drugmechdb-query

name	drugmechdb-query
description	Query the DrugMechDB drug mechanism-of-action database. Use whenever the user asks about drug mechanisms, drug-to-disease paths, biological targets of a drug, or wants to look up any biomedical entity (drug name, protein, disease, DrugBank ID, MESH ID, UniProt ID, GO term, etc.) in DrugMechDB.

DrugMechDB Query Skill

Search drug mechanism-of-action paths by entity name or ID. Each path is a directed graph: Drug → (intermediates) → Disease, with typed nodes and labeled edges.

Data

• Source: indication_paths.json
• Path: resources_metadata/drug_mechanism/DRUGMECHDB/indication_paths.json
• Records: ~4846 mechanism paths, ~32k relationships

Entity auto-detection

Input pattern	Detected as	Example
DB:DB00619	DrugBank ID	exact on node/graph IDs
MESH:D015464	MESH ID	exact on node/graph IDs
UniProt:P00519	UniProt protein	exact on node IDs
GO:0006915	GO term	exact on node IDs
CHEBI:*, HP:*, UBERON:*, CL:*, reactome:*, InterPro:*, PR:*, taxonomy:*	respective types	exact on node IDs
anything else	free text	substring match on drug/disease/node names

API

Function	Signature	Returns
load(path)	path to JSON	list[dict] — full database
build_index(db)	loaded db	(by_id, by_name, by_drug, by_disease) dicts for O(1) lookup
search(db, entity, index=None)	single query string	list[dict] — matching paths
search_batch(db, entities, index=None)	list of query strings	dict[str, list[dict]]
summarize(paths, entity)	search results	compact multi-line text
to_json(paths)	search results	list of flat dicts (id, drug, disease, nodes, links)

Node types (14)

BiologicalProcess, Cell, CellularComponent, ChemicalSubstance, Disease, Drug, GeneFamily, GrossAnatomicalStructure, MacromolecularComplex, MolecularActivity, OrganismTaxon, Pathway, PhenotypicFeature, Protein

Quick usage

import drugmechdb_query as dq

db = dq.load()  # uses default DATA_PATH
idx = dq.build_index(db)  # optional, recommended for repeated queries

# Single query — by name or ID
paths = dq.search(db, "imatinib", idx)
paths = dq.search(db, "UniProt:P00519", idx)
paths = dq.search(db, "MESH:D003920", idx)
print(dq.summarize(paths, "imatinib"))

# Batch query
results = dq.search_batch(db, ["metformin", "MESH:D003920", "asthma"], idx)
for entity, paths in results.items():
    print(dq.summarize(paths, entity))

# JSON export
print(dq.to_json(paths))

Output structure per path

graph:  { _id, drug, disease, drugbank, drug_mesh, disease_mesh }
nodes:  [{ id, label, name }, ...]
links:  [{ source, target, key }, ...]

key examples: decreases activity of, causes, positively regulates, treats, increases expression of, etc. (66 relation types total).