Accurate Simulations of Peptide Aggregation

描述(申请人提供)：已经证实，多肽和蛋白质聚集是许多疾病的核心。因此，对多肽或蛋白质何时以及如何聚集的详细了解将有助于广泛研究各种与健康相关的问题的研究人员。这项建议概述了利用独特的方法组合来系统研究多肽聚集的计划，这些方法包括：当前可用的实验热力学数据；以Kirkwood-Buff(Kb)积分为特征的优先相互作用理论；利用溶液中不同官能团之间的优先相互作用来进行多肽聚集的简单模型；以及计算机模拟。利用已有的小肽的活度系数实验数据，建立了一个可以分解和量化不同氨基酸侧链之间相互作用的理论和模型，从而能够预测任何小肽的聚集趋势。计算机模拟被用来研究聚集过程的原子级细节。一种新的能够再现实验KB积分的多肽和蛋白质力场(KBFF)将被完成并用于模拟。目的1.定量和表征多肽中观察到的官能团之间的相互作用。现有的实验数据将在水溶液中进行分析，以确定不同氨基酸和小肽体系的优先相互作用(PI)参数。将开发一个简单的PI模型，然后将用于分离和定量这些肽上不同功能基团之间的PI。目的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方法将扩展到包括所有氨基酸侧链。目的3.了解共溶剂在修饰分子间相互作用中的作用。将共溶剂加入到溶质和溶剂的溶液中，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一个工具。在我们的初步研究中，我们将重点关注尿素和NaCI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.