qsong-github/drugclaw/drugcentral

Name: drugcentral
Author: qsong-github

Claude Code and agent skill by qsong-github/drugclaw

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qsong-github/drugclaw
skills/drug_knowledgebase/drugcentral/SKILL.md
Updated 20 Oct 2026
Version 1.0.01 version recorded

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Query the DrugCentral drug pharmacology database. Use whenever the user asks about approved drug structures, drug targets, pharmacological actions, or wants to look up any entity (drug name, DrugCentral ID, CAS number, InChIKey) in DrugCentral.

Install

npx vskill@latest install qsong-github/drugclaw/drugcentral

SKILL.md

The same SKILL.md was published earlier as biotender-max/awesome-bio-agent-skills/drugcentral.

DrugCentral Query Skill

Search local DrugCentral flat files by any entity. Auto-detects query type:

Input Pattern	Detected As	Match Logic
`860` (numeric)	DrugCentral ID	exact on `ID`
`50-78-2` (NNN-NN-N)	CAS Number	exact on `CAS_RN`
`BSYNRYMUTXBXSQ` or full key	InChIKey (prefix or full)	prefix match on `InChIKey`
anything else	free text	substring on `INN` (drug name)

Data

Download from <https://drugcentral.org/download>:

File	Description	Required
`structures.smiles.tsv`	SMILES, InChI, InChIKey, ID, INN, CAS_RN	Yes
`drug.target.interaction.tsv`	Drug-target interaction profiles (gene, action, potency)	Recommended
`FDA+EMA+PMDA_Approved.csv`	Approval status (ID, drug_name)	Optional

Place files in DATA_DIR (default: resources_metadata/drug_knowledgebase/DrugCentral, or set env DRUGCENTRAL_DIR).

API

Function	Input	Returns
`search(entity)`	single entity string	`dict` with `structures`, `targets`, `approved`
`search_batch(entities)`	list or comma-separated string	`dict[str, dict]`
`summarize(result, entity)`	search result dict + label	compact text
`to_json(result)`	search result dict	JSON string

Key Fields

structures: ID, INN (drug name), CAS_RN, SMILES, InChI, InChIKey

targets (from DTI file): GENE, TARGET_NAME, TARGET_CLASS, ACTION_TYPE, ACT_VALUE, ACT_TYPE, ACT_UNIT, ACCESSION (UniProt), TDL, ORGANISM

approved: id, name, approved (bool)

Usage

python

from 18_DrugCentral import search, search_batch, summarize, to_json
# Single query — drug name
result = search("aspirin")
print(summarize(result))
# Single query — DrugCentral ID
result = search("860")
print(summarize(result))
# Single query — CAS number
result = search("50-78-2")
print(summarize(result))
# Batch query
results = search_batch(["metformin", "ibuprofen", "50-78-2"])
for entity, res in results.items():
    print(summarize(res, entity))
# JSON export
print(to_json(result))

See if __name__ == "__main__" block in 18_DrugCentral.py for runnable examples covering: drug name, DrugCentral ID, CAS number, InChIKey prefix, batch search, and JSON output.

Source

DrugCentral: <https://drugcentral.org/>
Paper: Avram et al., Nucleic Acids Research 2023, 51(D1):D1276–D1287. DOI: 10.1093/nar/gkac1085
License: CC BY-NC 4.0 (non-commercial)

Security

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Source

SKILL.md in the repositoryCheckingskills/drug_knowledgebase/drugcentral/SKILL.md

Popularity

Repository stars: 117
Repository forks: 3
7-day trend score: 0

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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