Evolution- and structure-based computational strategy reveals the impact of deleterious missense mutations on MODY 2 (maturity-onset diabetes of the young, type 2).
Evolution- and structure-based computational strategy reveals the impact of deleterious missense mutations on MODY 2 (maturity-onset diabetes of the young, type 2).
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作者：
George DC;Chakraborty C;Haneef SA;Nagasundaram N;Chen L;Zhu H
中枢糖酵解酶葡萄糖激酶（GCK）的杂合突变可导致常染色体显性遗传疾病，即年轻人2型成熟型糖尿病（MODY 2）。MODY 2的特点是早期发病：它通常出现在25岁之前，并表现为轻度的高血糖症。近年来，已知GCK突变的数量显著增加。因此，解释哪些突变导致疾病或赋予对疾病的易感性并表征这些有害突变在大规模分析中可能是一项艰巨的任务，并且在使用结构视角时可能是不可能的。实验分析的费力和耗时的性质使我们试图开发一种基于蛋白质生物物理学基础的糖尿病研究的具有成本效益的计算管道，并促进我们对表型效应和进化过程之间关系的理解。在这项研究中，我们通过使用广泛的基于进化和结构的计算方法，如SIFT，PolyPhen2，PhD-SNP，SNAP，SNPs & GO，fathmm和Align GVGD，研究GCK基因中的错义突变。基于使用这些方法获得的计算预测分数，三个突变，即E70K，A188T和W257R，根据它们对蛋白质结构和功能的影响被鉴定为高度有害的。使用进化保守预测器Consurf和Scorecons，我们进一步证明了大多数预测的有害突变，包括E70K，A188T和W257R，发生在GCK的高度保守区域。使用PoPMusic 2.1、I-mutant 3.0和Dmutant计算突变对蛋白质稳定性的影响。我们还通过计算机模拟进行了分子动力学（MD）模拟分析，以研究天然蛋白质和突变蛋白质之间的构象差异，并发现所识别的有害突变改变了蛋白质的稳定性，灵活性和溶剂可及表面积。此外，每个SNP在GCK中的功能作用使用SNP效应4.0、F-SNP和FASTSNP进行鉴定和表征。我们希望观察到的结果有助于识别影响蛋白质结构和功能的疾病相关突变。我们的计算机模拟研究结果从基于进化的结构中心的角度为GCK突变在MODY2中的作用提供了一个新的视角。本文描述的计算架构可用于预测大基因组测序项目最合适的疾病表型，并为糖尿病等复杂疾病提供个性化药物治疗。
Heterozygous mutations in the central glycolytic enzyme glucokinase (GCK) can result in an autosomal dominant inherited disease, namely maturity-onset diabetes of the young, type 2 (MODY 2). MODY 2 is characterised by early onset: it usually appears before 25 years of age and presents as a mild form of hyperglycaemia. In recent years, the number of known GCK mutations has markedly increased. As a result, interpreting which mutations cause a disease or confer susceptibility to a disease and characterising these deleterious mutations can be a difficult task in large-scale analyses and may be impossible when using a structural perspective. The laborious and time-consuming nature of the experimental analysis led us to attempt to develop a cost-effective computational pipeline for diabetic research that is based on the fundamentals of protein biophysics and that facilitates our understanding of the relationship between phenotypic effects and evolutionary processes. In this study, we investigate missense mutations in the GCK gene by using a wide array of evolution- and structure-based computational methods, such as SIFT, PolyPhen2, PhD-SNP, SNAP, SNPs&GO, fathmm, and Align GVGD. Based on the computational prediction scores obtained using these methods, three mutations, namely E70K, A188T, and W257R, were identified as highly deleterious on the basis of their effects on protein structure and function. Using the evolutionary conservation predictors Consurf and Scorecons, we further demonstrated that most of the predicted deleterious mutations, including E70K, A188T, and W257R, occur in highly conserved regions of GCK. The effects of the mutations on protein stability were computed using PoPMusic 2.1, I-mutant 3.0, and Dmutant. We also conducted molecular dynamics (MD) simulation analysis through in silico modelling to investigate the conformational differences between the native and the mutant proteins and found that the identified deleterious mutations alter the stability, flexibility, and solvent-accessible surface area of the protein. Furthermore, the functional role of each SNP in GCK was identified and characterised using SNPeffect 4.0, F-SNP, and FASTSNP. We hope that the observed results aid in the identification of disease-associated mutations that affect protein structure and function. Our in silico findings provide a new perspective on the role of GCK mutations in MODY2 from an evolution-based structure-centric point of view. The computational architecture described in this paper can be used to predict the most appropriate disease phenotypes for large-genome sequencing projects and to provide individualised drug therapy for complex diseases such as diabetes.