Pathogenic genetic variants from highly connected cancer susceptibility genes confer the loss of structural stability

• Published in: Scientific reports Vol. 11; no. 1; p. 19264
• Main Authors: Reza, Mahjerin Nasrin, Ferdous, Nadim, Emon, Md. Tabassum Hossain, Islam, Md. Shariful, Mohiuddin, A. K. M., Hossain, Mohammad Uzzal
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 28-09-2021; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114; 631/67; Algorithms; Ataxia Telangiectasia Mutated Proteins - genetics; BRCA1 protein; BRCA1 Protein - genetics; Breast cancer; Cancer; Computer applications; Conserved Sequence - genetics; DNA damage; DNA repair; Gene polymorphism; Genes, BRCA1; Genes, Neoplasm - genetics; Genes, p53 - genetics; Genetic diversity; Genetic Predisposition to Disease - genetics; Genetic variance; Humanities and Social Sciences; Humans; miRNA; Molecular dynamics; Molecular Dynamics Simulation; multidisciplinary; Neoplasms - genetics; p53 Protein; Polymorphism, Single Nucleotide - genetics; Precision medicine; Protein Stability; Protein Structure, Tertiary - genetics; Science; Science (multidisciplinary); Single-nucleotide polymorphism; Structure-function relationships; Tumor suppressor genes; Tumor Suppressor Protein p53 - genetics
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-98547-y

Genetic polymorphisms in DNA damage repair and tumor suppressor genes have been associated with increasing the risk of several types of cancer. Analyses of putative functional single nucleotide polymorphisms (SNP) in such genes can greatly improve human health by guiding choice of therapeutics. In this study, we selected nine genes responsible for various cancer types for gene enrichment analysis and found that BRCA1, ATM, and TP53 were more enriched in connectivity. Therefore, we used different computational algorithms to classify the nonsynonymous SNPs which are deleterious to the structure and/or function of these three proteins. The present study showed that the major pathogenic variants (V1687G and V1736G of BRCA1, I2865T and V2906A of ATM, V216G and L194H of TP53) might have a greater impact on the destabilization of the proteins. To stabilize the high-risk SNPs, we performed mutation site-specific molecular docking analysis and validated using molecular dynamics (MD) simulation and molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) studies. Additionally, SNPs of untranslated regions of these genes affecting miRNA binding were characterized. Hence, this study will assist in developing precision medicines for cancer types related to these polymorphisms.