BioNeMo ProteinMPNN

NVIDIA NIM for ProteinMPNN inverse folding and protein sequence design.

Deploy now

Model details

Developed by
NVIDIA
Model family
BioNeMo
Use case
biology
Variant
NIM
Hardware
A10G
License
NVIDIA AI Foundation Models Community License Agreement

View repository

Example usage

Call BioNeMo ProteinMPNN on Baseten using the NIM sequence design route.

Note: You need to procure your own NVAIE licenses to access this NIM. The NIM requires an ngc_api_key secret in your Baseten workspace — add your NVIDIA NGC API key (the nvapi-… value) as a secret named ngc_api_key before deploying.

Input

1import os
2import requests
3
4MODEL_ID = os.environ["BASETEN_MODEL_ID"]
5BASETEN_API_KEY = os.environ["BASETEN_API_KEY"]
6BASETEN_URL = (
7    f"https://model-{MODEL_ID}.api.baseten.co/environments/production/sync"
8    "/biology/ipd/proteinmpnn/predict"
9)
10
11pdb_text = requests.get("https://files.rcsb.org/download/1R42.pdb", timeout=30).text
12atom_lines = [line for line in pdb_text.splitlines() if line.startswith("ATOM")][:200]
13input_pdb = "\n".join(atom_lines)
14
15payload = {
16    "input_pdb": input_pdb,
17    "ca_only": False,
18    "use_soluble_model": False,
19    "num_seq_per_target": 3,
20    "sampling_temp": [0.1, 0.3],
21}
22
23response = requests.post(
24    BASETEN_URL,
25    headers={
26        "Authorization": f"Bearer {BASETEN_API_KEY}",
27        "Content-Type": "application/json",
28    },
29    json=payload,
30    timeout=300,
31)
32response.raise_for_status()
33result = response.json()
34print(result)
35

JSON output

1{
2    "mfasta": ">T=0.1, score=1.2345, seq=0\nMKTV...\n",
3    "scores": [
4        [
5            1.2345
6        ]
7    ],
8    "probs": [
9        [
10            "<probabilities>"
11        ]
12    ]
13}