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"""Build viewer-friendly Parquet splits for LiteFold/SwissSidechain."""
from __future__ import annotations
import argparse
import hashlib
import json
import re
import shutil
import zipfile
from collections import Counter, defaultdict
from pathlib import Path
from typing import Any
import pandas as pd
ENTRY_COLUMNS = [
"entry_id",
"residue_code",
"stereochemistry",
"smiles",
"smiles_reference_file",
"source_smi_path",
"source_pdb_path",
"source_mol2_path",
"source_top_path",
"source_rtp_path",
"source_hdb_path",
"has_smi",
"has_pdb",
"has_mol2",
"has_top",
"has_rtp",
"has_hdb",
"has_bundle",
"has_png",
"has_bundle_bbdep_lib",
"has_bundle_bbind_lib",
"bundle_file_extensions",
"pdb_residue_names",
"pdb_atom_names",
"pdb_elements",
"pdb_atom_count",
"pdb_heavy_atom_count",
"pdb_hydrogen_atom_count",
"mol2_molecule_name",
"mol2_molecule_type",
"mol2_charge_type",
"mol2_atom_names",
"mol2_atom_types",
"mol2_atom_charges",
"mol2_atom_count",
"mol2_bond_count",
"mol2_total_partial_charge",
"charmm_residue_name",
"charmm_residue_charge",
"charmm_residue_comment",
"charmm_atom_names",
"charmm_atom_types",
"charmm_atom_charges",
"charmm_atom_count",
"charmm_bond_count",
"gromacs_residue_name",
"gromacs_residue_comment",
"gromacs_atom_names",
"gromacs_atom_types",
"gromacs_atom_charges",
"gromacs_atom_count",
"gromacs_bond_count",
"gromacs_improper_count",
"hdb_rule_count",
"hdb_declared_rule_count",
"bbind_rotamer_rows",
"bbdep_rotamer_rows",
"split_bucket",
]
def stable_bucket(value: str, buckets: int = 10) -> int:
digest = hashlib.sha256(value.encode("utf-8")).hexdigest()[:16]
return int(digest, 16) % buckets
def parse_float(value: str | None) -> float | None:
if value is None:
return None
try:
return float(value)
except ValueError:
return None
def is_canonical_zip_path(name: str, expected_prefix: str) -> bool:
parts = Path(name).parts
return len(parts) >= 2 and parts[0] == expected_prefix
def read_zip_text_by_stem(path: Path, expected_prefix: str, suffixes: tuple[str, ...]) -> dict[str, dict[str, str]]:
items: dict[str, dict[str, str]] = {}
with zipfile.ZipFile(path) as zf:
for name in zf.namelist():
if name.endswith("/") or not name.lower().endswith(suffixes):
continue
stem = Path(name).stem
text = zf.read(name).decode("utf-8", errors="replace")
existing = items.get(stem)
if existing is None or (
is_canonical_zip_path(name, expected_prefix) and not is_canonical_zip_path(existing["path"], expected_prefix)
):
items[stem] = {"path": name, "text": text}
return items
def read_rtp_hdb_zip(path: Path, expected_prefix: str) -> tuple[dict[str, dict[str, str]], dict[str, dict[str, str]]]:
rtp: dict[str, dict[str, str]] = {}
hdb: dict[str, dict[str, str]] = {}
with zipfile.ZipFile(path) as zf:
for name in zf.namelist():
if name.endswith("/"):
continue
stem = Path(name).stem
suffix = Path(name).suffix.lower()
target = rtp if suffix == ".rtp" else hdb if suffix == ".hdb" else None
if target is None:
continue
text = zf.read(name).decode("utf-8", errors="replace")
existing = target.get(stem)
if existing is None or (
is_canonical_zip_path(name, expected_prefix) and not is_canonical_zip_path(existing["path"], expected_prefix)
):
target[stem] = {"path": name, "text": text}
return rtp, hdb
def parse_smi(text: str) -> tuple[str | None, str | None]:
for line in text.splitlines():
stripped = line.strip()
if not stripped:
continue
parts = stripped.split()
return parts[0], parts[1] if len(parts) > 1 else None
return None, None
def parse_pdb(text: str) -> dict[str, Any]:
atom_names: list[str] = []
elements: list[str] = []
residue_names: set[str] = set()
for line in text.splitlines():
if not (line.startswith("ATOM") or line.startswith("HETATM")):
continue
atom_name = line[12:16].strip()
residue_name = line[17:20].strip()
element = line[76:78].strip() if len(line) >= 78 else ""
if not element:
element = re.sub(r"[^A-Za-z]", "", atom_name)[:1]
if atom_name:
atom_names.append(atom_name)
if residue_name:
residue_names.add(residue_name)
if element:
elements.append(element.upper())
return {
"pdb_residue_names": sorted(residue_names),
"pdb_atom_names": atom_names,
"pdb_elements": elements,
"pdb_atom_count": len(atom_names),
"pdb_heavy_atom_count": sum(1 for element in elements if element != "H"),
"pdb_hydrogen_atom_count": sum(1 for element in elements if element == "H"),
}
def parse_mol2(text: str) -> dict[str, Any]:
section: str | None = None
molecule_lines: list[str] = []
atom_names: list[str] = []
atom_types: list[str] = []
charges: list[float] = []
bond_count = 0
for raw in text.splitlines():
line = raw.rstrip()
if line.startswith("@<TRIPOS>"):
section = line.removeprefix("@<TRIPOS>").strip()
continue
if not line.strip():
continue
if section == "MOLECULE":
molecule_lines.append(line.strip())
elif section == "ATOM":
parts = line.split()
if len(parts) >= 6:
atom_names.append(parts[1])
atom_types.append(parts[5])
if len(parts) >= 9:
charge = parse_float(parts[8])
if charge is not None:
charges.append(charge)
elif section == "BOND":
parts = line.split()
if len(parts) >= 4:
bond_count += 1
counts = molecule_lines[1].split() if len(molecule_lines) > 1 else []
declared_bonds = int(counts[1]) if len(counts) > 1 and counts[1].isdigit() else bond_count
return {
"mol2_molecule_name": molecule_lines[0] if molecule_lines else None,
"mol2_molecule_type": molecule_lines[2] if len(molecule_lines) > 2 else None,
"mol2_charge_type": molecule_lines[3] if len(molecule_lines) > 3 else None,
"mol2_atom_names": atom_names,
"mol2_atom_types": atom_types,
"mol2_atom_charges": charges,
"mol2_atom_count": len(atom_names),
"mol2_bond_count": declared_bonds,
"mol2_total_partial_charge": round(sum(charges), 6) if charges else None,
}
def parse_charmm_top(text: str) -> dict[str, Any]:
residue_name = None
residue_charge = None
residue_comment = None
atom_names: list[str] = []
atom_types: list[str] = []
atom_charges: list[float] = []
bond_count = 0
for raw in text.splitlines():
line = raw.strip()
if not line or line.startswith("!"):
continue
data, _, comment = line.partition("!")
parts = data.split()
if not parts:
continue
keyword = parts[0].upper()
if keyword == "RESI" and len(parts) >= 3:
residue_name = parts[1]
residue_charge = parse_float(parts[2])
residue_comment = comment.strip() or None
elif keyword == "ATOM" and len(parts) >= 4:
atom_names.append(parts[1])
atom_types.append(parts[2])
charge = parse_float(parts[3])
if charge is not None:
atom_charges.append(charge)
elif keyword in {"BOND", "DOUBLE"}:
bond_count += len(parts[1:]) // 2
return {
"charmm_residue_name": residue_name,
"charmm_residue_charge": residue_charge,
"charmm_residue_comment": residue_comment,
"charmm_atom_names": atom_names,
"charmm_atom_types": atom_types,
"charmm_atom_charges": atom_charges,
"charmm_atom_count": len(atom_names),
"charmm_bond_count": bond_count,
}
def parse_gromacs_rtp(text: str) -> dict[str, Any]:
residue_name = None
residue_comment = None
section = None
atom_names: list[str] = []
atom_types: list[str] = []
atom_charges: list[float] = []
bond_count = 0
improper_count = 0
for raw in text.splitlines():
line = raw.strip()
if not line or line.startswith(";"):
continue
data, _, comment = line.partition(";")
data = data.strip()
if data.startswith("[") and data.endswith("]"):
label = data.strip("[]").strip()
if residue_name is None and label not in {"atoms", "bonds", "impropers", "cmap"}:
residue_name = label
residue_comment = comment.strip() or None
section = None
else:
section = label.lower()
continue
parts = data.split()
if section == "atoms" and len(parts) >= 3:
atom_names.append(parts[0])
atom_types.append(parts[1])
charge = parse_float(parts[2])
if charge is not None:
atom_charges.append(charge)
elif section == "bonds" and len(parts) >= 2:
bond_count += 1
elif section == "impropers" and len(parts) >= 4:
improper_count += 1
return {
"gromacs_residue_name": residue_name,
"gromacs_residue_comment": residue_comment,
"gromacs_atom_names": atom_names,
"gromacs_atom_types": atom_types,
"gromacs_atom_charges": atom_charges,
"gromacs_atom_count": len(atom_names),
"gromacs_bond_count": bond_count,
"gromacs_improper_count": improper_count,
}
def parse_hdb(text: str) -> dict[str, Any]:
lines = [line.strip() for line in text.splitlines() if line.strip() and not line.strip().startswith(";")]
declared = None
if lines:
parts = lines[0].split()
if len(parts) >= 2:
try:
declared = int(parts[1])
except ValueError:
declared = None
return {
"hdb_rule_count": max(len(lines) - 1, 0),
"hdb_declared_rule_count": declared,
}
def archive_bundle_manifest(path: Path, stereochemistry: str) -> dict[str, dict[str, Any]]:
manifest: dict[str, dict[str, Any]] = defaultdict(lambda: {"extensions": Counter(), "paths": []})
with zipfile.ZipFile(path) as zf:
for name in zf.namelist():
if name.endswith("/"):
continue
parts = Path(name).parts
if len(parts) < 2:
continue
residue_code = parts[-2]
suffix = Path(name).suffix.lower() or "<none>"
manifest[residue_code]["extensions"][suffix] += 1
manifest[residue_code]["paths"].append(name)
result = {}
for residue_code, item in manifest.items():
extensions = item["extensions"]
result[residue_code] = {
"bundle_file_extensions": sorted(extensions),
"has_png": extensions.get(".png", 0) > 0,
"has_bundle_bbdep_lib": any(path.endswith("_bbdep_Gfeller.lib.zip") for path in item["paths"]),
"has_bundle_bbind_lib": any(path.endswith("_bbind_Gfeller.lib.zip") for path in item["paths"]),
"stereochemistry": stereochemistry,
}
return result
def parse_rotamer_counts(path: Path, stereochemistry: str, library_type: str) -> tuple[dict[str, int], list[dict[str, Any]]]:
counts: Counter[str] = Counter()
with zipfile.ZipFile(path) as zf:
name = next(n for n in zf.namelist() if n.endswith(".lib"))
with zf.open(name) as handle:
for raw in handle:
line = raw.decode("utf-8", errors="replace").strip()
if not line or line.startswith("#"):
continue
counts[line.split()[0]] += 1
rows = [
{
"stereochemistry": stereochemistry,
"library_type": library_type,
"residue_code": residue_code,
"row_count": int(row_count),
}
for residue_code, row_count in sorted(counts.items())
]
return dict(counts), rows
def build_rows_for_stereo(raw_dir: Path, stereochemistry: str) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]:
prefix = "L" if stereochemistry == "L" else "D"
smi = read_zip_text_by_stem(raw_dir / f"{prefix}_SMI.zip", f"{prefix}_SMI", (".smi",))
pdb = read_zip_text_by_stem(raw_dir / f"{prefix}_PDB.zip", f"{prefix}_PDB", (".pdb",))
mol2 = read_zip_text_by_stem(raw_dir / f"{prefix}_MOL2.zip", f"{prefix}_MOL2", (".mol2",))
top = read_zip_text_by_stem(raw_dir / f"{prefix}_top.zip", f"{prefix}_top", (".top",))
rtp, hdb = read_rtp_hdb_zip(raw_dir / f"{prefix}_rtp.zip", f"{prefix}_rtp")
bundle = archive_bundle_manifest(
raw_dir / ("L_sidechain.zip" if stereochemistry == "L" else "D_residues.zip"),
stereochemistry=stereochemistry,
)
bbind_counts, bbind_rows = parse_rotamer_counts(
raw_dir / f"{prefix}_bbind_Gfeller.lib.zip",
stereochemistry=stereochemistry,
library_type="bbind",
)
bbdep_counts, bbdep_rows = parse_rotamer_counts(
raw_dir / f"{prefix}_bbdep_Gfeller.lib.zip",
stereochemistry=stereochemistry,
library_type="bbdep",
)
rows: list[dict[str, Any]] = []
for residue_code in sorted(smi):
smiles, reference_file = parse_smi(smi[residue_code]["text"])
entry_id = f"{stereochemistry}:{residue_code}"
row = {
"entry_id": entry_id,
"residue_code": residue_code,
"stereochemistry": stereochemistry,
"smiles": smiles,
"smiles_reference_file": reference_file,
"source_smi_path": smi[residue_code]["path"],
"source_pdb_path": pdb.get(residue_code, {}).get("path"),
"source_mol2_path": mol2.get(residue_code, {}).get("path"),
"source_top_path": top.get(residue_code, {}).get("path"),
"source_rtp_path": rtp.get(residue_code, {}).get("path"),
"source_hdb_path": hdb.get(residue_code, {}).get("path"),
"has_smi": True,
"has_pdb": residue_code in pdb,
"has_mol2": residue_code in mol2,
"has_top": residue_code in top,
"has_rtp": residue_code in rtp,
"has_hdb": residue_code in hdb,
"has_bundle": residue_code in bundle,
"has_png": bool(bundle.get(residue_code, {}).get("has_png", False)),
"has_bundle_bbdep_lib": bool(bundle.get(residue_code, {}).get("has_bundle_bbdep_lib", False)),
"has_bundle_bbind_lib": bool(bundle.get(residue_code, {}).get("has_bundle_bbind_lib", False)),
"bundle_file_extensions": bundle.get(residue_code, {}).get("bundle_file_extensions", []),
"bbind_rotamer_rows": int(bbind_counts.get(residue_code, 0)),
"bbdep_rotamer_rows": int(bbdep_counts.get(residue_code, 0)),
"split_bucket": stable_bucket(entry_id),
}
row.update(parse_pdb(pdb[residue_code]["text"]) if residue_code in pdb else parse_pdb(""))
row.update(parse_mol2(mol2[residue_code]["text"]) if residue_code in mol2 else parse_mol2(""))
row.update(parse_charmm_top(top[residue_code]["text"]) if residue_code in top else parse_charmm_top(""))
row.update(parse_gromacs_rtp(rtp[residue_code]["text"]) if residue_code in rtp else parse_gromacs_rtp(""))
row.update(parse_hdb(hdb[residue_code]["text"]) if residue_code in hdb else parse_hdb(""))
rows.append(row)
manifest_rows = []
for label, mapping in [
("SMI", smi),
("PDB", pdb),
("MOL2", mol2),
("top", top),
("rtp", rtp),
("hdb", hdb),
]:
manifest_rows.append(
{
"stereochemistry": stereochemistry,
"archive_kind": label,
"unique_residue_codes": len(mapping),
"residue_codes": sorted(mapping),
}
)
return rows, bbind_rows + bbdep_rows + manifest_rows
def build_dataset(raw_dir: Path, out_dir: Path) -> dict[str, Any]:
l_rows, l_metadata = build_rows_for_stereo(raw_dir, "L")
d_rows, d_metadata = build_rows_for_stereo(raw_dir, "D")
rows = l_rows + d_rows
if out_dir.exists():
shutil.rmtree(out_dir)
data_dir = out_dir / "data"
metadata_dir = out_dir / "metadata"
data_dir.mkdir(parents=True, exist_ok=True)
metadata_dir.mkdir(parents=True, exist_ok=True)
df = pd.DataFrame.from_records(rows, columns=ENTRY_COLUMNS)
df = df.sort_values(["split_bucket", "entry_id"], kind="mergesort")
train = df[df["split_bucket"].ne(0)].sort_values("entry_id", kind="mergesort")
test = df[df["split_bucket"].eq(0)].sort_values("entry_id", kind="mergesort")
train.to_parquet(data_dir / "train-00000-of-00001.parquet", index=False, compression="zstd")
test.to_parquet(data_dir / "test-00000-of-00001.parquet", index=False, compression="zstd")
rotamer_rows = [row for row in l_metadata + d_metadata if row.get("library_type")]
manifest_rows = [row for row in l_metadata + d_metadata if row.get("archive_kind")]
pd.DataFrame.from_records(rotamer_rows).to_parquet(
metadata_dir / "rotamer_library_counts.parquet", index=False, compression="zstd"
)
pd.DataFrame.from_records(manifest_rows).to_parquet(
metadata_dir / "archive_manifest.parquet", index=False, compression="zstd"
)
stereo_counts = df["stereochemistry"].value_counts().to_dict()
summary = {
"source": "LiteFold/SwissSidechain",
"entry_rows": int(len(df)),
"splits": {
"train": int(len(train)),
"test": int(len(test)),
},
"split_strategy": "deterministic sha256(entry_id) % 10; bucket 0 is test, buckets 1-9 are train",
"stereochemistry_counts": {str(k): int(v) for k, v in stereo_counts.items()},
"entries_with_pdb": int(df["has_pdb"].sum()),
"entries_with_mol2": int(df["has_mol2"].sum()),
"entries_with_top": int(df["has_top"].sum()),
"entries_with_rtp": int(df["has_rtp"].sum()),
"entries_with_hdb": int(df["has_hdb"].sum()),
"entries_with_bundle": int(df["has_bundle"].sum()),
"entries_with_bbdep_rotamers": int(df["bbdep_rotamer_rows"].gt(0).sum()),
"entries_with_bbind_rotamers": int(df["bbind_rotamer_rows"].gt(0).sum()),
"total_bbdep_rotamer_rows": int(df["bbdep_rotamer_rows"].sum()),
"total_bbind_rotamer_rows": int(df["bbind_rotamer_rows"].sum()),
"archive_manifest_rows": int(len(manifest_rows)),
"rotamer_library_count_rows": int(len(rotamer_rows)),
"columns": ENTRY_COLUMNS,
"source_files_used": sorted(path.name for path in raw_dir.glob("*.zip")),
}
(out_dir / "dataset_summary.json").write_text(json.dumps(summary, indent=2) + "\n", encoding="utf-8")
return summary
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("--raw-dir", type=Path, default=Path("LiteFold_SwissSidechain_raw"))
parser.add_argument("--out-dir", type=Path, default=Path("LiteFold_SwissSidechain_processed"))
args = parser.parse_args()
summary = build_dataset(args.raw_dir, args.out_dir)
print(json.dumps(summary, indent=2))
if __name__ == "__main__":
main()
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