State Key Laboratory of Chemical Resources Engineering, Beijing University of Chemical Technology, Beijing, 100029, P.R. China.
College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, P.R. China.
Sci Rep. 2024 Nov 20;14(1):28690. doi: 10.1038/s41598-024-78232-6.
Glutathione Peroxidase 1 (GPx1) gene has been reported for its role in cellular redox homeostasis, and the dysregulation of its expression is linked with the progression of diverse cancers. Non-synonymous single nucleotide polymorphism (nsSNPs) have been emerged as the crucial factors, playing their role in GPx1 overexpression. To understand the deleterious mutational effects on the structure and function of GPx1 enzyme, we delved deeper into the exploration of possibly damaging nsSNPs using in-silico based approaches. Eight widely utilized computational tools were employed to roughly shortlist the deleterious nsSNPs. Their damaging effects on structure and function of the genes were evaluated by using different bioinformatics tools. Subsequently, the three final proposed deleterious mutants including mutations rs373838463, rs2107818892, and rs763687242, were docked with their reported binder, TNF receptor-associated factor 2 (TRAF2). The lowest binding affinity and stability of the docked mutant complexes as compared to the wild type GPx1 were validated by molecular dynamic simulation. Finally, the comparison of RMSD, RMSF, RoG and hydrogen bond analyses between wild-type and mutant's complexes validated the deleterious effects of proposed nsSNPs. This study successfully identified and verified the possibly damaging nsSNPs in GPx1 enzyme, which may be linked the progression of various types of cancer. Our findings underscore the value of in-silico approaches in mutational analysis and encourage further preclinical and clinical trials.
谷胱甘肽过氧化物酶 1（GPx1）基因因其在细胞氧化还原稳态中的作用而被报道，其表达的失调与多种癌症的进展有关。非 synonymous 单核苷酸多态性（nsSNPs）已成为关键因素，在 GPx1 过表达中发挥作用。为了了解对 GPx1 酶结构和功能的有害突变影响，我们使用基于计算的方法更深入地探讨了可能具有破坏性的 nsSNPs。使用了八种广泛使用的计算工具来大致筛选出有害的 nsSNPs。使用不同的生物信息学工具评估了它们对基因结构和功能的破坏性影响。随后，根据与报告的结合蛋白 TNF 受体相关因子 2（TRAF2）的对接结果，从三种最终提出的有害突变体中，包括突变 rs373838463、rs2107818892 和 rs763687242 中筛选出三个具有破坏性的突变体。与野生型 GPx1 相比，对接突变体复合物的最低结合亲和力和稳定性通过分子动力学模拟得到验证。最后，通过对 RMSD、RMSF、RoG 和氢键分析的比较，验证了野生型和突变型复合物之间的破坏性影响。这项研究成功地鉴定和验证了 GPx1 酶中可能具有破坏性的 nsSNPs，这可能与各种类型癌症的进展有关。我们的研究结果强调了计算方法在突变分析中的价值，并鼓励进一步进行临床前和临床试验。
