Computational Exploration of Single-Nucleotide Polymorphisms in the Human hRAS Gene: Implications and Insights

Abstract

Background

A group of genes called oncogenes includes the Harvey rat sarcoma virus ( hRAS) gene. Along with hRAS, Kirsten rat sarcoma viral oncogene homolog ( kRAS) and neuroblastoma RAS viral oncogene homolog ( nRAS) genes belong to the Rat sarcoma (Ras) family of oncogenes. These three genes result in Rho guanosine triphosphate hydrolases (GTPases) as their protein product. Instructions for producing the protein hRAS, which is mainly involved in controlling cell division, are provided by the hRAS gene. The hRAS protein transfers signals from outside through a process called signal transduction. Because the hRAS protein is a GTPase, it changes the chemical guanosine-5'-triphosphate (GTP) into guanosine diphosphate (GDP). GTP and GDP molecules operate as switches to turn on and off the hRAS. This study aimed to anticipate the structure and stability of the protein resulting from missense single-nucleotide polymorphisms (SNPs) in the human hRAS genes.

Methodology

To investigate the possible negative effects associated with these SNPs, bioinformatic analysis is typically essential. The following tools were employed for forecasting harmful SNPs: Scale-Invariant Feature Transform (SIFT), Protein Analysis Through Evolutionary Relationships (PANTHER), non-synonymous SNP by Protein Variation Effect Analyzer (PROVEAN), and non-synonymous SNP by Single Nucleotide Polymorphism Annotation Platform (SNAP).

Results

The present study identified a total of 11 SNPs using the SIFT approach, which were shown to have functional significance. Only two of these 11 SNPs were determined to be tolerable, whereas nine were shown to be detrimental. Among the 11 SNPs analyzed, seven (Q61H, Q99H, K117R, A121D, A146V, R169W, R169Q) were classified as possibly damaging,and four (G13V, Q22K, Q61K, Q13V) were categorized as probably benign according to the predictions made by PANTHER tools. Therefore, the seven SNPs were identified as high-risk SNPs.

Conclusions

Given that SNPs have the potential to be candidates for cellular alterations brought on by mutations that are associated with cancer, this study provides vital information about how SNPs might be utilized as a diagnostic marker for cancer.