OpenFold2 NIM

Predict a single protein-chain structure from an amino-acid sequence, with optional A3M multiple sequence alignments and mmCIF templates. Use this

SKILL.md

for basic hosted/local NIM use; load supplemental files only when the task needs deeper context:

```
references/api.md
```
: exact endpoints, schemas, Docker flags, response fields.
```
references/science.md
```
: model scope, strengths, limitations, and handoffs.
```
references/parameters.md
```
: MSA, template, model-selection, and relax effects.
```
references/validation.md
```
: artifact and scientific sanity checks.
```
references/examples.md
```
: compact hosted/local payload patterns.

Choose Mode

Ask only when context is unclear:

Hosted NVIDIA API or local Docker NIM?

Hosted URL:

https://health.api.nvidia.com/v1/biology/openfold/openfold2/predict-structure-from-msa-and-template

Local URL:

http://localhost:8000/biology/openfold/openfold2/predict-structure-from-msa-and-template

Local readiness:
```
http://localhost:8000/v1/health/ready
```

Mode difference: hosted and local use the same prediction path except local does not include

/v1/

. Hosted requests use

Authorization: Bearer $NGC_API_KEY

; local inference requests use no auth header after readiness.

Auth And Environment

Do not print API keys. Confirm they exist with shell tests, not echoes.

Hosted needs

NGC_API_KEY

in the request header. Supported local Docker startup uses

NGC_API_KEY

, or

NVIDIA_API_KEY

as a fallback, plus

LOCAL_NIM_CACHE

. A repo-root

.env

file may be sourced as a local override.

Local Docker

Use the official OpenFold2 NIM image and mount

LOCAL_NIM_CACHE

/opt/nim/.cache

. Current docs recommend at least 80 GB disk, 64 GB system RAM, 8 CPU cores, and one supported GPU; the container is roughly 55 GB and first startup downloads about 10 GB of model parameters.

For the exact startup preflight (

.env

sourcing,

NGC_API_KEY

NVIDIA_API_KEY

handling,

docker login

, and the

docker run

for

nvcr.io/nim/openfold/openfold2:latest

), copy the command block in

references/api.md

under Local Docker verbatim — do not drop

.env

NGC_API_KEY

LOCAL_NIM_CACHE

, or the no-auth local request.

Readiness check:

bash

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

Request Pattern

Use Python

requests

; curl escaping is fragile for A3M/mmCIF text. The

sequence

field is required.

input_id

alignments

selected_models

relax_prediction

use_templates

, and

explicit_templates

are optional.

python

import os
import requests

hosted = True
url = (
    "https://health.api.nvidia.com/v1/biology/openfold/openfold2/predict-structure-from-msa-and-template"
    if hosted
    else "http://localhost:8000/biology/openfold/openfold2/predict-structure-from-msa-and-template"
)
headers = {"Content-Type": "application/json"}
if hosted:
    headers["Authorization"] = f"Bearer {os.getenv('NGC_API_KEY')}"

seq = "MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPT"
payload = {
    "sequence": seq,
    "input_id": "kras_fragment",
    "selected_models": [1],
    "relax_prediction": False,
    "alignments": {
        "uniref90": {
            "a3m": {
                "alignment": f">query\n{seq}",
                "format": "a3m",
            }
        }
    },
}

response = requests.post(url, headers=headers, json=payload, timeout=300)
response.raise_for_status()
result = response.json()

Payload gotchas:

OpenFold2 is monomer-only. For protein-ligand, protein-DNA/RNA, or multi-chain complexes, use OpenFold3 or Boltz2 instead.
```
sequence
```
must use valid amino-acid IUPAC symbols.
Hosted API docs list sequence length 1-1000; local docs say current NIM supports sequences up to 2048 residues on supported hardware.
A3M alignments go under
```
alignments
```
by database name, then
```
a3m
```
with
```
alignment
```
and
```
format
```
. When the user needs to create or deepen an MSA, hand off to
```
msa-search-nim
```
/ MSA Search and map its A3M output into this
```
alignments
```
shape.
Starting with OpenFold2 2.0.0, use
```
explicit_templates
```
with mmCIF content; do not write new HHR-template examples.
```
selected_models
```
chooses AlphaFold2/OpenFold parameter sets 1-5. Select one or two models for smoke tests; use all five for stronger production runs.

Save And Interpret Output

The response includes one prediction per selected model, ordered by confidence. Save every returned structure-like text field and the full JSON response so field-shape differences are auditable. Production answers should explicitly write

.pdb

.cif

artifacts, preserve the response JSON, and print any confidence/ranking fields the service returns.

python

from pathlib import Path
import json

Path("openfold2_response.json").write_text(json.dumps(result, indent=2))

def save_strings(obj, prefix="openfold2"):
    i = 0
    if isinstance(obj, dict):
        for key, value in obj.items():
            if isinstance(value, str) and ("ATOM" in value or value.lstrip().startswith("data_")):
                i += 1
                ext = "cif" if value.lstrip().startswith("data_") else "pdb"
                Path(f"{prefix}_{key}_{i}.{ext}").write_text(value)
            elif isinstance(value, (dict, list)):
                i += save_strings(value, f"{prefix}_{key}")
    elif isinstance(obj, list):
        for idx, value in enumerate(obj, start=1):
            if isinstance(value, (dict, list)):
                i += save_strings(value, f"{prefix}_{idx}")
    return i

saved = save_strings(result)
print(f"saved {saved} structure artifact(s)")

For production monomer runs:

Use
```
selected_models: [1, 2, 3, 4, 5]
```
unless the user requests a smoke test.
Use
```
relax_prediction: True
```
in Python payloads when relaxation is desired; JSON examples may show
```
true
```
.
State the sequence length caveat: hosted API docs list 1-1000 residues, while local support-matrix docs list up to 2048 residues on supported hardware.
If the task is a complex rather than a monomer, redirect to OpenFold3 or Boltz2.

Treat tiny toy sequences and single-sequence MSAs as API smoke tests, not quality evidence. For scientific interpretation and validation, read

references/science.md

and

references/validation.md

Troubleshooting

```
401
```
: missing, expired, or unauthorized NGC API key.
```
422
```
: invalid amino-acid characters, sequence too long, malformed A3M, bad
```
selected_models
```
, or malformed mmCIF template object.
Local
```
404
```
: remove
```
/v1/
```
from the prediction URL.
Weak structures: use MSA Search to generate deeper A3M alignments and add biologically relevant mmCIF templates when appropriate.
Local startup stalls: first run downloads parameters into
```
LOCAL_NIM_CACHE
```
.

openfold2-nim

NPX Install

Tags

SKILL.md Content