Computational Analysis of nsSNPs of ADA Gene in Severe Combined Immunodeficiency Using Molecular Modeling and Dynamics Simulation - Soukaina Essadssi; Al Mehdi Krami; Lamiae Elkhattabi; Zouhair Elkarhat; Ghita Amalou; Houria Abdelghaffar; Hassan Rouba; Abdelhamid Barakat (Journal of Immunology Research)
Severe combined immunodeficiency (SCID) is the most severe form of primary immunodeficiency (PID), characterized by fatal opportunistic infections. The ADA gene encodes adenosine deaminase, an enzyme that catalyzes the irreversible deamination of adenosine and deoxyadenosine in the catabolic pathway of purine. Mutations of the ADA gene have been identified in patients with severe combined immunodeficiency. In this study, we performed a bioinformatics analysis of the human ADA gene to identify potentially harmful nonsynonymous SNPs and their effect on protein structure and stability. Using eleven prediction tools, we identified 15 nsSNPs (H15D, H15P, H17Q, H17Y, D19N, T26I, G140E, C153F, A183D, G216R, H258Y, C262Y, S291L, S291W, and K34OE) as harmful. The results of ConSurf’s analysis revealed that all these nsSNPs are localised in the highly conserved positions and affect the structure of the native proteins. In addition, our computational analysis showed that the H15D, G140E, G216R, and S291L mutations identified as being associated with severe combined immunodeficiency affect protein structure. Similarly, the results of the analyses of Rmsd, Rmsf, and Rg showed that all these factors influence protein stability, flexibility, and compaction with different levels of impact. This study is the first comprehensive computational analysis of nsSNPs of the ADA gene. However, functional analyses are needed to elucidate the biological mechanisms of these polymorphisms in severe combined immunodeficiency.