biology
BioNeMo ProteinMPNN
BioNeMo ProteinMPNNNVIDIA NIM for ProteinMPNN inverse folding and protein sequence design.
Model details
View repositoryExample 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.
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)
35JSON 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}
