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| DOI | Trouver le DOI : https://doi.org/10.1039/D1NJ02015C |
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| Auteur | Rechercher : Kobryn, Alexander E.1; Rechercher : Maruyama, Yutaka; Rechercher : Velázquez-Martínez, Carlos A.; Rechercher : Yoshida, NorioIdentifiant ORCID : https://orcid.org/0000-0002-2023-7254; Rechercher : Gusarov, Sergey1Identifiant ORCID : https://orcid.org/0000-0003-2033-705X |
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| Affiliation | - Conseil national de recherches Canada. Nanotechnologie
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| Format | Texte, Article |
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| Résumé | The angiotensin-converting enzyme 2 (ACE2) protein is a cell gate receptor for the SARS-CoV-2 virus, responsible for the development of symptoms associated with the Covid-19 disease. Pharmacological inhibition of the SARS-CoV-2 spike receptor binding domain (RBD) and ACE2 interaction is one of the most attractive ways to prevent viral replication in human cells. Unfortunately, at this stage there is no complete picture of this process and so the computational modelling might provide an important insight valuable for the development of new and efficient inhibitors. In this work we propose the use of the molecular theory of solvation to study the nanomorphology of the spike–ACE2 binding formed by a complex solvent (water, ions, and dissolved drug-like molecules) and leading to the viral protein with cell membrane receptors. In contrast to the typical molecular dynamics, the statistical–mechanical theory of solvation directly provides distributions of complex solvents around the binding location as well as the thermodynamics of solvation. We present an example of the application of the three-dimensional theory of solvation to model the nanomorphology formed by solvent environment around binding surfaces of interacting proteins. The results of our calculations are compared with the other published data. Our recent developments allow the application of the methodology to be extended to potential drug screening and virulence analysis. |
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| Date de publication | 2021-07-20 |
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| Maison d’édition | Royal Society of Chemistry |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Numéro du CNRC | NRC-NANO-134 |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | 358edb87-168d-4c46-b833-e5015e314a27 |
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| Enregistrement créé | 2021-09-03 |
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| Enregistrement modifié | 2021-09-08 |
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