MGATRx: Discovering Drug Repositioning Candidates Using Multi-View Graph Attention.

ABSTRACT: In-silico drug repositioning or predicting new indications for approved or late-stage clinical trial drugs is a resourceful and time-efficient strategy in drug discovery. However, inferring novel candidate drugs for a disease is challenging, given the heterogeneity and sparseness of the underlying biological entities and their relationships (e.g., disease/drug annotations). By integrating drug-centric and disease-centric annotations as multi-views, we propose a multi-view graph attention network for indication discovery (MGATRx). Unlike most current similarity-based methods, we employ graph attention network on the heterogeneous drug and disease data to learn the representation of nodes and identify associations. MGATRx outperformed four other state-of-art methods used for computational dr

SUBMITTER: Yella JK 

PROVIDER: S-EPMC10038065 | biostudies-literature | 2022 Sep-Oct

REPOSITORIES: biostudies-literature