boltz2-nim

name: boltz2-nimdescription: >  Use Boltz2 NIM for biomolecular structure prediction and binding affinity. Invoke for Boltz2, protein structures, protein-ligand/DNA/RNA complexes, SMILES or CCD ligands, pIC50/IC50 affinity scoring, mmCIF output, hosted NVIDIA API calls, or local Docker deployment.license: Apache-2.0 AND CC-BY-4.0compatibility: "requests>=2.28"allowed-tools: Bash, Read, Write, AskUserQuestion

Boltz2 NIM

Predict biomolecular structures and optional ligand affinity. Use this guide for first-pass hosted/local usage; load supplemental files only when needed:

• references/api.md: exact endpoints, schemas, Docker flags, response fields.
• references/science.md: purpose, strengths, limitations, and handoffs.
• references/parameters.md: prediction, sampling, MSA, template, affinity tuning.
• references/validation.md: mmCIF, confidence, affinity, and chemistry checks.
• references/examples.md: compact hosted/local payload patterns.

Instructions

Read credentials from the environment only when needed. Check presence with bool(os.getenv("NGC_API_KEY")); keep key values and Authorization headers out of terminal output, logs, saved artifacts, and the final response. Avoid environment dumps when diagnosing authentication. If the hosted key is absent, report the missing variable before submitting a request.

Choose Mode

Ask only when context is unclear:

Hosted NVIDIA API or local Docker NIM?

• Hosted: https://health.api.nvidia.com/v1/biology/mit/boltz2/predict
• Local: http://localhost:8000/biology/mit/boltz2/predict

Hosted requests use Authorization: Bearer $NGC_API_KEY. Supported local Docker startup uses NGC_API_KEY (or NVIDIA_API_KEY via the preflight) for registry login, entitlement checks, and first-run model downloads; pass it into the container with -e NGC_API_KEY. Local inference requests use no auth header after readiness. Warm-cache key-free startup varies by image/version and should not be assumed.

Local Docker

For local setup answers, copy the preflight below before docker login, docker run, readiness, and the no-auth local request. Do not invent a cache default or drop the .env load or NVIDIA_API_KEY fallback.

set -a
[ -f .env ] && . ./.env
set +a

if [ -z "${NGC_API_KEY:-}" ] && [ -n "${NVIDIA_API_KEY:-}" ]; then
  export NGC_API_KEY="$NVIDIA_API_KEY"
fi
: "${NGC_API_KEY:?Set NGC_API_KEY or NVIDIA_API_KEY}"
: "${LOCAL_NIM_CACHE:?Set LOCAL_NIM_CACHE}"

echo "$NGC_API_KEY" | docker login nvcr.io --username '$oauthtoken' --password-stdin

mkdir -p "${LOCAL_NIM_CACHE}"
chmod 755 "${LOCAL_NIM_CACHE}"

docker run --rm --name boltz2 --gpus all \
  --shm-size=16G \
  -e NGC_API_KEY \
  -v "${LOCAL_NIM_CACHE}:/opt/nim/.cache" \
  -p 8000:8000 \
  nvcr.io/nim/mit/boltz2:1.6.0

Readiness:

until curl -sf http://localhost:8000/v1/health/ready; do sleep 5; done

First startup downloads about 30 GB of model weights.

Examples

Prediction Request

import os
import requests

HOSTED = True
url = (
    "https://health.api.nvidia.com/v1/biology/mit/boltz2/predict"
    if HOSTED else "http://localhost:8000/biology/mit/boltz2/predict"
)
headers = {"Content-Type": "application/json"}
if HOSTED:
    api_key = os.getenv("NGC_API_KEY")
    if not api_key:
        raise SystemExit("NGC_API_KEY is required for the hosted API")
    headers["Authorization"] = f"Bearer {api_key}"

payload = {
    "polymers": [{
        "id": "A",
        "molecule_type": "protein",
        "sequence": "MTEYKLVVVGACGVGKSALTIQLIQNHFVDEYDPT",
    }],
    "recycling_steps": 3,
    "sampling_steps": 50,
    "diffusion_samples": 1,
    "step_scale": 1.638,
    "output_format": "mmcif",
}
response = requests.post(url, headers=headers, json=payload, timeout=300)
response.raise_for_status()
result = response.json()

Payload essentials:

• Protein polymer: {"molecule_type": "protein", "sequence": "..."}.
• DNA/RNA polymer: add another polymer with molecule_type "dna" or "rna".
• Ligand by SMILES: {"id": "L1", "smiles": "CC(=O)OC1=CC=CC=C1C(=O)O"}.
• Ligand by CCD: {"id": "L1", "ccd": "ATP"}.
• Affinity: set "predict_affinity": True on exactly one ligand; report affinity_pic50, affinity_pred_value, and affinity_probability_binary.
• Precomputed A3M MSA goes under the protein polymer. The A3M record uses alignment, format, and rank; do not use a stale data field.

protein_with_msa = {
    "id": "A",
    "molecule_type": "protein",
    "sequence": "MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPT",
    "msa": {"msa_search": {"a3m": {
        "alignment": ">query\nMTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPT",
        "format": "a3m",
        "rank": 0,
    }}},
}

Save And Report Output

Save every .cif artifact and read the confidence/affinity fields using the snippet in references/examples.md under Save Structures And Affinity. Visualize in PyMOL, ChimeraX, or UCSF Chimera. For confidence/affinity sanity checks, read references/validation.md.

Limits And Troubleshooting

• Polymers/request: 12. Ligands/request: 20. Chain length: 4096 residues.
• Affinity prediction supports one ligand per request and adds runtime.
• 422: invalid sequence, invalid CCD/SMILES, malformed MSA, or multiple affinity ligands.
• Local URL/auth: local path has no hosted auth header; wait on /v1/health/ready.
• Local startup: use --gpus all, --shm-size=16G, and the /opt/nim/.cache mount.