Improved Potential Energy Functions for Molecular Simulation

改进的分子模拟势能函数

• 批准号: 9808317
• 负责人: Jay Ponder
• 金额: $ 35.51万
• 依托单位: Washington University School of Medicine
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-10-01 至 2002-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9808317&HistoricalAwards=false
• 关键词: Improved; Potential; Energy; Functions; Molecular

The project intends to improve and extend the accuracy and application of empirical potential energy functions for peptides and proteins. These functions form the basis of an extensive set of modeling techniques widely used to rationalize and predict the structure and conformational energetics of organic molecules and biopolymers. Based on simple principles from classical chemical physics, this type computer modeling software is widely used in a variety of settings ranging from undergraduate chemistry and biochemistry to research at the forefront of structural biology. While empirical potential energy functions often exhibit exquisite accuracy in modeling nonpolar organics, their application to typical biological systems presents several additional difficulties. The major goal of this project is to find solutions to the problems that most limit current application of this methodology in protein modeling: (1) achieving chemical accuracy for protein structure and energetics as governed by basic physics, and (2) describing widely varied chemical environments such as the solvent exposed surface of a protein and its hydrophobic interior. Since the treatment of electrostatic interactions is the largest source of error in these calculations, particular emphasis will be placed upon developing an atom-centered approach to electrostatics with inclusion of dipole polarization effects. A class of hybrid methods is proposed for further development, using a shell of explicit water coupled with a reaction field treatment of long range bulk solvent effects.

该项目旨在提高和扩展肽和蛋白质经验势能函数的准确性和应用。 这些函数构成了广泛用于合理化和预测有机分子和生物聚合物的结构和构象能量学的广泛建模技术的基础。 这种类型的计算机建模软件基于经典化学物理学的简单原理，广泛应用于从本科化学和生物化学到结构生物学前沿研究的各种环境中。 虽然经验势能函数在非极性有机物建模中通常表现出极高的准确性，但它们在典型生物系统中的应用却带来了一些额外的困难。 该项目的主要目标是找到解决当前该方法在蛋白质建模中应用的最大问题的解决方案：（1）实现由基础物理学控制的蛋白质结构和能量学的化学准确性，以及（2）描述广泛不同的化学环境，例如蛋白质的溶剂暴露表面及其疏水内部。 由于静电相互作用的处理是这些计算中最大的误差源，因此将特别强调开发一种以原子为中心的静电学方法，其中包括偶极子极化效应。 提出了一类混合方法以供进一步开发，使用明确的水壳与长程本体溶剂效应的反应场处理相结合。