Computational Approaches to Assist Drug Repositioning for COVID-19

Abstract

COVID-19, caused by the SARS-CoV-2 virus, has become a leading cause of morbidity and mortality worldwide. Drug repositioning, the process of finding new therapeutic indications for marketed drugs, is a promising alternative to new drug development, with lower costs and shorter development times. Here, we present two computational approaches that have been designed to assist drug repurposing projects for COVID-19. The aim of these methods is to provide rankings of drugs that can be used for directing experimental research. Our first approach consists of a novel non-negative matrix factorisation algorithm to rank broad spectrum antivirals that have been approved, or are being developed, for viruses. Our second approach, rooted in ideas from network medicine, aims at ranking drugs by estimating the perturbation each drug induces on a subnetwork of the human interactome that is crucial for SARS-CoV-2 infection/replication. Using graph kernels and host proteins weighted by gene expression data from SARS-CoV-2 infected cell lines, we obtained a ranking of 1853 therapeutically diverse FDA-approved drugs. Our experiments show that nine out of 10 of our top predicted broad spectrum antivirals are already indicated for compassionate use in COVID-19 patients worldwide; and that the ranking obtained by our perturbation analysis approach aligns with independent experimental data on in vitro screenings.  Finally, we present the COVID-19 Repositioning Explorer (CoREx), an interactive online tool that we developed for assisting drug repositioning projects for COVID-19. CoRex allows scientists to explore the interplay between approved drugs and SARS-CoV-2 host proteins in the context of biological networks, protein function, drug clinical use, and the Connectivity Map. Funding Information: This work was supported by Biotechnology and Biological Sciences Research Council (https://bbsrc.ukri.org/) grants BB/K004131/1, BB/F00964X/1 and BB/M025047/1, Consejo Nacional de Ciencia y Tecnologia Paraguay - CONACyT (http://www.conacyt.gov.py/) grants 14-INV-088, PINV15-315, and PINV20-337, National Science Foundation Advances in Bio Informatics (https://www.nsf.gov/) grant 1660648 and the Fundacao Getulio Vargas. Conflicts of Interest: None to declare.