SARS-CoV-2 infectivity is largely determined by the virus Spike protein binding to the ACE2 receptor. Meanwhile, marked infection rate differences were reported between populations and individuals. To understand the disease dynamic, we developed a computational approach to study the implications of both SARS-CoV-2 RBD mutations and ACE2 polymorphism on the stability of the virus-receptor complex. We used the 6LZG PDB RBD/ACE2 3D model, the mCSM platform, the LigPlot+ and PyMol software to analyze the data on SARS-CoV-2 mutations and ACE variants retrieved from GISAID and Ensembl/GnomAD repository. We observed that out of 351 RBD point mutations, 83% destabilizes the complex according to free energy (ΔΔG) differences. We also spotted variations in the patterns of polar and hydrophobic interactions between the mutations occurring in 15 out of 18 contact residues. Similarly, comparison of the effect on the complex stability of different ACE2 variants showed that the pattern of molecular interactions and the complex stability varies also according to ACE2 polymorphism. We infer that it is important to consider both ACE2 variants and circulating SARS-CoV-2 RBD mutations to assess the stability of the virus-receptor association and evaluate infectivity. This approach might offers a good molecular ground to mitigate the virus spreading.
In this study, we evaluated the use of a predictive computational approach for SARS-CoV-2 genetic variations analysis in improving the current variant labeling system. First, we reviewed the basis of the system developed by the World Health Organization (WHO) for the labeling of SARS-CoV-2 genetic variants and the derivative adapted by the United States Centers for Disease Control and Prevention (CDC). Both labeling systems are based on the virus’ major attributes. However, we found that the labeling criteria of the SARS-CoV-2 variants derived from these attributes are not accurately defined and are used differently by the two agencies. Consequently, discrepancies exist between the labels given by WHO and the CDC to the same variants. Our observations suggest that giving the variant of concern (VOC) label to a new variant is premature and might not be appropriate. Therefore, we used a comparative computational approach to predict the effects of the mutations on the virus structure and functions of five VOCs. By linking these data to the criteria used by WHO/CDC for variant labeling, we ascertained that a predictive computational comparative approach of the genetic variations is a good way for rapid and more accurate labeling of SARS-CoV-2 variants. We propose to label all emergent variants, variant under monitoring or variant being monitored (VUM/VBM), and to carry out computational predictive studies with thorough comparison to existing variants, upon which more appropriate and informative labels can be attributed. Furthermore, harmonization of the variant labeling system would be globally beneficial to communicate about and fight the COVID-19 pandemic.
We herein report a computational study on the implications of SARS-CoV-2 RBD mutations and the Angiotensin Converting Enzyme 2 (ACE2) receptor genetic variations on the stability of the virus-host association. In silico analysis of the complex between the virus mutated forms and ACE2 isoform 1 showed that out of 351 RBD point mutations, 83% destabilizes the complex, while 17% have mild stabilizing effect. Study of the complex SARS-CoV-2 Wuhan strain RBD region /ACE2 isoform 1, 6LZG PDB 3D model revealed 18 contact residues. Interestingly, mutations occurring in 15 out of these residues show variations in the patterns of polar and hydrophobic interactions as compared to the original complex. Similarly, comparison of the effect on the complex stability of different ACE2 variants showed that the pattern of molecular interactions and the virus-receptor complex stability varies also according to ACE2 polymorphism. This could explain the large inter-individual variation of disease susceptibility and/or severity. The observation of a high variability in the interactions patterns highlights the complexity of the molecular interplay between SARS-CoV-2 and the ACE2 receptor. We infer that it is important to consider both ACE2 genetic variants and SARS-CoV-2 RBD mutations to assess the stability of the virus-receptor association and evaluate the infectivity of circulating SARS-CoV-2. These findings point toward the importance of individuals genetic typing of the circulating viral form as well as the ACE2 receptor. This will offer a good molecular ground to adjust the mitigation efforts for a better control of the virus spreading.
Objective This study aimed to identify novel genetic variants in the CR2 extracellular domain of the epidermal growth factor receptor (EGFR) in healthy individuals and patients with six different types of adenocarcinoma, in Arabian peninsula populations. It also aimed to investigate the effects of these variants on the EGFR structure and their eventual relevance to tumorigenesis. Results We detected seven new EGFR genetic variants in 168 cancer patients and 114 controls. A SNP rs374670788 was more frequent in bladder cancer but not significantly associated to. However, a missense mutation (V550M) was significantly associated to colon, ovary, lung, bladder and thyroid cancer samples (p < 0.05). Three mutations (H590R, E602K and T605T) were found in the heterozygous form only in colon cancer patients. Genomic analysis of the synonymous mutation (G632G) showed that the T/A genotype could be associated to thyroid cancer in Arab patients (p < 0.05). An additional novel SNP rs571064657 was observed in control individuals. Computational analysis of the genetic variants revealed a reduction in the stabilization of the EGFR tethered form for both V550M and the common R521K variant with low energetic state (− ∆∆G). Molecular interactions analysis suggested that these mutations might affect the receptor’s function and promote tumorigenesis.
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