Drug-target interaction prediction using Multi Graph Regularized Nuclear Norm Minimization.

ABSTRACT: The identification of potential interactions between drugs and target proteins is crucial in pharmaceutical sciences. The experimental validation of interactions in genomic drug discovery is laborious and expensive; hence, there is a need for efficient and accurate in-silico techniques which can predict potential drug-target interactions to narrow down the search space for experimental verification. In this work, we propose a new framework, namely, Multi-Graph Regularized Nuclear Norm Minimization, which predicts the interactions between drugs and target proteins from three inputs: known drug-target interaction network, similarities over drugs and those over targets. The proposed method focuses on finding a low-rank interaction matrix that is structured by the proximities of drugs and targ

SUBMITTER: Mongia A 

PROVIDER: S-EPMC6964976 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature