Prediction of potential inhibitors of the dimeric SARS-CoV2 main proteinase through the MM/GBSA approach

利用MM/GBSA方法预测二聚体SARS-CoV-2主蛋白酶的潜在抑制剂

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Abstract

Since the emergence of SARS-CoV2, to date, no effective antiviral drug has been approved to treat the disease, and no vaccine against SARS-CoV2 is available. Under this scenario, the combination of two HIV-1 protease inhibitors, lopinavir and ritonavir, has attracted attention since they have been previously employed against the SARS-CoV main proteinase (M(pro)) and exhibited some signs of effectiveness. Recently, the 3D structure of SARS-CoV2 M(pro) was constructed based on the monomeric SARS-CoV M(pro) and employed to identify potential approved small inhibitors against SARS-CoV2 M(pro), allowing the selection of 15 drugs among 1903 approved drugs to be employed. In this study, we performed docking of these 15 approved drugs against the recently solved X-ray crystallography structure of SARS-CoV2 M(pro) in the monomeric and dimeric states; the latter is the functional state that was determined in a biological context, and these were submitted to molecular dynamics (MD) simulations coupled with the molecular mechanics generalized Born surface area (MM/GBSA) approach to obtain insight into the inhibitory activity of these compounds. Similar studies were performed with lopinavir and ritonavir coupled to monomeric and dimeric SARS-CoV M(pro) and SARS-CoV2 M(pro) to compare the inhibitory differences. Our study provides the structural and energetic basis of the inhibitory properties of lopinavir and ritonavir on SARS-CoV M(pro) and SARS-CoV2 M(pro), allowing us to identify two FDA-approved drugs that can be used against SARS-CoV2 M(pro). This study also demonstrated that drug discovery requires the dimeric state to obtain good results.

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