| Download | - View accepted manuscript: Modeling the interaction of SARS-CoV-2 binding to the ACE2 receptor via molecular theory of solvation (PDF, 2.4 MiB)
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| DOI | Resolve DOI: https://doi.org/10.1039/D1NJ02015C |
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| Author | Search for: Kobryn, Alexander E.1; Search for: Maruyama, Yutaka; Search for: Velázquez-Martínez, Carlos A.; Search for: Yoshida, NorioORCID identifier: https://orcid.org/0000-0002-2023-7254; Search for: Gusarov, Sergey1ORCID identifier: https://orcid.org/0000-0003-2033-705X |
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| Affiliation | - National Research Council Canada. Nanotechnology
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| Format | Text, Article |
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| Abstract | 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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| Publication date | 2021-07-20 |
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| Publisher | Royal Society of Chemistry |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NRC number | NRC-NANO-134 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 358edb87-168d-4c46-b833-e5015e314a27 |
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| Record created | 2021-09-03 |
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| Record modified | 2021-09-08 |
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