260 lines
9.1 KiB
Python
Executable File
260 lines
9.1 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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批量处理16元环大环内酯分子
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处理文件: ring16/temp_filtered_complete.csv (1241个分子)
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输出文件夹: output/ring16_fragments/
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"""
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import sys
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from pathlib import Path
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# 添加项目根目录到 Python 路径
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# 获取脚本所在目录的父目录（项目根目录）
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script_dir = Path(__file__).resolve().parent
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project_root = script_dir.parent
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sys.path.insert(0, str(project_root))
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from rdkit import Chem
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import pandas as pd
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import json
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from tqdm import tqdm
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from datetime import datetime
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from src.ring_numbering import (
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assign_ring_numbering,
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validate_numbering,
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get_ring_atoms
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)
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from src.fragment_cleaver import cleave_side_chains
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def log_message(message, log_file, log_type='info'):
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"""记录日志信息"""
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timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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log_entry = f"[{timestamp}] {message}\n"
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with open(log_file, 'a', encoding='utf-8') as f:
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f.write(log_entry)
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if log_type == 'error':
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print(f"❌ {message}")
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else:
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print(f"✓ {message}")
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def process_single_molecule(idx, row, output_base_dir, log_file, error_log_file, multiple_lactone_log):
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"""处理单个分子"""
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try:
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# 获取分子信息
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molecule_id = row['IDs']
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molecule_name = row['molecule_pref_name']
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smiles = row['smiles']
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parent_id = f"ring16_mol_{idx}"
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# 解析SMILES
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mol = Chem.MolFromSmiles(smiles)
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if mol is None:
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log_message(f"分子 {idx} ({molecule_id}) SMILES解析失败", error_log_file, 'error')
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return None, 'parse_failed'
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# 检查环上是否有多个内酯键
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from src.ring_numbering import find_lactone_carbon, get_ring_atoms
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# 获取16元环上的所有原子
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ring_atoms = get_ring_atoms(mol)
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if len(ring_atoms) > 0:
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# 使用更严格的SMARTS模式：环上的氧连接到环上的羰基碳
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# [r16;O] 环上的氧，连接到 [r16;#6] 环上的碳，该碳有双键氧 (=O)
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lactone_pattern = Chem.MolFromSmarts("[r16;#8][r16;#6](=[#8])")
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if lactone_pattern:
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matches = mol.GetSubstructMatches(lactone_pattern)
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# 提取环上的内酯碳索引（match[1]是羰基碳）
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lactone_carbons_on_ring = []
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for match in matches:
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if len(match) >= 2:
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carbonyl_carbon = match[1] # 羰基碳
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# 确保这个碳确实在16元环上
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if carbonyl_carbon in ring_atoms:
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lactone_carbons_on_ring.append(carbonyl_carbon)
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# 去重
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lactone_carbons_on_ring = list(set(lactone_carbons_on_ring))
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# 只有当环上有多个内酯键时才过滤
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if len(lactone_carbons_on_ring) > 1:
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log_message(
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f"分子 {idx} ({molecule_id}, {molecule_name}) 环上有{len(lactone_carbons_on_ring)}个内酯键，已过滤。环上内酯碳索引: {lactone_carbons_on_ring}",
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multiple_lactone_log,
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'info'
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)
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return None, 'multiple_lactones'
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# 分配编号
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numbering = assign_ring_numbering(mol)
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if len(numbering) == 0:
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log_message(f"分子 {idx} ({molecule_id}) 编号失败", error_log_file, 'error')
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return None, 'numbering_failed'
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# 验证编号
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if not validate_numbering(mol, numbering):
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log_message(f"分子 {idx} ({molecule_id}) 编号验证失败", error_log_file, 'error')
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return None, 'validation_failed'
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# 侧链断裂
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try:
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mol_fragments = cleave_side_chains(mol, smiles, parent_id, numbering)
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except Exception as e:
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log_message(f"分子 {idx} ({molecule_id}) 裂解失败: {str(e)}", error_log_file, 'error')
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return None, 'cleavage_failed'
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# 创建分子专属文件夹
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mol_output_dir = output_base_dir / parent_id
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mol_output_dir.mkdir(parents=True, exist_ok=True)
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# 保存整个MoleculeFragments对象
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mol_fragments_path = mol_output_dir / f"{parent_id}_all_fragments.json"
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mol_fragments.to_json_file(str(mol_fragments_path))
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# 保存每个碎片
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for frag in mol_fragments.fragments:
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frag_path = mol_output_dir / f"{frag.fragment_id}.json"
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frag.to_json_file(str(frag_path))
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# 保存分子信息到metadata
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metadata = {
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'parent_id': parent_id,
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'molecule_id': molecule_id,
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'molecule_name': molecule_name,
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'smiles': smiles,
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'ring_size': 16,
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'num_fragments': len(mol_fragments.fragments),
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'processing_date': datetime.now().isoformat()
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}
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metadata_path = mol_output_dir / 'metadata.json'
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with open(metadata_path, 'w', encoding='utf-8') as f:
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json.dump(metadata, f, indent=2, ensure_ascii=False)
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return len(mol_fragments.fragments), 'success'
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except Exception as e:
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log_message(f"分子 {idx} 未预期错误: {str(e)}", error_log_file, 'error')
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return None, 'unexpected_error'
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def main():
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print("="*80)
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print("16元环大环内酯批量处理程序")
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print("="*80)
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print()
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# 读取数据
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input_file = Path('ring16/temp_filtered_complete.csv')
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if not input_file.exists():
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print(f"❌ 错误: 找不到输入文件 {input_file}")
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return
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df = pd.read_csv(input_file)
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print(f"✓ 读取数据集: {len(df)} 个分子")
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print(f" 文件: {input_file}")
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print()
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# 创建输出文件夹
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output_base_dir = Path('output/ring16_fragments')
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output_base_dir.mkdir(parents=True, exist_ok=True)
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# 创建日志文件
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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log_file = output_base_dir / f'processing_log_{timestamp}.txt'
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error_log_file = output_base_dir / f'error_log_{timestamp}.txt'
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multiple_lactone_log = output_base_dir / f'multiple_lactone_log_{timestamp}.txt'
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print(f"✓ 输出文件夹: {output_base_dir}")
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print(f"✓ 日志文件: {log_file}")
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print()
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# 统计信息
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stats = {
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'total': len(df),
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'success': 0,
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'failed_parse': 0,
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'failed_numbering': 0,
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'failed_validation': 0,
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'failed_cleavage': 0,
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'failed_unexpected': 0,
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'multiple_lactones': 0,
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'total_fragments': 0
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}
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# 批量处理
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print("开始批量处理...")
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print()
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log_message(f"开始批量处理 {len(df)} 个16元环分子", log_file)
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for idx in tqdm(range(len(df)), desc="处理进度"):
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num_fragments, status = process_single_molecule(
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idx, df.iloc[idx], output_base_dir, log_file, error_log_file, multiple_lactone_log
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)
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if status == 'success':
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stats['success'] += 1
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stats['total_fragments'] += num_fragments
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elif status == 'parse_failed':
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stats['failed_parse'] += 1
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elif status == 'numbering_failed':
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stats['failed_numbering'] += 1
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elif status == 'validation_failed':
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stats['failed_validation'] += 1
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elif status == 'cleavage_failed':
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stats['failed_cleavage'] += 1
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elif status == 'multiple_lactones':
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stats['multiple_lactones'] += 1
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else:
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stats['failed_unexpected'] += 1
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print()
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print("="*80)
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print("处理完成！")
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print("="*80)
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print()
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# 打印统计结果
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print("统计结果:")
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print(f" 总分子数: {stats['total']}")
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print(f" 成功处理: {stats['success']} ({stats['success']/stats['total']*100:.2f}%)")
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print(f" 总碎片数: {stats['total_fragments']}")
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if stats['success'] > 0:
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print(f" 平均碎片: {stats['total_fragments']/stats['success']:.2f} 个/分子")
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print()
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print("失败情况:")
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print(f" SMILES解析失败: {stats['failed_parse']}")
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print(f" 编号失败: {stats['failed_numbering']}")
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print(f" 验证失败: {stats['failed_validation']}")
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print(f" 裂解失败: {stats['failed_cleavage']}")
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print(f" 多个内酯键: {stats['multiple_lactones']}")
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print(f" 其他错误: {stats['failed_unexpected']}")
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total_failed = stats['total'] - stats['success']
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print(f" 总失败: {total_failed} ({total_failed/stats['total']*100:.2f}%)")
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print()
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# 保存统计结果
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stats_file = output_base_dir / 'processing_statistics.json'
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with open(stats_file, 'w', encoding='utf-8') as f:
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json.dump(stats, f, indent=2)
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print(f"✓ 统计结果已保存: {stats_file}")
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print(f"✓ 输出文件夹: {output_base_dir}")
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print()
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log_message(f"处理完成: 成功 {stats['success']}/{stats['total']}", log_file)
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if __name__ == '__main__':
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main()
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