Logic-based machine learning predicts how escitalopram attenuates cardiomyocyte hypertrophy.

ABSTRACT: Cardiomyocyte hypertrophy is a key clinical predictor of heart failure. High-throughput and AI-driven screens have the potential to identify drugs and downstream pathways that modulate cardiomyocyte hypertrophy. Here, we developed LogiRx, a logic-based mechanistic machine learning method that predicts drug-induced pathways. We applied LogiRx to discover how drugs discovered in a previous compound screen attenuate cardiomyocyte hypertrophy. We experimentally validated LogiRx predictions in neonatal cardiomyocytes, adult mice, and two patient databases. Using LogiRx, we predicted antihypertrophic pathways for seven drugs currently used to treat noncardiac disease. We experimentally validated that escitalopram (Lexapro) and mifepristone inhibit hypertrophy of cultured cardiomyocytes in two co

SUBMITTER: Eggertsen TG 

PROVIDER: S-EPMC11912418 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature