Affiliation:
1. Tianjin Medical University
Abstract
Abstract
The outbreak of coronavirus disease 2019 (COVID-19) SARS-CoV-2 has caused widespread panic in the world and has mutated at an extremely rapid rate and thus there is an urgent need for the development of COVID-19 inhibitors. In this study, we used a de novo design method, which integrates a recurrent neural network, reinforcement learning and molecular docking to generate inhibitors of SARS-CoV-2 main protease. Approximately 30,000 molecules were generated after a 120h generation process, and multiple physicochemical filters and molecular docking scores were used for further screening. Finally, five molecules were selected as drug candidates, and their binding stability was verified by molecular dynamics simulation and binding free energy analysis. The results showed that these molecules could be used as candidates for further generation and testing against SARS-CoV-2. Besides, a pharmacophore model based on superior molecules was constructed to provide a reference for subsequent drug screening.
Publisher
Research Square Platform LLC
Reference45 articles.
1. Ramos-Guzmán C, Ruiz-Pernia JJ, Tuón I (2020) Unraveling the SARS-CoV-2 Main. Protease Mechanism Using Multiscale DFT/MM Methods
2. A pneumonia outbreak associated with a new coronavirus of probable bat origin;Zhou P;Nature,2020
3. Omicron and Delta Variant of SARSã¤oV A Comparative Computational Study of Spike Protein;Kumar S;J Med Virol,2021
4. From SARS to MERS: 10 years of research on highly pathogenic human coronaviruses;Hilgenfeld R;Antiviral Res,2013
5. Isolation of a Novel Coronavirus from a Man with Pneumonia in Saudi Arabia;Zaki AM;N Engl J Med,2012
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