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J Struct Biol . Molecular insights into the binding interactions and energetics of the omicron spike variant with hACE2 and a neutralizing antibody

tetano

Editor, Senior Moderator
J Struct Biol


. 2024 Mar 15:108087.
doi: 10.1016/j.jsb.2024.108087. Online ahead of print. Molecular insights into the binding interactions and energetics of the omicron spike variant with hACE2 and a neutralizing antibody

Vipul Kumar[SUP] 1 [/SUP], Seyad Shefrin[SUP] 2 [/SUP], Durai Sundar[SUP] 3 [/SUP]



Affiliations
Abstract

The global spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) since 2019 has led to a continuous evolution of viral variants, with the latest concern being the Omicron (B.1.1.529) variant. In this study, classical molecular dynamics simulations were conducted to elucidate the biophysical aspects of the Omicron spike protein's receptor-binding domain (RBD) in its interaction with human angiotensin-converting enzyme 2 (hACE2) and a neutralizing antibody, comparing it to the wildtype (WT). To model the Omicron variant, 15 in silico mutations were introduced in the RBD region of WT (retrieved from PDB). The simulations of WT spike-hACE2 and Omicron spike-hACE2 complexes revealed comparable binding stability and dynamics. Notably, the Q493R mutation in the Omicron spike increased interactions with hACE2, particularly with ASP38 and ASP355. Additionally, mutations such as N417K, T478K, and Y505H contributed to enhanced structural stability in the Omicron variant. Conversely, when comparing WT with Omicron in complex with a neutralizing antibody, simulation results demonstrated poorer binding dynamics and stability for the Omicron variant. The E484K mutation significantly decreased binding interactions, resulting in an overall decrease in binding energy (∼-57 kcal/mol) compared to WT (∼-84 kcal/mol). This study provides valuable molecular insights into the heightened infectivity of the Omicron variant, shedding light on the specific mutations influencing its interactions with hACE2 and neutralizing antibodies.

Keywords: Modelled mutants; Molecular dynamics simulation; Receptor binding domain; SARS-CoV2.

 
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