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利用局部 DNA 序列上下文和规律进行 hTERT 基因中 nsSNP 的计算机筛选

In silico discrimination of nsSNPs in hTERT gene by means of local DNA sequence context and regularity.

机构信息

Medical Biotechnology Division, School of Biosciences and Technology, VIT University, Vellore, 632014, Tamil Nadu, India.

出版信息

J Mol Model. 2013 Sep;19(9):3517-27. doi: 10.1007/s00894-013-1888-7. Epub 2013 May 29.

Abstract

Understanding and predicting the significance of novel genetic variants revealed by DNA sequencing is a major challenge to integrate and interpret in medical genetics with medical practice. Recent studies have afforded significant advances in characterization and predicting the association of single nucleotide polymorphisms in human TERT with various disorders, but the results remain inconclusive. In this context, a comparative study between disease causing and novel mutations in hTERT gene was performed computationally. Out of 59 missense mutations, five variants were predicted to be less stable with the most deleterious effect on hTERT gene by in silico tools, in which two mutations (L584W and M970T) were not previously reported to be involved in any of the human disorders. To get insight into the structural and functional impact due to the mutation, docking study and interaction analysis was performed followed by 6 ns molecular dynamics simulation. These results may provide new perspectives for the targeted drug discovery in the coming future.

摘要

理解和预测 DNA 测序揭示的新型遗传变异的意义,是将其与医学实践相结合并进行解释的主要挑战。最近的研究在表征和预测人类 TERT 单核苷酸多态性与各种疾病的相关性方面取得了重大进展,但结果仍不确定。在这种情况下,对 hTERT 基因中的致病突变和新型突变进行了计算比较研究。在 59 种错义突变中,有 5 种变体通过计算机工具预测为稳定性降低,对 hTERT 基因的破坏性影响最大,其中 2 种突变(L584W 和 M970T)以前没有报道与任何人类疾病有关。为了深入了解突变引起的结构和功能影响,进行了对接研究和相互作用分析,然后进行了 6ns 分子动力学模拟。这些结果可能为未来的靶向药物发现提供新的视角。

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