首页> 外文会议>Pacific Symposium on Biocomputing 2006 >MODELING AND ANALYZING THREE-DIMENSIONAL STRUCTURES OF HUMAN DISEASE PROTEINS
【24h】

MODELING AND ANALYZING THREE-DIMENSIONAL STRUCTURES OF HUMAN DISEASE PROTEINS

机译:人类疾病蛋白质三维结构的建模与分析

获取原文
获取原文并翻译 | 示例

摘要

Three-dimensional structures of proteins, experimental or predicted, show us how these molecular machines actually work. With the help of information on disease-related mutations, they can also show us how they malfunction in diseases. Such understanding, currently lacking for most human diseases, is an important first step before designing drugs or therapies to cure specific diseases. Here we used homology modeling to model human disease-related proteins, and studied structural characteristics of disease related mutations and compared them with non synonymous SNPs. 1484 domains from 874 proteins were modeled, and together with experimentally determined structures of 369 domains they provided the structural coverage of 48% of total residues in 1237 human disease proteins. We found that disease-related mutations have statistically significantly preference to form clusters on protein surfaces. In contrast, the non-synonymous SNPs appear to be randomly distributed on the surface. We interpret these results as an indication that disease mutations affect protein-protein interaction interfaces. This interpretation is supported by the analysis of 8 experimentally determined complexes between disease proteins, where disease-related mutations are clearly located in the binding interface of proteins, while SNPs are not. The non-uniform distribution of disease mutations indicates that we can use this feature as guidance in modeling and evaluating human disease proteins and their complexes. We set up a resource for Disease Protein Models, which can be used for studying the relation between disease and mutation / polymorphism sites in the context of protein 3D structures and complexes.
机译:实验或预测的蛋白质三维结构向我们展示了这些分子机器如何真正发挥作用。借助有关疾病相关突变的信息,它们还可以向我们展示它们如何在疾病中失灵。目前对于大多数人类疾病尚缺乏这种了解,这是设计用于治疗特定疾病的药物或疗法之前的重要的第一步。在这里,我们使用同源性建模对人类疾病相关蛋白进行建模,研究疾病相关突变的结构特征,并将其与非同义SNP进行比较。对来自874个蛋白质的1484个结构域进行了建模,并与369个结构域的实验确定的结构一起,提供了1237种人类疾病蛋白中48%的总残基的结构覆盖率。我们发现与疾病相关的突变具有统计学上显着的偏好,以在蛋白质表面上形成簇。相反,非同义SNP似乎随机分布在表面上。我们将这些结果解释为疾病突变影响蛋白质-蛋白质相互作用界面的指示。对疾病蛋白之间的8种实验确定的复合物的分析支持了这种解释,其中与疾病相关的突变明显位于蛋白的结合界面中,而SNP则不然。疾病突变的不均匀分布表明我们可以将此功能用作建模和评估人类疾病蛋白及其复合物的指导。我们建立了疾病蛋白质模型资源,可用于研究疾病与蛋白质3D结构和复合物背景下的突变/多态性位点之间的关系。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号