add cleanATOM
This commit is contained in:
182
analysis_pdb.py
182
analysis_pdb.py
@@ -9,7 +9,7 @@
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@version :1.0
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'''
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# micromamba create -n modeller modeller biopython pymol-open-source biopandas requests -y -c conda-forge -c salilab
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# modeller注册码：MODELIRANJE
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# modeller注册码：MODELIRANJE (<conda_env>//lib/modeller-10.4/modlib/modeller/config.py)
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from dataclasses import dataclass, field
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from Bio.PDB import PDBParser
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from Bio.SeqUtils import seq1
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@@ -23,6 +23,7 @@ from Bio import SeqIO
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import requests
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from copy import deepcopy
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from pymol import cmd
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import os
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@dataclass
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class PDBAnalyzer:
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@@ -51,6 +52,31 @@ class PDBAnalyzer:
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self.protein_state = 'Holo' if 'HETATM' in self.biodata.df.keys() else 'Apo'
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self.chain_id_list = self.biodata.df['ATOM']['chain_id'].drop_duplicates().to_list()
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def cleanATOM(self, out_file=None, ext="_clean.pdb") -> Path: # from pyrosetta.toolbox import cleanATOM
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"""Extract all ATOM and TER records in a PDB file and write them to a new file.
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Args:
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pdb_file (str): Path of the PDB file from which ATOM and TER records
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will be extracted
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out_file (str): Optional argument to specify a particular output filename.
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Defaults to <pdb_file>.clean.pdb.
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ext (str): File extension to use for output file. Defaults to ".clean.pdb"
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"""
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pdb_file = self.path.as_posix()
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# find all ATOM and TER lines
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with open(pdb_file, "r") as fid:
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good = [l for l in fid if l.startswith(("ATOM", "TER"))]
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# default output file to <pdb_file>_clean.pdb
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if out_file is None:
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out_file = os.path.splitext(pdb_file)[0] + ext
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# write the selected records to a new file
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with open(out_file, "w") as fid:
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fid.writelines(good)
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return Path(out_file)
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def check_continuity(self, chain, missing_char):
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"""
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Check the continuity of residues in a protein chain.
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@@ -370,6 +396,92 @@ def import_and_merge_pdb_strings(pdb_strings, merged_object_name, output_file):
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# 保存合并后的对象
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cmd.save(output_file, merged_object_name)
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'''
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# 示例: 使用biopython提取A链（将会保留HETATM）
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chain_extractor = analyzer.extract_chain('A') # 假设要提取的链ID是 'A'
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chain_extractor.save('biopython_extracted_chain_A.pdb') # 保存为PDB文件
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# 示例: 使用biopandas提取A链（将不会保留HETATM）
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chain_extractor = analyzer.split_chain('A') # 假设要提取的链ID是 'A'
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chain_extractor.to_pdb('biopandas_extracted_chain_A.pdb') # 保存为PDB文件
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# A链改B链, 并分割保存为单独文件
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analyzer.change_chain_identifier('A', 'B', split=True).to_pdb(f'{PDB_ID}_B.pdb')
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# 分割所有的链
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split_dict = {}
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for j in analyzer.chain_id_list:
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fn = Path(f'{PDB_ID}_{j}.pdb')
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analyzer.split_chain(j).to_pdb(fn.as_posix())
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split_dict[j]=fn.read_text()
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'''
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def fix_all(path:Path):
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pdbfiles = [i for i in path.glob('*.pdb')]
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for i in pdbfiles:
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PDB_file_path = i
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PDB_ID = i.stem
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analyzer = PDBAnalyzer(PDB_file_path)
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sequences = analyzer.extract_sequences(missing_char='-') # 或者 'X', 或者 ''
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print(f'Residues info for {PDB_ID}: \n',sequences)
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missing_info = analyzer.extract_sequences_info()
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print(f'Missing residues info for {PDB_ID}:\n {missing_info}')
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# 示例: 使用biopython提取A链（将会保留HETATM）
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chain_extractor = analyzer.extract_chain('A') # 假设要提取的链ID是 'A'
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chain_extractor.save('biopython_extracted_chain_A.pdb') # 保存为PDB文件
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# 示例: 使用biopandas提取A链（将不会保留HETATM）
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chain_extractor = analyzer.split_chain('A') # 假设要提取的链ID是 'A'
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chain_extractor.to_pdb('biopandas_extracted_chain_A.pdb') # 保存为PDB文件
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# A链改B链, 并分割保存为单独文件
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analyzer.change_chain_identifier('A', 'B', split=True).to_pdb(f'{PDB_ID}_B.pdb')
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# 分割所有的链
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split_dict = {}
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for j in analyzer.chain_id_list:
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fn = Path(f'{PDB_ID}_{j}.pdb')
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analyzer.split_chain(j).to_pdb(fn.as_posix())
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split_dict[j]=fn.read_text()
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# 修复loop区域
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from build_modeller import PDBModeler
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from modeller import ModellerError
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mc_dict = {}
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for mc in missing_info:
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out_file = f'5sws_{mc}.pdb'
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analyzer.split_chain(mc).to_pdb(out_file) # get misschain pdb file
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mc_fasta = analyzer.filter_sequences(mc) # get misschain fasta file
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if len(mc_fasta) == 1:
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mc_fasta = mc_fasta[0]
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out_fasta_file = Path(f'{PDB_ID}_{mc}.fasta')
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analyzer.write_seq_to_fasta_single_line(mc_fasta, out_fasta_file)
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print(f'>{mc_fasta.description}')
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print(mc_fasta.seq)
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modeller = PDBModeler(PDB_file_path, out_fasta_file, Path('.'), mc, 1, 'refine.very_fast')
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try:
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modeller_results = modeller.make_model()
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except ModellerError:
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print(f'Failed to build model for chain {mc}')
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print(f'No loops detected in {out_fasta_file.name}')
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print(f'may pdb file sequence is not correct')
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continue
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except Exception as e:
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raise e
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print(f'Model files: {[file.name for file in modeller_results]}')
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# change id to original
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for i in modeller_results:
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manalyzer = PDBAnalyzer(i)
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manalyzer.change_chain_identifier('A', mc, split=False).to_pdb(i)
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if len(modeller_results) == 1:
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# use pymol to align
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aligner = PDBAlign(PDB_file_path, modeller_results[0],Path(f'{PDB_ID}_merge_model.pdb'))
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pdbstr = aligner.align()
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mc_dict[mc] = pdbstr
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else:
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print('more than one model file, please set num_loop to 1')
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elif len(mc_fasta) == 0:
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continue
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else:
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raise ValueError(f'only can fix one chain content: {mc_fasta}')
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# 使用示例
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split_dict.update(mc_dict) # 更新 split_dict
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import_and_merge_pdb_strings(split_dict, "merged_object", f'{PDB_ID}.modellerfix.pdb')
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if __name__ == "__main__":
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# import argparse
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# parser = argparse.ArgumentParser(description="Build model by Modeller")
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@@ -380,71 +492,7 @@ if __name__ == "__main__":
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# parser.add_argument("-m", "--md_level", help="MD level")
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# parser.add_argument("-c", "--chain", help="Chain ID")
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# args = parser.parse_args()
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pdbfiles = [i for i in Path('../PDBfile').glob('*.pdb')]
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for i in pdbfiles:
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PDB_file_path = i
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PDB_ID = i.stem
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analyzer = PDBAnalyzer(PDB_file_path)
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sequences = analyzer.extract_sequences(missing_char='-') # 或者 'X', 或者 ''
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print(f'Residues info for {PDB_ID}: \n',sequences)
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missing_info = analyzer.extract_sequences_info()
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print(f'Missing residues info for {PDB_ID}:\n {missing_info}')
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# 示例: 使用biopython提取A链（将会保留HETATM）
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chain_extractor = analyzer.extract_chain('A') # 假设要提取的链ID是 'A'
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chain_extractor.save('biopython_extracted_chain_A.pdb') # 保存为PDB文件
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# 示例: 使用biopandas提取A链（将不会保留HETATM）
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chain_extractor = analyzer.split_chain('A') # 假设要提取的链ID是 'A'
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chain_extractor.to_pdb('biopandas_extracted_chain_A.pdb') # 保存为PDB文件
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# A链改B链, 并分割保存为单独文件
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analyzer.change_chain_identifier('A', 'B', split=True).to_pdb(f'{PDB_ID}_B.pdb')
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# 分割所有的链
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split_dict = {}
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for j in analyzer.chain_id_list:
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fn = Path(f'{PDB_ID}_{j}.pdb')
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analyzer.split_chain(j).to_pdb(fn.as_posix())
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split_dict[j]=fn.read_text()
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# 修复loop区域
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from build_modeller import PDBModeler
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from modeller import ModellerError
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mc_dict = {}
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for mc in missing_info:
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out_file = f'5sws_{mc}.pdb'
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analyzer.split_chain(mc).to_pdb(out_file) # get misschain pdb file
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mc_fasta = analyzer.filter_sequences(mc) # get misschain fasta file
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if len(mc_fasta) == 1:
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mc_fasta = mc_fasta[0]
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out_fasta_file = Path(f'{PDB_ID}_{mc}.fasta')
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analyzer.write_seq_to_fasta_single_line(mc_fasta, out_fasta_file)
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print(f'>{mc_fasta.description}')
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print(mc_fasta.seq)
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modeller = PDBModeler(PDB_file_path, out_fasta_file, Path('.'), mc, 1, 'refine.very_fast')
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try:
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modeller_results = modeller.make_model()
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except ModellerError:
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print(f'Failed to build model for chain {mc}')
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print(f'No loops detected in {out_fasta_file.name}')
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print(f'may pdb file sequence is not correct')
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continue
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except Exception as e:
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raise e
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print(f'Model files: {[file.name for file in modeller_results]}')
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# change id to original
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for i in modeller_results:
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manalyzer = PDBAnalyzer(i)
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manalyzer.change_chain_identifier('A', mc, split=False).to_pdb(i)
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if len(modeller_results) == 1:
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# use pymol to align
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aligner = PDBAlign(PDB_file_path, modeller_results[0],Path(f'{PDB_ID}_merge_model.pdb'))
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pdbstr = aligner.align()
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mc_dict[mc] = pdbstr
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else:
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print('more than one model file, please set num_loop to 1')
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elif len(mc_fasta) == 0:
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continue
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else:
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raise ValueError(f'only can fix one chain content: {mc_fasta}')
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# fix_all(Path('./pdb_test1'))
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pass
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# 使用示例
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split_dict.update(mc_dict) # 更新 split_dict
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import_and_merge_pdb_strings(split_dict, "merged_object", f'{PDB_ID}.modellerfix.pdb')
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