Conceptual Aspects of the Protein Folding Problem

描述（由申请人提供）：所提出的工作进一步发展了蛋白质折叠动力学和结构预测的统计能量景观方法。具体目标是：1）阐明变构蛋白的折叠和功能能量景观的耦合，专注于局部挫折的作用2）阐明膜蛋白的体外和体内折叠的机制，并提高我们预测其结构的能力。能量景观理论提供了数学技术的特点，在概率方面的能量的合奏部分折叠的蛋白质配置和动力学之间的相互转换。我们将使用分析和计算机模拟的方法，将提供定量估计的作用，最低限度的挫折网络的相互作用，引导蛋白质的天然状态和挫折的作用，阻碍了流动。据预测，变构蛋白会积极利用挫折来塑造功能景观。变构蛋白如激酶的突变可导致蛋白质致癌。膜蛋白折叠的错误可以导致囊性纤维化等疾病。了解膜蛋白景观的进展可以帮助预测它们的结构，这是设计药物的重要一步。PHS 398/2590（Rev. 11/07） 公共卫生相关性：折叠是将基因组数据转化为功能的关键步骤。我们在折叠的能量景观理论方面的工作有助于预测药物靶点的蛋白质结构。阐明折叠机制对于理解由折叠错误引起的疾病也很重要，例如囊性纤维化和II型糖尿病。PHS 398/2590（Rev. 11/07）

DESCRIPTION (provided by applicant): The proposed work develops further the statistical energy landscape approach to protein folding dynamics and structural prediction. The specific aims are: 1) to elucidate coupling of the folding and functional energy landscapes of allosteric proteins, concentrating on the role of local frustration 2) to elucidate the mechanism of in vitro and in vivo folding of membrane proteins and to improve our ability to predict their structure. Energy landscape theory provides mathematical techniques for characterizing in probabilistic terms the energies of the ensembles of partially folded protein configurations and the dynamics of interconverting between them. We will use analytical and computer simulation approaches that will provide quantitative estimates for the role of minimally frustrated networks of interactions in guiding the protein to its native state and the role that frustration has in impeding that flow. Allosteric proteins are predicted to positively use frustration to sculpt the functional landscape. Mutation in allosteric proteins such as kinases can cause a protein to be oncogenic. Errors in the folding of membrane proteins can lead specifically to diseases such as cystic fibrosis. Advances in understanding the landscape of membrane protein can help predict their structure an important step in designing drugs. PHS 398/2590 (Rev. 11/07) Page Continuation Format Page PUBLIC HEALTH RELEVANCE: Folding is a key step in translating genomic data into function. Our work on the energy landscape theory of folding helps predict protein structures of drug targets. The elucidation of folding mechanism is also important for understanding diseases caused by errors in folding, such as cystic fibrosis and Type II diabetes. PHS 398/2590 (Rev. 11/07) Page Continuation Format Page