权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Coarse-Grained Models of Proteins

蛋白质的粗粒度模型

基本信息

批准号：
8209105
负责人：
ROBERT L JERNIGAN
金额：
$ 30.8万
依托单位：
IOWA STATE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2004
资助国家：
美国
起止时间：
2004-07-01 至 2013-12-31
项目状态：
已结题

项目摘要

Many aspects of protein motion can be comprehended with coarse-grained models. Our hypothesis is that atomic detail is not required to explain many aspects of protein behavior, and this simplification can facilitate a deeper understanding. The overall goal is to develop an understanding of how protein motions and function are contolled by structure, why protein sequences fold to a limited set of structures, and to establish the roles of tight packing and the shapes of proteins on their motions. In this project we will investigate the relationships among motions, shapes, structures, interactions and levels of cooperativity. Aim I: Modeling protein dynamics with Elastic Networks. We will use elastic network models to study how proteins restrict their motions to the motions most essential for function. Normal mode analyses will be performed to discern these important functional motions with high computational efficiency to develop molecular mechanisms. We will investigate the atomic motions in active sites of enzymes to see how the large domain motions control the atom movements. We will use elastic networks to interpret single molecule pulling experiments and predict the order in which proteins unravel. Preliminary results show that elastic network models are applicable not only to fluctuations around native conformations, but also to transient states arising when an external force is applied to deform a protein and break its native contacts. These results suggest that structure controls the global motions of proteins, even for transient states. To further verify this hypothesis we will perform more single molecule pulling simulations, and structural analyses of transient protein conformations along folding pathways. The major successes achieved with the elastic models rely upon having good representations of the packing density and protein shape, which we will investigate in Aim II. Aim II: Modeling Protein Packing and Cooperativity of Interactions. Dense packing of residues in proteins is one of their most important characteristic features. We plan to continue our studies of internal packing. The emphasis for new potentials will be on the relative orientations of amino acids in proteins. We will develop many-body contact potentials for identifying native structures among decoys in threading, and also study orientational distributions within clusters of nearby residues in proteins, using regular polyhedra such as icosahedra, or Catalan solids such as tetrakis hexahedra. Our rationale is to use various polyhedral models to comprehend protein packing and amino acid interactions for developing improved many-body potentials. A better understanding of the cooperativity of interactions within proteins is extremely important because this directly influences the ways in which proteins move and respond to forces. Both Aims are highly interconnected and will significantly advance our knowledge of protein structure, dynamics and function.

蛋白质运动的许多方面可以通过粗粒度模型来理解。我们的假设是原子细节不需要解释蛋白质行为的许多方面，这种简化可以促进蛋白质的结构。更深刻的理解。总体目标是了解蛋白质的运动和功能是如何控制的结构，为什么蛋白质序列折叠成一组有限的结构，并建立的作用，紧密堆积和蛋白质运动的形状。在这个项目中，我们将研究在运动、形状、结构、相互作用和合作水平之间。目的一：蛋白质建模动态与弹性网络。我们将使用弹性网络模型来研究蛋白质如何限制其运动到对功能最重要的运动将进行正常模式分析，重要的功能运动与高计算效率，以发展分子机制。我们将研究酶活性位点中的原子运动，以了解大畴运动如何控制酶的活性原子运动我们将使用弹性网络来解释单分子拉伸实验，并预测蛋白质分解的顺序。初步结果表明，弹性网络模型不仅适用于天然构象周围的波动，但也适用于施加外力时产生的瞬态使蛋白质变形并破坏其天然联系。这些结果表明，结构控制着全球蛋白质的运动，即使是瞬态。为了进一步验证这一假设，我们将执行更多的单分子拉伸模拟，以及蛋白质沿着折叠的瞬时构象的结构分析途径。弹性模型取得的主要成功依赖于具有良好的表示，包装密度和蛋白质形状，我们将在目标II中进行研究。目的二：蛋白质包装模型和相互作用的协同性。蛋白质中残基的密集堆积是其最重要的功能之一特征我们计划继续研究内部包装。强调新的潜力将是蛋白质中氨基酸的相对方向。我们将开发多体接触电位，在线程中识别诱饵之间的天然结构，并研究内部的取向分布。蛋白质中邻近残基的簇，使用正多面体如二十面体，或加泰罗尼亚固体如四面体我们的基本原理是使用各种多面体模型来理解蛋白质包装和氨基酸相互作用以开发改进的多体电位。更好地了解蛋白质内部相互作用的协同性是非常重要的，因为这直接影响到蛋白质在其中移动并对力做出反应。这两个目标是高度相互关联的，推进我们对蛋白质结构、动力学和功能的认识。