Drug Repurposing and New Therapeutic Strategies for SARS-CoV-2 Disease Using a Novel Molecular Modeling-AI Hybrid Workflow
Scott Bembenek
Abstract
The recent outbreak of the novel coronavirus (SARS-CoV-2) poses a significant challenge to the scientific and medical communities to find immediate treatments. The usual process of identifying viable molecules and transforming them into a safe and effective drug takes 10-15 years, with around 5 years of that time spent in preclinical research and development alone. The fastest strategy is to identify existing drugs or late-stage clinical molecules (originally intended for other therapeutic targets) that already have some level of efficacy. To this end, we tasked our novel molecular modeling-AI hybrid computational platform with finding potential inhibitors of the SARS-CoV-2 main protease (Mpro, 3CLpro). Over 13,000 FDA-approved drugs and clinical candidates (represented by just under 30,000 protomers) were examined. This effort resulted in the identification of several promising molecules. Moreover, it provided insight into key chemical motifs surely to be beneficial in the design of future inhibitors. Finally, it facilitated a unique perspective into other potentially therapeutic targets and pathways for SARS-CoV-2.
CORDITE (CORona Drug InTEractions database) collects and aggregates data from PubMed, MedRxiv, BioRxiv, ChemRxiv and PMC for SARS-CoV-2. Its main focus is set on drug interactions either addressing viral proteins or human proteins that could be used to treat COVID.
It collects and provides up-to-date information on computational predictions, in vitro, as well as in vivo study data.
The information provided is for research only and we cannot guarantee the correctness of the data.
