Molecular Modeling Evaluation of the Binding Effect of Ritonavir, Lopinavir and Darunavir to Severe Acute Respiratory Syndrome Coronavirus 2 Proteases

This article has been Reviewed by the following groups

Read the full article

Abstract

Three anti-HIV drugs, ritonavir, lopinavir and darunavir, might have therapeutic effect on coronavirus disease 2019 (COVID-19). In this study, the structure models of two severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteases, coronavirus endopeptidase C30 (CEP_C30) and papain like viral protease (PLVP), were built by homology modeling. Ritonavir, lopinavir and darunavir were then docked to the models, respectively, followed by energy minimization of the protease-drug complexes. In the simulations, ritonavir can bind to CEP_C30 most suitably, and induce significant conformation changes of CEP_C30; lopinavir can also bind to CEP_C30 suitably, and induce significant conformation changes of CEP_C30; darunavir can bind to PLVP suitably with slight conformation changes of PLVP. It is suggested that the therapeutic effect of ritonavir and lopinavir on COVID-19 may be mainly due to their inhibitory effect on CEP_C30, while ritonavir may have stronger efficacy; the inhibitory effect of darunavir on SARS-CoV-2 and its potential therapeutic effect may be mainly due to its inhibitory effect on PLVP.

Article activity feed

  1. SciScore for 10.1101/2020.01.31.929695: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    2.1 Homology Modeling of the Proteases: Since there was no gene of protease identified in the ten SARS-CoV-2 genes directly, the protease-like conserved domains in the orf1ab polyprotein (GenBank: QHO60603.1) of the virus were analyzed through NCBI Conserved Domain Search Service (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) [14–17].
    Proteases
    suggested: None

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    However, there are still limitations in this study. As the catalytic mechanisms of CEP_C30 and PLVP are still unknown, in further studies, it should still be focused on to figure out these mechanisms and how ritonavir, lopinavir and darunavir block these procedures. The safety and actual effects of these drugs on human body should also be carried out and verified by randomized clinical control studies further.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.