Conceptual Aspects of the Protein Folding Problem

描述(由申请人提供)：拟议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图景方法。其具体目的是：1)阐明变构蛋白折叠和功能能谱的偶联，集中于局部受挫的作用；2)阐明膜蛋白在体外和体内折叠的机制，提高我们预测其结构的能力。能量景观理论提供了用概率术语描述部分折叠蛋白质构型的系综的能量以及它们之间相互转换的动力学的数学技术。我们将使用分析和计算机模拟方法，为最小受挫的相互作用网络在将蛋白质引导到其自然状态中所起的作用以及受挫在阻碍流动中的作用提供定量估计。变构蛋白被预测将积极地利用挫折来塑造功能景观。变构蛋白(如蛋白激酶)的突变可导致蛋白质致癌。膜蛋白折叠错误可能导致囊性纤维化等疾病。了解膜蛋白结构的进展有助于预测其结构，这是药物设计的重要一步。PHS 398/2590(11/07版)页面续格式页面 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标的蛋白质结构。折叠机制的阐明对于理解折叠过程中的错误引起的疾病，如囊性纤维化和II型糖尿病也很重要。PHS 398/2590(11/07版)页面续格式页面

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