genmol-nim

Original：🇺🇸 English

Translated

Generate novel drug-like molecules using the GenMol NIM microservice. Use for de novo generation, scaffold decoration, motif extension, lead optimization, SAFE notation, QED or LogP ranking, hosted NVIDIA API calls, or local Docker deployment. GenMol takes SAFE notation in the smiles field, not ordinary SMILES.

4installs

Sourcenvidia-bionemo/bionemo-agent-toolkit

Added on2026-08-21

NPX Install

npx skill4agent add nvidia-bionemo/bionemo-agent-toolkit genmol-nim

SKILL.md Content

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GenMol NIM

Generate drug-like molecules with GenMol. Use this

SKILL.md

for first-pass hosted/local usage; load supplemental files only when needed:

```
references/api.md
```
: endpoints, schema, Docker flags, response fields.
```
references/science.md
```
: use cases, strengths, limits, and handoffs.
```
references/parameters.md
```
: SAFE patterns and tuning effects.
```
references/validation.md
```
: chemical and artifact checks.
```
references/examples.md
```
: compact request patterns.

Choose Mode

Ask only when context is unclear:

Hosted NVIDIA API or local Docker NIM?

Hosted:

https://health.api.nvidia.com/v1/biology/nvidia/genmol/generate

Local:
```
http://localhost:8000/generate
```

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

Use shell env first; source repo-root

.env

only if present. Do not print keys. For local setup answers, include this sequence: env preflight,

docker login

,

docker run

, readiness loop, then a no-auth localhost request. Do not invent a cache default or drop the

NVIDIA_API_KEY

fallback.

For the exact startup preflight (

.env

sourcing,

NVIDIA_API_KEY

fallback,

--shm-size=2G

, both

--ulimit

flags,

docker login

, and the

docker run

for

nvcr.io/nim/nvidia/genmol:1.0.1

), copy the command block in

references/api.md

under Docker run reference verbatim.

GenMol is single-GPU;

NIM_TEST_GPU

defaults to

. Wait for readiness:

bash

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

SAFE Input

The API field is named

smiles

, but GenMol expects SAFE notation. Masked positions use

[*{min-max}]

.

De novo:
```
safe_input = "[*{20-30}]"
```

Scaffold decoration:

safe_input = scaffold_to_safe("C1CC(=O)NC1", 10, 15)

Motif extension:

safe_input = f"[*{{5-10}}].{motif_safe}.[*{{5-10}}]"

Lead optimization: encode the hit, then replace a fragment with
```
.[*{5-12}]
```

Use

safe-mol

for conditioned generation. Simple ring scaffolds may raise

SAFEFragmentationError

; fall back to the original SMILES plus a SAFE mask.

See the

scaffold_to_safe

helper in

references/examples.md

under Scaffold Decoration.

Wider masks increase diversity; tight masks keep analog size more predictable.

Request Pattern

python

import os
import requests

HOSTED = True
url = (
    "https://health.api.nvidia.com/v1/biology/nvidia/genmol/generate"
    if HOSTED else "http://localhost:8000/generate"
)
headers = {"Content-Type": "application/json"}
if HOSTED:
    headers["Authorization"] = f"Bearer {os.getenv('NGC_API_KEY')}"

payload = {
    "smiles": "[*{20-30}]",  # SAFE notation
    "num_molecules": 30,
    "temperature": "1.0",    # string, not float
    "noise": "1.0",          # string, not float
    "step_size": 1,
    "scoring": "QED",        # or "LogP"
    "unique": False,
}

response = requests.post(url, headers=headers, json=payload, timeout=180)
response.raise_for_status()
result = response.json()

Gotchas:

```
temperature
```
and
```
noise
```
are strings.
```
num_molecules
```
is 1-1000; invalid/duplicate molecules may be filtered, so request extra when the user needs a minimum count.
```
scoring
```
is
```
"QED"
```
for drug-likeness or
```
"LogP"
```
for lipophilicity.
Set
```
unique=True
```
for deduplicated analog lists.

Save And Report Output

Sort molecules by score, print the top ranks, and write a

.smi

file as shown in

references/examples.md

under Save Ranked Results. For chemical validity, uniqueness, PAINS/alerts, and visualization with RDKit, read

references/validation.md

.

Limits And Troubleshooting

Fewer molecules than requested is expected after filtering.
Invalid SAFE strings cause
```
status: "failed"
```
or validation errors.
Install
```
safe-mol
```
only for scaffold, motif, or lead-optimization workflows; de novo masks work without conversion.
Local startup downloads about 20 GB into
```
LOCAL_NIM_CACHE
```
.
Container issues: confirm
```
nvidia-smi
```
, NVIDIA Container Toolkit, and
```
--runtime=nvidia
```
; use
```
NIM_TEST_GPU
```
to choose the single visible GPU.