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, Alaa Eldeen Muhammad
Department of Microbiology and Immunology, Faculty of Pharmacy, University of Sadat City, Sadat City, Egypt.
Department of Microbiology and Immunology, Faculty of Pharmacy, Sinai University, Ismailia, Egypt.
Front Genet. 2022 Aug 16;13:872845. doi: 10.3389/fgene.2022.872845. eCollection 2022.
The gene is a well-known oncogene that acts as a major player in carcinogenesis. Mutations in the gene have been linked to multiple types of human tumors. Therefore, the identification of the most deleterious single nucleotide polymorphisms (SNPs) in the gene is necessary to understand the key factors of tumor pathogenesis and therapy. We aimed to retrieve missense SNPs and analyze them comprehensively using sequence and structure approaches to determine 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 tools, 17 mutations were found to be the most deleterious mutations in . All SNPs except S145L were found to decrease 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. As a consequence, all other 14 mutations were expected to increase the risk of carcinogenesis, with 5 mutations (G13R, G13C, G13V, P34R, and V152F) 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 toward 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 14 mutations could reveal new insights into the pathogenesis and management of different types of tumors.
该基因是一种著名的致癌基因，在致癌过程中起主要作用。该基因的突变与多种类型的人类肿瘤有关。因此，识别该基因中最有害的单核苷酸多态性（SNP）对于了解肿瘤发病机制和治疗的关键因素至关重要。我们旨在检索错义SNP，并使用序列和结构方法对其进行全面分析，以确定可能增加致癌风险的最有害SNP。我们还采用结构生物学方法和对接工具来研究筛选出的SNP的行为。在检索错义SNP并使用六种工具对其进行分析后，发现17个突变是该基因中最有害的突变。除S145L外，所有SNP均被发现会降低稳定性，除R164C外，所有SNP均位于高度保守的残基和重要功能域上。此外，除G60E和S145L外，所有突变对GTP的结合亲和力均较高，这意味着恶性倾向增加。因此，预计所有其他14个突变都会增加致癌风险，其中5个突变（G13R、G13C、G13V、P34R和V152F）的风险最高。通过基于轨迹分析的分子动力学模拟，确保了这些SNP模型的热力学稳定性。与天然NRAS蛋白相比，这些模型对天然底物GTP的自由结合亲和力更高。Gly13 SNP蛋白呈现出一种不同的构象状态，可能有利于核苷酸交换和催化潜力。对所有这14个突变进一步应用实验方法可能会揭示不同类型肿瘤发病机制和治疗的新见解。
