add

scripts/move_sdf.py

@@ -0,0 +1,95 @@
+import pandas as pd
+from pathlib import Path
+import shutil
+from rdkit import Chem
+from concurrent.futures import ProcessPoolExecutor, as_completed
+
+# 路径设置
+SOURCE_DIR = Path(r"D:\inhibitor\data\COCUNUT\COCONUT_sdf")
+DEST_DIR = Path(r"C:\Users\pylyz\Documents\project\unidock-mcp\scripts\data\molecules")
+
+DEST_DIR.mkdir(parents=True, exist_ok=True)
+
+def process_row(row):
+    identifier = row['identifier']
+    smiles = row['canonical_smiles']
+    sdf_filename = f"{identifier}.sdf"
+    src_sdf = SOURCE_DIR / sdf_filename
+    dst_sdf = DEST_DIR / sdf_filename
+
+    result = {
+        "identifier": identifier,
+        "smiles": smiles,
+        "src_exists": src_sdf.exists(),
+        "copied": False,
+        "rdkit_ok": False,
+        "error": ""
+    }
+
+    if src_sdf.exists():
+        try:
+            shutil.copy2(src_sdf, dst_sdf)
+            result['copied'] = True
+        except Exception as e:
+            result['error'] = f"拷贝失败: {e}"
+            return result
+        try:
+            # 检查SDF文件能否被RDKit读取
+            suppl = Chem.SDMolSupplier(str(dst_sdf), sanitize=False)
+            mols = [mol for mol in suppl if mol is not None]
+            if len(mols) > 0:
+                result['rdkit_ok'] = True
+            else:
+                result['error'] = "RDKit无法读取SDF"
+        except Exception as e:
+            result['error'] = f"RDKit异常: {e}"
+    else:
+        result['error'] = "SDF文件不存在"
+    return result
+
+def main():
+    csv_path = "coconut_data_info.csv"
+    df = pd.read_csv(csv_path, dtype=str)
+
+    results = []
+    with ProcessPoolExecutor() as executor:
+        futures = [executor.submit(process_row, row) for _, row in df.iterrows()]
+        for fut in as_completed(futures):
+            results.append(fut.result())
+
+    copied_and_valid = [r for r in results if r['src_exists'] and r['copied'] and r['rdkit_ok']]
+    copied_but_invalid = [r for r in results if r['src_exists'] and r['copied'] and not r['rdkit_ok']]
+    no_sdf = [r for r in results if not r['src_exists']]
+    failed_copy = [r for r in results if r['src_exists'] and not r['copied']]
+
+    print("=" * 60)
+    print(f"总分子数: {len(df)}")
+    print(f"有SDF并成功拷贝且可被RDKit读取: {len(copied_and_valid)}")
+    print(f"有SDF拷贝后不能被RDKit读取(坏文件): {len(copied_but_invalid)}")
+    print(f"没有SDF文件: {len(no_sdf)}")
+    print(f"SDF存在但拷贝失败: {len(failed_copy)}")
+    print("=" * 60)
+
+    # 输出详细清单
+    if copied_but_invalid:
+        print("拷贝后坏SDF列表（identifier）：")
+        for r in copied_but_invalid:
+            print(f"  {r['identifier']} ({r['error']})")
+        print("-" * 30)
+    if no_sdf:
+        print("没有SDF文件的canonical_smiles：")
+        for r in no_sdf:
+            print(f"  {r['smiles']} ({r['identifier']})")
+        # 也可以保存为文本文件
+        with open("no_sdf_smiles.txt", "w", encoding="utf-8") as f:
+            for r in no_sdf:
+                f.write(f"{r['smiles']}\t{r['identifier']}\n")
+        print("所有无SDF分子的smiles已保存到 no_sdf_smiles.txt")
+    if failed_copy:
+        print("拷贝失败的分子：")
+        for r in failed_copy:
+            print(f"  {r['identifier']} ({r['error']})")
+        print("-" * 30)
+
+if __name__ == "__main__":
+    main()

scripts/sdf2to3d.py

@@ -0,0 +1,94 @@
+"""
+-------------------------------------------------------------
+批量2D SDF文件 → 3D SDF文件 并行转换脚本 (joblib版)
+-------------------------------------------------------------
+功能：
+- 从指定目录读取2D SDF文件（每个分子一个SDF文件），并行批量生成3D SDF文件，保留原有属性
+- 支持失败分子详细记录和统计
+- 源文件与目标3D SDF目录分离，防止覆盖
+
+依赖安装：
+    conda install -y -c conda-forge rdkit joblib
+
+用法示例：
+    python batch_2d_to_3d.py --src_dir ./2d_sdf_dir --out_dir ./3d_sdf_dir --n_jobs 8
+
+-------------------------------------------------------------
+"""
+
+from pathlib import Path
+from rdkit import Chem
+from rdkit.Chem import AllChem
+from joblib import Parallel, delayed
+import argparse
+
+def convert_2d_to_3d_sdf(sdf_path, out_dir, max_attempts=10):
+    identifier = sdf_path.stem
+    out_sdf = out_dir / f"{identifier}.sdf"
+    try:
+        suppl = Chem.SDMolSupplier(str(sdf_path), sanitize=True)
+        mols = [mol for mol in suppl if mol is not None]
+        if not mols:
+            return identifier, False, "SDF读取失败"
+        mol = mols[0]
+        mol = Chem.AddHs(mol)
+        params = AllChem.ETKDGv3()
+        last_error = ""
+        for attempt in range(max_attempts):
+            try:
+                status = AllChem.EmbedMolecule(mol, params)
+                if status == 0:
+                    AllChem.UFFOptimizeMolecule(mol)
+                    writer = Chem.SDWriter(str(out_sdf))
+                    writer.write(mol)
+                    writer.close()
+                    return identifier, True, f"成功（第{attempt+1}次）"
+                else:
+                    last_error = f"Embed失败: status={status}"
+            except Exception as e:
+                last_error = f"3D生成异常: {e}"
+        return identifier, False, last_error if last_error else f"3D构象生成失败（已重试{max_attempts}次）"
+    except Exception as e:
+        return identifier, False, f"异常: {e}"
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--src_dir', type=str, required=True, help='2D SDF文件夹路径')
+    parser.add_argument('--out_dir', type=str, required=True, help='3D SDF输出文件夹路径')
+    parser.add_argument('--n_jobs', type=int, default=4, help='并行进程数')
+    parser.add_argument('--max_attempts', type=int, default=10, help='最大Embed尝试次数')
+    args = parser.parse_args()
+
+    src_dir = Path(args.src_dir)
+    out_dir = Path(args.out_dir)
+    out_dir.mkdir(parents=True, exist_ok=True)
+
+    sdf_files = list(src_dir.glob("*.sdf"))
+    print(f"共检测到2D SDF文件 {len(sdf_files)} 个，开始并行3D生成...")
+
+    results = Parallel(n_jobs=args.n_jobs)(
+        delayed(convert_2d_to_3d_sdf)(sdf_file, out_dir, args.max_attempts) for sdf_file in sdf_files
+    )
+
+    # 分类统计
+    success = [r for r in results if r[1]]
+    failed = [r for r in results if not r[1]]
+
+    print("="*60)
+    print(f"总2D SDF: {len(sdf_files)}")
+    print(f"成功生成3D SDF: {len(success)}")
+    print(f"失败: {len(failed)}")
+    if failed:
+        print("失败分子列表：")
+        for ident, _, msg in failed:
+            print(f"  {ident}: {msg}")
+        # 保存失败到文件
+        failfile = out_dir / "failed_2dto3d.txt"
+        with open(failfile, "w", encoding="utf-8") as f:
+            for ident, _, msg in failed:
+                f.write(f"{ident}\t{msg}\n")
+        print(f"失败分子已保存到: {failfile.resolve()}")
+    print("="*60)
+
+if __name__ == '__main__':
+    main()