#!/usr/bin/env python3
"""Build a self-contained 3D protein-ligand viewer with inline JS libraries.
Usage:
python build_viewer.py --drug metformin
python build_viewer.py --drug metformin --sequence CUSTOMSEQ --title "Custom Title"
When --sequence is omitted, the script looks up the protein target from a
built-in drug-target table (drug name -> target protein -> amino acid sequence).
Fetches drug SMILES from PubChem, predicts a protein-ligand complex with
OpenFold3 NIM, and generates an interactive 3D viewer saved to canvas.
"""
import argparse, subprocess, json, os, sys
CANVAS = os.path.expanduser("~/.openclaw/canvas")
OF3_HOST = os.environ.get("OPENFOLD3_HOST", "172.17.0.1")
OF3_URL = f"http://{OF3_HOST}:8000/biology/openfold/openfold3/predict"
PUBCHEM_URL = "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/{}/property/IsomericSMILES/JSON"
# Drug -> (target protein name, amino acid sequence)
# Sequences are canonical fragments from UniProt, chosen to be under 300 aa
# for fast OpenFold3 prediction while covering the drug binding domain.
DRUG_TARGETS = {
"metformin": (
"Insulin B-chain",
"FVNQHLCGSHLVEALYLVCGERGFFYTPKT",
),
"atorvastatin": (
"HMG-CoA reductase (catalytic domain)",
"EIGTVGGGTQLFNQLESRIRAVLKDAGFLEEARAVIDRPGPYLEDVVTASNLKEGATLITSPAKLLREVGLTPETISKALKESGVRFIRIATTAPYAMNPVSAVEIAGATLYPVSALTEIARGMFVFQSGKYSMSSSGIVLPVVFATLME",
),
"rosuvastatin": (
"HMG-CoA reductase (catalytic domain)",
"EIGTVGGGTQLFNQLESRIRAVLKDAGFLEEARAVIDRPGPYLEDVVTASNLKEGATLITSPAKLLREVGLTPETISKALKESGVRFIRIATTAPYAMNPVSAVEIAGATLYPVSALTEIARGMFVFQSGKYSMSSSGIVLPVVFATLME",
),
"lisinopril": (
"ACE (binding domain)",
"QGSERRGPFKSWYGSSPDIIRDQIRKQLQELLQELNEERDCTSIHPFHNIFSEDDASFEERKVLKNMMDTLKRNVQEAVDTYGFK",
),
"enalapril": (
"ACE (binding domain)",
"QGSERRGPFKSWYGSSPDIIRDQIRKQLQELLQELNEERDCTSIHPFHNIFSEDDASFEERKVLKNMMDTLKRNVQEAVDTYGFK",
),
"losartan": (
"Angiotensin II receptor type 1 (transmembrane domain)",
"MILNSSTEDGIKRIQDDCPKAGRHNYIFVMIPTLYSIIFVVGIFGNSLVVIVIYFYMKLKTVASVFLLNLALADLCFLLTLPLWAVYTAMEYRWPFGNYLCKIASASVSFNLYASVFLLTCLSIDRYLAIVHPMKSRLRRTMLVAKVTCIIIWLLAGLASLPAIIHRNVFFIENTNITVCAFHYESQNSTLPIGLGLTKNILGFLFPFLIILTSYTLIWKALKKAYEIQKNKPRNDDIFKIIMAIVLFFFFSWIPHQIFTFLDVLIQLGIIRDCRIADIVDTAMPITICIAYFNNCLNPLFYGFLGKKFKRYFLQLLKYIPPKAKSHSNLSTRMSTLSYRPSDNVSSSTKKPAPCFEVE",
),
"amlodipine": (
"L-type calcium channel Cav1.2 (domain III)",
"QCIDDYDTQFFLQDNAKFEGMCLRDIPDDRDNFDLFLKRVDIGPEDYYLNQHFLDAAENPDPEISFQFEGRILRGFIDIIYDLSDWFDPNEDY",
),
"empagliflozin": (
"SGLT2 (sodium-glucose cotransporter 2)",
"MDSSRQSGAHQHPPAQRVELQGLADEADARALRGEFSLHPELAARAATPEQAFALGGELPMERDSQLCMGFVHTYFNMTGYSEAETLTGAGPPMAYAIPPQAKEVEEMKEFFQKFGKTYPGLKDIFPETKIDFLRNIMLQHMGIGLASATLVPMYIAAEMTAHMGCMHRFLYASYVAAEFLAIVFAVILFNLGERRKHFS",
),
"semaglutide": (
"GLP-1 receptor (extracellular domain)",
"RPQGATVSLWETVQKWREYRRQCQRSLTEDPPPATDLFCNRTFDEYACWPDGEPGSFVNVSCPWYLPWASSVPQGHVYRFCTAEGLWLQKDNSSLPWRDLSECEESKRGERNSPEEQLLS",
),
}
def fetch_js(url):
r = subprocess.run(["curl", "-sL", url], capture_output=True, text=True, timeout=30)
if r.returncode != 0:
print(f" ERROR: curl failed for {url} (exit {r.returncode})", file=sys.stderr)
if r.stderr:
print(f" {r.stderr[:300]}", file=sys.stderr)
raise RuntimeError(f"Failed to fetch {url}")
if len(r.stdout) < 1000:
print(f" WARN: {url} returned only {len(r.stdout)} bytes", file=sys.stderr)
return r.stdout
def lookup_smiles(drug):
try:
r = subprocess.run(
["curl", "-sf", PUBCHEM_URL.format(drug)],
capture_output=True, text=True, timeout=15
)
d = json.loads(r.stdout)
props = d["PropertyTable"]["Properties"][0]
return props.get("IsomericSMILES", props.get("CanonicalSMILES", props.get("SMILES", "")))
except Exception as e:
print(f" PubChem lookup failed: {e}", file=sys.stderr)
return ""
def resolve_target(drug):
"""Look up drug in built-in table. Returns (target_name, sequence) or None."""
key = drug.strip().lower()
if key in DRUG_TARGETS:
return DRUG_TARGETS[key]
for k, v in DRUG_TARGETS.items():
if k in key or key in k:
return v
return None
def predict_structure(sequence, smiles=""):
molecules = [{
"type": "protein", "id": "A", "sequence": sequence,
"msa": {"main": {"a3m": {
"alignment": f">query\n{sequence}", "format": "a3m"
}}}
}]
if smiles:
molecules.append({"type": "ligand", "smiles": smiles})
body = json.dumps({"inputs": [{
"input_id": "viewer", "molecules": molecules, "output_format": "pdb"
}]})
r = subprocess.run(
["curl", "-sf", "--max-time", "300", "-X", "POST",
"-H", "Content-Type: application/json", "-d", body, OF3_URL],
capture_output=True, text=True, timeout=305
)
if r.returncode != 0 or not r.stdout.strip():
print(f" OpenFold3 prediction failed (exit {r.returncode})", file=sys.stderr)
if r.stderr:
print(f" {r.stderr[:300]}", file=sys.stderr)
sys.exit(1)
result = json.loads(r.stdout)
out = result["outputs"][0]["structures_with_scores"][0]
return out["structure"], out
def build_html(title, drug, smiles, sequence, pdb, scores, jquery_js, mol3d_js):
pdb_escaped = pdb.replace("\\", "\\\\").replace("`", "\\`").replace("${", "\\${")
has_ligand = bool(smiles)
conf = scores.get('confidence_score', 0)
plddt = scores.get('complex_plddt_score', 0)
ptm = scores.get('ptm_score', 0)
iptm = scores.get('iptm_score', 0)
ligand_legend = f'{drug.capitalize()} (ligand)
Protein ({len(sequence)} aa)
{ligand_legend}
Drag to rotate · Scroll to zoom · Double-click toggle spin
"""
def main():
parser = argparse.ArgumentParser(description="Build 3D protein-ligand viewer")
parser.add_argument("--drug", required=True, help="Drug name (e.g. metformin)")
parser.add_argument("--sequence", default=None, help="Protein target sequence (auto-resolved if omitted)")
parser.add_argument("--title", default=None, help="Viewer title")
parser.add_argument("--output", default=None, help="Output HTML path")
parser.add_argument("--openfold-host", default=None, help="OpenFold3 host IP")
args = parser.parse_args()
if args.openfold_host:
global OF3_URL
OF3_URL = f"http://{args.openfold_host}:8000/biology/openfold/openfold3/predict"
sequence = args.sequence
target_name = None
if not sequence:
target = resolve_target(args.drug)
if target:
target_name, sequence = target
print(f"Target: {target_name}")
else:
print(f"ERROR: No built-in target for '{args.drug}'. Pass --sequence explicitly.", file=sys.stderr)
print(f"Known drugs: {', '.join(sorted(DRUG_TARGETS.keys()))}", file=sys.stderr)
sys.exit(1)
title = args.title or f"{args.drug.capitalize()}: {target_name or 'Protein-Ligand Complex'}"
output = args.output or os.path.join(CANVAS, f"{args.drug}_complex.html")
os.makedirs(os.path.dirname(output), exist_ok=True)
print(f"Drug: {args.drug}")
print(f"Sequence: {sequence[:40]}{'...' if len(sequence) > 40 else ''} ({len(sequence)} aa)")
print("Fetching jQuery...")
jq = fetch_js("https://code.jquery.com/jquery-3.6.0.min.js")
print(f" {len(jq)} bytes")
print("Fetching 3Dmol...")
mol3d = fetch_js("https://3Dmol.org/build/3Dmol-min.js")
print(f" {len(mol3d)} bytes")
if len(jq) < 1000 or len(mol3d) < 1000:
print("ERROR: JS library download failed", file=sys.stderr)
sys.exit(1)
print("Looking up SMILES on PubChem...")
smiles = lookup_smiles(args.drug)
print(f" SMILES: {smiles}")
pdb_cache = os.path.join(CANVAS, f"{args.drug}_complex.pdb")
scores_cache = os.path.join(CANVAS, f"{args.drug}_complex_scores.json")
if os.path.exists(pdb_cache) and os.path.getsize(pdb_cache) > 1000:
pdb = open(pdb_cache).read()
if os.path.exists(scores_cache):
scores = json.loads(open(scores_cache).read())
else:
scores = {"confidence_score": 0, "complex_plddt_score": 0, "ptm_score": 0, "iptm_score": 0}
print(f"PDB from cache: {len(pdb)} bytes")
else:
mode = "protein-ligand complex" if smiles else "protein only"
print(f"Predicting {mode} with OpenFold3...")
pdb, scores = predict_structure(sequence, smiles)
with open(pdb_cache, "w") as f:
f.write(pdb)
with open(scores_cache, "w") as f:
json.dump(scores, f, indent=2)
print(f" {len(pdb)} bytes, confidence: {scores.get('confidence_score',0):.1%}")
html = build_html(title, args.drug, smiles, sequence, pdb, scores, jq, mol3d)
with open(output, "w") as f:
f.write(html)
print(f"\nViewer saved: {output} ({len(html)} bytes)")
print(f"Open: http://localhost:18789/__openclaw__/canvas/{os.path.basename(output)}")
if __name__ == "__main__":
main()