Determinants of Folding Mechanism in Small Proteins

描述（由申请人提供）：大多数蛋白质在进化上针对功能进行了优化，但针对折叠未进行优化。因此，了解蛋白质折叠机制将有助于我们设计出在不改变其功能的情况下优化折叠的蛋白质。此外，错误折叠和聚集是致命疾病的基础，如囊性纤维化、阿尔茨海默病和其他淀粉样变性以及II型糖尿病。蛋白质折叠的预测框架，特别是在非天然状态下及其序列测定，将极大地影响折叠相关疾病的生物医学研究。我们将通过对几种快速折叠蛋白质的动力学和热力学的研究，发展和验证这样一个蛋白质折叠的预测框架。我们打算从全原子的角度来理解这些蛋白质折叠机制的决定因素，并通过与实验的广泛比较来验证我们的理解。在显式溶剂和隐式溶剂中的全原子分子力学力场将被用来表征非天然状态和折叠路径。 1)我们计划：（a）研究序列和拓扑结构在确定具有锌指基序的两种工程化蛋白质FSD 1和PDA 8D的折叠速率和途径中的相互作用;（B）通过突变扰乱B它们的折叠途径以在该家族中实现亚微秒折叠速率。2)我们将调查：（a）是什么使得基于拓扑结构的蛋白A的预测速率正确，但是Engrailed Homeodomain的预测速率偏离了40倍;（B）是什么使得蛋白A对突变如此敏感-单个突变可以改变其速率10倍或更高;（c）是什么使得Engrailed Homeodomain耐受序列的剧烈变化而折叠速率几乎没有变化。我们将计算探测它们折叠过程的许多方面，变性状态，过渡状态，中间状态（如果有的话），以及通往天然状态的途径，以了解差异。

DESCRIPTION (provided by applicant): Most proteins are evolutionarily optimized for function, but not for folding. Thus, understanding protein folding mechanisms will help us design proteins that are optimized for folding without altering their functions. In addition, misfolding and aggregation underlie fatal diseases such as cystic fibrosis, Alzheimer's disease and other amyloidoses, and type-II diabetes. A predictive framework for protein folding, particularly in the nonnative states and its sequence determination, will greatly impact biomedical research of folding-related diseases. We will develop and validate such a predictive framework for protein folding through the studies of kinetics and thermodynamics of a few fast-folding proteins. We intend to understand the determinants of folding mechanisms for these proteins at all-atom details and validate our understanding by comparing with experiment extensively. An all-atom molecular mechanics force field in both explicit solvent and in implicit solvent will be used to characterize the nonnative states and the folding pathways. 1) We plan to: (a) investigate the interplay of sequence and topology in the determination of the folding rates and pathways for two engineered proteins with Zn-finger motif: FSD1 and PDA8D; (b) perturb their folding pathways by mutation to achieve sub-microsecond folding rates in this family. 2) We will investigate: (a) what makes the predicted rate of protein A based on topology correct, but the predicted rate of Engrailed Homeodomain off by a factor of 40; (b) what makes protein A so sensitive to mutation -- a single mutation can change its rate by a factor of 10 or higher; (c) what makes Engrailed Homeodomain tolerate drastic changes in sequence with little change in folding rates. We will computationally probe many aspects of their folding processes, the denatured states, the transition states, the intermediate states if any, and the pathways towards native states to understand the differences.