Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike RBD and human ACE2

Abstract

The association of the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with human angiotensin-converting enzyme 2 (hACE2) represents the first required step for cellular entry. SARS-CoV-2 has continued to evolve with the emergence of several novel variants, and amino acid changes in the RBD have been implicated with increased fitness and potential for immune evasion. Reliably predicting the effect of amino acid changes on the ability of the RBD to interact more strongly with the hACE2 can help assess the implications for public health and the potential for spillover and adaptation into other animals. Here, we introduce a two-step framework that first relies on 48 independent 4-ns molecular dynamics (MD) trajectories of RBD−hACE2 variants to collect binding energy terms decomposed into Coulombic, covalent, van der Waals, lipophilic, generalized Born solvation, hydrogen bonding, π−π packing, and self-contact correction terms. The second step implements a neural network to classify and quantitatively predict binding affinity changes using the decomposed energy terms as descriptors. The computational base achieves a validation accuracy of 82.8% for classifying single–amino acid substitution variants of the RBD as worsening or improving binding affinity for hACE2 and a correlation coefficient of 0.73 between predicted and experimentally calculated changes in binding affinities. Both metrics are calculated using a fivefold cross-validation test. Our method thus sets up a framework for screening binding affinity changes caused by unknown single– and multiple–amino acid changes offering a valuable tool to predict host adaptation of SARS-CoV-2 variants toward tighter hACE2 binding.

Phage-Displayed Mimotopes of SARS-CoV-2 Spike Protein Targeted to Authentic and Alternative Cellular Receptors

“…These observation are consistent with the hypothesis that the evolution of the virus in the human population can occur not only by escaping immune pressure or increasing the affinity of RBD towards the canonical ACE2 receptor, as commonly assumed [98], but also through adaptation of the virus to alternative receptors and co-receptors of expressed on-host cells. In the retrospective analysis, the discovered cluster of FGFR interacting with SARS-CoV-2 spike amino acids was compared with corresponding amino acids of the These observation are consistent with the hypothesis that the evolution of the virus in the human population can occur not only by escaping immune pressure or increasing the affinity of RBD towards the canonical ACE2 receptor, as commonly assumed [98], but also through adaptation of the virus to alternative receptors and co-receptors of expressed on-host cells. In the retrospective analysis, the discovered cluster of FGFR interacting with SARS-CoV-2 spike amino acids was compared with corresponding amino acids of the SARS-CoV spike.…”

“…Calu-3 cells are sensitive to SARS-CoV-2 infection and, like other human cancer cells, are commonly used for propagation of the SARS-CoV and SARS-CoV-2 viruses in cell culture [30,72,77,[114][115][116][117]. These observation are consistent with the hypothesis that the evolution of the virus in the human population can occur not only by escaping immune pressure and increasing the affinity of RBD to ACE2, as commonly assumed [98], but also through exchanging virus receptors and co-receptors during the adaptation to a new host cell [1,10].…”

The Development of SARS-CoV-2 Variants: The Gene Makes the Disease

“…Close to them within the RBD, K417N, and K417T mutations have been repeatedly described to protect against binding to certain monoclonal antibodies [55]. Nevertheless, both K417N and K417T are expected to moderately decrease ACE2-binding affinity [76,147,148]. The main impact of the K417N mutation seems to be its ability to destabilize the RBD-down conformation (Figure 1B), thereby increasing the propensity of the open configuration [36].…”

Assessing Differential Binding of Aggregation-Induced Emission-Based Luminogens to Host Interacting Surface Proteins of SARS-CoV-2 and Influenza Virus–An in silico Approach

“…For instance, we have shown that one of the aromatic rings of TPE core forms a cation–π interaction with –NH group of Asn501. However, some of the recent SARS-CoV-2 variants have Tyr in place of Asn at this position ( Chen et al, 2021 ; Dejnirattisai et al, 2021 ). Such mutations may affect the quality of TPE binding to the spike protein, which may or may not affect the emission patterns.…”