Affiliation:
1. School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
2. School of Bioengineering and Biosciences, Lovely Professional University, Phagwara 144411, India
3. Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, India
Abstract
Background: AKT1 is a serine/threonine kinase necessary for the mediation of apoptosis, angiogenesis, metabolism, and cell proliferation in both normal and cancerous cells. The mutations in the AKT1 gene have been associated with different types of cancer. Further, the AKT1 gene mutations are also reported to be associated with other diseases such as Proteus syndrome and Cowden syndromes. Hence, this study aims to identify the deleterious AKT1 missense SNPs and predict their effect on the function and structure of the AKT1 protein using various computational tools. Methods: Extensive in silico approaches were applied to identify deleterious SNPs of the human AKT1 gene and assessment of their impact on the function and structure of the AKT1 protein. The association of these highly deleterious missense SNPs with different forms of cancers was also analyzed. The in silico approach can help in reducing the cost and time required to identify SNPs associated with diseases. Results: In this study, 12 highly deleterious SNPs were identified which could affect the structure and function of the AKT1 protein. Out of the 12, four SNPs—namely, G157R, G159V, G336D, and H265Y—were predicted to be located at highly conserved residues. G157R could affect the ligand binding to the AKT1 protein. Another highly deleterious SNP, R273Q, was predicted to be associated with liver cancer. Conclusions: This study can be useful for pharmacogenomics, molecular diagnosis of diseases, and developing inhibitors of the AKT1 oncogene.
Subject
Paleontology,Space and Planetary Science,General Biochemistry, Genetics and Molecular Biology,Ecology, Evolution, Behavior and Systematics
Reference80 articles.
1. Genetic Variation, Comparative Genomics, and the Diagnosis of Disease;Eichler;N. Engl. J. Med.,2019
2. Rozario, L.T., Sharker, T., and Nila, T.A. (2021). In Silico Analysis of Deleterious SNPs of Human MTUS1 Gene and Their Impacts on Subsequent Protein Structure and Function. PLoS ONE, 16.
3. Single-Nucleotide Polymorphisms (SNP) Mining and Their Effect on the Tridimensional Protein Structure Prediction in a Set of Immunity-Related Expressed Sequence Tags (EST) in Atlantic Salmon (Salmo Salar);Maisey;Front. Genet.,2020
4. Human Non-Synonymous SNPs: Server and Survey;Ramensky;Nucleic Acids Res.,2002
5. Bioinformatic Tools for Identifying Disease Gene and SNP Candidates;Barnes;Genetic Variation: Methods and Protocols,2010