Predicting inhibitors of OATP1B1 via heterogeneous OATP-ligand interaction graph neural network (HOLIgraph).

ABSTRACT: Organic anion transporting polypeptides (OATPs) are membrane transporters crucial for drug uptake and distribution in the human body. OATPs can mediate drug-drug interactions (DDIs) in which the interaction of one drug with an OATP impairs the uptake of another drug, resulting in potentially fatal pharmacological effects. Predicting OATP-mediated DDIs is challenging, due to limited information on OATP inhibition mechanisms and inconsistent experimental OATP inhibition data across different studies. This study introduces Heterogeneous OATP-Ligand Interaction Graph Neural Network (HOLIgraph), a novel computational model that integrates molecular modeling with a graph neural network to enhance the prediction of drug-induced OATP inhibition. By combining ligand (i.e., drug) molecular features

SUBMITTER: Mardikoraem M 

PROVIDER: S-EPMC12054207 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature