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b/druggpt_min_multi.py |
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# -*- coding: utf-8 -*- |
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""" |
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Created on Sun Jul 23 08:12:43 2023 |
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@author: Sen |
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""" |
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#%% |
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import os |
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import argparse |
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import shutil |
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import logging |
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from openbabel import openbabel |
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parser = argparse.ArgumentParser() |
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parser.add_argument('-d', type=str, default=None, help='Input the dirpath') |
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args = parser.parse_args() |
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dirpath = args.d |
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if dirpath[-1] != '/' : |
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dirpath = dirpath + '/' |
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#%% |
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def create_directory(dir_name): |
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# 使用os.path.exists()检查目录是否存在 |
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if not os.path.exists(dir_name): |
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# 如果目录不存在,使用os.makedirs()创建它 |
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os.makedirs(dir_name) |
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input_dirpath = dirpath #文件夹以/结尾 |
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dir_name = os.path.basename(os.path.dirname(input_dirpath)) |
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dir_path = os.path.dirname(os.path.dirname(input_dirpath)) |
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output_dirpath = os.path.join(dir_path,dir_name+'_min') |
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create_directory(output_dirpath) |
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logging.basicConfig(level=logging.CRITICAL) |
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openbabel.obErrorLog.StopLogging() |
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#%% |
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def sdf_min(input_sdf, output_sdf): |
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# 创建一个分子对象 |
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mol = openbabel.OBMol() |
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# 创建转换器,用于文件读写 |
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conv = openbabel.OBConversion() |
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conv.SetInAndOutFormats("sdf", "sdf") |
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# 从SDF文件中读取分子 |
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conv.ReadFile(mol, input_sdf) |
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# 创建力场对象,使用MMFF94力场 |
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forcefield = openbabel.OBForceField.FindForceField("MMFF94") |
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# 为分子设置力场 |
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success = forcefield.Setup(mol) |
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if not success: |
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raise Exception("Error setting up force field") |
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# 进行能量最小化 |
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forcefield.SteepestDescent(10000) # 原来是5000步最速下降法 |
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forcefield.GetCoordinates(mol) # 将能量最小化后的坐标保存到分子对象 |
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# 将能量最小化后的分子写入到SDF文件 |
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conv.WriteFile(mol, output_sdf) |
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#%% |
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from tqdm import tqdm |
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from concurrent.futures import ProcessPoolExecutor |
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import multiprocessing |
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def handle_file(filename): |
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if '.sdf' == filename[-4:]: |
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input_sdf_file = os.path.join(input_dirpath, filename) |
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output_sdf_file = os.path.join(output_dirpath, filename) |
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try: |
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sdf_min(input_sdf_file, output_sdf_file) |
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except Exception as e: |
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print(f"An error occurred while processing the file '{input_sdf_file}': {e}") |
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try: |
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os.remove(output_sdf_file) |
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print(output_sdf_file + ' was successfully removed') |
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except Exception: |
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if os.path.exists(output_sdf_file): |
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print('please remove '+output_sdf_file) |
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else: |
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src_file = os.path.join(input_dirpath, filename) |
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dst_file = os.path.join(output_dirpath, filename) |
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shutil.copy(src_file, dst_file) |
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def main(): |
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file_list = os.listdir(input_dirpath) |
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# 获取系统的 CPU 核心数 |
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num_cores = multiprocessing.cpu_count() |
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# 创建一个进程池 |
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with ProcessPoolExecutor(max_workers=num_cores) as executor: |
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# 使用 tqdm 提供进度条功能 |
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list(tqdm(executor.map(handle_file, file_list), total=len(file_list))) |
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#%% |
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import pandas as pd |
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import os |
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import hashlib |
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class dir_check(): |
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def __init__(self,dirpath): |
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self.dirpath = dirpath |
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self.mapping_file = os.path.join(self.dirpath, 'hash_ligand_mapping.csv') |
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self.mapping_data = pd.read_csv(self.mapping_file, header=None) |
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self.smiles_list = self.mapping_data.iloc[:, 1].tolist() |
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self.hash_list = self.mapping_data.iloc[:, 0].tolist() |
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self.filename_list = os.listdir(self.dirpath) |
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self.sdf_filename_list = [x for x in self.filename_list if x[-4:] == '.sdf'] |
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def mapping_file_check(self): |
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for i in range(len(self.smiles_list)): |
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if hashlib.sha1(self.smiles_list[i].encode()).hexdigest() != self.hash_list[i]: |
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print('error in mapping file') |
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print('mapping file check completed') |
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def dir_file_check(self): |
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filename_hash_list = [x[:-4] for x in self.sdf_filename_list] |
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for filename_hash in filename_hash_list: |
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if filename_hash not in self.hash_list: |
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filename = filename_hash+'.sdf' |
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print(filename + ' not in mapping file') |
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os.remove(os.path.join(self.dirpath,filename)) |
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print('remove ' + os.path.join(self.dirpath,filename)) |
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#%% |
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if __name__ == '__main__': |
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main() |
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check = dir_check(output_dirpath) |
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check.mapping_file_check() |
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check.dir_file_check() |
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