Bioactivity and Assay Data Retrieval

SkillDev tools

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

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Bioactivity and Assay Data Retrieval skill

What this skill tells your AI

The instructions your AI receives, as published by learningmatter-mit/atomisticskills in .agents/skills/drug-bioactivity-assay/SKILL.md and read by ahel’s review.

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

Signals

GitHub stars
164
Forks
24
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
drug-bioactivity-assay
Source
github.com/learningmatter-mit/atomisticskills