In-silico investigation of systematic missense mutations of middle east respiratory coronavirus spike protein

Abstract

Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe pneumonia-like symptoms and is still pose a significant threat to global public health. A key component in the virulence of MERS-CoV is the Spike (S) protein, which binds with the host membrane receptor dipeptidyl peptidase 4 (DPP4). The goal of the present investigation is to examine the effects of missense mutations in the MERS-CoV S protein on protein stability and binding affinity with DPP4 to provide insight that is useful in developing vaccines to prevent coronavirus infection. We utilized a saturation mutagenesis approach to simulate all possible mutations in the MERS-CoV full-length S, S Receptor Binding Domain (RBD) and DPP4. We found the mutations in MERS-CoV S protein residues, G552, C503, C526, N468, G570, S532, S451, S419, S465, and S435, affect protein stability. We identified key residues, G538, E513, V555, S557, L506, L507, R511, M452, D537, and S454 in the S protein RBD region are important in the binding of MERS-CoV S protein to the DPP4 receptor. We investigated the effects of MERS-CoV S protein viral mutations on protein stability and binding affinity. In addition, we studied all DPP4 mutations and found the functional substitution R336T weakens both DPP4 protein stability and S-DPP4 binding affinity. We compared the S protein structures of MERS-CoV, SARS-CoV, and SARS-CoV-2 viruses and identified the residues like C526, C383, and N468 located in equivalent positions of these viruses have effects on S protein structure. These findings provide further information on how mutations in coronavirus S proteins effect protein function.

Keywords: MERS-CoV; S-DPP4 binding affinity; SARS-CoV-2; computational saturation mutagenesis; protein stability; spike missense mutations.

FIGURE 1

Stability heatmaps of the full-length (A) and the receptor-binding domain (B) MERS-CoV S protein. The pie charts represent the distribution of predictions of free folding energy following mutagenesis of the (C) full-length MERS-CoV S protein and the (D) receptor-binding domain (RBD) of the MERS-CoV S protein.

FIGURE 2

Structure of the RBD regions of SARS-CoV-2, SARS-CoV, and MERS-CoV S proteins (A). The percentages of highly destabilizing, moderately destabilizing, neutral, and moderately stabilizing mutations found within the core and external core subdomains are depicted in (B).

FIGURE 3

Top mutations in the MERS-CoV S RBD. (A) Illustrates the top mutations in the MERS-CoV S RBD, which is shown in complex with the DPP4 receptor. (B) Depicts the energy landscape of the MERS-CoV S protein and top mutations in the MERS-CoV. The line graph depicts the mean ΔΔG, with red lines indicating destabilization and blue lines indicating stabilization. The bubbles indicate the predicted ΔΔG of alanine mutations. The MERS-CoV S protein heatmap is shown beneath the line graph. The stability heatmap is directly beneath the line graph. The bottom of panel B displays the top positions with respect to mean stabilization and destabilization.

FIGURE 4

(A) Percentages of ΔΔΔG values that represent increased or decreased binding affinity in the MERS-CoV S RBD. (B) The energy landscape with respect to binding affinity. The affinity heatmap is depicted below. And the chart at the bottom displays the ΔΔΔG values for the top stabilizing and destabilizing residues. (C) Picture displays the position in the MERS-CoV S RBD with respect to binding affinity.

FIGURE 5

Charts of the predicted ΔΔΔG of residues predicted to interact within the interface of the MERS-CoV S protein and the DPP4 receptor. The lines indicate which residues are predicted to contact another in the two proteins.

FIGURE 6

Stability and binding affinity of positions associated with reports of viral variants obtained from ViPR, displayed in pie charts (A) and in heatmaps (B).

FIGURE 7

(A) Illustration of the MERS-CoV S protein and DPP4 interface with the K267 and A291 residues displayed. (B) The binding affinity heatmap and ΔΔΔG values for mutations generated in each position investigated by Kleine et al. (2020).

FIGURE 8

(A) Shows the R336T mutation in the interface of the MERS-CoV S RBD and the DPP4 receptor. The identity matrix for the hamster, mouse, and human DPP4 receptors. (B) The sequence logo for human, mouse, and hamster is displayed for the sequence surrounding the R336T mutation. (C) Is a heatmap showing the ΔΔG and ΔΔΔG values for mutations generated in the position of the R336 residue.