Chemical classification program synthesis using generative artificial intelligence.

ABSTRACT: Accurately classifying chemical structures is essential for cheminformatics and bioinformatics, including tasks such as identifying bioactive compounds of interest, screening molecules for toxicity to humans, finding non-organic compounds with desirable material properties, or organizing large chemical libraries for drug discovery or environmental monitoring. However, manual classification is labor-intensive and difficult to scale to large chemical databases. Existing automated approaches either rely on manually constructed classification rules, or are deep learning methods that lack explainability. This work presents an approach that uses generative artificial intelligence to automatically write chemical classifier programs for classes in the Chemical Entities of Biological Interest (ChEB

SUBMITTER: Mungall CJ 

PROVIDER: S-EPMC12490122 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature