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import math
import os
import re
import subprocess
import tempfile
import urllib.request
from pathlib import Path
from typing import Optional
# AutoDock Vina binary location
_VINA_BINARY: str | None = None
_VINA_URL = "https://github.com/ccsb-scripps/AutoDock-Vina/releases/download/v1.2.3/vina_1.2.3_linux_x86_64"
_EXE_NAME = "vina"
_VINA_SHA256 = ""
def _verify_checksum(path: Path) -> None:
if not _VINA_SHA256:
return
import hashlib
h = hashlib.sha256()
with open(path, "rb") as f:
for chunk in iter(lambda: f.read(8192), b""):
h.update(chunk)
digest = h.hexdigest()
if digest != _VINA_SHA256:
path.unlink(missing_ok=True)
raise RuntimeError(
f"Vina binary checksum mismatch (got {digest}, expected {_VINA_SHA256})."
)
def _ensure_vina() -> str:
"""Locate the AutoDock Vina binary."""
global _VINA_BINARY
if _VINA_BINARY and os.path.isfile(_VINA_BINARY):
return _VINA_BINARY
import shutil
for candidate in ["/usr/local/bin/vina", shutil.which("vina") or ""]:
if candidate and os.path.isfile(candidate):
_VINA_BINARY = candidate
return _VINA_BINARY
bin_dir = Path(tempfile.gettempdir()) / "vina_bin"
bin_dir.mkdir(exist_ok=True)
exe_path = bin_dir / _EXE_NAME
if not exe_path.is_file():
print(f"[docking] Downloading AutoDock Vina from {_VINA_URL} ...")
urllib.request.urlretrieve(_VINA_URL, str(exe_path))
_verify_checksum(exe_path)
os.chmod(str(exe_path), 0o755)
_VINA_BINARY = str(exe_path)
return _VINA_BINARY
# ---------------------------------------------------------------------------
# PDB fetching
# ---------------------------------------------------------------------------
def fetch_pdb_from_rcsb(pdb_id: str) -> str:
"""Download a PDB file from RCSB by 4-character PDB ID."""
pdb_id = pdb_id.strip().upper()
if len(pdb_id) != 4:
raise ValueError(f"Invalid PDB ID: {pdb_id!r}")
url = f"https://files.rcsb.org/download/{pdb_id}.pdb"
try:
data = urllib.request.urlopen(url, timeout=30).read().decode("utf-8", errors="replace")
except Exception as e:
raise RuntimeError(f"Failed to fetch PDB {pdb_id} from RCSB: {e}")
if "ATOM" not in data and "HETATM" not in data:
raise RuntimeError(f"PDB {pdb_id} from RCSB contains no coordinate data")
return data
# ---------------------------------------------------------------------------
# Grid center computation
# ---------------------------------------------------------------------------
_ATOM_RE = re.compile(
r"^(ATOM|HETATM)\s+\d+\s+\S+\s+(\S)\s+(\d+)\s+"
r"([-\d.]+)\s+([-\d.]+)\s+([-\d.]+)"
)
def compute_grid_center(pdb_text: str) -> list[float]:
"""Compute the geometric centre of all ATOM (non-ligand) records."""
xs, ys, zs = [], [], []
for line in pdb_text.splitlines():
if line.startswith("ATOM"):
m = _ATOM_RE.match(line)
if m:
xs.append(float(m.group(4)))
ys.append(float(m.group(5)))
zs.append(float(m.group(6)))
if not xs:
return [0.0, 0.0, 0.0]
return [sum(xs) / len(xs), sum(ys) / len(ys), sum(zs) / len(zs)]
# ---------------------------------------------------------------------------
# Ligand prep (SMILES -> PDBQT via NCI CACTUS + Open Babel)
# ---------------------------------------------------------------------------
def smiles_to_pdbqt(smiles: str) -> str:
"""Convert SMILES to PDBQT via NCI CACTUS (3D SDF) + Open Babel."""
try:
url = f"https://cactus.nci.nih.gov/chemical/structure/{smiles}/file?format=sdf&get3d=true"
sdf_bytes = urllib.request.urlopen(url, timeout=30).read()
except Exception as e:
raise RuntimeError(f"Failed to get 3D structure from CACTUS: {e}")
with tempfile.NamedTemporaryFile(suffix=".sdf", delete=False, mode="wb") as f:
f.write(sdf_bytes)
sdf_path = f.name
try:
return _sdf_to_pdbqt(sdf_path)
finally:
os.unlink(sdf_path)
def _sdf_to_pdbqt(sdf_path: str) -> str:
"""Convert SDF to PDBQT using Open Babel."""
pdbqt_path = sdf_path.rsplit(".", 1)[0] + ".pdbqt"
try:
result = subprocess.run(
[
"obabel",
sdf_path,
"-O", pdbqt_path,
"--partialcharge", "gasteiger",
"-p", "7.4",
],
capture_output=True,
text=True,
timeout=60,
)
if result.returncode != 0:
raise RuntimeError(f"Open Babel ligand conversion failed: {result.stderr[:1000]}")
if not os.path.isfile(pdbqt_path):
raise RuntimeError("Open Babel did not produce a PDBQT output file")
with open(pdbqt_path, "r") as f:
content = f.read()
if not content.strip():
raise RuntimeError("PDBQT conversion produced empty output")
return content
except FileNotFoundError:
raise RuntimeError(
"Open Babel (`obabel`) is not installed. "
"Add it to the Dockerfile: RUN apt-get update && apt-get install -y openbabel"
)
finally:
if os.path.isfile(pdbqt_path):
os.unlink(pdbqt_path)
# ---------------------------------------------------------------------------
# Receptor prep (PDB -> PDBQT rigid receptor)
# ---------------------------------------------------------------------------
def pdb_to_pdbqt_receptor(pdb_text: str) -> str:
"""Convert a plain PDB receptor to PDBQT (rigid, for Vina)."""
in_path = None
out_path = None
try:
with tempfile.NamedTemporaryFile(suffix=".pdb", delete=False, mode="w") as f:
f.write(pdb_text)
in_path = f.name
out_path = in_path.rsplit(".", 1)[0] + ".pdbqt"
result = subprocess.run(
[
"obabel",
in_path,
"-O", out_path,
"-xr",
"--partialcharge", "gasteiger",
],
capture_output=True,
text=True,
timeout=120,
)
if result.returncode != 0:
raise RuntimeError(f"Open Babel receptor conversion failed: {result.stderr[:1000]}")
if not os.path.isfile(out_path):
raise RuntimeError("Open Babel did not produce a receptor PDBQT output file")
with open(out_path, "r") as f:
content = f.read()
if not content.strip():
raise RuntimeError("Receptor PDBQT conversion produced empty output")
return content
except FileNotFoundError:
raise RuntimeError(
"Open Babel (`obabel`) is not installed. "
"Add it to the Dockerfile: RUN apt-get update && apt-get install -y openbabel"
)
finally:
if in_path and os.path.isfile(in_path):
os.unlink(in_path)
if out_path and os.path.isfile(out_path):
os.unlink(out_path)
# ---------------------------------------------------------------------------
# Vina execution + multi-pose parsing
# ---------------------------------------------------------------------------
def run_vina(
protein_pdbqt: str | bytes,
ligand_pdbqt: str,
grid_center: list[float] = [0, 0, 0],
grid_size: list[float] = [20, 20, 20],
exhaustiveness: int = 8,
num_modes: int = 9,
) -> dict:
"""Run AutoDock Vina and return parsed multi-pose results."""
vina_bin = _ensure_vina()
with tempfile.TemporaryDirectory() as tmp:
prot_path = os.path.join(tmp, "protein.pdbqt")
if isinstance(protein_pdbqt, bytes):
with open(prot_path, "wb") as f:
f.write(protein_pdbqt)
else:
with open(prot_path, "w") as f:
f.write(protein_pdbqt)
lig_path = os.path.join(tmp, "ligand.pdbqt")
with open(lig_path, "w") as f:
f.write(ligand_pdbqt)
out_path = os.path.join(tmp, "output.pdbqt")
cmd = [
vina_bin,
"--receptor", prot_path,
"--ligand", lig_path,
"--center_x", str(grid_center[0]),
"--center_y", str(grid_center[1]),
"--center_z", str(grid_center[2]),
"--size_x", str(grid_size[0]),
"--size_y", str(grid_size[1]),
"--size_z", str(grid_size[2]),
"--exhaustiveness", str(exhaustiveness),
"--num_modes", str(num_modes),
"--out", out_path,
]
result = subprocess.run(cmd, capture_output=True, text=True, timeout=300)
if result.returncode != 0:
raise RuntimeError(f"Vina failed: {result.stderr[:2000]}")
with open(out_path, "r") as f:
output_pdbqt = f.read()
vina_log = result.stdout
poses = _parse_vina_poses(output_pdbqt, vina_log)
ligand_pdb = _extract_ligand_pdb(output_pdbqt)
best_affinity = None
if poses:
best_affinity = poses[0]["affinity"]
return {
"poses": poses,
"num_poses": len(poses),
"affinity": best_affinity,
"vina_log": vina_log,
"ligand_pdb": ligand_pdb,
"result_sdf": output_pdbqt,
}
def _parse_vina_poses(output_pdbqt: str, vina_log: str) -> list[dict]:
"""Parse Vina output PDBQT into a list of per-pose dicts."""
affinity_from_log: dict[int, float] = {}
for line in vina_log.splitlines():
m = re.match(r"\s*(\d+)\s+([-\d.]+)\s+([-\d.]+)\s+([-\d.]+)", line)
if m:
mode = int(m.group(1))
affinity_from_log[mode] = float(m.group(2))
models: dict[int, list[str]] = {}
current_model: int | None = None
for line in output_pdbqt.splitlines():
if line.startswith("MODEL"):
parts = line.split()
if len(parts) >= 2:
current_model = int(parts[1])
models[current_model] = []
elif line.startswith("ENDMDL"):
current_model = None
elif current_model is not None:
models.setdefault(current_model, []).append(line)
poses = []
for model_id in sorted(models.keys()):
atom_count = sum(1 for l in models[model_id] if l.startswith("HETATM") or l.startswith("ATOM"))
affinity = affinity_from_log.get(model_id, None)
poses.append({
"model": model_id,
"atoms": atom_count,
"affinity": affinity,
})
return poses
def _extract_ligand_pdb(output_pdbqt: str) -> str:
"""Extract HETATM lines from the best (first) model as PDB for 3D viewer."""
in_model = False
lines: list[str] = []
for line in output_pdbqt.splitlines():
if line.startswith("MODEL") and not in_model:
in_model = True
continue
if line.startswith("ENDMDL"):
break
if in_model and (line.startswith("HETATM") or line.startswith("ATOM")):
pdb_line = _pdbqt_line_to_pdb(line)
lines.append(pdb_line)
if not lines:
return ""
lines.append("END")
return "\n".join(lines)
def _pdbqt_line_to_pdb(pdbqt_line: str) -> str:
"""Convert a PDBQT ATOM/HETATM line to a standard PDB ATOM/HETATM line."""
fields = pdbqt_line.split()
if len(fields) < 7:
return pdbqt_line
record = fields[0]
atom_num = fields[1]
atom_name = fields[2]
res_name = fields[3]
chain = fields[4] if len(fields[4]) == 1 and fields[4].isalpha() else "A"
res_seq = fields[5]
x = float(fields[6])
y = float(fields[7])
z = float(fields[8]) if len(fields) > 8 else 0.0
return (
f"{record:<6}{atom_num:>5s} {atom_name:<4s}{res_name:<3s} "
f"{chain}{res_seq:>4s} "
f"{x:8.3f}{y:8.3f}{z:8.3f} 1.00 0.00 "
)
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