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Kegg drug

Skill BioTender-max/awesome-bio-agent-skills/skills/drugclaw/kegg_drug

A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell analysis, clinical AI, and protein design.From the repository description

Install
npx -y skills add BioTender-max/awesome-bio-agent-skills --skill kegg_drug

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SKILL.md

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68 · KEGG Drug

Approved drugs — structures, targets, pathways & drug-drug interactions
Category: Drug-centric | Type: DB | Subcategory: DDI
API: https://rest.kegg.jp (free, no key required for academic use)

ResourceURL
Homepagehttps://www.genome.jp/kegg/
API docshttps://www.kegg.jp/kegg/docs/keggapi.html
Paperhttps://academic.oup.com/nar/article/38/suppl_1/D355/3112250

What it provides

  • Drug metadata: name, formula, molecular weight, efficacy, class
  • Targets: gene/protein targets for each approved drug
  • Interactions (DDI): drug-drug interaction annotations
  • Pathways: linked KEGG pathway IDs

Quick start

from 68_KEGG_Drug import query

# Single entity
results = query("aspirin")

# Multiple entities
results = query(["aspirin", "metformin", "imatinib"])

# By KEGG Drug ID
results = query("D00109")

# Specific fields only
results = query("warfarin", fields="targets")
results = query("warfarin", fields="interactions")

query() interface

query(entities, fields="all") -> list[dict]
ParameterTypeDescription
entitiesstr | list[str]Drug name(s) or KEGG Drug ID(s) (e.g. "D00109")
fieldsstr"all" — full entry; "targets" — targets only; "interactions" — DDI only

Return structure (fields="all")

[
  {
    "drug_id": "dr:D00109",
    "query": "aspirin",
    "name": "Aspirin (JP18/USP/INN); ...",
    "formula": "C9H8O4",
    "mol_weight": "180.0423",
    "targets": ["PTGS1 ...", "PTGS2 ..."],
    "interactions": ["Warfarin [precaution] ...", ...],
    "pathways": ["map07112 ...", ...],
    "classes": ["Analgesic ...", ...]
  }
]

If a name cannot be resolved, the entry contains {"query": "xxx", "error": "No match found"}.


Lower-level functions

FunctionInputOutputDescription
search(query, limit=10)drug name/keywordlist[{id, name}]Keyword search
get_entry(drug_id)KEGG Drug IDdictFull parsed entry
get_targets(drug_id)KEGG Drug IDlist[str]Target lines
get_interactions(drug_id)KEGG Drug IDlist[str]DDI lines

Notes

  • KEGG REST API is free for academic use; commercial use requires a license.
  • Rate limit: no official cap, but keep requests reasonable (~1 req/sec).
  • Drug IDs look like D00109 or dr:D00109; both formats accepted.
  • Not all drugs have interaction or target annotations — empty list means no data.

What ships with it: 5 files

17.3 KB alongside SKILL.md, 4 of them executable

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