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一种综合计算框架,用于评估α-L-艾杜糖醛酸酶 IDUA 基因的突变景观。

An Integrated Computational Framework to Assess the Mutational Landscape of α-L-Iduronidase IDUA Gene.

机构信息

Department of Integrative Biology, School of BioSciences and Technology, VIT University, Vellore, Tamil Nadu, 632014, India.

出版信息

J Cell Biochem. 2018 Jan;119(1):555-565. doi: 10.1002/jcb.26214. Epub 2017 Jul 31.

Abstract

Mucopolysaccharidosis type I is a lysosomal genetic disorder caused due to the deficiency of the α-L-iduronidase enzyme (IDUA). Mutations associated with IDUA lead to mild to severe forms of diseases characterized by different clinical features. In the present study, we first performed a comprehensive analysis using various in silico prediction tools to screen and prioritize the missense mutations or nonsynonymous SNPs (nsSNPs) associated with IDUA. Subsequently, statistical analysis was empowered to examine the predictive ability and accuracy of the in silico prediction tool results supporting the disease phenotype ranging from mild to severe. Till date, no study has been carried out in IDUA in analyzing the impact of the nsSNPs at the structural level. In this context with the aid of pathogenic and stability prediction in silico tools, we identified nsSNPs R89Q, R89W, and P533R to be most deleterious and disease-causing having impact on the function of the protein. Extensive molecular dynamics analysis was performed using Gromacs to understand the deleterious nature of the mutants. Variations observed between the trajectory files of native and mutants R89Q, R89W, and P533R using Gromacs utilities enabled us to measure the adverse effects on the protein and could be the underlying reasons for the disease pathogenesis. These findings may be helpful in understanding the genotype-phenotype relationship and molecular basis of the disease to design drugs for better treatment. J. Cell. Biochem. 119: 555-565, 2018. © 2017 Wiley Periodicals, Inc.

摘要

黏多糖贮积症 I 型是一种溶酶体遗传性疾病,由α-L-艾杜糖苷酸酶(IDUA)缺乏引起。与 IDUA 相关的突变导致疾病的轻度至重度形式,其特征是不同的临床特征。在本研究中,我们首先使用各种计算机预测工具进行全面分析,以筛选和优先考虑与 IDUA 相关的错义突变或非同义 SNP(nsSNP)。随后,进行统计分析,以检查计算机预测工具结果对从轻度到重度疾病表型的预测能力和准确性。迄今为止,尚未在 IDUA 中进行分析 nsSNP 在结构水平上对疾病表型的影响的研究。在这种情况下,借助致病和稳定性计算机预测工具,我们确定了 nsSNP R89Q、R89W 和 P533R 是最具破坏性和致病的,对蛋白质的功能有影响。使用 Gromacs 进行了广泛的分子动力学分析,以了解突变体的有害性质。使用 Gromacs 实用程序在天然和突变体 R89Q、R89W 和 P533R 的轨迹文件之间观察到的变化使我们能够测量对蛋白质的不利影响,这可能是疾病发病机制的潜在原因。这些发现可能有助于理解基因型-表型关系和疾病的分子基础,以设计更好的治疗药物。J. Cell. Biochem. 119: 555-565, 2018. © 2017 Wiley Periodicals, Inc.

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