Opeyemi S Soremekun1, Mahmoud E S Soliman2. 1. Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, 4001, South Africa. 2. Molecular Bio-computation and Drug Design Laboratory, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, 4001, South Africa. Electronic address: soliman@ukzn.ac.za.
Abstract
BACKGROUND: Genetic polymorphisms have been identified as one of the underlying factors in disease pathogenesis and drug resistance since they account for protein dysfunctionality, or in some cases, aberrancy. This explains the high degree of inactivity that characterizes the polymorphic variants of ULBP6 binding protein, which in turn disrupts its primary interaction with human Natural Killer Group 2-member D (NKG2D) and accounts for an impediment to immuno-surveillance. The possible identification of deleterious non-synonymous Single Nucleotide Polymorphisms (nsSNPs) present in the ULBP6 gene is essential for the development of novel gene therapies to prevent the translation of dysfunctional protein variants. METHODS/ RESULTS: In this study, for the first time, we employed an SNP-informatics approach (SNPs retrieval, pathogenic/mutational analysis, phenotypic analysis, and structural analysis) and molecular dynamics techniques to identify and characterize undesirable SNPs coupled with their impact on ULBP6 structural activities relative to dysfunctionality. V52F was predictively pathogenic amongst SNPs studied. Conformational and dynamic studies revealed that in comparison to wildtype ULBP6 (ULBP6wt), pathogenic ULBP6V52F demonstrated considerable structural inactivity, which could, in turn, impede biological protein-protein interactions. Moreover, ULBP6V52F showed relatively limited motions in the conformational space as deduced from estimations of structural stability, fluctuations, and principal components. CONCLUSION: This study provides a workable paradigm for investigating pathological nsSNPS using computational platforms which findings present ULBP6V52F as a novel and attractive immunotherapeutic target in combatting immune-associated disorders.
BACKGROUND: Genetic polymorphisms have been identified as one of the underlying factors in disease pathogenesis and drug resistance since they account for protein dysfunctionality, or in some cases, aberrancy. This explains the high degree of inactivity that characterizes the polymorphic variants of ULBP6 binding protein, which in turn disrupts its primary interaction with humanNatural Killer Group 2-member D (NKG2D) and accounts for an impediment to immuno-surveillance. The possible identification of deleterious non-synonymous Single Nucleotide Polymorphisms (nsSNPs) present in the ULBP6 gene is essential for the development of novel gene therapies to prevent the translation of dysfunctional protein variants. METHODS/ RESULTS: In this study, for the first time, we employed an SNP-informatics approach (SNPs retrieval, pathogenic/mutational analysis, phenotypic analysis, and structural analysis) and molecular dynamics techniques to identify and characterize undesirable SNPs coupled with their impact on ULBP6 structural activities relative to dysfunctionality. V52F was predictively pathogenic amongst SNPs studied. Conformational and dynamic studies revealed that in comparison to wildtype ULBP6 (ULBP6wt), pathogenic ULBP6V52F demonstrated considerable structural inactivity, which could, in turn, impede biological protein-protein interactions. Moreover, ULBP6V52F showed relatively limited motions in the conformational space as deduced from estimations of structural stability, fluctuations, and principal components. CONCLUSION: This study provides a workable paradigm for investigating pathological nsSNPS using computational platforms which findings present ULBP6V52F as a novel and attractive immunotherapeutic target in combatting immune-associated disorders.
Authors: Mary B Ajadi; Opeyemi S Soremekun; Adeniyi T Adewumi; Hezekiel M Kumalo; Mahmoud E S Soliman Journal: Protein J Date: 2021-01-29 Impact factor: 2.371