Bioinformatic Characterization of the Functional and Structural Effect of Single Nucleotide Mutations in Patients with High-Grade Glioma.

Gliomas are neoplasms of the central nervous system that originate in glial cells. The genetic characteristics of this type of neoplasm are the loss of function of tumor suppressor genes such as and somatic mutations in genes such as . Additionally, in clinical cases, de novo single nucleotide polymorphisms (SNP) are reported, of which their pathogenicity and their effects on the function and stability of the protein are known. Non-synonymous SNPs were analyzed for their structural and functional effect on proteins using a set of bioinformatics tools such as SIFT, PolyPhen-2, PhD-SNP, I-Mutant 3.0, MUpro, and mutation3D. A structural comparison between normal and mutated residues for disease-associated coding SNPs was performed using TM-aling and the SWISS MODEL. A total of 13 SNPs were obtained for the gene, 1 SNP for , and 1 for , which would be functionally detrimental and associated with disease. Additionally, these changes compromise the structure and function of the protein; the A161S SNP for that has not been reported in any databases was classified as detrimental. All non-synonymous SNPs reported for were in the region of the deoxyribonucleic acid (DNA) binding domain and had a great impact on the function and stability of the protein. In addition, the two polymorphisms detected in and genes compromise the structure and activity of the protein. Both genes are related to the development of high-grade gliomas. All the data obtained in this study must be validated through experimental approaches.