KinomeMETA: a web platform for kinome-wide polypharmacology profiling with meta-learning.

ABSTRACT: Kinase-targeted inhibitors hold promise for new therapeutic options, with multi-target inhibitors offering the potential for broader efficacy while minimizing polypharmacology risks. However, comprehensive experimental profiling of kinome-wide activity is expensive, and existing computational approaches often lack scalability or accuracy for understudied kinases. We introduce KinomeMETA, an artificial intelligence (AI)-powered web platform that significantly expands the predictive range with scalability for predicting the polypharmacological effects of small molecules across the kinome. By leveraging a novel meta-learning algorithm, KinomeMETA efficiently utilizes sparse activity data, enabling rapid generalization to new kinase tasks even with limited information. This significantly expan

SUBMITTER: Li Z 

PROVIDER: S-EPMC11223815 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature