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Navigating Chemical Space By Interfacing Generative Artificial Intelligence and Molecular Docking

Ziqiao Xu, Orrette Wauchope, View ORCID ProfileAaron T. Frank
doi: https://doi.org/10.1101/2020.06.09.143289
Ziqiao Xu
athe University of Michigan, Department of Chemistry, Ann Arbor, 48109, United States of America
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Orrette Wauchope
bCity University of New York, Baruch College, Department of Natural Sciences, New York, 10010, United States of America
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Aaron T. Frank
athe University of Michigan, Department of Chemistry, Ann Arbor, 48109, United States of America
cthe University of Michigan, Biophysics, Ann Arbor, 48109, United States of America
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  • ORCID record for Aaron T. Frank
  • For correspondence: afrankz@umich.edu
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Abstract

Here we report the testing and application of a simple, structure-aware framework to design target-specific screening libraries for drug development. Our approach combines advances in generative artificial intelligence (AI) with conventional molecular docking to rapidly explore chemical space conditioned on the unique physiochemical properties of the active site of a biomolecular target. As a proof-of-concept, we used our framework to construct a focused library for cyclin-dependent kinase type-2 (CDK2). We then used it to rapidly generate a library specific to the active site of the main protease (Mpro) of the SARS-CoV-2 virus, which causes COVID-19. By comparing approved and experimental drugs to compounds in our library, we also identified six drugs, namely, Naratriptan, Etryptamine, Panobinostat, Procainamide, Sertraline, and Lidamidine, as possible SARS-CoV-2 Mpro targeting compounds and, as such, potential drug repurposing candidates. To complement the open-science COVID-19 drug discovery initiatives, we make our SARS-CoV-2 Mpro library fully accessible to the research community (https://github.com/atfrank/SARS-CoV-2).

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/atfrank/SARS-CoV-2

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted June 11, 2020.
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Navigating Chemical Space By Interfacing Generative Artificial Intelligence and Molecular Docking
Ziqiao Xu, Orrette Wauchope, Aaron T. Frank
bioRxiv 2020.06.09.143289; doi: https://doi.org/10.1101/2020.06.09.143289
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Navigating Chemical Space By Interfacing Generative Artificial Intelligence and Molecular Docking
Ziqiao Xu, Orrette Wauchope, Aaron T. Frank
bioRxiv 2020.06.09.143289; doi: https://doi.org/10.1101/2020.06.09.143289

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