lingyuzeng
c0ead42384
Implement the standard/non-standard/not-macrolactone classification layer and integrate it into analyzer, fragmenter, and CLI outputs. Port the remaining legacy package capabilities into new visualization and workflow modules, restore batch/statistics/SDF scripts on top of the flat CSV workflow, and update active docs to the new package API.
58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
from __future__ import annotations
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import argparse
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import json
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from collections import Counter
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from pathlib import Path
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import pandas as pd
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from rdkit import Chem
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from rdkit.Chem import AllChem
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def build_parser() -> argparse.ArgumentParser:
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parser = argparse.ArgumentParser(
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description="Generate cleavage statistics and ETKDGv3 parent-molecule SDF files from flat fragment CSV."
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)
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parser.add_argument("--input", required=True)
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parser.add_argument("--output-dir", required=True)
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return parser
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def main(argv: list[str] | None = None) -> None:
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args = build_parser().parse_args(argv)
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dataframe = pd.read_csv(args.input)
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output_dir = Path(args.output_dir)
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sdf_dir = output_dir / "sdf"
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output_dir.mkdir(parents=True, exist_ok=True)
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sdf_dir.mkdir(parents=True, exist_ok=True)
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position_counts = Counter(int(position) for position in dataframe["cleavage_position"])
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stats = {
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"position_counts": dict(sorted(position_counts.items())),
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"total_fragments": int(len(dataframe)),
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"total_parent_molecules": int(dataframe["parent_id"].nunique()),
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}
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(output_dir / "cleavage_position_statistics.json").write_text(
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json.dumps(stats, indent=2, ensure_ascii=False) + "\n",
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encoding="utf-8",
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)
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parent_rows = dataframe[["parent_id", "parent_smiles"]].drop_duplicates()
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for parent in parent_rows.itertuples(index=False):
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mol = Chem.MolFromSmiles(parent.parent_smiles)
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if mol is None:
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continue
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mol = Chem.AddHs(mol)
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params = AllChem.ETKDGv3()
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if AllChem.EmbedMolecule(mol, params) != 0:
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continue
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AllChem.UFFOptimizeMolecule(mol)
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writer = Chem.SDWriter(str(sdf_dir / f"{parent.parent_id}_3d.sdf"))
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writer.write(mol)
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writer.close()
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if __name__ == "__main__":
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main()
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