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bembenek_covid19_computional_models_v2.pdf (839.48 kB)

Drug Repurposing and New Therapeutic Strategies for SARS-CoV-2 Disease Using a Novel Molecular Modeling-AI Hybrid Workflow

preprint
revised on 12.06.2020, 19:13 and posted on 16.06.2020, 05:40 by Scott Bembenek

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.

History

Email Address of Submitting Author

sbembenek@denovicontx.com

Institution

Denovicon Therapeutics

Country

United States

ORCID For Submitting Author

0000-0003-1756-7188

Declaration of Conflict of Interest

No conflict of interest

Version Notes

Version-2.0

Exports