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Potential COVID-2019 3C-like Protease Inhibitors Designed Using Generative Deep Learning Approaches

preprint
revised on 19.02.2020 and posted on 19.02.2020 by Alex Zhavoronkov, Vladimir Aladinskiy, Alexander Zhebrak, Bogdan Zagribelnyy, Victor Terentiev, Dmitry S. Bezrukov, Daniil Polykovskiy, Rim Shayakhmetov, Andrey Filimonov, Philipp Orekhov, Yilin Yan, Olga Popova, Quentin Vanhaelen, Alex Aliper, Yan Ivanenkov

The emergence of the 2019 novel coronavirus (COVID-19), for which there is no vaccine or any known effective treatment created a sense of urgency for novel drug discovery approaches. One of the most important COVID-19 protein targets is the 3C-like protease for which the crystal structure is known. Most of the immediate efforts are focused on drug repurposing of known clinically-approved drugs and virtual screening for the molecules available from chemical libraries that may not work well. For example, the IC50 of lopinavir, an HIV protease inhibitor, against the 3C-like protease is approximately 50 micromolar, which is far from ideal. In an attempt to address this challenge, on January 28th, 2020 Insilico Medicine decided to utilize a part of its generative chemistry pipeline to design novel drug-like inhibitors of COVID-19 and started generation on January 30th. It utilized three of its previously validated generative chemistry approaches: crystal-derived pocked-based generator, homology modelling-based generation, and ligand-based generation. Novel druglike compounds generated using these approaches were published at www.insilico.com/ncov-sprint/. Several molecules will be synthesized and tested using the internal resources; however, the team is seeking collaborations to synthesize, test, and, if needed, optimize the published molecules.

History

Email Address of Submitting Author

alex@insilico.com

Institution

Insilico Medicine

Country

Hong Kong, China

ORCID For Submitting Author

0000-0001-7067-8966

Declaration of Conflict of Interest

All authors are affiliated with Insilico Medicine Hong Kong Ltd, a company developing an AI-based end-to-end integrated pipeline for drug discovery and development and engaged in aging and cancer research.

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