4.5 Article

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

Journal

JOURNAL OF MOLECULAR GRAPHICS & MODELLING
Volume 101, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jmgm.2020.107762

Keywords

SARS-CoV2; Proteinase; SARS-CoV; Docking; MD simulations

Funding

  1. CONACYT [CB-A1-S-21278]
  2. SIP/IPN [20201015]

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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. (C) 2020 Elsevier Inc. All rights reserved.

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