Systematic investigation of predicted effect of nonsynonymous SNPs in human prion protein gene: a molecular modeling and molecular dynamics study.
Systematic investigation of predicted effect of nonsynonymous SNPs in human prion protein gene: a molecular modeling and molecular dynamics study.
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人朊病毒蛋白基因中非同义 SNP 预测效应的系统研究：分子建模和分子动力学研究。
DOI：
10.1080/07391102.2012.763216
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发表时间：
2014
影响因子：
4.4
通讯作者：
Zhi,Degui
中科院分区：
文献类型：
--
作者：
Jahandideh,Samad;Zhi,Degui
人朊蛋白（HuPrP）基因中的非同义突变有助于HuPrPC向HuPrPSc的转化和淀粉样蛋白的形成，其进而导致朊病毒疾病，如家族性Creutzfeldt-Jakob病和Gerstmann-Straussler-Scheinker病。为了更好地理解和预测HuPrP突变的作用，我们开发了以下程序：首先，我们查阅了人类基因组变异数据库和dbSNP数据库，我们回顾了文献，用于检索HuPrP基因的聚集相关nsSNP。接下来，我们使用了三种不同的方法-多态性表型分析（PolyPhen），PANTHER和Auto-Mute -来预测nsSNP对表型的影响。我们将预测结果与实验报告的这些nsSNP的影响进行比较，以评估三种方法的准确性：PolyPhen预测22个nsSNP中的17个为“可能具有破坏性”或“可能具有破坏性”; PANTHER预测22个nsSNP中的8个为“有害”; Auto-Mute预测20个nsSNP中的9个为“疾病”。最后，利用分子建模和分子动力学（MD）模拟方法研究了天然蛋白质对突变模型的结构分析。除了比较预测方法外，我们的结果还显示了我们的程序用于预测破坏性nsSNPs的适用性。我们的研究还阐明了HuPrP基因中聚集相关nsSNPs预测值与分子模拟和MD模拟结果之间的明显关系。总之，该程序将使研究人员能够为广泛的MD模拟选择优秀的候选者，以便破译HuPrP聚集的更多细节。http://proteopedia.org/w/Journal:JBSD:34
Nonsynonymous mutations in the human prion protein (HuPrP) gene contribute to the conversion of HuPrPCto HuPrPScand amyloid formation which in turn leads to prion diseases such as familial Creutzfeldt–Jakob disease and Gerstmann–Straussler–Scheinker disease. In order to better understand and predict the role of HuPrP mutations, we developed the following procedure: first, we consulted the Human Genome Variation database and dbSNP databases, and we reviewed literature for the retrieval of aggregation-related nsSNPs of the HuPrP gene. Next, we used three different methods – Polymorphism Phenotyping (PolyPhen), PANTHER, and Auto-Mute – to predict the effect of nsSNPs on the phenotype. We compared the predictions against experimentally reported effects of these nsSNPs to evaluate the accuracy of the three methods: PolyPhen predicted 17 out of 22 nsSNPs as “probably damaging” or “possibly damaging”; PANTHER predicted 8 out of 22 nsSNPs as “Deleterious”; and Auto-Mute predicted 9 out of 20 nsSNPs as “Disease”. Finally, structural analyses of the native protein against mutated models were investigated using molecular modeling and molecular dynamics (MD) simulation methods. In addition to comparing predictor methods, our results show the applicability of our procedure for the prediction of damaging nsSNPs. Our study also elucidates the obvious relationship between predicted values of aggregation-related nsSNPs in HuPrP gene and molecular modeling and MD simulations results. In conclusion, this procedure would enable researchers to select outstanding candidates for extensive MD simulations in order to decipher more details of HuPrP aggregation.An animated interactive 3D complement (I3DC) is available in Proteopedia at http://proteopedia.org/w/Journal:JBSD:34