Abstract
To date, more than 263 million people have been infected with SARS-CoV-2 during the COVID-19 pandemic. In many countries, the global spread occurred in multiple pandemic waves characterized by the emergence of new SARS-CoV-2 variants. Here we report a sequence and structural-bioinformatics analysis to estimate the effects of amino acid substitutions on the affinity of the SARS-CoV-2 spike receptor binding domain (RBD) to the human receptor hACE2. This is done through qualitative electrostatics and hydrophobicity analysis as well as molecular dynamics simulations used to develop a high-precision empirical scoring function (ESF) closely related to the linear interaction energy method and calibrated on a large set of experimental binding energies. For the latest variant of concern (VOC), B.1.1.529 Omicron, our Halo difference point cloud studies reveal the largest impact on the RBD binding interface compared to all other VOC. Moreover, according to our ESF model, Omicron achieves a much higher ACE2 binding affinity than the wild type and, in particular, the highest among all VOCs except Alpha and thus requires special attention and monitoring.
【초록키워드】 pandemic, VoC, COVID-19 pandemic, variant, molecular dynamics, omicron, molecular dynamics simulations, variants, binding affinity, Molecular dynamics simulation, Receptor binding domain, Spread, SARS-CoV-2 variants, RBD, hydrophobicity, Alpha, B.1.1.529, Bioinformatics analysis, wild type, affinity, binding, Amino acid, Interaction, Analysis, ACE2 binding, amino acid substitutions, sequence, amino acid substitution, Effect, receptor hACE2, new SARS-CoV-2, Halo, highest, develop, occurred, linear, characterized, the RBD, much higher, calibrated, infected with SARS-CoV-2, the SARS-CoV-2, 【제목키워드】 SARS-CoV-2 variant, RBD, B.1.1.529, hACE2 receptor, reveal,