Accurate Simulations of Peptide Aggregation

肽聚集的精确模拟

• 批准号: 7915265
• 负责人: PAUL E SMITH
• 金额: $ 21.68万
• 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/7915265
• 关键词: Affect; Amino Acids; Charge; Computer Simulation; Data; Disease; Health; Heart; Modeling; Peptides; Process; Proteins; Research; Research Design; Research Personnel; Role; Series; Side; Simulate; Solutions; Solvents; System; Testing; Thermodynamics; Urea; Vertebral column; aqueous; biological systems; functional group; intermolecular interaction; molecular dynamics; programs; protein aggregation; simulation; solute; theories; tool

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 cosolvents in modifying intermolecular interactions. The addition of cosolvents 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.

已经确定肽和蛋白质聚集是许多疾病的核心。因此，一个 详细了解肽或蛋白质何时以及如何倾向于聚集将是有益的 向研究各种健康相关问题的广泛研究人员提供。该提案概述了一项计划 使用独特的方法组合对肽聚集进行系统研究，包括： 目前可用的实验热力学数据；优先相互作用理论的特征 通过 Kirkwood-Buff (KB) 积分；使用优先相互作用的肽聚集的简单模型 溶液中不同官能团之间；和计算机模拟。理论和模型的发展 并证明可以分解和量化不同氨基酸侧之间的相互作用 使用小肽活性系数的现有实验数据来预测链，从而能够预测 任何小肽的聚集趋势。建议通过计算机模拟来研究 聚合过程的原子级细节。一种新的肽和蛋白质力场 (KBFF)，可以 重现实验 KB 积分将完成并用于模拟。 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优先 不同氨基酸和小肽系统的相互作用（PI）参数。 Pis 的简单模型将 被开发出来，然后用于隔离和量化不同功能组之间的 Pi 那些肽。 目标 2. 产生专门为研究优先相互作用而设计的精确力场 生物分子系统。 KBFF 方法将扩展到包括所有氨基酸侧链。 目标 3. 了解助溶剂在改变分子间相互作用中的作用。添加的 溶质和溶剂溶液中的共溶剂改变了溶质分子之间的相互作用。这 提供了研究生物系统中常见的分子间相互作用强度的工具 如何修改它们。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。