Drug Repurposing by Simulating Flow Through Protein-Protein Interaction Networks.

ABSTRACT: As drug development is extremely expensive, the identification of novel indications for in-market drugs is financially attractive. Multiple algorithms are used to support such drug repurposing, but highly reliable methods combining simulation of intracellular networks and machine learning are currently not available. We developed an algorithm that simulates drug effects on the flow of information through protein-protein interaction networks, and used support vector machine to identify potentially effective drugs in our model disease, psoriasis. Using this method, we screened about 1,500 marketed and investigational substances, identified 51 drugs that were potentially effective, and selected three of them for experimental confirmation. All drugs inhibited tumor necrosis factor alpha-induce

SUBMITTER: Manczinger M 

PROVIDER: S-EPMC5836852 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature