnPxER0eDBwp9oAIqzRON4Vb6kGH1QKJpP5bntzHOuzp788+b0JEUiIiKSGRb+RAPQ/LmzUVuZLamItzUexrjRBvbkJyIi8lMs/GVIq9Viy5at2LFjB7RabX+nQzJkscQhQuLCWpEjQ5H59FPsyU9EROSnZFX422w23HTTTZg4cSJmzJgBANi3bx/Gjx/f+efee+/t5yx9T6VS4dpr52D+/PlQqdh4ic4nCAJWp6ZILuJNppHsyU9EROSnZFVVCoKAWbNmQa/Xo7y8vMv3srOzAYAj4DToiaKIoqIC7Ny9F4XFpWhra4VGo0VsTDTmz50NiyUOgiDAaDRhQ0Ya1qVnInd7LgwRSTBFJkCnD0aztQHVFfmorcqG2RSC1WcV8ezJT0RE5J9kVfirVCrcc889OHz48HmF/w033IDhw4cjNTUVl112WY/2LwiAStX3v+RQKhVd/vbEZrNhy5a3oNNpsHDhIqhUSp8chzHyi6mursbapzJQeexHGCJm4uLLkqHTB6LZ2oTyiq/xWNpmmEeG4rFHV8JkMmHUqIvw4vObUFRUiPd37kbBVxs6PyjEWaKx8K4HYbG4LuLj4+MRHx8PpVKBkBAd6uub4XB415NfTq8ZYxjTXzFyzYsxjBmMMXLNqy9j3JEyTieIoihe8BF72apVq/DZZ58hJycHVVVVOHjwIEwmE373u9+huroan3/+ueTRyDFjxgAADh8+7IuUe1VTUxOCgoIAAI2NjQgMDOznjKgvHDt2DPf++mEow2YgOnGxy1V5nQ47Sr/OguNMDl5+4RmMHDmyHzIlIiIiuZBS48pqxN+ViIgIREREAADmz5+P9PR01NXVYejQoZL35XSKqKtr6u0UPZI6otrU9N8c6+ub0dbmm+MwRj4xoiji4ZTfQQyehnHxS+BwAg6nA4IgQKVSwG53ov0zuoBx8UtQkufAwym/wwub/9DlQ7AcngtjGOMvMXLNizGMGYwxcs2rL2PccTpFKBTeDYjLrvA/dOgQGhoa4HA4cOjQIZSUlECtVuOSSy7BBx98gPDwcAwZMqRH+xZFwG6/sBf3QjgcTq+Of/Y23sb05DiMkU9MYeEBVH5fj2nJi9D1d3Dt/xBFscvj4ycvRu72HBw4cAAWS5zP8mIMYxgjj2MwhjGMkXdefRlzLilzd2TV1QcA5s2bhw8//BB1dXWYN28eAgICkJmZieuvvx4NDQ3YuHEjbzqkQWfn7r0wRCS5nN7jikKpgiEiCTt27fFxZkRERDRYyG7E/7vvvjvvsZ/+9Kf9kAlR3ykoKsXYqQslxRjNCSjYt95HGREREdFgI7sRfyJ/1NxshVqrlxSj1ujR0tLso4yIiIhosGHhTyQDOp0etlarpBhbmxUBATofZURERESDjeym+lD7ImV/+csbCAoK4IJlfiLOEo3yqnyEhZu9jqmpzEecJdqHWREREdFgwhF/GVKpVLj++kW48cYboVLxs5k/mD93Nmors+F02L3a3umwo7YqGwvmzfFxZkRERDRYsPAnkgGLJQ4RpmCUHcjyavuy/VthNoUgJibWx5kRERHRYMHhZBmy2+3YsWMHgoICMHPmteDns4FLFEUUFRVg5+69KCwuRVtbKzQaLWJjojF/7mxYLHEQBAGCIGB1agpWrFyDkjwRUfFL3K7cW7Z/K+ync7E6I42tbYmIiMhrLPxlqLW1FXfe+QsAwNGjJ6DV8gZOOfC2iO9QU1ONdemZqKyuR7h5JsZOXQh9YBCsTY0or8zHmrWbYTaFYHVqCoxGE4xGEzZkpGFdeiZyt+fCEJEEU2QCdPpgNFsbUF2Rj9qq7PaYjDQYjaZ+fDWIiIhooGHhT+QFqUV8TU01VqxcA5VhBqYnL4ZCqYIgAGq1EhqdAaEGM5yxySg7kIUVK9dgw38KeaPRhM2bNqK4uBA7du1B4b71sNnaoFZrEBsTjQXLliMmJpYj/URERCQZC38iD6QW8eufXounnl4PlWEGJiQudbtfhVKFCYlLUZInYl16JjZv2tg57cdiiYPFEgeVSoEhQwJRV9d0wUt6ExERkX/j5HGibohie1HeUcS7mncP/LeIVw2djhUpK1FZ3YCoyYu9OkZU/BJUVtejuLiwN1MnIiIi6oKFP1E3iooKUCWxiC8rr4J+2KVuPyScS6FUwRCRhB279lxIqkRERETdYuFP1I2du/fCEJEkqYi3izoodRGSjmM0J6CgqLQnKRIRERF5hYU/UTcKikoxwpwgKUahVMPa4t1CXB3UGj1aWpolxRARERFJwZt7ZUij0eC5515CYKAWGo2mv9Pxa83NVqi1ekkxao0etjZpRbytzYqAALZtJSIiIt9h4S9DarUaP/vZbezmIgM6nR62VisQ7H3M0PAINNaWAZjvdUxNZT7iLNHSEyQiIiLyEqf6EHUjzhKN41X5kmL0QaFoPpUHp8O76T5Ohx21VdlYMG9OT1IkIiIi8goLfxmy2+344IM92LlzJ+x2aXPFqXfNnzsbtZXZkop4W+NhjBttQNmBLK9iyvZvhdkUgpiY2AtJlYiIiKhbnOojQ62trbj55iUAgKNHT0Cr5dzv3iaKIoqKCrBz914UFpeira0VGo0WsTHRmD93NiyWuM6FtCJMwSg7kNXtYlwdyvZvReTIUDy66hE8suoxlOSJiIpf4rIrkNNhR9n+rbCfzsXqjDSuxktEREQ+xcKf/E5NTTXWpWeisroe4eaZGDt1IfSBQbA2NaK8Mh9r1m6G2RSC1akpMBpNWJ2aghUr10gq4o1GEzZkpGFdeiZyt+fCEJEEU2QCdPpgNFsbUF2Rj9qq7Pbj/Gd7IiIiIl9i4U9+paamGitWroHKMAPTkxdDoVRBEAC1WgmNzoBQgxnO2GSUHcjCipVrsOECinij0YTNmzaiuLgQO3btQeG+9bDZ2qBWaxAbE40Fy5YjJiaWI/1ERETUJ1j4k98QRRHr0jOhMszodtqOQqnChMSlKMlr337zpo09LuI7pgtZLHFQqRTs1ERERET9hoU/+Y2iogJUVTdgWvJir7aPil+C3O25KC4u7DLnn0U8ERERDUTs6kN+Y+fuvTBEJLmco++KQqmCISIJO3bt8XFmRERERL7Hwp/8RkFRKUaYEyTFGM0JKCgq9VFGRERERH2HU31kSKPRIDPzGej1Wmg0mv5OZ9BobrZCrdVLilFr9GhpafZRRkRERER9h4W/DKnVatx9972cQ97LdDo9bK1WINj7GFubFQEBXEeBiIiIBj4W/jTgebsYV5wlGuVV+QgLN3u975rKfMRZon2YPREREVHfYOEvQw6HA19++TmCg3WYNCkeAPu8uyNlMa75c2fjsbXPwRmb7NUNvk6HHbVV2ViwbHkfPBMiIiIi32LhL0MtLS1ITp4HADh69AS0Wk41cUXqYlzrn16LCFMwyg5kddvHv0PZ/q0wm0IQExPbB8+GiIiIyLfY1YcGpHMX43I3gt+xGJdq6HQ89fR6PLrqEdhrc1CStwVOh91ljNNhR0neFthP52J1agpX1iUiIqJBgYU/DUgdi3FFTfZ+Ma7K6nqcOvUDNmSkIdj5DXK3P4TS/CycOVWBxh9P4sypCpTmZyF3+0MIdn6DDRlpMBpNPn4mRERERH2DU31oQLqQxbgeXbUKmzdtRHFxIXbs2oPCfeths7VBrdYgNiYaC5YtR0xMLEf6iYiIaFBh4U8DUkFRKcZOXSgpxmhOQMG+9QAAQRBgscTBYomDSqVg61QiIiIa9DjVhwYkLsZFREREJA0LfxqQOhfjkoCLcREREZE/41QfGVKr1XjiiTTo9Rqo1er+TkeWuBgXERERkTQc8ZchjUaD5csfxCOPPAKNRtPf6cjS/LmzUVuZ7bYl57k6F+OaN8fHmRERERHJEwt/GpAslrjOxbi8wcW4iIiIyN+x8Jchh8OB/fvzkZeXB4fD0d/pyJIgCFidmsLFuIiIiIi8xDn+MtTS0oJZs5IAAEePnoBWyxtSXTEaTdiQkYZ16ZnI3Z4LQ0QSTJEJ0OmD0WxtQHVFPmqrsmE2hWA1F+MiIiIiP8fCnwY0o9HExbiIiIiIvMDCnwY8LsZFRERE5Bnn+BMRERER+QGO+JOsiKKIoqIC7Ny9F4XFpWhra4VGo0VsTDTmz50NiyWO03aIiIiIeoCFP8lGTU011qVnorK6HuHmmRg7dSH0gUGwNjWivDIfa9Zubr9RNzWFN+oSERERScTCn2ShpqYaK1augcowA9OTF0OhVEEQALVaCY3OgFCDGc7YZJQdyMKKlWuwgV16iIiIiCRh4S9DarUaKSmp0Ok0UKvV/Z2Oz4miiHXpmVAZZmBC4lK32ymUKkxIXIqSvPbtN2/ayGk/RERERF7izb0ypNFosGrVajzxxBPQaDT9nY7PFRUVoKq6AVGTF3u1fVT8ElRW16O4uNDHmRERERENHiz8qd/t3L0XhogkKJTe/QJKoVTBEJGEHbv2+DgzIiIiosGDhb8MOZ1OlJaW4Ntvv4XTOfh70RcUlWKEOUFSjNGcgIKiUh9lRERERDT4cI6/DDU3N2PGjCkAgKNHT0Cr1fVzRr7V3GyFWquXFKPW6NHS0uyjjIiIiIgGH474U7/T6fSwtVolxdjarAgIGNwfiIiIiIh6Ewt/6ndxlmgcr8qXFFNTmY84S7SPMiIiIiIafFj4U7+bP3c2aiuz4XTYvdre6bCjtiobC+bN8XFmRERERIMHC3/qdxZLHCJMwSg7kOXV9mX7t8JsCkFMTKyPMyMiIiIaPFj4U78TBAGrU1Ngr81BSd4WtyP/TocdJXlbYD+di9WpKVy8i4iIiEgCdvUhWTAaTdiQkYZ16ZnI3Z4LQ0QSTJEJ0OmD0WxtQHVFPmqrsmE2hWB1RhqMRlN/p0xEREQ0oMiq8LfZbLj11lvx7bffIiwsDDk5OZ3fe/bZZ/Hyyy/jl7/8JVasWNGPWfqeWq3G/ff/BgEBaqjV6v5Op88YjSZs3rQRxcWF2LFrDwr3rYfN1ga1WoPYmGgsWLYcMTGxHOknIiIi6gFZFf6CIGDWrFnQ6/UoLy/vfPz06dN4++23e2H/gErV97OblEpFl789UakCsG5dOkJCdKivb4bD4d0iXlKPI9eY+Ph4xMfHQ6lU+O1r0NMYuebFGMYMxhi55sUYxgzGGLnm1Zcx7kgZDxVEURQv+Ii9bNWqVfjss886R/yffvpp2O12vPnmmz0e8R8zZgwA4PDhw72aKxERERFRf5FS48pqxN+VkydP4t1338WOHTvw5ptvXtC+nE4RdXVNvZSZ96SOXDudTlRXH0NwcADCwobB249mPR0hZ8zgiZFrXoxhzGCMkWtejGHMYIyRa159GeOO0ylCofBu2F/2hf+rr76KRYsWISwsDAAgiiJEUezRPG9RBOz2C3txL4TD4fTq+E1NTbD8Z3Gqo0dPQKuVtkKtt8dhzOCNkWtejGHMYIyRa16MYcxgjJFrXn0Zcy4pc3dkV/gfOnQIDQ0NcDgcOHToEMrLy5GTk4NXX30VAPDnP/8ZkZGRuPHGG/s5U/JEFEUUFRVg5+69KCwuRVtbKzQaLWJjojF/7mxYLHG8UZeIiIioj8iu8J83b16Xr9PS0vDb3/4WALBkyRLccMMNuOaaa/orPfJSTU011qVnorK6HuHmmRg7dSH0gUGwNjWivDIfa9Zubm/NmZrC1pxEREREfUB2hf93333Xo++RfNTUVGPFyjVQGWZgevJiKJQqCAKgViuh0RkQajDDGZuMsgNZWLFyDTawLz8RERGRz3HlXupVoihiXXomVIYZmJC4FAql68+WCqUKExKXQjV0OtalZ0KGzaWIiIiIBhUW/tSriooKUFXdgKjJi73aPip+CSqr61FcXOjjzIiIiIj8Gwt/6lU7d++FISLJ7Uj/uRRKFQwRSdixa4+PMyMiIiLyb7Kb40+ASqXCXXf9ElqtGirVwPoRFRSVYuzUhZJijOYEFOxb76OMiIiIiAhg4S9LWq0W69dvxJAhgaira+rXtQekam62Qq3VS4pRa/RoaWn2UUZEREREBHCqD/UynU4PW6tVUoytzYqAAGmLlBERERGRNCz8ZUgURZw69QN++OGHAdftJs4SjeNV+ZJiairzEfeflYqJiIiIyDdY+MuQ1WrFuHGjMXz4cFit0kbP+9v8ubNRW5kNp8Pu1fZOhx21VdlYMG+OjzMjIiIi8m8s/KlXWSxxiDAFo+xAllfbl+3fCrMpBDExsT7OjIiIiMi/sfCnXiUIAlanpsBem4OSvC1uR/6dDjtK8rbAfjoXq1NTIAhCH2dKRERE5F/Y1Yd6ndFowoaMNKxLz0Tu9lwYIpJgikyATh+MZmsDqivyUVuVDbMpBKsz0mA0mvo7ZSIiIqJBj4U/+YTRaMLmTRtRXFyIHbv2oHDfethsbVCrNYiNicaCZcsRExPLkX4iIiKiPsLCn3xGEARYLHGwWOKgUikG5LoERERERIMF5/gTEREREfkBjvjLkEqlwi233AqNRgWVij8iIiIiIrpwrCplSKvV4vnnX+bUGCIiIiLqNZzqQ0RERETkBzjiL0OiKKKpqQkaTfvXREREREQXioW/DFmtVowebQQAHD16Alqtrp8zav8AUlRUgJ2796KwuBRtba3QaLSIjYnG/LmzYbHEsTUnERERkYyx8CePamqqsS49E5XV9Qg3z8TYqQuhDwyCtakR5ZX5WLN2c/tiXKkpXIyLiIiISKZY+FO3amqqsWLlGqgMMzA9eTEUShUEAVCrldDoDAg1mOGMTUbZgSysWLkGG7gSLxEREZEs8eZecksURaxLz4TKMAMTEpdCoXT9OVGhVGFC4lKohk7HuvRM3pdAREREJEMs/MmtoqICVFU3IGryYq+2j4pfgsrqehQXF/o4MyIiIiKSioU/ubVz914YIpLcjvSfS6FUwRCRhB279vg4MyIiIiKSioU/uVVQVIoR5gRJMUZzAgqKSn2UERERERH1FG/ulSGlUonk5Ouh0aigVCr7LY/mZivUWr2kGLVGj5aWZh9lREREREQ9xcJfhgICAvD663/FkCGBqKtrgt3u7Jc8dDo9bK1WINj7GFubFQEB/b/uABERERF1xak+5FacJRrHq/IlxdRU5iPOEu2jjIiIiIiop1j4k1vz585GbWU2nA67V9s7HXbUVmVjwbw5Ps6MiIiIiKRi4S9DTU1NGDo0CIIgoKmpqd/ysFjiEGEKRtmBLK+2L9u/FWZTCGJiYn2cGRERERFJxcKf3BIEAatTU2CvzUFJ3ha3I/9Ohx0leVtgP52L1akpEAShjzMlIiIiIk94cy91y2g0YUNGGtalZyJ3ey4MEUkwRSZApw9Gs7UB1RX5qK3KhtkUgtUZaTAaTf2dMhERERG5wMKfPDIaTdi8aSOKiwuxY9ceFO5bD5utDWq1BrEx0ViwbDliYmI50k9EREQkYyz8ySuCIMBiiYPFEgeVStHvrUaJiIiISBrO8SciIiIi8gMs/ImIiIiI/ACn+siQUqnET386G2q1Ekqlsr/TISIiIqJBgIW/DAUEBODtt7M4j56IiIiIeg2n+hARERER+QEW/kREREREfoCFvww1NTXhoouGIzAwEE1NTf2dDhERERENApzjL1NWq7W/UyAiIiKiQYQj/kREREREfoAj/n5IFEUUFRVg5+69KCwuRVtbKzQaLWJjojF/7mxYLHEQBKG/0yQiIiKiXsTC38/U1FRjXXomKqvrEW6eibFTF0IfGARrUyPKK/OxZu1mmE0hWJ2aAqPR1N/pEhEREVEvYeHvR2pqqrFi5RqoDDMwPXkxFEoVBAFQq5XQ6AwINZjhjE1G2YEsrFi5Bhsy0lj8ExEREQ0SnOPvJ0RRxLr0TKgMMzAhcSkUStef+RRKFSYkLoVq6HSsS8+EKIp9nCkRERER+QILfxlSKBSYMeNyJCUlQaHonR9RUVEBqqobEDV5sVfbR8UvQWV1PYqLC3vl+ERERETUv1j4y5BOp8P77+/BJ598Ap1O1yv73Ll7LwwRSW5H+s+lUKpgiEjCjl17euX4RERERNS/WPj7iYKiUowwJ0iKMZoTUFBU6qOMiIiIiKgvsfD3E83NVqi1ekkxao0eLS3NPsqIiIiIiPoSC38ZampqwiWXmDFs2DA0NTX1yj51Oj1srdJWA7a1WREQ0DtTjYiIiIiof7Hwl6na2lqcOnWq1/YXZ4nG8ap8STE1lfmIs0T3Wg5ERERE1H9Y+PuJ+XNno7YyG06H3avtnQ47aquysWDeHB9nRkRERER9gYW/n7BY4hBhCkbZgSyvti/bvxVmUwhiYmJ9nBkRERER9QUW/n5CEASsTk2BvTYHJXlb3I78Ox12lORtgf10LlanpkAQhD7OlIiIiIh8QVaFv81mw0033YSJEydixowZAIAvvvgCV1xxBSZNmoT58+cjLy+vn7McuIxGEzZkpCHY+Q1ytz+E0vwsnDlVgcYfT+LMqQqU5mchd/tDCHZ+gw0ZaTAaTf2dMhERERH1Eu9Wc+ojgiBg1qxZ0Ov1KC8vBwAMHz4cf/jDHxAYGIi7774bL730Ei699NIe7h9Qqfr+s45Sqejytydn56hUKrzO2ZvjjBp1EV58fhOKigrx/s7dKPhqA9raWqHRaBFnicbCux6ExRLb7Ui/1OfDmL6LkWtejGHMYIyRa16MYcxgjJFrXn0Z446UyRmCKIriBR+xl61atQqfffYZcnJyOh+zWq1YuHAhrrnmGjz66KOS9zlmzBgAwOHDh3stT19pbm7GlVdeCQD49NNPe231XiIiIiIaXKTUuLIa8Xdn/fr1eO211xAQEICrrrqqx/txOkXU1fVOX3wplEoFQkJ0qK9vhsPh9CrmX//6tDOmpcW7nHtyHMYMrhi55sUYxgzGGLnmxRjGDMYYuebVlzHuOJ0iFArvhv0HROF/1113Yc6cOVi1ahWeeuopvP/++z3ajygCdvuFvbgXwuFwSj4+YxjTkxi55sUYxgzGGLnmxRjGDMYYuebVlzHnkjJ3R3aF/6FDh9DQ0ACHw4FDhw6hoqICRqMRAQEBUCqV0Gg0/Z0iEREREdGAI6uuPgAwb948fPjhh6irq8O8efNw6NAhLFu2DEuWLIFGo8Hjjz/e3yn6nNVqRWzsBERGRsJqtfZ3OkREREQ0CMhuxP+7774777F77rmnHzLpP6Io4ujRqs6viYiIiIgulOxG/ImIiIiIqPex8CciIiIi8gMs/ImIiIiI/AALfyIiIiIiP8DCn4iIiIjID8iuqw8BgiBg/PgoKJUKCIJ3K7EREREREXWHhb8M6fV6fPHF1xgyJBB1dU3drugmiiKKigqwc/deFBaXoq2tFRqNFrEx0Zg/dzYsljh+eCAiIiIiFv4DWU1NNdalZ6Kyuh7h5pkYO3Uh9IFBsDY1orwyH2vWbobZFILVqSkwGk39nS4RERER9SMW/gNUTU01VqxcA5VhBqYnL4ZCqYIgAGq1EhqdAaEGM5yxySg7kIUVK9dgQ0Yai38iIiIiP8abe2XIarVi2rRETJw4EVar9bzvi6KIdemZUBlmYELiUiiUrj+/KZQqTEhcCtXQ6ViXnslVgImIiIj8GAt/GRJFEd99V4aSkhKXxXpRUQGqqhsQNXmxV/uLil+Cyup6FBcX9naqRERERDRAsPAfgHbu3gtDRJLbkf5zKZQqGCKSsGPXHh9nRkRERERyxcJ/ACooKsUIc4KkGKM5AQVFpT7KiIiIiIjkjoX/ANTcbIVaq5cUo9bo0dLS7KOMiIiIiEju2NVHRjp68r+7/f3Ox269/W7Ex8V06cmv0+lha7UCwd7v29ZmRUCAzgdZExEREdFAwMJfJs7uyR9mmtb5+OjE36K8pqRLT/44SzTKq/IRFm72fv+V+YizRPsidSIiIiIaADjVRwY6evI3KGMwPflZjJ98HUKGXITQoaMQFh6BqPhFmJ78LBqUMVixcg2mXhqP2spsOB12r/bvdNhRW5WNBfPm+PiZEBEREZFcccS/n53bkx9o78Jzz+++glqthM3mgCj+tyd/SZ6Ibe/uxChTMMoOZHXGdKds/1aYTSGIiYn19dMhIiIiIpniiH8/60lP/qqaBiy+fj7stTkoydviduTf6bCjJG8L7KdzsTo1BYIg9GbqRERERDSAcMS/n/W0J/+XX+VjQ0Ya1qVnInd7LgwRSTBFJkCnD0aztQHVFfmorcpuvy8gIw1Go8nHz4SIiIiI5IyFfz8rKCrF2KkLuzxma2vG288tgiAIWHp/FlTqrt14jOYEFOxbD6PRhM2bNqK4uBA7du1B4b71sNnaoFZrEBsTjQXLliMmJpYj/URERETEwr+/uezJL4o4cbTwP1+K58Wc3ZNfEARYLHGwWOKgUikwZEgg6uqaYLc7fZ47EREREQ0cLPx9pKMn/87de1FYXIq2tlZoNFrExkSzJz8RERER9TkW/j5wdk/+cPNMjJ26EPrAIFibGlFemc+e/ERERETU59jVp5ed25M/Kn4RwsLNCAwZjrBwM3vyExEREVG/YOHfi87tye+uU09HT37V0OldevJ7gz35iYiIiKgnWPj3IvbkJyIiIiK54hz/XtRbPflDTZchQB8GQMCPtZX4obqEPfmJiIiI6IKw8O9Frnrye+KuJ79txlWw2dpQdeA59uQnIiIiogvGwr8XuezJ7wF78hMRERFRX+Ac/17U2ZNfAvbkJyIiIqK+wMK/F8VZonG8Kl9SjKue/M3NzVi4cA5mzpyJ5ubm3kyRiIiIiPwUC/9eNH/u7F7pye90OpGT8zmys7PhdHKaDxERERFdOBb+vchiiUMEe/ITERERkQyx8O9FgiBgdWoKe/ITERERkeywq08vMxpNXXryGyKSYIpMgE4fjGZrA6or8tmTn4iIiIj6HAt/Hzi3J3/hvvWw2dqgVmvYk5+IiIiI+gULfx9hT34iIiIikhMW/jKl10tbCIyIiIiIqDu8uVeGAgMD8f33J9HU1ITAwMD+ToeIiIiIBgEW/kREREREfoCFPxERERGRH2DhL0MtLS1YunQx5s+fj5aWlv5Oh4iIiIgGAd7cK0MOhwP//Ofezq9V/CkRERER0QXiiD8RERERkR9g4U9ERERE5AdY+BMRERER+QEW/kREREREfoCFPxERERGRHxBEURT7O4m+oNPpYLPZMXLkRX1+bEEAFAoBTqcIb15tUXTi6NEqAEBERAS8/Xwm9TiMGXwxcs2LMYwZjDFyzYsxjBmMMXLNqy9j3Dl27Huo1So0Nzd7Pq6/FP5hYWFobW2F0Wjs71SIiIiIiHpFTU0NtFotzpw543Fbvyn8iYiIiIj8Gef4ExERERH5ARb+RERERER+gIU/EREREZEfYOFPREREROQHWPgTEREREfkBFv5ERERERH6AhT8RERERkR9g4U9ERERE5AdY+BMRERER+QEW/kREREREfoCFPxERERGRH2DhT0RERETkB1j4+5jNZsNNN92EiRMnYsaMGV7F7Nu3D7Nnz0ZMTAyuvfZafPbZZx5j/v3vf+Pqq6/GpEmTcM0112Dv3r1e5/j2229j/Pjx+O1vf+tx2++//x7jx4/v/LNgwQKPMV9//TWuu+46WCwWXHfddR6337x5c5djjB8/HtXV1d3GtLa2Yvny5Zg8eTIuu+wyvPTSSx6PY7fbsWbNGiQmJmLhwoUoLCx0u62rn6PD4cDatWsxZcoULFy4EN98843HmBMnTuC6665DVFQUbrrpJq+Os3PnTlx99dWIiYlBcnKyV8f54osvcMUVV2DSpEmYP38+8vLyPMZ0ePbZZzF+/Hhs2LCh2+337dvX5Wd07733enWMDz74ALNnz4bFYsGvfvUrjzGrVq3qcpyoqCiPMadPn8ayZcsQGxuLK664AllZWR5jGhsb8cADDyA+Ph5Lly5FRUVFlxhX/y89nQOuYjydA65iPJ0DrmI8nQPdXWdcnQPuYro7D9wdo7tzwFWMp3PAVYync8BVjKdzwNV11mq14qGHHkJCQgJuvvlmHD161GNMSUkJ5syZ4/a66yrm9ddfxxVXXAGLxeL1cd59911MmzYNMTExWLRoEf797397jOnw8MMPY/z48Xjrrbc8xmzbtq3Lz+fJJ5/06jh/+9vfcPXVVyMuLs6rmJ///OddjnPNNdd4jKmoqMCNN94Ii8WCWbNmITs722PMiRMncPvttyM+Ph533XUXTp06dd7PCOj63unpWnDu9p6uA65iPF0HXMV4ug64iung7jrgKsbT+4G743R3LXAV4+la4CrG07XAVYyna4GrWsjTOeAqxtvzoDex8PcxQRAwa9YsXHrppV7HtLa24t5778U777yDoKAg/O53v/MYExQUhLS0NLz33nvQ6/XYuHGjV8dqa2vDSy+9BLVa7XV+QPt/kOzsbLz++uvdbldfX49f/epXuPjii5GVlYUbb7zR477vuOMOZGdnIzs7G1OmTMGoUaNgNBq7jfn000+xd+9ePPLII7j22muxceNGnD59utuY9957D1u3bsXmzZsxZswYrFixAk6n0+W2rn6O77//Pt566y0899xzGDt2LB555BGIothtjFKpxKJFi3DJJZd4fRyHw4GVK1fiH//4BxoaGpCRkeExZvjw4fjDH/6ArVu34scffzzvg5C78/L06dN4++23vcqrQ8fP6umnn/YYU1FRgQcffBBXX301srKyznvjdhWTmpraeYyIiAhMmTLFY8z27dvxxRdf4Nlnn0V0dDTS0tI8/mz+8pe/ICcnB2+88QYUCgUee+yxLsdx9f/S0zngKsbTOeAqxtM54CrG0zng7jrj7hzoLgZwfR642t7TOeAqxtM54CrG0zngKsbTOeDqOvvaa6/h888/x+uvvw6lUoknnnjCY4xWq8WyZcsQHh7u8nV2FaNSqfDUU0/hf//3f3Hw4EE8//zzHmPGjBmDP/3pT3j99ddRXl6ON954w2MMAJSXl+PDDz/0OjcAGDFiROfP6MEHH/QY8+WXX+LJJ5/Ez3/+c7z99tuIjY31GLNp0yZkZ2fjww8/RGBg4HnngauYv/71r/jmm2/w17/+FUFBQVi/fr3HmGeffRZHjx7F3//+d1RVVeGZZ54573U4973T07Xg3O09XQdcxXi6DriK8XQdcBUDdH8dcBcDuH8/cBXj6VrgKsbTtcBVjKdrgasYT9eCDmfXQp7OAVcx3pwHvU3VZ0fyUyqVCvfccw8OHz6M8vJyr2KuvPLKzq8nTZqEHTt2eIwZMWIERowYAZvNhqCgIAwdOtSrY7399tuIioqCIAhebd/h3nvvxZAhQ7B8+XLMmzfP7XaffPIJGhoasGLFChiNRq9O7qCgIAQFBeHkyZPIz8/HAw884DG/UaNGQa1WY+TIkfjhhx+gVqs9fpj55ptvEBoaimnTpuHo0aPYs2cPqqqqEBkZed62rn6On3/+OSIjIzFlyhScOnUKu3fvxtGjRxEREeE2Jjw8HLfffjs+/PBDtLa2enWc5OTkzu+PGTMGJ0+e9BgzduxYAIDVaoVWq+38d3cxAPDKK69g4cKFePPNN73aHgBuuOEGDB8+HKmpqbjsssu6jdm9ezfUajV++9vfQqPRnHc+uIoJDQ1FaGgoioqKUFVVhQceeMBjzOjRowEAZrMZYWFh0Ov1Xc4hVzHffPMNIiMjMWnSJEyZMgUvv/wy2traoNFoALj+f+npHHAV4+kccBXj6RxwFePpHHB3nXF3DnQXA7g+D1xt7+kccBXj6RxwFePpHHAV4+kccHWd/fzzzxEbG4uYmBgkJSVh48aNsNlsndcfVzFjx47F2LFj8corr5z3GruLue222zq/P2zYMJw5c8ZjjMViAQDU1tZCpVKddw64e9/44x//iBtvvNHlOeAu5tSpU7j++usRGRmJJ554AiEhId3G7NixA6NGjcIdd9wBABg/frzH43Qca/fu3WhqasKSJUs8xowZMwZKpRKRkZEICgo67/+cq5hvvvkGkyZNQlRUFCwWCz7//PPzXodz3zs9XQvO3d7TdcBVjKfrgKsYT9cBVzFA99cBdzGA+/cDVzGergWuYjxdC1zFeLoWuIrxdC3ocHYt5OkccBUzb948j+dBb+OIv4wdPHgQ77//PpYuXerV9n/7298wefJkFBcXY/bs2R63b2lpwSuvvILf/OY3XucUFBSEDRs24H//938RGRmJVatWoa6uzu32x48fhyAIePDBB3H55Ze7/KTtzrvvvgsAWLRokcdtIyMjcemll+JXv/oVXnjhBSxfvhzBwcHdxoSHh6OhoQEnTpzAwYMHAQA//vijV7kBQF1dHfR6PQB0/u3ptwwX4osvvsAXX3zh9fmwfv16JCYmoq6uDldddZXH7U+ePIl3333X7a9bz2U0GvH888/j1VdfhUajwcMPP+zxZ1tTUwO1Wo0lS5bgyiuvdFv4uLJ161aEhIR4dW7HxMQgKioKCxcuxPvvv4/U1FSPMeHh4aipqUFjYyPKy8shiiLq6+vP2+7s/5fengNS/y+7i/F0Dpwb4805cHaMt+fA2THenAdnb+/tOeDq+Xs6B86O8fYcODvGm3Pg3Ovs6dOnO3/2gYGBcDqd5xXlUq/N3cVs27YNFRUVLqcFuIp56KGHcPnllyMwMBBTp071GFNSUoKioiLccsstXuc2btw4vPTSS3jppZdw6tQprFmzxmNMTU0NWltbce211+Lqq6/GO++84/VrsHXrVowZMwYJCQkeY6644gqEh4dj6tSpKCwsxCOPPOIxJjw8HEeOHEFrayuOHDly3vuCq/fO7q4FPXmv7S7G3XXAXUx31wFXMZ6uA65iPF0HXMV4uhZ09xq4uxa4ivF0LXAV4+la4KoWqq2t7fb9QGr95Css/GWqoqICd955JxISEvDwww97FZOcnIytW7di8uTJeOKJJzwWYf/3f/+H+Ph4XHzxxQAAURTdTnXpEBYWhoULFyIqKgqLFy9Ga2vreXNNzxYaGgpRFDFv3jz84he/wJtvvuly9MSVrKwsXHHFFfjJT37icdtt27YhNzcX6enpuPPOO/HHP/6x27wA4JZbbsGYMWMwc+ZMbN++HUD76I+3hgwZgqamJgDo/Nvb37RIdeDAAfz617/GokWLuoz8deeuu+7C22+/DaPRiKeeesrj9q+++ioWLVqEsLAwAO3nQ3fnUEREBGbNmoUJEyZg/vz5OHXqlMeLWFhYGBoaGnDffffh2muvxTPPPIPDhw97zK2lpQW7du3CwoULodVqvXouBw8exCuvvIL58+fjiSee6PwZuXP33XdDo9Hg0ksvxddffw21Wn3ez/Pc/5fenAM9+b/sKsbTOeAqxtM5cG6MN+fAuTGezoNzt/fmHHD1XDydA66ei6dz4NwYb86Bc6+z554DgiB0vn7uYrwZ/HAV8+GHH+Kxxx7rnB7hTUxqairefPNNOJ1O/OEPf/AY8/zzz+Oee+7p/I2F0+k8L99zYyZOnIgrrrgCcXFxmDlz5nn3EriKCQ0NRV1dHZ588klMmjQJa9asgdVq9fh8ampqkJube95ov7uYZ555BlarFW+++Sbi4+OxevVqjzHLly/HiRMnEBcXh++///689wVX751hYWFurwU9ea91F9PddcBdTHfXAVcxnq4DrmIuuuiibq8D7l6z7q4F7p5Pd9cCVzF/+tOfur0WuIrxdC1wVQup1epu3w+k1k++wqk+feDQoUNoaGiAw+HAoUOHYDKZoNPp3G5fU1ODO+64A0OHDsWaNWtw6tQpDBs2DEql0m1Mfn4+lEolQkNDoVarodVqPU6P6ZjesmfPHgDAsWPHYDabu73J9/PPP8fx48cxefJkvP/++9BqtRg1apTb7adNmwaFQgG1Wt154fDmfoKvv/4aFRUVLkdnXOl4rgEBAdBoNLDZbKirq+s2N6VSiYyMDDQ1NeHtt9/GiRMnuv2Qce7PccaMGdi1axf27duHDz74AJGRkecd79yY4cOH4+TJk2hubobNZsOhQ4cQERHR5TU5N8Zms+Gee+5BXFwcfv3rX+P48ePnvRGdG1NRUQGj0YiAgAAolcrzfj3pKqa8vBw5OTl49dVXAQB//vOfERkZ2Xlfxrnbl5SUQK1W45JLLsEHH3yA8PBwDBkypNtjxMfHAwC0Wm3ncz73fHD1/2Xv3r1oaGhwe4/IuTGiKEIQBOh0OqjVajQ0NKC1tRWBgYFuY4KCgvDyyy/j9OnTeOWVVzB8+HAoFP8dG3H1/9LTOeAqZujQoTh69Kjbc8BVzJkzZ7o9B1zFlJeXw2AwuD0HXMVUVlbi448/dnsOuIr56quvOn9Nf+554Gr7adOm4eWXX3Z7Dri7/u3Zs8ftOeAqxul0dnsOuIoJDAzs9hxwdZ29/PLL8cYbb6C4uBiffPIJpk2b1uX5uIppaWlBdXU1bDYbmpqacOjQoS5TMFzF5OTk4MEHH8SCBQtwww034IcffsCwYcO6jfnXv/6FiIgI6HQ6KBSK84okVzHff/99lxttn3zySYwePRrTp093G/P3v/8dF110EX7yk5/g888/7yygujvOjBkz8MEHH3SeBwqFost7nLv3tG3btkGpVOL6668/7zxwFyMIAgICAqBSqXDq1KnO64O7mOHDh+PNN9/E8ePH8eyzz573IcvVe+fIkSNx/Phxl9cCd++1ycnJbq8DrmJsNhu++uort9cBVzHHjx/H448/7vY64Cpm5syZ+OSTT9xeB1zFFBcX45FHHnH7fuAqZvLkyQDcvx+4e91Gjx7t9lrgKubOO+/s9lrgKkan03V7LXBVC82dOxerV692+37gKsZkMuHQoUPd1gS9TiSfGzduXJc/X375ZbfbZ2VlnRdz9OjRbmPeeecd8bLLLhMnTZokzp8/X/zkk0885lVdXS0WFRWJRUVF4owZM8Q777xTPH78eLcx+fn54uzZs8VJkyaJs2bNEnfv3u3xOG+99ZZ4+eWXi1OmTBEzMjI8bi+Korhq1Spx+vTpos1m82r7pqYm8Ve/+pUYFxcnXnrppeLatWtFp9PZbUx5ebk4Y8YMMTY2VrzzzjvF6urqbrc/92eSk5MjPvHEE2JiYqI4f/58sbCw0GOMNz/bc79/2223nfeYp+O8/PLL4qWXXipaLBZx8eLFXuX2f//3f53nw7hx48SVK1eKtbW1brf/4IMPxKuuukqcNGmSuGDBAnHfvn0ej/Hll1+KmzZtEqdOnSpOnz5dfO2117yKue2228QbbrjB65/N9u3bxdtuu020WCzitGnTxJdfftljTE5OjjhlyhQxPj5e/M1vfiOeOXOmy/aufnYVFRXdngPuft7dnQOuYlauXNntOeAqxtM54CqmsrKy23PAVcxrr73m9jxw9/y7OwfcxXR3DriKyc/P7/YccBXzf//3f92eA66us42NjeJvfvMbMT4+XrzxxhvFiooKjzFffvlltz9PVzHnngNXXXWVx5gnn3xSnDx5shgXFyfedtttXuVWXl4uFhUVif/617/EcePGic8884zY0NDQbcxf//pXccaMGWJMTIx44403imVlZR6PY7PZxMcff1xMSEgQr7rqKvH999/3GON0OsVrrrlGvP/++12eB65iDh48KC5atEicNGmSmJSUJGZlZXmM2bZtmxgfHy9OmTJFfOyxx8SWlpYuMa7eO48dO+b2WuBq+/z8/G6vA65i1qxZ0+154ypm8+bN3V4HXMV8/fXX3V4HXMW899573b4fuKs3ursWuIvp7lrQXYy7a4GrmHfeeafba4GrWshms3X7fuAqxtP7gS8IoujlhGsiIiIiIhqwOMefiIiIiMgPsPAnIiIiIvIDLPyJiIiIiPwAC38iIiIiIj/Awp+IiIiIyA+w8CciIiIi8gMs/ImIiIiI/ABX7iUiIlkYP348AGDkyJH46KOP+jkbIqLBh4U/EZEf27x5M5577rkujymVSoSGhmLChAn4xS9+gaSkpH7KjoiIehOn+hARURcOhwOnT5/G559/jnvvvRcffvhhf6dERES9gIU/EREBAK78//buJiTKLY7j+PeaUDNQDJpmtQuCglYiEoGB24kWuRJMCko31rSJwhaBRNvEhYaiRJEoiGQbEWmTiUJUK41AhEyhF2wYtCnIdO4iODfv2IWuxoX7fD+r/zlz5pznWc3veeZ5OX6c3t5e2tvbOXToEAC5XI779+//x1smSdoKXuojSQKguLiYiooKANbW1rh48SIAb9++DWMGBgYYGRlhdnaWTCbD6uoqe/fupaqqiqamJoqKisLY+vp6nj59CsDDhw8ZGBhgeHiYbDZLZWUlLS0t7N+//x+3aXJykoaGBlZWVkgkEty9ezcclEiSfo3BX5KUJ5fLhbq0tDTUIyMjjI+Prxs7NzfH3Nwck5OTPHjwgO3bt+fNd+HCBebn50P7yZMnXL58mb6+vp9uw9TUFE1NTaysrLBz5056enoM/ZK0CQZ/SRIAHz9+5NmzZ2QyGTo6OkJ/bW1tqJPJJMlkkt27dxOLxfjy5QvDw8MMDQ0xOzvL6OgoJ0+ezJs7nU7T0tJCPB7nxo0bLC0t8eLFC2ZmZjh48GDe+NevX9PQ0EA2myUej9PV1cWRI0d+z45LUkQY/CVJAIyNjTE2NhbaxcXFXLlyhRMnToS+Y8eO0dHRwcTEBB8+fODr16/r5piamtow+KdSqXAA8fz5c/r7+4Hv/xb8Pfhns1nOnTtHOp1mx44ddHZ2Ul5evmX7KUlRZfCXJG0onU4zMzMT2p8+faK2tpZ379799DtLS0sb9ldWVoY6kUiEenl5OW9sJpMhk8kAcO3atXXflST9ez7VR5IEwKlTp5ienqa7u5tYLEYul6O7uzu8TOvRo0ch9B84cIDW1lZ6e3tpbm4Oc/x4b8CPdu3aFerCwr/OOW00ftu2baHu6upicXFxczsmSQIM/pKkHxQWFlJVVcX58+dDX1tbGwDv378PfXV1dSSTSSoqKvIu99mssrIyzp49C8DCwgKNjY18/vx5S9eQpCgy+EuS8pw+fZpYLAbAq1evGB8fZ9++feHzwcFBHj9+zL1797h9+/aWr3/16lWqq6sBmJ6e5tKlS3z79m3L15GkKDH4S5LyJBIJampqQrunp4fq6mpKSkoAePnyJY2Njdy8efO3PGKzoKCAW7ducfjwYeD7jcfXr1/f8nUkKUoM/pKkDZ05c4aCgu8/ExMTE7x584Y7d+5w9OhR4vE4e/bsIZVKkUqlfsv68Xiczs7O8B6BwcHBcNmRJOnX/ZH72Z1YkiRJkv43POMvSZIkRYDBX5IkSYoAg78kSZIUAQZ/SZIkKQIM/pIkSVIEGPwlSZKkCDD4S5IkSRFg8JckSZIiwOAvSZIkRYDBX5IkSYoAg78kSZIUAQZ/SZIkKQL+BArzlbfRs3vyAAAAAElFTkSuQmCC\n"},"metadata":{}}],"source":["#@title Plotting docking scores\n","\n","from pathlib import Path\n","import numpy as np\n","import seaborn as sns\n","import matplotlib.pyplot as plt\n","\n","# Load energy data\n","output_energy_file = Path('GalaxyDock_fb.E.info')\n","energy_array = np.array([float(line.split()[1]) for line in output_energy_file.read_text().splitlines() if not line.startswith('!') and not line.startswith('Bank')], dtype=np.float64)\n","rank_array = np.array(range(1, 51))\n","\n","# Set font size multiplier for better readability\n","font_size = 2\n","\n","# Seaborn style and theme setup\n","sns.set_style(\"whitegrid\") # Clean background with grid\n","sns.set_theme(rc={'figure.figsize':(8, 6)}) # Adjust figure size for better aspect ratio\n","sns.set_theme(font_scale=1.5) # Moderate scaling for better font size balance\n","\n","# Create rank range for the x-axis\n","rmsd_range = list(range(1, 52))\n","\n","# Create the plot\n","fig, ax = plt.subplots() # Create figure and axis\n","\n","# Scatter plot with adjusted point size and color\n","ax = sns.scatterplot(x=rank_array, y=energy_array, s=100, color='royalblue', edgecolor='black', alpha=0.7)\n","\n","# Customize axis ticks\n","plt.xticks(fontsize=font_size*3, fontweight='bold') # Increase x-tick font size\n","plt.yticks(fontsize=font_size*3, fontweight='bold') # Increase y-tick font size\n","\n","# Set axis labels with enhanced font sizes and label padding\n","plt.xlabel('Rank', fontsize=font_size*6.0, labelpad=font_size*2, fontweight='bold')\n","plt.ylabel('Score', fontsize=font_size*6.0, labelpad=font_size*2, fontweight='bold')\n","\n","# Add a vertical line for visual separation (at rank 2)\n","ax.axvline(2.0, linestyle='--', color='black', linewidth=1.5)\n","\n","# Customize axis spines and gridlines\n","ax.spines['bottom'].set_color('black')\n","ax.spines['top'].set_color('black')\n","ax.spines['right'].set_color('black')\n","ax.spines['left'].set_color('black')\n","\n","# Customize x-ticks to match the rank range\n","ax.set_xticks(np.array(rmsd_range))\n","\n","# Set plot title with a larger font size\n","ax.set_title(\"Rank vs Score\", fontsize=font_size*7, fontweight='bold')\n","\n","# Adjust layout to prevent clipping and enhance spacing\n","plt.tight_layout()\n","\n","# Show the plot\n","plt.show()"]},{"cell_type":"markdown","metadata":{"id":"j4oTkrslRfs7"},"source":["Calculate the RMSD between the crystal structure and the GDDL docking pose selected from the ranking above."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Lw0nJHHrTJF8","colab":{"base_uri":"https://localhost:8080/","height":216},"executionInfo":{"status":"error","timestamp":1735394726298,"user_tz":-540,"elapsed":238,"user":{"displayName":"­김동우 / 학생 / 약학과","userId":"17104096532647650828"}},"outputId":"efc1816b-bdfe-4ba3-a14a-42e884bc54ff"},"outputs":[{"output_type":"error","ename":"FileNotFoundError","evalue":"[Errno 2] No such file or directory: '/content/iitp_demonstrate/2qeh/rmsd.info'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)","\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mnum\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf'/content/iitp_demonstrate/{target}/rmsd.info'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mfp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfp\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mnum\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/content/iitp_demonstrate/2qeh/rmsd.info'"]}],"source":["#@title Calculating RMSD of predicted structures\n","\n","num = 0\n","with open(f'/content/iitp_demonstrate/{target}/rmsd.info') as fp:\n"," for line in fp:\n"," num += 1\n"," if num == rank:\n"," rmsd = line.split()[3].strip('\\n')\n","\n","print(f'RMSD between the crystal structure and the GDDL docking pose selected from the ranking above: {rmsd} Å')"]},{"cell_type":"markdown","metadata":{"id":"OS-8w93HWfXn"},"source":["GDDL does not output just a single structure; instead, it provides 50 different structures ranked by increasing energy. This can also be helpful in studying the multi-state of the target ligand. By examining the relationship between the actual GDDL energy and the RMSD of each docking pose, we can observe a significant correlation. In other words, the GDDL energy is indeed useful in assessing the stability of the structures."]},{"cell_type":"code","execution_count":null,"metadata":{"cellView":"form","id":"BdUIJw2SacmS","colab":{"base_uri":"https://localhost:8080/","height":400},"executionInfo":{"status":"error","timestamp":1735394746170,"user_tz":-540,"elapsed":948,"user":{"displayName":"­김동우 / 학생 / 약학과","userId":"17104096532647650828"}},"outputId":"53941ae1-e7a9-4e4d-db68-ce897712d568"},"outputs":[{"output_type":"error","ename":"FileNotFoundError","evalue":"[Errno 2] No such file or directory: 'rmsd.info'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)","\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 39\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 40\u001b[0m \u001b[0;31m# Load RMSD and energy data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 41\u001b[0;31m \u001b[0mrmsd_results\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0menergy_array\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'\\n'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[0;32min\u001b[0m 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\u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1118\u001b[0m \u001b[0mencoding\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtext_encoding\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mencoding\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1119\u001b[0;31m return self._accessor.open(self, mode, buffering, encoding, errors,\n\u001b[0m\u001b[1;32m 1120\u001b[0m newline)\n\u001b[1;32m 1121\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'rmsd.info'"]}],"source":["#@title Plotting the relationship between RMSD and docking energy\n","\n","import pandas as pd\n","import matplotlib.pyplot as plt\n","import numpy as np\n","import seaborn as sns\n","from scipy.stats import linregress, kendalltau, spearmanr\n","from sklearn.metrics import mean_absolute_error, mean_squared_error\n","from pathlib import Path\n","\n","# Function to add trendline and display regression metrics\n","def add_trendline_and_metrics(ax, x, y, title):\n"," slope, intercept, r_value, p_value, std_err = linregress(x, y)\n"," trendline = np.array(x) * slope + intercept\n"," ax.plot(x, trendline, color=\"g\", linestyle=\"--\", label=f\"y = {slope:.2f}x + {intercept:.2f}\")\n","\n"," # Calculating Kendall Tau and Spearman correlation\n"," tau, _ = kendalltau(x, y)\n"," spearman_corr, _ = spearmanr(x, y)\n","\n"," # Calculating MAE and RMSE\n"," mae = mean_absolute_error(y, np.array(x) * slope + intercept)\n"," rmse = np.sqrt(mean_squared_error(y, np.array(x) * slope + intercept))\n","\n"," # Display metrics on the plot with adjusted font size\n"," ax.text(\n"," 0.05, 0.85,\n"," f\"$R^2$ = {r_value**2:.2f}\\n\"\n"," f\"p = {p_value:.2e}\\n\"\n"," f\"Kendall Tau = {tau:.2f}\\n\"\n"," f\"Spearman = {spearman_corr:.2f}\\n\"\n"," f\"MAE = {mae:.2f}\\n\"\n"," f\"RMSE = {rmse:.2f}\",\n"," transform=ax.transAxes,\n"," fontsize=12, # Adjusted font size for metrics\n"," verticalalignment=\"top\",\n"," )\n"," ax.legend(loc=\"upper left\", fontsize=12) # Adjusted font size for legend\n","\n","# Load RMSD and energy data\n","rmsd_results = energy_array = np.array([float(line.split()[3].strip('\\n')) for line in Path('rmsd.info').read_text().splitlines() if not line.startswith('!') and not line.startswith('Bank')], dtype=np.float64)\n","energy_array = np.array([float(line.split()[1]) for line in Path('GalaxyDock_fb.E.info').read_text().splitlines() if not line.startswith('!') and not line.startswith('Bank')], dtype=np.float64)\n","\n","# Create a scatter plot using Seaborn\n","sns.set(style=\"whitegrid\") # Set Seaborn style\n","fig, ax = plt.subplots(figsize=(8, 6)) # Create figure and axis\n","\n","sns.scatterplot(x=rmsd_results, y=energy_array, ax=ax, s=50, color='b', alpha=0.5, edgecolors='k')\n","\n","# Add trendline and metrics\n","add_trendline_and_metrics(ax, rmsd_results, energy_array, \"RMSD vs GDDL Score\")\n","\n","# Set titles and labels with adjusted font sizes\n","ax.set_title(\"RMSD vs GDDL Score\", fontsize=16)\n","ax.set_xlabel(\"RMSD\", fontsize=14)\n","ax.set_ylabel(\"GDDL Score\", fontsize=14)\n","\n","# Show grid\n","ax.grid(True)\n","\n","# Adjust layout for better appearance\n","plt.tight_layout()\n","\n","# Display the plot\n","plt.show()"]},{"cell_type":"markdown","metadata":{"id":"TJf9XwY0xSrS"},"source":["The process of converting MOL2 files into SDF files for prolif processing."]},{"cell_type":"code","execution_count":null,"metadata":{"cellView":"form","id":"yvQrl-_FxMYt","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1735394748582,"user_tz":-540,"elapsed":247,"user":{"displayName":"­김동우 / 학생 / 약학과","userId":"17104096532647650828"}},"outputId":"166f5ee0-65d9-45dc-fb04-254564bee58e"},"outputs":[{"output_type":"stream","name":"stdout","text":["Successfully combined all molecules of output files into /content/iitp_demonstrate/2qeh/GalaxyDock_fb_combined.sdf\n","Successfully combined the selected rank molecule file into /content/iitp_demonstrate/2qeh/final_ligand.sdf\n"]}],"source":["#@title Converting docking results into SDF files\n","\n","import subprocess as sp\n","from openbabel import pybel\n","\n","mol2_file_path = f\"/content/iitp_demonstrate/{target}/GalaxyDock_fb.mol2\"\n","sdf_output_file = f\"/content/iitp_demonstrate/{target}/GalaxyDock_fb_combined.sdf\"\n","rank_mol2_file = f\"/content/iitp_demonstrate/{target}/final_ligand.mol2\"\n","sdf_rank_file = f\"/content/iitp_demonstrate/{target}/final_ligand.sdf\"\n","\n","try:\n"," with open(sdf_output_file, \"w\") as sdf_file:\n"," for mol in pybel.readfile(\"mol2\", mol2_file_path):\n"," sdf_file.write(mol.write(\"sdf\"))\n"," print(f\"Successfully combined all molecules of output files into {sdf_output_file}\")\n","\n"," with open(sdf_rank_file, \"w\") as sdf_file:\n"," for mol in pybel.readfile(\"mol2\", rank_mol2_file):\n"," sdf_file.write(mol.write(\"sdf\"))\n"," print(f\"Successfully combined the selected rank molecule file into {sdf_rank_file}\")\n","except Exception as e:\n"," print(f\"Error during .mol2 to .sdf conversion: {e}\")"]},{"cell_type":"markdown","metadata":{"id":"yo7zXGM4L9vj"},"source":["Utilizing Prolif, visualize the types of interactions between the ligand and protein in each protein-ligand docking pose from the GDDL output."]},{"cell_type":"code","execution_count":null,"metadata":{"cellView":"form","id":"D3mkNnSEJSYQ","colab":{"base_uri":"https://localhost:8080/","height":1000,"referenced_widgets":["2cdf47f1d6634fac939006444c260bb4","29a74d0be2034bd1bb5f1befd79e9a99","d1eb97ef2f3f4f9baaf598cd97b15b76","36007fbb7b9e4286b6c0967b4d544490","b403dedce52a4ce689cf64fb612cc9bc","72f00a8c61ec4e4eaf1c211e217d817b","cedb6fff8cce4b549ab0c7008bab4964","e05ab44f20834921915e7c0b92d30d91","3fd4535907e84cd0ad39cdc7ff0ee367","b7bab9b2656744ed9a68d6f30881ffd1","840a4087f92f4f30b66e1189b0fcfe33"]},"executionInfo":{"status":"ok","timestamp":1735394760888,"user_tz":-540,"elapsed":9283,"user":{"displayName":"­김동우 / 학생 / 약학과","userId":"17104096532647650828"}},"outputId":"3bba47bf-3c2f-481c-c4b7-2901d5eb8664"},"outputs":[{"output_type":"stream","name":"stderr","text":["WARNING:MDAnalysis.coordinates.AMBER:netCDF4 is not available. Writing AMBER ncdf files will be slow.\n","/usr/local/lib/python3.10/dist-packages/MDAnalysis/topology/tables.py:52: DeprecationWarning: Deprecated in version 2.8.0\n","MDAnalysis.topology.tables has been moved to MDAnalysis.guesser.tables. This import point will be removed in MDAnalysis version 3.0.0\n"," warnings.warn(wmsg, category=DeprecationWarning)\n"]},{"output_type":"display_data","data":{"text/plain":[" 0%| | 0/50 [00:00"]},"metadata":{},"execution_count":33},{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{}}],"source":["#@title Displaying protein-ligand interactions using ProLIF\n","\n","import prolif as plf\n","from rdkit import Chem\n","\n","poses_path = sdf_output_file\n","pose_iterable = plf.sdf_supplier(poses_path)\n","\n","rdkit_prot = Chem.MolFromPDBFile(f'/content/iitp_demonstrate/{target}/{target}_pro.pdb', removeHs=False)\n","protein_mol = plf.Molecule(rdkit_prot)\n","\n","fp = plf.Fingerprint()\n","fp.run_from_iterable(pose_iterable, protein_mol)\n","\n","fp.plot_barcode(xlabel=\"Pose\")"]},{"cell_type":"markdown","metadata":{"id":"yO6otcmILuiP"},"source":["Visualize which residues of the protein interact with the ligand in the docking pose corresponding to the selected rank."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"qevPEBhPLuT8","colab":{"base_uri":"https://localhost:8080/","height":612},"executionInfo":{"status":"ok","timestamp":1735394761811,"user_tz":-540,"elapsed":6,"user":{"displayName":"­김동우 / 학생 / 약학과","userId":"17104096532647650828"}},"outputId":"0bb13af1-da7b-4cad-aaa7-afd65073dc22"},"outputs":[{"output_type":"execute_result","data":{"text/plain":[""],"text/html":[""]},"metadata":{},"execution_count":34}],"source":["fp.plot_lignetwork(pose_iterable[rank])"]},{"cell_type":"markdown","metadata":{"id":"F1au9MFzf1mo"},"source":["Both the protein (PDB format) and ligand (mol2 format) files generated by GDDL can be downloaded."]},{"cell_type":"code","execution_count":null,"metadata":{"cellView":"form","id":"Yd8T71d_f1ZM","colab":{"base_uri":"https://localhost:8080/","height":17},"executionInfo":{"status":"ok","timestamp":1735394765044,"user_tz":-540,"elapsed":249,"user":{"displayName":"­김동우 / 학생 / 약학과","userId":"17104096532647650828"}},"outputId":"c5599b17-f5a3-47ed-c346-a3b9344f3449"},"outputs":[{"output_type":"display_data","data":{"text/plain":[""],"application/javascript":["\n"," async function download(id, filename, size) {\n"," if (!google.colab.kernel.accessAllowed) {\n"," return;\n"," }\n"," const div = document.createElement('div');\n"," const label = document.createElement('label');\n"," label.textContent = `Downloading \"${filename}\": `;\n"," div.appendChild(label);\n"," const progress = document.createElement('progress');\n"," progress.max = size;\n"," div.appendChild(progress);\n"," document.body.appendChild(div);\n","\n"," const buffers = [];\n"," let downloaded = 0;\n","\n"," const channel = await google.colab.kernel.comms.open(id);\n"," // Send a message to notify the kernel that we're ready.\n"," channel.send({})\n","\n"," for await (const message of channel.messages) {\n"," // Send a message to notify the kernel that we're ready.\n"," channel.send({})\n"," if (message.buffers) {\n"," for (const buffer of message.buffers) {\n"," buffers.push(buffer);\n"," downloaded += buffer.byteLength;\n"," progress.value = downloaded;\n"," }\n"," }\n"," }\n"," const blob = new Blob(buffers, {type: 'application/binary'});\n"," const a = document.createElement('a');\n"," a.href = window.URL.createObjectURL(blob);\n"," a.download = filename;\n"," div.appendChild(a);\n"," a.click();\n"," div.remove();\n"," }\n"," "]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":[""],"application/javascript":["download(\"download_db3e8716-efdf-47a0-bcf5-ff3c1e075d6c\", \"pdb_processed.pdb\", 96632)"]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":[""],"application/javascript":["\n"," async function download(id, filename, size) {\n"," if (!google.colab.kernel.accessAllowed) {\n"," return;\n"," }\n"," const div = document.createElement('div');\n"," const label = document.createElement('label');\n"," label.textContent = `Downloading \"${filename}\": `;\n"," div.appendChild(label);\n"," const progress = document.createElement('progress');\n"," progress.max = size;\n"," div.appendChild(progress);\n"," document.body.appendChild(div);\n","\n"," const buffers = [];\n"," let downloaded = 0;\n","\n"," const channel = await google.colab.kernel.comms.open(id);\n"," // Send a message to notify the kernel that we're ready.\n"," channel.send({})\n","\n"," for await (const message of channel.messages) {\n"," // Send a message to notify the kernel that we're ready.\n"," channel.send({})\n"," if (message.buffers) {\n"," for (const buffer of message.buffers) {\n"," buffers.push(buffer);\n"," downloaded += buffer.byteLength;\n"," progress.value = downloaded;\n"," }\n"," }\n"," }\n"," const blob = new Blob(buffers, {type: 'application/binary'});\n"," const a = document.createElement('a');\n"," a.href = window.URL.createObjectURL(blob);\n"," a.download = filename;\n"," div.appendChild(a);\n"," a.click();\n"," div.remove();\n"," }\n"," "]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":[""],"application/javascript":["download(\"download_38292521-c02f-464d-8de5-1df32a9089f1\", \"GalaxyDock_fb.mol2\", 179500)"]},"metadata":{}}],"source":["#@title Saving docking results into Google Drive\n","\n","from google.colab import files\n","\n","output_pdb = 'pdb_processed.pdb'\n","files.download(output_pdb)\n","output_mol2 = 'GalaxyDock_fb.mol2'\n","files.download(output_mol2)"]},{"cell_type":"markdown","metadata":{"id":"Z9iT3-PWPTNX"},"source":["# Section 4: Re-scoring GDDL docking results using BindingRMSD.\n","BindingRMSD CASF-2016 Docking power benchmark results\n","![그림1.png](data:image/png;base64,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)"]},{"cell_type":"markdown","metadata":{"id":"Uy64LzqlR9t_"},"source":["# 4-1. Re-scoring for Docked Protein-Ligand Complex\n","\n"]},{"cell_type":"markdown","metadata":{"id":"M7bbvQ_t9BFY"},"source":["Performing BindingRMSD model using docking result file.\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"uM9qqdAI8_di","colab":{"base_uri":"https://localhost:8080/","height":414},"executionInfo":{"status":"error","timestamp":1735394775325,"user_tz":-540,"elapsed":6854,"user":{"displayName":"­김동우 / 학생 / 약학과","userId":"17104096532647650828"}},"outputId":"e1056185-bf2b-4f23-e1ec-8e63c46044bf"},"outputs":[{"output_type":"stream","name":"stdout","text":["python3 /content/BindingRMSD/inference.py -r /content/iitp_demonstrate/2qeh/pdb_processed.pdb -l /content/iitp_demonstrate/2qeh/GalaxyDock_fb_combined.sdf -o /content/output.tsv --model_path /content/BindingRMSD/save\n"]},{"output_type":"error","ename":"CalledProcessError","evalue":"Command '['python3', '/content/BindingRMSD/inference.py', '-r', '/content/iitp_demonstrate/2qeh/pdb_processed.pdb', '-l', '/content/iitp_demonstrate/2qeh/GalaxyDock_fb_combined.sdf', '-o', '/content/output.tsv', '--model_path', '/content/BindingRMSD/save']' returned non-zero exit status 1.","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mCalledProcessError\u001b[0m Traceback (most recent call last)","\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0;34m\" \"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0mcommand\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 16\u001b[0;31m \u001b[0msp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcommand\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcheck\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 17\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[0;31m# Run the command using subprocess\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/lib/python3.10/subprocess.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(input, capture_output, timeout, check, *popenargs, **kwargs)\u001b[0m\n\u001b[1;32m 524\u001b[0m \u001b[0mretcode\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprocess\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpoll\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 525\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mcheck\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mretcode\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 526\u001b[0;31m raise CalledProcessError(retcode, process.args,\n\u001b[0m\u001b[1;32m 527\u001b[0m output=stdout, stderr=stderr)\n\u001b[1;32m 528\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mCompletedProcess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprocess\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mretcode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstdout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstderr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mCalledProcessError\u001b[0m: Command '['python3', '/content/BindingRMSD/inference.py', '-r', '/content/iitp_demonstrate/2qeh/pdb_processed.pdb', '-l', '/content/iitp_demonstrate/2qeh/GalaxyDock_fb_combined.sdf', '-o', '/content/output.tsv', '--model_path', '/content/BindingRMSD/save']' returned non-zero exit status 1."]}],"source":["protein_file_path = f\"/content/iitp_demonstrate/{target}/pdb_processed.pdb\"\n","output_file = \"/content/output.tsv\"\n","model_path = \"/content/BindingRMSD/save\"\n","\n","# Construct the command\n","command = [\n"," \"python3\",\n"," \"/content/BindingRMSD/inference.py\",\n"," \"-r\", protein_file_path,\n"," \"-l\", sdf_output_file,\n"," \"-o\", output_file,\n"," \"--model_path\", model_path\n","]\n","\n","print( \" \".join( command ))\n","sp.run(command, check=True)\n","\n","# Run the command using subprocess\n","try:\n"," sp.run(command, check=True)\n"," print(f\"Inference completed successfully. Results saved to {output_file}\")\n","except sp.CalledProcessError as e:\n"," print(f\"Error during inference: {e}\")"]},{"cell_type":"markdown","metadata":{"id":"dVbzc1PO9SjP"},"source":["The prediction results of Binding RMSD are saved as a TSV file, and the saved TSV file is displayed as a DataFrame using pandas.\n","\n","The ***Predicted_RMSD*** column is generated using the Binding RMSD regression model, which directly predicts the RMSD of the bound ligand pose in a given protein-ligand complex.\n","The ***Is_Above_2A*** column is generated using the Binding RMSD binary classification model, which predicts whether the RMSD of the bound ligand pose in a given protein-ligand complex is above 2 Å.\n","For both models, values closer to 0 indicate better performance."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"NiIKhvIF8XA5"},"outputs":[],"source":["import pandas as pd\n","\n","df = pd.read_csv( output_file, sep='\\t')\n","df.head()"]},{"cell_type":"markdown","metadata":{"id":"z-naQSJ1_l_b"},"source":["# 4-2. 3D Visualization: Crystal Structure vs Docked Poses\n"]},{"cell_type":"markdown","metadata":{"id":"Gw-7sgT5_lzD"},"source":["Re-score the poses of ligands docked using GDDL to a crystal protein-ligand complex using the Binding RMSD model. After sorting the results to select the best-predicted pose, visualize it in 3D using Py3Dmol.\n","\n","\n","\n","\n","\n","\n"]},{"cell_type":"markdown","metadata":{"id":"gijErYBDAHLn"},"source":["Sort based on ***Predicted_RMSD*** and visualize the results.\n","\n","\n","\n","\n","\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"cellView":"form","id":"MOMc-GvC8dnl"},"outputs":[],"source":["#@title Visualizing crystal structure and docked poses\n","\n","import py3Dmol\n","from rdkit import Chem\n","from rdkit.Chem import AllChem\n","import os\n","\n","# Function to visualize PDB and specific ligand from SDF, along with a native ligand\n","def visualize_pdb_with_ligand_and_native(pdb_file, sdf_file, ligand_index, native_pdb_file=None):\n"," # Load PDB structure\n"," with open(pdb_file, 'r') as file:\n"," pdb_data = file.read()\n","\n"," # Load SDF file and select the ligand by index\n"," suppl = Chem.SDMolSupplier(sdf_file, sanitize=False)\n"," if ligand_index < len(suppl) and suppl[ligand_index] is not None:\n"," ligand = suppl[ligand_index]\n"," ligand_block = Chem.MolToMolBlock(ligand) # Convert ligand to MOL block\n"," else:\n"," print(f\"Invalid index: {ligand_index}. The file contains {len(suppl)} molecules.\")\n"," return\n","\n"," # Check if native ligand file exists\n"," native_data = None\n"," if native_pdb_file and os.path.isfile(native_pdb_file):\n"," with open(native_pdb_file, 'r') as file:\n"," native_data = file.read()\n","\n"," # Create 3D visualization\n"," view = py3Dmol.view(width=800, height=600)\n"," view.addModel(pdb_data, \"pdb\") # Load PDB file\n"," view.setStyle({'cartoon': {'color': 'spectrum'}}) # Cartoon style for protein\n","\n"," # Add ligand to the visualization\n"," view.addModel(ligand_block, \"mol\") # Load MOL block for ligand\n"," view.setStyle({'model': 1}, {'stick': {'colorscheme': 'cyanCarbon'}}) # Stick style for ligand\n","\n"," # Add native ligand if available\n"," if native_data:\n"," view.addModel(native_data, \"pdb\") # Load native PDB\n"," view.setStyle({'model': 2}, {'stick': {'colorscheme': 'magentaCarbon'}}) # Stick style for native ligand\n","\n"," view.zoomTo() # Adjust the view to fit all structures\n"," return view\n","\n","# Example usage\n","df_sorted = df.sort_values(by='Predicted_RMSD', ascending=True)\n","best_pRMSD_index = int(df_sorted.index[0])\n","native_pdb_file = f\"/content/iitp_demonstrate/{target}/{target}_lig.pdb\"\n","view = visualize_pdb_with_ligand_and_native(protein_file_path, sdf_output_file, best_pRMSD_index, native_pdb_file=native_pdb_file)\n","if view:\n"," view.show()"]},{"cell_type":"markdown","metadata":{"id":"gKUwe2iuAQ_P"},"source":["Sort based on ***Is_Above_2A*** and visualize the results.\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"1ukBE-s18XWl"},"outputs":[],"source":["# Example usage\n","df_sorted = df.sort_values(by='Is_Above_2A', ascending=True)\n","best_pRMSD_index = int(df_sorted.index[0])\n","native_pdb_file = f\"/content/iitp_demonstrate/{target}/{target}_lig.pdb\"\n","view = visualize_pdb_with_ligand_and_native(protein_file_path, sdf_output_file, best_pRMSD_index, native_pdb_file=native_pdb_file)\n","if view:\n"," view.show()"]},{"cell_type":"markdown","metadata":{"id":"pbzt9Z2jAWx6"},"source":["# 4-3. Crystal Ligand Pose vs Docked Ligand Pose: RMSD and Prediction Comparison\n"]},{"cell_type":"markdown","metadata":{"id":"8CotmXzhHq4Q"},"source":["Load the precomputed RMSD file and create an RMSD list.\n","\n","\n","\n","\n","\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"aMOIsY60Hqvv"},"outputs":[],"source":["with open(f'/content/iitp_demonstrate/{target}/rmsd.info') as fp:\n"," rmsd_results = []\n"," for line in fp:\n"," if not line.startswith('!'):\n"," rmsd_results.append(float(line.split()[3].strip('\\n')))"]},{"cell_type":"markdown","metadata":{"id":"Gsk956HdIJ4p"},"source":["A code that plots the results predicted by the regression and binary classification models against the actual RMSD of the docked pose from the crystal structure.\n","\n","\n","\n","\n","\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"cellView":"form","id":"bYXEg_fPHqmG"},"outputs":[],"source":["#@title Comparing actual vs. predicted RMSD values\n","\n","import pandas as pd\n","import matplotlib.pyplot as plt\n","import numpy as np\n","from scipy.stats import linregress, kendalltau, spearmanr\n","from sklearn.metrics import mean_absolute_error, mean_squared_error\n","\n","def add_trendline_and_metrics(ax, x, y, title):\n"," slope, intercept, r_value, p_value, std_err = linregress(x, y)\n"," trendline = np.array(x) * slope + intercept\n"," ax.plot(x, trendline, color=\"g\", linestyle=\"--\", label=f\"y = {slope:.2f}x + {intercept:.2f}\")\n","\n"," tau, _ = kendalltau(x, y)\n"," spearman_corr, _ = spearmanr(x, y)\n"," mae = mean_absolute_error(y, np.array(x) * slope + intercept)\n"," rmse = np.sqrt(mean_squared_error(y, np.array(x) * slope + intercept))\n","\n"," ax.text(\n"," 0.05, 0.95,\n"," f\"$R^2$ = {r_value**2:.2f}\\n\"\n"," f\"p = {p_value:.2e}\\n\"\n"," f\"Kendall Tau = {tau:.2f}\\n\"\n"," f\"Spearman = {spearman_corr:.2f}\\n\"\n"," f\"MAE = {mae:.2f}\\n\"\n"," f\"RMSE = {rmse:.2f}\",\n"," transform=ax.transAxes,\n"," fontsize=10,\n"," verticalalignment=\"top\",\n"," )\n"," ax.legend(loc=\"upper left\")\n","\n","# Create side-by-side scatter plots\n","fig, ax = plt.subplots(1, 2, figsize=(12, 6), sharey=False)\n","\n","ax[0].scatter(rmsd_results, df[\"Predicted_RMSD\"], color='b', alpha=0.7, edgecolors='k')\n","add_trendline_and_metrics(ax[0], rmsd_results, df[\"Predicted_RMSD\"], \"x_data vs y_data_predicted\")\n","ax[0].plot([0, max(df[\"Predicted_RMSD\"])], [0, max(df[\"Predicted_RMSD\"])], color=\"orange\", linestyle=\"-\", label=\"y = x\")\n","ax[0].set_title(\"RMSD Results vs Predicted RMSD\")\n","ax[0].set_xlabel(\"RMSD Results\")\n","ax[0].set_ylabel(\"Predicted RMSD\")\n","ax[0].grid(True)\n","ax[0].legend()\n","\n","ax[1].scatter(rmsd_results, df[\"Is_Above_2A\"], color='r', alpha=0.7, edgecolors='k')\n","add_trendline_and_metrics(ax[1], rmsd_results, df[\"Is_Above_2A\"], \"x_data vs y_data_is_above_2a\")\n","ax[1].plot([0, 2, 2, max(df[\"Predicted_RMSD\"])], [0, 0, 1, 1], color=\"orange\", linestyle=\"-\", label=\"Threshold at 2\")\n","ax[1].set_title(\"RMSD Results vs Is Above 2Å\")\n","ax[1].set_xlabel(\"RMSD Results\")\n","ax[1].set_ylabel(\"Probability (Is Above 2Å)\")\n","ax[1].set_ylim(-0.05, 1.05)\n","ax[1].grid(True)\n","ax[1].legend()\n","\n","plt.tight_layout()\n","plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Jeuhr3gYH4pN"},"outputs":[],"source":[]}],"metadata":{"colab":{"provenance":[{"file_id":"19g07_1P0c2mqh0HE8hwVZff9eMB_fOBF","timestamp":1736750988354},{"file_id":"1Pw2U9xcXUq0NBvY3p_u_s99gsdWSM451","timestamp":1736733337048}]},"kernelspec":{"display_name":"Python 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