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Protein-Ligand Docking Simulations with AutoDock4 Focused on the Main Protease of SARS-CoV-2.
de Azevedo Junior, Walter Filgueira; Bitencourt-Ferreira, Gabriela; Godoy, Joana Retzke; Adriano, Hilda Mayela Aran; Dos Santos Bezerra, Wallyson André; Dos Santos Soares, Alexandra Martins.
  • de Azevedo Junior WF; Pontifical Catholic University of Rio Grande do Sul (PUCRS), Av. Ipiranga, 6681 Porto Alegre/RS 90619-900, Brazil.
  • Bitencourt-Ferreira G; Pontifical Catholic University of Rio Grande do Sul (PUCRS), Av. Ipiranga, 6681 Porto Alegre/RS 90619-900, Brazil.
  • Godoy JR; Pontifical Catholic University of Rio Grande do Sul (PUCRS), Av. Ipiranga, 6681 Porto Alegre/RS 90619-900, Brazil.
  • Adriano HMA; Universidad de Celaya, Carretera Panamericana, Rancho Pinto km 269, 38080 Celaya, Gto. Zip Code 38080, Guanajuato, Mexico.
  • Dos Santos Bezerra WA; Department of Chemical Engineering, Federal University of Maranhao, Avenida dos Portugueses, 1966 Sao Luís / MA 65080-805, Brazil.
  • Dos Santos Soares AM; Department of Chemical Engineering, Federal University of Maranhao, Avenida dos Portugueses, 1966 Sao Luís / MA 65080-805, Brazil.
Curr Med Chem ; 28(37): 7614-7633, 2021.
Article in English | MEDLINE | ID: covidwho-1158306
ABSTRACT

BACKGROUND:

The main protease of SARS-CoV-2 (Mpro) is one of the targets identified in SARS-CoV-2, the causative agent of COVID-19. The application of X-ray diffraction crystallography made available the three-dimensional structure of this protein target in complex with ligands, which paved the way for docking studies.

OBJECTIVE:

Our goal here is to review recent efforts in the application of docking simulations to identify inhibitors of the Mpro using the program AutoDock4.

METHODS:

We searched PubMed to identify studies that applied AutoDock4 for docking against this protein target. We used the structures available for Mpro to analyze intermolecular interactions and reviewed the methods used to search for inhibitors.

RESULTS:

The application of docking against the structures available for the Mpro found ligands with an estimated inhibition in the nanomolar range. Such computational approaches focused on the crystal structures revealed potential inhibitors of Mpro that might exhibit pharmacological activity against SARS-CoV-2. Nevertheless, most of these studies lack the proper validation of the docking protocol. Also, they all ignored the potential use of machine learning to predict affinity.

CONCLUSION:

The combination of structural data with computational approaches opened the possibility to accelerate the search for drugs to treat COVID-19. Several studies used AutoDock4 to search for inhibitors of Mpro. Most of them did not employ a validated docking protocol, which lends support to critics of their computational methodology. Furthermore, one of these studies reported the binding of chloroquine and hydroxychloroquine to Mpro. This study ignores the scientific evidence against the use of these antimalarial drugs to treat COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Protease Inhibitors / Coronavirus 3C Proteases / SARS-CoV-2 Type of study: Prognostic study / Reviews Language: English Journal: Curr Med Chem Journal subject: Chemistry Year: 2021 Document Type: Article Affiliation country: 0929867328666210329094111

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Protease Inhibitors / Coronavirus 3C Proteases / SARS-CoV-2 Type of study: Prognostic study / Reviews Language: English Journal: Curr Med Chem Journal subject: Chemistry Year: 2021 Document Type: Article Affiliation country: 0929867328666210329094111