Understanding Beta-Sheet Structure in Aqueous Solution

描述（由申请人提供）：本研究的长期目标是了解使用通过双态机制折叠的小蛋白质进行β折叠的结构原理。我们利用Pin WW结构域的序列，34个残基的3-链反向平行β-折叠，结合天然和非天然氨基酸突变来理解对于过渡态形成和基态稳定性至关重要的结构特征。我们的化学合成能力WW域与不同的骨干连接和一个恒定的β-片核心结构，使我们能够了解什么方面的拓扑结构（结构）是重要的预测折叠率的预测，是准确的数量级左右。合成的可及性还允许我们在WW结构域结构中进行细微的改变，以更好地理解这些改变如何影响WW结构域变体所表现出的折叠速率范围。可以处理序列中几乎每个位置处的突变的热力学和动力学数据以提供Phi（phi）分析（phi）= Δ G ++/Δ G），以辨别折叠自由能的扰动在过渡态中反映的程度。我们对某些结构特征的重要性进行预测，包括氢键，疏水相互作用，构象偏好，链连接性（拓扑结构）等，在基态和过渡态，可以使用phi分析进行实验测试。了解β折叠对于改善序列的折叠预测和开始了解13-折叠和错误折叠之间的平衡是重要的，后者的过程提供了似乎引起神经变性的聚集体。

DESCRIPTION (provided by applicant): The long term objective of this research is to understand the structural principles of beta-sheet folding using a small protein that folds by a two state mechanism. We utilize sequences of the Pin WW domain, a 34 residue 3-stranded antiparallel Beta-sheet, incorporating both natural and unnatural amino acid mutations to understand the structural features that are critical for the transition state formation and ground state stability. Our ability to chemically synthesize WW domains with varied backbone connectivity and a constant Beta-sheet core structure allows us to understand what aspect of topology (structure) is important for predicting folding rates-a prediction that is accurate within an order of magnitude or so. Synthetic accessibility also allows us to make subtle changes in WW domain structure to better understand how these changes influence the range of folding rates exhibited by WW domain variants. Thermodynamic and kinetic data for mutations at nearly every position in the sequence can be processed to afford a Phi (phi) analysis (phi) = deltadeltaG++/deltadeltaG) to discern the extent to which a perturbation in the free energy of folding is mirrored in the transition state. We make predictions about the importance of certain structural features including hydrogen bonding, hydrophobic interactions, conformational preferences, chain connectivity (topology), etc. in both the ground state and transition states that can be tested experimentally using a phi analysis. Understanding Beta-sheet folding is important to improve fold predictions from sequence and to begin to understand the balance between 13-sheet folding and misfolding-the latter process affords aggregates that appear to cause neurodegeneration.