Investigation on the role of nsSNPs in HNPCC genes--a bioinformatics approach

Abstract

Background: A central focus of cancer genetics is the study of mutations that are causally implicated in tumorigenesis. The identification of such causal mutations not only provides insight into cancer biology but also presents anticancer therapeutic targets and diagnostic markers. Missense mutations are nucleotide substitutions that change an amino acid in a protein, the deleterious effects of these mutations are commonly attributed to their impact on primary amino acid sequence and protein structure.

Methods: The method to identify functional SNPs from a pool, containing both functional and neutral SNPs is challenging by experimental protocols. To explore possible relationships between genetic mutation and phenotypic variation, we employed different bioinformatics algorithms like Sorting Intolerant from Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), and PupaSuite to predict the impact of these amino acid substitutions on protein activity of mismatch repair (MMR) genes causing hereditary nonpolyposis colorectal cancer (HNPCC).

Results: SIFT classified 22 of 125 variants (18%) as 'Intolerant." PolyPhen classified 40 of 125 amino acid substitutions (32%) as "Probably or possibly damaging". The PupaSuite predicted the phenotypic effect of SNPs on the structure and function of the affected protein. Based on the PolyPhen scores and availability of three-dimensional structures, structure analysis was carried out with the major mutations that occurred in the native protein coded by MSH2 and MSH6 genes. The amino acid residues in the native and mutant model protein were further analyzed for solvent accessibility and secondary structure to check the stability of the proteins.

Conclusion: Based on this approach, we have shown that four nsSNPs, which were predicted to have functional consequences (MSH2-Y43C, MSH6-Y538S, MSH6-S580L, and MSH6-K854M), were already found to be associated with cancer risk. Our study demonstrates the presence of other deleterious mutations and also endorses with in vivo experimental studies.

Figure 1

Proposed methodology for the functional nonsynonymous coding SNPs analysis.

Figure 2

(A) Native structure of MSH2 gene with 'A' chain of PDB ID 2O8C(orange). (B) Superimposed structure of native tyrosine (orange) with mutant amino acid cysteine (pale green) at 43 position in 2O8C with RMSD 4.30 Å. (C) Superimposed structure of native histidine (orange) with mutant amino acid glutamine (pale green) at 639 position in 2O8C with RMSD 3.93 Å. (D) Superimposed structure of native proline (orange) with mutant amino acid leucine (pale green) at 670 position in 2O8C with RMSD 3.65 Å.

Figure 3

(A) Native structure of MSH6 gene with 'B' chain of PDB ID 2O8C(orange). (B) Superimposed structure of native tyrosine (orange) with mutant amino acid serine (pale green) at 538 position in 2O8C with RMSD 3.52 Å. (C) Superimposed structure of native serine (orange) with mutant amino acid leucine (pale green) at 580 position in 2O8C with RMSD 3.37 Å. (D)Superimposed structure of native lysine (orange) with mutant amino acid methionine (pale green) at 854 position in 2O8C with RMSD 3.30 Å.