title: Improved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem.
abstract: Conventional one-drug-one-gene approach has been of limited success in modern drug discovery. Polypharmacology, which focuses on searching for multi-targeted drugs to perturb disease-causing networks instead of designing selective ligands to target individual proteins, has emerged as a new drug discovery paradigm. Although many methods for single-target virtual screening have been developed to improve the efficiency of drug discovery, few of these algorithms are designed for polypharmacology. Here, we present a novel theoretical framework and a corresponding algorithm for genome-scale multi-target virtual screening based on the one-class collaborative filtering technique. Our method overcomes the sparseness of the protein-chemical interaction data by means of interaction matrix weighting and dual regularization from both chemicals and proteins. While the statistical foundation behind our method is general enough to encompass genome-wide drug off-target prediction, the program is specifically tailored to find protein targets for new chemicals with little to no available interaction data. We extensively evaluate our method using a number of the most widely accepted gene-specific and cross-gene family benchmarks and demonstrate that our method outperforms other state-of-the-art algorithms for predicting the interaction of new chemicals with multiple proteins. Thus, the proposed algorithm may provide a powerful tool for multi-target drug design.
authors.affiliation: Department of Computer Science, Hunter College, The City University of New York, New York, New York 10065, United States.
authors.forename: Hansaim
authors.initials: H
authors.lastname: Lim
authors.affiliation: Department of Computer Science, University of Northern Iowa, Cedar Falls, Iowa 50614, United States.
authors.forename: Paul
authors.initials: P
authors.lastname: Gray
authors.affiliation: Department of Computer Science, Hunter College, The City University of New York, New York, New York 10065, United States.|Ph.D. Program in Computer Science, Biochemistry and Biology, The Graduate Center, The City University of New York, New York, New York 10065, United States.
authors.forename: Lei
authors.initials: L
authors.lastname: Xie
authors.affiliation: Department of Computer Science, University of Northern Iowa, Cedar Falls, Iowa 50614, United States.
authors.forename: Aleksandar
authors.initials: A
authors.lastname: Poleksic
mesh_terms: D000465:Algorithms; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D016678:Genome; D064798:Polypharmacology; D015203:Reproducibility of Results