Predicting Impact of Mutations on Proteins

描述(由申请人提供)：广泛的目标是通过探索编码区突变对蛋白质结构的影响，帮助理解个体基因组变异如何有助于疾病易感性和对药物的反应。这项工作将集中在开发一种计算方法来预测非同义单核苷酸多态的功能影响，使用来自多个序列比对的特征、实验结构(如果可用)和比较模型的组合。目的1：定量确定nsSNP变体的基于序列和结构的特征，这些特征在预测功能效应方面信息量最大，并以最佳方式将它们结合在预测算法中。目的：与加州大学旧金山分校的膜转运蛋白药物基因组学(PMT)项目的生物学家合作，通过预测nsSNPs对人类膜转运蛋白的影响来应用和验证该方法。人类膜转运蛋白是一类对确定治疗药物有效水平至关重要的蛋白质。AIM3：通过实施和维护一个网络服务器，提供对人类nsSNPs的功能预测，并双向链接到UCSC基因组浏览器，最大限度地发挥该方法对生物学家的效用。

DESCRIPTION (provided by applicant): The broad goal is to contribute to the understanding of how individual genomic variation contributes to disease susceptibility and response to drugs, by exploring the effects of mutations in coding regions on protein structure. The work will focus on developing a computational method to predict the functional effects of non-synonymous single nucleotide polymorphisms, using a combination of features derived from multiple sequence alignments, experimental structures when available, and comparative models otherwise. AIM1: Quantitatively identify the sequence- and structure-based features of nsSNP variants that are most informative in predicting functional effects and the best way to combine them in a predictive algorithm. AIM2: Apply and validate the method by predicting the impact of nsSNPs in human membrane transporters, a class of proteins important for determining the levels at which therapeutic drugs are effective, in collaboration with biologists in the UCSF Pharmacogenomics of Membrane Transporters (PMT) project. AIM3: Maximize the utility of the method to biologists by implementing and maintaining a webserver that provides functional predictions for human nsSNPs, bi-directionally linked to the UCSC Genome Browser.