Searching the druggable genome using large language models.

Lars Schimmelpfennig; Matthew Cannon; Quentin Cody; Joshua McMichael; Adam C Coffman; Susanna Kiwala; Kilannin Krysiak; Alex H Wagner; Malachi Griffith; Obi L Griffith

doi:10.1093/bioinformatics/btag632

PubMed · 42631692

Searching the druggable genome using large language models.

Lars Schimmelpfennig·Matthew Cannon·Quentin Cody·Joshua McMichael·Adam C Coffman·Susanna Kiwala·Kilannin Krysiak·Alex H Wagner·Malachi Griffith·Obi L Griffith

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Abstract

SUMMARY: The druggable genome encompasses the genes that are known or predicted to interact with drugs. The Drug-Gene Interaction Database (DGIdb) provides an integrated resource for discovering and contextualizing these interactions, supporting a broad range of research and clinical applications. DGIdb is currently accessed through structured web interfaces and API calls, requiring users to translate natural-language questions into database-specific query patterns. To allow for the use of DGIdb through natural language, we developed the DGIdb Model Context Protocol (MCP) server, which allows large language models (LLMs) access to up-to-date information through the DGIdb API. We demonstrate that the MCP server improves an LLM's ability to answer questions requiring accurate, up-to-date biomedical knowledge drawn from structured external resources. AVAILABILITY AND IMPLEMENTATION: The DGIdb MCP server is detailed at https://github.com/dgidb/dgidb-mcp-server and includes instructions for accessing the server through the Claude desktop app.

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Large Language Models Software Genome Genomics Databases, Genetic Journal Article Research Support, N.I.H., Extramural

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Lars Schimmelpfennig, Matthew Cannon, Quentin Cody, Joshua McMichael, Adam C Coffman, Susanna Kiwala, Kilannin Krysiak, Alex H Wagner, Malachi Griffith, Obi L Griffith. 2026-08-31. Searching the druggable genome using large language models.. https://doi.org/10.1093/bioinformatics%2Fbtag632

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