Complex prediction

from kallima import KallimaClient

client = KallimaClient(api_key)

antigen = client.antigens.create(
    project_id=project_id,
    name="TNF-alpha",
    sequence="MSTESMIRDVELAEEALPKKTGGPQGSRRCLFLSLFSFIVAGATTLFCLLHFGVIG...",
)
antigen_id = antigen["id"]

job = client.complex_predictions.submit(
    variant_id=variant_id,
    antigen_id=antigen_id,
)
job.wait(timeout=3600)  # up to 40 min for large antigens

result = job.results

print(result["confidence_score"])  # pTM — global fold confidence, 0–1
print(result["iptm"])              # interface pTM — confidence in the binding pose, 0–1
print(result["model_used"])        # "boltz2"

for chain, plddt_array in (result["per_chain_plddt"] or {}).items():
    mean = sum(plddt_array) / len(plddt_array)
    print(f"Chain {chain}: mean pLDDT {mean:.2f}")

interface = result["interface_residues"] or {}
# Keys are chain IDs; values are lists of residue positions at the interface
for chain, residues in interface.items():
    print(f"Chain {chain} interface residues: {residues}")

import httpx

pdb_url = job.results["pdb_url"]
pdb_bytes = httpx.get(pdb_url).content

with open("complex.pdb", "wb") as f:
    f.write(pdb_bytes)

for job in client.complex_predictions.list(variant_id=variant_id):
    print(job.id, job.status, job["created_at"])

for antigen in client.antigens.list(project_id=project_id):
    print(antigen["id"], antigen["name"])