Accurate Simulations of Peptide Aggregation

肽聚集的精确模拟

• 批准号: 7316614
• 负责人: PAUL E SMITH
• 金额: $ 21.9万
• 依托单位: KANSAS STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7316614
• 关键词: Affect; Amino Acids; Biological; Charge; Classification; Computer Simulation; Data; Disease; Health; Heart; Modeling; Peptides; Process; Proteins; Range; Research; Research Design; Research Personnel; Role; Series; Side; Simulate; Solutions; Solvents; System; Testing; Thermodynamics; Urea; Vertebral column; aqueous; functional group; intermolecular interaction; molecular dynamics; programs; protein aggregation; simulation; solute; theories; tool

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.

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。该提案概述了使用独特的方法组合对肽聚集进行系统研究的计划，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建立肽聚集的简单模型；和计算机模拟。开发并证明了一种理论和模型，可以利用现有的小肽活性系数实验数据来分解和量化不同氨基酸侧链之间的相互作用，从而能够预测任何小肽的聚集趋势。提出计算机模拟来研究聚合过程的原子级细节。将完成一个可以重现实验 KB 积分的新肽和蛋白质力场 (KBFF)，并将其用于模拟。目标 1. 量化和表征肽中观察到的官能团之间的相互作用。将在水溶液中对现有实验数据进行分析，以确定不同氨基酸和小肽系统的优先相互作用（PI）参数。将开发一个简单的 PI 模型，然后用于分离和量化这些肽的不同功能组之间的 PI。目标 2. 产生专为研究生物分子系统中的优先相互作用而设计的精确力场。 KBFF 方法将扩展到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。将共溶剂添加到溶质和溶剂的溶液中会改变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修改它们提供了一个工具。在我们的初步研究中，我们将重点关注尿素和氯化钠的影响。