Predicting Impact of Mutations on Proteins

描述（由申请人提供）：总体目标是通过探索编码区突变对蛋白质结构的影响，有助于理解个体基因组变异如何影响疾病易感性和对药物的反应。这项工作将侧重于开发一种计算方法来预测非同义单核苷酸多态性的功能影响，使用来自多个序列比对的特征组合，可用的实验结构，以及其他比较模型。目的1：定量识别在预测功能效应方面信息量最大的nsSNP变异的序列和结构特征，以及将它们结合到预测算法中的最佳方法。目的2：与UCSF膜转运体药物基因组学（PMT）项目的生物学家合作，通过预测nssnp对人类膜转运体的影响，应用并验证该方法。膜转运体是一类对确定治疗药物有效水平很重要的蛋白质。AIM3：通过实现和维护一个提供人类nssnp功能预测的web服务器，使该方法对生物学家的效用最大化，该服务器与UCSC基因组浏览器双向链接。

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.