CONCEPTUAL ASPECTS OF THE PROTEIN FOLDING PROBLEM

本文的工作进一步发展了统计能量景观方法在蛋白质折叠动力学和结构预测中的应用。具体目标是：1）发展基本的统计力学理论，用于测量折叠过程中景观的能量景观; 2）预测和解释蛋白质折叠早期事件的结构方面; 3）了解长时间尺度上折叠动力学障碍和蛋白质亚稳定性的微观起源; 4）进一步发展基于严格的统计算法，用于预测蛋白质三级结构。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。分析和计算机模拟的方法提出，将提供定量估计的作用，个别氨基酸发挥引导蛋白质的天然状态，并在阻碍流动。折叠动力学的变化影响蛋白质运输，并被认为参与许多疾病的发病机制，包括阿尔茨海默病，II型糖尿病和囊性纤维化。从序列预测准确的三维蛋白质结构的能力的提高将在通常利用从人类和细菌基因组测序计划获得的数据方面具有很大的价值。

The proposed work develops further the statistical energy landscape approach to protein folding dynamics and structure prediction. The specific aims are: 1) to develop fundamental statistical mechanical theories for surveying the energy landscapes of landscapes during folding; 2) to predict and interpret the structural aspects of the early events in protein folding; 3) to understand the microscopic origin of kinetic barriers to folding on long time scales and of protein metastability; 4) to further develop rigorously based statistical algorithms for the prediction of protein tertiary 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. Both analytical and computer simulation approaches are proposed that will provide quantitative estimates for the role individual amino acids play both in guiding the protein to its native state and in impeding that flow. Changes in folding kinetics affect protein trafficking and are thought to be involved in the pathogenesis of many diseases including Alzheimer's disease, type II diabetes and cystic fibrosis. The improved ability to predict accurate three dimensional protein structures from sequence will be of great value in generally making use of data obtained from both human and bacterial genome sequencing projects.