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VirtualFlow_COVID_19_ds_2.pdf (14.63 MB)

A Multi-Pronged Approach Targeting SARS-CoV-2 Proteins Using Ultra-Large Virtual Screening

preprint
submitted on 21.07.2020 and posted on 24.07.2020 by Christoph Gorgulla, Krishna PadmanabhaDas, Kendra E. Leigh, Marco Cespugli, Patrick D. Fischer, Zi-Fu Wang, Guilhem Tesseyre, Shreya Pandita, Alec Shnapir, Anthony Calderaio, Colin Hutcheson, Minko Gechev, Alexander Rose, Noam Lewis, Erez Yaffe, Roni Luxenburg, Henry D. Herce, Vedat Durmaz, Thanos D. Halazonetis, Konstantin Fackeldey, Justin J. Patten, Alexander Chuprina, Igor Dziuba, Alla Plekhova, Yurii Moroz, Dmytro Radchenko, Olga Tarkhanova, Irina Yavnyuk, Christian C. Gruber, Ryan Yust, Dave Payne, Anders M. Näär, Mark N. Namchuk, Robert A. Davey, Gerhard Wagner, Jamie Kinney, Haribabu Arthanari

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), previously known as 2019 novel coronavirus (2019-nCoV), has spread rapidly across the globe, creating an unparalleled global health burden and spurring a deepening economic crisis. As of July 7th, 2020, almost seven months into the outbreak, there are no approved vaccines and few treatments available. Developing drugs that target multiple points in the viral life cycle could serve as a strategy to tackle the current as well as future coronavirus pandemics. Here we leverage the power of our recently developed in silico screening platform, VirtualFlow, to identify inhibitors that target SARS-CoV-2. VirtualFlow is able to efficiently harness the power of computing clusters and cloud-based computing platforms to carry out ultra-large scale virtual screens. In this unprecedented structure-based multi-target virtual screening campaign, we have used VirtualFlow to screen an average of approximately 1 billion molecules against each of 40 different target sites on 17 different potential viral and host targets in the cloud. In addition to targeting the active sites of viral enzymes, we also target critical auxiliary sites such as functionally important protein-protein interaction interfaces. This multi-target approach not only increases the likelihood of finding a potent inhibitor, but could also help identify a collection of anti-coronavirus drugs that would retain efficacy in the face of viral mutation. Drugs belonging to different regimen classes could be combined to develop possible combination therapies, and top hits that bind at highly conserved sites would be potential candidates for further development as coronavirus drugs. Here, we present the top 200 in silico hits for each target site. While in-house experimental validation of some of these compounds is currently underway, we want to make this array of potential inhibitor candidates available to researchers worldwide in consideration of the pressing need for fast-tracked drug development.

Funding

GM136859

History

Email Address of Submitting Author

hari@hms.harvard.edu

Institution

Harvard Medical School

Country

United States

ORCID For Submitting Author

0000-0002-7281-1289

Declaration of Conflict of Interest

Alexander Chuprina, Dmytro Radchenko,  and Iryna Iavniuk work for Enamine, Kyiv Ukraine. Igor Dziuba works for UkrOrgSyntez Ltd, Kyiv Ukraine. Olga Tarkhanova, Alla Plekhova, and Yurii Moroz work for Chemspace Kyiv, Ukraine. Enamine, UkrOrgSyntez, and Chemspace are companies that are involved in the synthesis and distribution of drug-like compounds. Yurii Moroz is a scientific advisor for Enamine.

Version Notes

Version 1 as of July 21st 2020

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