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HBD-2 variants and SARS-CoV-2: New insights into inter-individual susceptibility
BACKGROUND: A deep understanding of the causes of liability to SARS-CoV-2 is essential to develop new diagnostic tests and therapeutics against this serious virus in order to overcome this pandemic completely. In the light of the discovered role of antimicrobial peptides [such as human b-defensin-2...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780532/ https://www.ncbi.nlm.nih.gov/pubmed/36569842 http://dx.doi.org/10.3389/fimmu.2022.1008463 |
Sumario: | BACKGROUND: A deep understanding of the causes of liability to SARS-CoV-2 is essential to develop new diagnostic tests and therapeutics against this serious virus in order to overcome this pandemic completely. In the light of the discovered role of antimicrobial peptides [such as human b-defensin-2 (hBD-2) and cathelicidin LL-37] in the defense against SARS-CoV-2, it became important to identify the damaging missense mutations in the genes of these molecules and study their role in the pathogenesis of COVID-19. METHODS: We conducted a comprehensive analysis with multiple in silico approaches to identify the damaging missense SNPs for hBD-2 and LL-37; moreover, we applied docking methods and molecular dynamics analysis to study the impact of the filtered mutations. RESULTS: The comprehensive analysis reveals the presence of three damaging SNPs in hBD-2; these SNPs were predicted to decrease the stability of hBD-2 with a damaging impact on hBD-2 structure as well. G51D and C53G mutations were located in highly conserved positions and were associated with differences in the secondary structures of hBD-2. Docking-coupled molecular dynamics simulation analysis revealed compromised binding affinity for hBD-2 SNPs towards the SARS-CoV-2 spike domain. Different protein–protein binding profiles for hBD-2 SNPs, in relation to their native form, were guided through residue-wise levels and differential adopted conformation/orientation. CONCLUSIONS: The presented model paves the way for identifying patients prone to COVID-19 in a way that would guide the personalization of both the diagnostic and management protocols for this serious disease. |
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