An Integrated Computational and Experimental Approach to Identifying Inhibitors for SARS-CoV-2 3CL Protease.

Tianhua Zhai,Shozeb Haider,Daniel Kraut,Fangyuan Zhang,Zuyi Huang

doi:10.3389/fmolb.2021.661424

Abstract

The newly evolved SARS-CoV-2 has caused the COVID-19 pandemic, and the SARS-CoV-2 main protease 3CLpro is essential for the rapid replication of the virus. Inhibiting this protease may open an alternative avenue toward therapeutic intervention. In this work, a computational docking approach was developed to identify potential small-molecule inhibitors for SARS-CoV-2 3CLpro. Totally 288 potential hits were identified from a half-million bioactive chemicals via a protein-ligand docking protocol. To further evaluate the docking results, a quantitative structure activity relationship (QSAR) model of 3CLpro inhibitors was developed based on existing small molecule inhibitors of the 3CLproSARS– CoV– 1 and their corresponding IC50 data. The QSAR model assesses the physicochemical properties of identified compounds and estimates their inhibitory effects on 3CLproSARS– CoV– 2. Seventy-one potential inhibitors of 3CLpro were selected through these computational approaches and further evaluated via an enzyme activity assay. The results show that two chemicals, i.e., 5-((1-([1,1′-biphenyl]-4-yl)-2,5-dimethyl-1H-pyrrol-3-yl)methylene)pyrimidine-2,4,6(1H,3H,5H)-trione and N-(4-((3-(4-chlorophenylsulfonamido)quinoxalin-2-yl)amino)phenyl)acetamide, effectively inhibited 3CLpro SARS-CoV-2 with IC50’s of 19 ± 3 μM and 38 ± 3 μM, respectively. The compounds contain two basic structures, pyrimidinetrione and quinoxaline, which were newly found in 3CLpro inhibitor structures and are of high interest for lead optimization. The findings from this work, such as 3CLpro inhibitor candidates and the QSAR model, will be helpful to accelerate the discovery of inhibitors for related coronaviruses that may carry proteases with similar structures to SARS-CoV-2 3CLpro.

Highlights

Coronaviruses are enveloped RNA viruses that infect the respiratory tracts of humans and animals (De Wilde et al, 2018; Huang et al, 2020)
The docking scores for the structure 6LU7 were used to narrow down the candidates for the step in which IC50 values of the selected candidates were predicted by a quantitative structure activity relationship (QSAR) model
In order to inhibit the replication of Severe acute respiratory syndrome (SARS)-CoV-2, an integrated computational and experimental approach was developed in this work to identify potential compounds that inhibit 3CLproSARS-CoV-2. 288 potential inhibitors of the main protease (3CLpro) of SARS-CoV-2 were identified through virtual screening of half a million compounds from existing databases

Summary

Introduction

Coronaviruses are enveloped RNA viruses that infect the respiratory tracts of humans and animals (De Wilde et al, 2018; Huang et al, 2020). Severe acute respiratory syndrome (SARS) and Middle East Respiratory Syndrome (MERS) are coronaviruses that have caused many human deaths in the twenty-first century (Hilgenfeld and Peiris, 2013). A new coronavirus, named SARS-CoV-2, was Identifying Inhibitors for SARS-CoV-2 3CLProtease detected in December 2019 in Wuhan, China (Kong et al, 2020). It was quickly traced in other countries (Lai et al, 2020). The disease caused by SARS-CoV-2, i.e., COVID-19, is a severe health problem, because of its rapid spread worldwide, and due to its high fatality rate (Lai et al, 2020; Xu et al, 2020).

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Discussion

Conclusion