Accurate Simulations of Peptide Aggregation

肽聚集的精确模拟

• 批准号: 7487767
• 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/7487767
• 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

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， 详细了解肽或蛋白质往往趋于汇总的确切何时以及如何汇总将是有益的 对于研究各种与健康相关的问题的广泛研究人员。该提案概述了一个计划 为了系统地研究肽聚集，使用独特的方法组合，包括： 当前可用的实验热力学数据；优先相互作用的理论特征 由Kirkwood-Buff（KB）积分；使用优先相互作用的肽聚集的简单模型 解决方案中的不同官能团之间；和计算机模拟。开发了理论和模型 并证明可以分解和量化不同氨基酸侧之间的相互作用 使用现有的有关小肽活性系数的链条，从而预测 任何小肽聚集的趋势。提出了计算机模拟来调查 聚合过程的原子级别细节。一个可以可以 重现实验性KB积分将完成并用于模拟。 目标1。量化和表征在肽中观察到的官能团之间的相互作用。 对现有实验数据的分析将在水溶液中进行，以确定优先 不同氨基酸和小肽系统的相互作用（PI）参数。 PI的简单模型将 被开发，然后将用于隔离和量化不同函数组之间的PI 那些肽。 目标2。生成专门设计的精确力场，用于研究优先相互作用 生物分子系统。 KBFF方法将扩展到包括所有氨基酸侧链。 目的3。了解助溶剂在修改分子间相互作用中的作用。添加 溶于溶质和溶剂的溶液的溶质改变了溶质分子之间的相互作用。这 提供了一种工具来研究生物系统中常见的分子间相互作用的强度， 如何修改它们。在初步研究中，我们将重点关注尿素和NACI的影响。