Impact of Mutations in Medical Science: A Focus on ErbB2 Gene

Introduction: Epidermal growth factor receptor family of receptor tyrosine kinases plays important roles in the development and severity of many cancers across human populations. Single-nucleotide polymorphisms (SNPs) play a major role in understanding the genetic basis of many complex human diseases. It is still a major challenge to identify the functional SNPs in a disease-related gene. Purpose: To explore possible relationships between genetic mutation and phenotypic variations of ErbB2 gene. Materials and Methods: In present study, different bioinformatics algorithms such as sorting intolerant from tolerant (SIFT), polymorphism phenotyping (PolyPhen), and I-mutant server to predict the impact of these amino acid substitutions on ErbB2 were employed. Results: SIFT analysis resulted in 9 of 109 non-synonymous SNPs (nsSNPs) were predicted to be “damaging” and “possibly damaging,” “probably damaging” and “benign” by PolyPhen program. I-mutant 3.0 results demonstrated that all respective mutations would decrease the overall stability of the protein. The orthologous multiple alignments of nsSNPs with ids namely rs28933368 (E914K), rs193171026 (L46F), rs149937802 (R34W), rs140980495 (R536Q), and rs144533600 (E1244K) showed that all mutations were found to be either conserved or the flanking amino acids showed a low degree of conservation except rs149937802 (R34W) where a high rate of mutation was observed among orthologs, which needs further investigation. Conclusion: Current analysis represents the application of computational tools in understanding functional variation from the perspective of structure, expression, evolution, and phenotype.