Automated Annotation of Sites of Metabolism from Biotransformation Data.

ABSTRACT: Computational models predicting the Sites-of-Metabolism (SOMs) of small organic molecules have become invaluable tools for studying and optimizing the metabolic properties of xenobiotics. However, the performance of SOM predictors has shown signs of plateauing in recent years, primarily due to the limited availability of training data. While vast amounts of biotransformation data in the form of substrate-metabolite pairs exist, their potential for SOM prediction remains largely untapped due to the absence of annotations. Annotating SOMs requires expert knowledge and is a highly time-consuming process. To address this challenge, we introduce AutoSOM, the first open-source tool that automatically extracts SOMs by mapping structural differences using transformation rules. AutoSOM is both fast

SUBMITTER: Jacob RA 

PROVIDER: S-EPMC12264948 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature