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