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    • SCIENTIFIC PRODUCTION
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    • Dpto. Química Física y Química Inorgánica
    • DEP63 - Artículos de revista
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    • DEP63 - Artículos de revista
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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/80099

    Título
    Computational study on the affinity of potential drugs to SARS-CoV-2 main protease
    Autor
    Martín, Verónica
    Sanz-Novo, Miguel
    León, Iker
    Redondo, Pilar
    Largo, Antonio
    Barrientos, Carmen
    Año del Documento
    2022
    Documento Fuente
    Journal of Physics-Condensed Matter, 2022, 34, 294005(13pp)
    Abstract
    Herein, we report a computational investigation of the binding affinity of dexamethasone, betamethasone, chloroquine and hydroxychloroquine to SARS-CoV-2 main protease using molecular and quantum mechanics as well as molecular docking methodologies. We aim to provide information on the anti-COVID-19 mechanism of the abovementioned potential drugs against SARS-CoV-2 coronavirus. Hence, the 6w63 structure of the SARS-CoV-2 main protease was selected as potential target site for the docking analysis. The study includes an initial conformational analysis of dexamethasone, betamethasone, chloroquine and hydroxychloroquine. For the most stable conformers, a spectroscopic analysis has been carried out. In addition, global and local reactivity indexes have been calculated to predict the chemical reactivity of these molecules. The molecular docking results indicate that dexamethasone and betamethasone have a higher affinity than chloroquine and hydroxychloroquine for their theoretical 6w63 target. Additionally, dexamethasone and betamethasone show a hydrogen bond with the His41 residue of the 6w63 protein, while the interaction between chloroquine and hydroxychloroquine with this amino acid is weak. Thus, we confirm the importance of His41 amino acid as a target to inhibit the SARS-CoV-2 Mpro activity.
    ISSN
    0953-8984
    Revisión por pares
    SI
    DOI
    10.1088/1361-648X/ac6c6c
    Patrocinador
    Ministerio de Ciencia e Innovación (referencia: PID2020-117742GB-I00)
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/80099
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
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    • DEP63 - Artículos de revista [354]
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