AUTHOR=Behairy Mohammed Y. , Soltan Mohamed A. , Eldeen Muhammad Alaa , Abdulhakim Jawaher A. , Alnoman Maryam M. , Abdel-Daim Mohamed M. , Otifi Hassan , Al-Qahtani Saleh M. , Zaki Mohamed Samir A. , Alsharif Ghadi , Albogami Sarah , Jafri Ibrahim , Fayad Eman , Darwish Khaled M. , Elhady Sameh S. , Eid Refaat A. 

TITLE=HBD-2 variants and SARS-CoV-2: New insights into inter-individual susceptibility

JOURNAL=Frontiers in Immunology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.1008463

DOI=10.3389/fimmu.2022.1008463

ISSN=1664-3224

ABSTRACT=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 β-defensins (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. 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. The throughout analysis reveals the presence of 3 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 on 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 SNP hBD-2 towards the SARS-CoV-2 spike domain. Differential protein-protein binding profiles for SNP hBD-2 variant in relation to their native form were guided through residue-wise levels and differential conformational orientations being impacted by the above-identified SNPs. This model paves the way for identifying liable patients towards COVID-19 in a way that would guide the personalization of both the diagnostic and management protocols for such disease.