Computational screening of disease associated mutations on NPC1 gene and its structural consequence in Niemann-Pick type-C1

In Silico Tools and Approaches for the Prediction of Functional and Structural Effects of Single-Nucleotide Polymorphisms on Proteins: An Expert Review

Single-nucleotide polymorphisms (SNPs) are single-base variants that contribute to human biological variation and pathogenesis of many human diseases. Among all SNP types, nonsynonymous single-nucleotide polymorphisms (nsSNPs) can alter many structural, biochemical, and functional features of a protein such as folding characteristics, charge distribution, stability, dynamics, and interactions with other proteins/nucleotides. These modifications in the protein structure can lead nsSNPs to be closely associated with many multifactorial diseases such as cancer, diabetes, and neurodegenerative diseases. Predicting structural and functional effects of nsSNPs with experimental approaches can be time-consuming and costly; hence, computational prediction tools and algorithms are being widely and increasingly utilized in biology and medical research. This expert review examines the in silico tools and algorithms for the prediction of functional or structural effects of SNP variants, in addition to the description of the phenotypic effects of nsSNPs on protein structure, association between pathogenicity of variants, and functional or structural features of disease-associated variants. Finally, case studies investigating the functional and structural effects of nsSNPs on selected protein structures are highlighted. We conclude that creating a consistent workflow with a combination of in silico approaches or tools should be considered to increase the performance, accuracy, and precision of the biological and clinical predictions made in silico.

Phenotype Prediction of Pathogenic Nonsynonymous Single Nucleotide Polymorphisms in WFS1

Wolfram syndrome (WS) is a rare, progressive, neurodegenerative disorder that has an autosomal recessive pattern of inheritance. The gene for WS, wolfram syndrome 1 gene (WFS1), is located on human chromosome 4p16.1 and encodes a transmembrane protein. To date, approximately 230 mutations in WFS1 have been confirmed, in which nonsynonymous single nucleotide polymorphisms (nsSNPs) are the most common forms of genetic variation. Nonetheless, there is poor knowledge on the relationship between SNP genotype and phenotype in other nsSNPs of the WFS1 gene. Here, we analysed 395 nsSNPs associated with the WFS1 gene using different computational methods and identified 20 nsSNPs to be potentially pathogenic. Furthermore, to identify the amino acid distributions and significances of pathogenic nsSNPs in the protein of WFS1, its transmembrane domain was constructed by the TMHMM server, which suggested that mutations outside of the TMhelix could have more effects on protein function. The predicted pathogenic mutations for the nsSNPs of the WFS1 gene provide an excellent guide for screening pathogenic mutations.