| Autor: |
Senbiao Fang, Chuqi Lei, Meng Li, Yongfan Ming, Liren Liu, Xuming Zhou, Min Li |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 5125-5135 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2001-0370 |
| DOI: |
10.1016/j.csbj.2023.10.030 |
| Popis: |
Background: The emerging mutants of the 2019-nCoV coronavirus are posing unprecedented challenges to the pandemic prevention. A thorough, understanding of the mutational characterization responsible for the pathogenic mechanisms of mutations in 2019-nCoV-Spike is indispensable for developing effective drugs and new vaccines. Methods: We employed computational methods and viral infection assays to examine the interaction pattern and binding affinity between ACE2 and both single- and multi-mutants of the Spike proteins. Results: Using data from the CNCB-NGDC databank and analysis of the 2019-nCoV-Spike/ACE2 interface crystal structure, we identified 31 amino acids that may significantly contribute to viral infectivity. Subsequently, we performed molecular dynamics simulations for 589 single-mutants that emerged from the nonsynonymous substitutions of the aforementioned 31 residues. Ultimately, we discovered 8 single-mutants that exhibited significantly higher binding affinities ( |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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