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In Silico Prediction of Novel Inhibitors of SARS-CoV-2 Main Protease through Structure-Based Virtual Screening and Molecular Dynamic Simulation.

ABSTRACT: The unprecedented pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is threatening global health. SARS-CoV-2 has caused severe disease with significant mortality since December 2019. The enzyme chymotrypsin-like protease (3CLpro) or main protease (M^pro) of the virus is considered to be a promising drug target due to its crucial role in viral replication and its genomic dissimilarity to human proteases. In this study, we implemented a structure-based virtual screening (VS) protocol in search of compounds that could inhibit the viral M^pro. A library of >eight hundred compounds was screened by molecular docking into multiple structures of M^pro, and the result was analyzed by consensus strategy. Those compounds that were ranked mutually in the 'Top-100' position in at least 50% of the structures were selected and their analogous binding modes predicted simultaneously in all the structures were considered as bioactive poses. Subsequently, based on the predicted physiological and pharmacokinetic behavior and interaction analysis, eleven compounds were identified as 'Hits' against SARS-CoV-2 M^pro. Those eleven compounds, along with the apo form of M^pro and one reference inhibitor (X77), were subjected to molecular dynamic simulation to explore the ligand-induced structural and dynamic behavior of M^pro. The MM-GBSA calculations reflect that eight out of eleven compounds specifically possess high to good binding affinities for M^pro. This study provides valuable insights to design more potent and selective inhibitors of SARS-CoV-2 M^pro.

SUBMITTER: Halim SA

PROVIDER: S-EPMC8471057 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The continued toll of COVID-19 has halted the smooth functioning of civilization on a global scale. With a limited understanding of all the essential components of viral machinery and the lack of structural information of this new virus, initial drug discovery efforts had limited success. The availability of high-resolution crystal structures of functionally essential SARS-CoV-2 proteins, including 3CLpro, supports the development of target-specific therapeutics. 3CLpro, the main protease responsible for the processing of viral polypeptide, plays a vital role in SARS-CoV-2 viral replication and translation and is an important target in other coronaviruses. Additionally, 3CLpro is the target of repurposed drugs, such as lopinavir and ritonavir. In this study, target proteins were retrieved from the protein data bank (PDB IDs: 6 M03, 6LU7, 2GZ7, 6 W63, 6SQS, 6YB7, and 6YVF) representing different open states of the main protease to accommodate macromolecular substrate. A hydroxyethylamine (HEA) library was constructed from harvested chemical structures from all the series being used in our laboratories for screening against malaria and Leishmania parasites. The database consisted of ∼1000 structure entries, of which 70% were new to ChemSpider at the time of screening. This in-house library was subjected to high throughput virtual screening (HTVS), followed by standard precision (SP) and then extra precision (XP) docking (Schrodinger LLC 2021). The ligand strain and complex energy of top hits were calculated by Molecular Mechanics Generalized Born Surface Area (MM/GBSA) method. Promising hit compounds (n = 40) specifically binding to 3CLpro with high energy and average MM/GBSA scores were then subjected to (100-ns) MD simulations. Using this sequential selection followed by an in-silico validation approach, we found a promising HEA-based compound (N,N'-((3S,3'S)-piperazine-1,4-diylbis(3-hydroxy-1-phenylbutane-4,2-diyl))bis(2-(5-methyl-1,3-dioxoisoindolin-2-yl)-3-phenylpropanamide)), which showed high in vitro antiviral activity against SARS-CoV-2. Further to reduce the size of the otherwise larger ligand, a pharmacophore-based predicted library of ∼42 derivatives was constructed, which were added to the previous compound library and rescreened virtually. Out of several hits from the predicted library, two compounds were synthesized, tested against SARS-CoV-2 culture, and found to have markedly improved antiviral activity.

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In Silico Prediction of Novel Inhibitors of SARS-CoV-2 Main Protease through Structure-Based Virtual Screening and Molecular Dynamic Simulation.

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