DrugRepoBank Query Skill

SkillDatabases & data

Query the DrugRepoBank drug repurposing evidence database. Use whenever the user asks about repurposing candidates, drug, disease, target repurposing evidence, or wants to look up any entity (drug name, DrugBank ID, ChEMBL ID, PubChem CID, TTD target ID, UniProt ID, disease name) in DrugRepoBank.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the DrugRepoBank Query Skill skill

What this skill tells your AI

The instructions your AI receives, as published by qsong-github/drugclaw in skills/drug_repurposing/drugrepobank/SKILL.md and read by ahel’s review.

Search four linked tables (Drug, Target, DrugTargetInteraction, Literature) for repurposing evidence. Auto-detects entity type by prefix:

Input Pattern	Detected As	Example
`DB00945`	DrugBank ID	exact on `DrugBank_ID` / `DrugID`
`T47101`	TTD Target ID	exact on `TargetID`
`FGFR1_HUMAN`	UniProt ID	exact on `UniprotID`
`CHEMBL2103749`	ChEMBL ID	exact on `ChEMBL ID` in Drug table
`16129704` (digits)	PubChem CID	exact on `PubChem_Compound_ID` / `PubChemID`
anything else	free text	substring on drug Name, TargetName, Disease, NewDisease

API

Function	Input	Returns
`load_all()`	—	`dict` with keys `drug`, `dti`, `lit`, `target` (lists of row-dicts)
`search(tables, entity)`	tables dict + single entity string	`dict` with keys `entity`, `entity_type`, `drug`, `target`, `dti`, `literature`
`search_batch(tables, entities)`	tables dict + list of entity strings	`dict[str, search_result]`
`summarize(result)`	single `search()` result	compact one-line LLM-readable text
`to_json(result)`	single `search()` result	JSON string (trimmed heavy fields)

Usage

See if __name__ == "__main__" block in 42_DrugRepoBank.py for runnable examples covering: drug name, DrugBank ID, TTD target ID, UniProt ID, ChEMBL ID, disease free-text, batch search, and JSON output.

Data

Four CSV tables in DATA_DIR:

File	Key Columns	Description
`Drug.csv`	DrugBank_ID, Name, Drug Groups, PubChem_Compound_ID, ChEMBL ID, SMILES	Drug identifiers & structures
`DrugTargetInteraction.csv`	UniprotID, PubchemID, TargetID, DrugID, Highest_status, MOA	Drug–target links with mechanism of action
`Literature.csv`	DrugName, DrugID, Target, Disease, NewDisease, Evidence, Insilico, Invitro, Invivo, Clinicaltrial, PMID	Repurposing evidence & literature references
`Targets.csv`	TargetID, UniprotID, TargetName, TargetGeneName, TargetType, Function	Target annotations & pathway memberships

Path: DATA_DIR variable in 42_DrugRepoBank.py (resources_metadata/drug_repurposing/DrugRepoBank)
Source: https://awi.cuhk.edu.cn/DrugRepoBank/php/index.php
Paper: Huang et al., Database 2024, baae051. DOI:10.1093/database/baae051

Signals

GitHub stars: 116
Forks: 3
Last commit: Aug 2026

Advanced

Item type: skill
Key: drugrepobank-query
Source: github.com/qsong-github/drugclaw

github.com/qsong-github/drugclaw

DrugRepoBank Query Skill

What this skill tells your AI

API

Usage

Data

Signals

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