In-silico study to identify the pathogenic single nucleotide polymorphisms in the coding region of CDKN2A gene

Abstract

Background: CDKN2A, encoding two important tumor suppressor proteins p16 and p14, is a tumor suppressor gene. Mutations in this gene and subsequently the defect in p16 and p14 proteins lead to the downregulation of RB1/p53 and cancer malignancy. To identify the structural and functional effects of mutations, various powerful bioinformatics tools are available. The aim of this study is the identification of high-risk non-synonymous single nucleotide variants in the CDKN2A gene via bioinformatics tools.

Materials and Methods: Among the identified polymorphisms in this gene, 353 missense variants are retrieved from the national center for biotechnology information/single nucleotide polymorphism database (NCBI/dbSNP). Then, the pathogenicity of missense variants are considered using different bioinformatics tools. The stability of these mutant proteins, conservation of amino acids and the secondary and tertiary structural changes are analyzed by bioinformatics tools. After the identification of high-risk mutations, the changes in the hydrophobicity of high-risk amino acid substitutions are considered.

Results: Deleterious single nucleotide polymorphisms (SNPs) were screened step by step using the bioinformatics tools. The results obtained from the set of bioinformatics tools identify high-risk mutations in CDKN2A gene.

Conclusion: 18 high-risk mutations including L16R/Q, G23D/R/S, L32P, N42K, G55D, G67D/R, P81R, H83R, G89D/S, A102E, G101R, G122R, and V126D were identified. According to the previous experimental studies, the association of L16R, G23D/R/S, L32P, G67R, H83R, G89D, G101R, and V126D amino acid substitutions with various cancers has been confirmed.