In silico analysis of non-synonymous single nucleotide polymorphism in a human KLK-2 gene associated with prostate cancer

Background: nsSNPs lead to amino acid substitution and potentially affect the structure, function, stability, and biochemical properties of proteins. In this study, we investigated the phenotypic effects of nsSNPs on the KLK2 gene using in silico tools. Materials and methods: We analyzed nsSNP variants and their stability using SIFT, PolyPhen-2, PROVEAN and MUpro, I-Mutant2.0 tools. Bioinformatics prediction tools including SNAP, SNAP&GO, SNPeffect 4.0, ProtParam, and PredictProtein were also used in this study. Results: Of the total 196 nsSNPs analyzed, 47 were considered to be damaging as predicted by SIFT, PolyPhen-2, and PROVEAN. Besides, three point mutations (M1T, M1R, and L6P)in signal peptide encoding KLK-2 gene, and one point mutation (H65Y)in active site were deleterious. Analysis by MUpro and I-Mutant2.0 demonstrated that M1T leads to decreased stability, whereas L6P results in increased stability. SNAP and SNAP&GO predicted only M1T as neutral, but the substitution of H65Y by both servers was predicted effect and disease, respectively. ProtParam classified the KLK2 variants as unstable proteins. SNPeffect predicted three SNPs (R250W, V18 L, and D225A)one of which did not affect the aggregation-prone regions, amyloid-forming regions, and chaperone binding site. Conclusion: Function, stability and biochemical properties of hk2 might be affected by different nsSNPs. © 2019 Elsevier B.V