Dados do Trabalho

Título

IN SILICO APPROACH TO THE ANALYSIS OF HUMAN NME1 GENE SINGLE NUCLEOTIDE POLYMORPHISMS

Introdução

Missense variants of single nucleotide polymorphisms (SNPs) are mutations that can alter protein expression due to a change in the sequence of translated amino acids. Reduced levels of mRNA transcription of the NME1 gene, caused by these mutations, have been identified in highly metastatic cells of sporadic gastric, breast and ovarian cancers. Therefore, online software tools, through in silico analysis, use NME1 gene SNPs to predict the possible polymorphisms that changed the structure and function of proteins, consequently relating them to the possible development of pathologies and malignancies.

Objetivo

Identify whether the presence of NME1 gene variants can cause functional and structural deviations of the encoded proteins through bioinformatics tools with an in-silico systematic approach.

Método

The NME1 gene sequence was obtained from the NCBI dbSNP database. Seven bioinformatics tools available to the public online and systematic in-silico approach were used to predict their impact on protein stability and its pathogenic effect, namely: SIFT, PredictSNP, PolyPhen-1 and PolyPhen-2, MAAP, MuPRO , I- Mutant 2.0 and PROVEAN

Resultado

In total, 4047 SNPs were found in the NME1 gene according to the NCBI dbSNP database. 159 SNPs were categorized missenses (nsSNPs), by different computer biology programs, their probable deleterious effects were predicted, associating them with the predisposition of diseases. Of those, 10 and 7 SNPs were identified, respectively, as deleterious by the SIFT and PolyPhen programs. Additionally, MuPRO showed a decrease in stability for 7 nsSNPs upon mutation and 4 snSNPs probably change the protein structure by PROVEAN. The results of the in silico prediction analysis demonstrate that SNPs rs375550760 (R27H) and rs121917887 (S120G) were considered highly deleterious in 100% of the analyzed tools.

Conclusão

The available bioinformatics tools and the data present in the studied database suggest that two polymorphisms of the NME1 gene cause protein functional and structural deviations, reducing its stability. The presence of these pathogenic variants increases the possibility of changing the regulation of transcription and cell cycle. Therefore, the likelihood of their involvement in predisposing human malignancies increases. This prediction can be analyzed through studies in neoplastic tissues on a wide population base with the purpose of selecting risk markers for tumor development, enabling methods to predict aggressiveness or to diagnose the tumor early.

Palavras-chave

NM23 Nucleoside Diphosphate Kinases; Apoptosis; Polymorphism, Single Nucleotide; Computer Simulation.