Accurate Simulations of Peptide Aggregation

描述（由申请人提供）：已经确定肽和蛋白质聚集是许多疾病的核心。因此，详细了解肽或蛋白质何时以及如何倾向于聚集将有利于研究各种健康相关问题的广泛研究人员。该提案概述了一个程序的肽聚集的系统研究使用一个独特的组合的方法，包括：目前可用的实验热力学数据;优先相互作用的理论，其特征在于Kirkwood-Buff（KB）积分;一个简单的模型，肽聚集在溶液中使用不同的官能团之间的优先相互作用;和计算机模拟。一个理论和模型的开发和证明，可以分解和量化不同的氨基酸侧链之间的相互作用，使用现有的实验数据的活性系数的小肽，从而使预测的趋势聚集的任何小肽。计算机模拟提出了调查原子水平的聚集过程的细节。一个新的肽和蛋白质力场（KBFF），可以重现实验KB积分将完成和用于模拟。目标1.定量和表征肽中观察到的官能团之间的相互作用。现有的实验数据的分析将在水溶液中进行，以确定不同的氨基酸和小肽系统的优先相互作用（PI）参数。将开发PI的简单模型，然后将其用于分离和定量这些肽上不同官能团之间的PI。目标2.产生一个精确的力场，专门用于研究生物分子系统中的优先相互作用。KBFF方法将扩展至包括所有氨基酸侧链。目标3。了解共溶剂在改变分子间相互作用中的作用。向溶质和溶剂的溶液中添加共溶剂改变了溶质分子之间的相互作用。这为研究生物系统中常见的分子间相互作用的强度以及如何对其进行修饰提供了工具。在我们的初步研究中，我们将重点关注尿素和NaCl的影响。

DESCRIPTION (provided by applicant): It has been established that peptide and protein aggregation lies at the heart of many diseases. Hence, a detailed understanding of exactly when and how peptides or proteins tend to aggregate would be beneficial to a wide range of researchers studying a variety of health related issues. This proposal outlines a program for the systematic study of peptide aggregation using a unique combination of approaches including: currently available experimental thermodynamic data; the theory of preferential interactions as characterized by Kirkwood-Buff (KB) integrals; a simple model for peptide aggregation using preferential interactions between different functional groups in solution; and computer simulation. A theory and model is developed and demonstrated that can decompose and quantify the interactions between different amino acid side chains using existing experimental data on activity coefficients of small peptides, thus enabling predictions of the tendency for aggregation of any small peptide. Computer simulations are proposed to investigate the atomic level details of the aggregation process. A new peptide and protein force field (KBFF) that can reproduce the experimental KB integrals will be completed and used for the simulations. Aim 1. To quantify and characterize the interactions between functional groups observed in peptides. Analysis of existing experimental data will be performed in aqueous solution to determine preferential interaction (PI) parameters for different amino acid and small peptide systems. A simple model of the PIs will be developed and will then be used to isolate and quantify the PIs between different function groups on those peptides. Aim 2. To produce an accurate force field specifically designed for the study of preferential interactions in biomolecular systems. The KBFF approach will be extended to include all amino acid side chains. Aim 3. To understand the role of co-solvents in modifying intermolecular interactions. The addition of co-solvents to a solution of a solute and solvent changes the interactions between the solute molecules. This provides a tool for investigating the strength of intermolecular interactions common in biological systems and how they may be modified. We will focus on the effects of urea and NaCI during our initial studies.