Department of Bioinformatics and Computational Biology, George Mason University, Fairfax, VA 22030, USA.
Clinical Biochemistry and Translational Medicine Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka 1000, Bangladesh.
Biomolecules. 2021 Nov 20;11(11):1733. doi: 10.3390/biom11111733.
Single nucleotide polymorphisms (SNPs) help to understand the phenotypic variations in humans. Genome-wide association studies (GWAS) have identified SNPs located in the tumor protein 63 (TP63) locus to be associated with the genetic susceptibility of cancers. However, there is a lack of in-depth characterization of the structural and functional impacts of the SNPs located at the gene. The current study was designed for the comprehensive characterization of the coding and non-coding SNPs in the human gene for their functional and structural significance. The functional and structural effects of the SNPs were investigated using a wide variety of computational tools and approaches, including molecular dynamics (MD) simulation. The deleterious impact of eight nonsynonymous SNPs (nsSNPs) affecting protein stability, structure, and functions was measured by using 13 bioinformatics tools. These eight nsSNPs are in highly conserved positions in protein and were predicted to decrease protein stability and have a deleterious impact on the TP63 protein function. Molecular docking analysis showed five nsSNPs to reduce the binding affinity of TP63 protein to DNA with significant results for three SNPs (R319H, G349E, and C347F). Further, MD simulations revealed the possible disruption of TP63 and DNA binding, hampering the essential protein function. PolymiRTS study found five non-coding SNPs in miRNA binding sites, and the GTEx portal recognized five eQTLs SNPs in single tissue of the lung, heart (LV), and cerebral hemisphere (brain). Characterized nsSNPs and non-coding SNPs will help researchers to focus on gene loci and ascertain their association with certain diseases.
单核苷酸多态性（SNPs）有助于理解人类的表型变异。全基因组关联研究（GWAS）已经确定了位于肿瘤蛋白 63（TP63）基因座的 SNPs 与癌症的遗传易感性有关。然而，位于基因的 SNPs 的结构和功能影响还缺乏深入的特征描述。本研究旨在全面描述人类基因中的编码和非编码 SNPs，以研究它们的功能和结构意义。利用多种计算工具和方法，包括分子动力学（MD）模拟，研究了 SNPs 的功能和结构效应。使用 13 种生物信息学工具测量了影响蛋白质稳定性、结构和功能的 8 个非同义 SNPs（nsSNPs）的有害影响。这 8 个 nsSNPs 位于蛋白质高度保守的位置，预测会降低蛋白质稳定性，并对 TP63 蛋白质功能产生有害影响。分子对接分析表明，有 5 个 nsSNPs 降低了 TP63 蛋白与 DNA 的结合亲和力，其中 3 个 SNPs（R319H、G349E 和 C347F）的结果具有统计学意义。此外，MD 模拟显示，TP63 和 DNA 结合可能被破坏，从而阻碍了重要的蛋白质功能。PolymiRTS 研究发现了 miRNA 结合位点的 5 个非编码 SNPs，GTEx 门户在肺、心脏（LV）和大脑半球（脑）的单个组织中识别出 5 个 eQTLs SNPs。特征化的 nsSNPs 和非编码 SNPs 将帮助研究人员关注基因座，并确定它们与某些疾病的关联。
