Computational Analysis of Deleterious SNPs in NRAS to Assess Their Potential Correlation With Carcinogenesis - Behairy, Mohammed Y.; Soltan, Mohamed A.; Adam, Mohamed S.; Refaat, Ahmed M.; Ezz, Ehab M.; Albogami, Sarah; Fayad, Eman; Althobaiti, Fayez; Gouda, Ahmed M.; Sileem, Ashraf E.; Elfaky, Mahmoud A.; Darwish, Khaled M.; et al. (Frontiers in Genetics, 2022)
NRAS gene is a well-known oncogene that acts as a major player in carcinogenesis. Mutations in the NRAS gene were linked to multiple types of human tumors. Therefore, the identification of the most deleterious SNPs in NRAS gene has become a necessity to understand the key factors of tumor pathogenesis and therapy. We aimed to retrieve NRAS missense SNPs and analyze them comprehensively using sequence and structure approaches to find the most deleterious SNPs that could increase the risk of carcinogenesis. We also adopted structural biology methods and docking tools to investigate the behavior of the filtered SNPs. After retrieving missense SNPs and analyzing them using six in silico tools, seventeen mutations were found to be the most deleterious mutations in NRAS. All SNPs except S145L were found to decrease NRAS stability and all SNPs were found on highly conserved residues and important functional domains except R164C. In addition, all mutations except G60E and S145L showed a higher binding affinity to GTP, implicating an increase in malignancy tendency. Consequently, all other fourteen mutations were expected to increase the risk of carcinogenesis with the presence of five mutations (G13R, G13C, G13V, P34R, and V152F) that are expected to have the highest risk. Thermodynamic stability was ensured for these SNP models through molecular dynamics simulation based on trajectory analysis. Free-binding affinity towards the natural substrate, GTP, was higher for these models as compared to the native NRAS protein. The Gly13 SNP proteins depict a differential conformational state that could favor nucleotide exchange and catalytic potentiality. A further application of experimental methods with all these fourteen mutations could reveal new insights into the pathogenesis and the management of different types of tumors.