Coarse-Grained Models of Proteins

蛋白质运动的许多方面都可以用粗粒度模型来理解。我们的假设是 不需要原子细节来解释蛋白质行为的许多方面，这种简化可以促进 更深入的理解。总体目标是加深对蛋白质运动和功能的理解。 受结构控制，为什么蛋白质序列折叠成一组有限的结构，并确定 紧密堆积和蛋白质运动时的形状。在这个项目中，我们将研究这些关系 在运动、形状、结构、相互作用和协作性水平之间。目标一：模拟蛋白质 弹性网络的动力学。我们将使用弹性网络模型来研究蛋白质如何限制其 动作对动作的作用最重要。将执行正常模式分析以识别这些 具有高计算效率的重要功能运动，以开发分子机制。我们会 研究酶活性部位的原子运动，以了解大域运动如何控制 原子运动。我们将使用弹性网络来解释单分子拉动实验，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 围绕天然构象的波动，以及施加外力时产生的瞬变状态 使蛋白质变形并破坏其天然接触。这些结果表明，结构控制着全球 蛋白质的运动，即使是瞬变状态。为了进一步验证这一假设，我们将执行更多单次 分子拉动模拟和瞬时蛋白质折叠构象的结构分析 小路。使用弹性模型取得的主要成功依赖于对 堆积密度和蛋白质形状，我们将在Aim II中进行研究。Aim II：模拟蛋白质堆积和 相互作用的协作性。蛋白质中残基的紧密堆积是它们最重要的之一。 有特色的特征。我们计划继续研究内包装。对新潜力的重视 将取决于蛋白质中氨基酸的相对取向。我们将开发多体接触势来实现 在穿线过程中识别诱饵中的天然结构，并研究 蛋白质中邻近残基的簇，使用规则多面体，如二十面体，或加泰罗尼亚固体，如 四角六面体。我们的基本原理是使用各种多面体模型来理解蛋白质堆积 和氨基酸相互作用，以发展改进的多体潜力。更好地理解 蛋白质内部相互作用的协作性是极其重要的，因为这直接影响 蛋白质在其中运动并对力做出反应。这两个目标高度相关，并将显著 提高我们对蛋白质结构、动力学和功能的认识。

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.