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SKILL verified MIT Self-run

Drug Bioactivity Assay

skill-learningmatter-mit-atomisticskills-drug-bioactivity-assay · by learningmatter-mit

Fetch biological assays and target proteins a chemical has been tested against via PubChem.

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Install

$ agentstack add skill-learningmatter-mit-atomisticskills-drug-bioactivity-assay

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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2mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Bioactivity and Assay Data Retrieval

Goal

To programmatically retrieve the testing history of a specific chemical compound against biological targets using PubChem's Assay Summary endpoint. This skill allows filtering for "Active" outcomes, providing assay IDs (AIDs), target GeneIDs, and micromolar activity values to assess a compound's promiscuity or target specificity.

Instructions

1. Extract All Assays

Retrieve all assays for a given compound (CID), regardless of outcome:

# Env: base-agent
python .agents/skills/drug-bioactivity-assay/scripts/get_assays.py \
  --cid 2244 \
  --limit 50 \
  --outdir research/aspirin_assays \
  --output aspirin_all_assays.json

2. Extract Only 'Active' Results

Use the --active_only flag to strictly return assays where the compound was marked as "Active" or showed positive binding/inhibition.

# Env: base-agent
python .agents/skills/drug-bioactivity-assay/scripts/get_assays.py \
  --cid 5291 \
  --active_only \
  --limit 50 \
  --outdir research/imatinib_assays \
  --output imatinib_active_assays.json

Parameters:

  • --cid: PubChem CID of the target molecule (e.g., 5291 for Imatinib).
  • --outdir: Directory to save the resulting JSON file.
  • --active_only: (Optional) Flag to strictly filter results to assays where the test outcome was "Active".
  • --limit: (Optional) Maximum number of assays to retrieve (default: 1000) to keep JSON sizes manageable.
  • --output: (Optional) Output filename (default: assay_summary.json).

Examples

We can test extracting known active targets for the cancer drug Imatinib (CID: 5291).

# Env: base-agent
python .agents/skills/drug-bioactivity-assay/scripts/get_assays.py \
  --cid 5291 \
  --active_only \
  --limit 20 \
  --outdir .agents/skills/drug-bioactivity-assay/examples/imatinib \
  --output assays_imatinib_active.json

Constraints

  • Assay Availability: Compounds with no biological testing history in PubChem will return 0 results.
  • Reporting Variations: High-throughput screening (HTS) assay results often lack explicit target GeneIDs or quantitative Activity Values compared to confirmatory literature assays. The script retrieves whatever is available natively in the column.
  • Network Limits: PubChem can sporadically drop connections when rendering very large assay summaries. The script automatically handles connection drops and HTTP 503 blocking via exponential backoff.


Author: Bowen Deng Contact: GitHub @learningmatter-mit

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.