Structural Dynamics of Biomolecular Systems

许多蛋白质起着分子机器的作用。在许多情况下，理解控制生物分子系统机制的原理是一项计算挑战，因为涉及由多个亚基组成的大分子结构和由构象变构变化表现出来的合作相互作用，这超出了原子模拟的范围。我们最近资助的R33的目标是开发和利用低分辨率模型来探索这种复杂系统的集体动力学，并在结构和功能之间建立桥梁，基于范式结构-编码-动态-编码-功能。我们为此目的引入的弹性网络模型和方法已经在许多应用中发现了实用性，并帮助我们深入了解蛋白质的内在结构编码能力，从而有利于功能亚态之间天然结构的重构。在本研究中，我们建议在之前工作的基础上，与斯坦福大学NCBC Simbios （PI: Altman）合作，使用基于物理和计算效率的模型，进一步探索变构和/或多聚体蛋白的结构->动力学->功能映射。Simbios小组已经开始构建一个新的模拟包Simbody，其效用有望通过协作工作得到显着增强。我们的具体目标是(1)建立模型和方法，在多个分辨率水平上自动粗粒度复杂结构和评估他们的集体动力学，朝着使用Simbody产生的模型（结构）和数据（运动）；(2)通过信息理论方法来补充Aim 1中发展的基于物理的方法，以描述变构系统中的信号转导途径/机制，并建立这些途径与结构动力学之间的联系；(3)以细菌伴侣蛋白GroEL-GroES和DnaK伴侣蛋白系统为原型，深入了解分子伴侣蛋白的机制；与Gierasch实验室合作，目前正在进行nih支持的实验，以了解DnaK系统的变构动力学。该项目的一个重要成果将是建立一种模拟Megadaltons数量级生物分子系统机制的方法，除了我们与Simbios团队的合作外，还将与Schulten实验室合作实现。

Many proteins function as molecular machines. Understanding the principles that control the machinery of biomolecular systems is a computational challenge in many cases due to the involvement of macromolecular structures composed of multiple subunits and cooperative interactions manifested by allosteric changes in conformations, which are beyond the range of atomic simulations. Our goal in a recently funded R33 has been to develop and utilize low resolution models for exploring the collective dynamics of such complex systems, and bridging between structure and function, based on the paradigm structure-encodes-dynamics-encodes-function. The elastic network models and methods we introduced to this aim have found utility in many applications and helped us gain insights into the intrinsic, structure- encoded ability of proteins to favor the reconfiguration of native structures between functional substates. In the present R01, we are proposing to build on our previous work, to further explore the structure -> dynamics -> function mapping of allosteric and/or multimeric proteins using physically-based and computationally efficient models in collaboration with the NCBC Simbios at Stanford U (PI: Altman). The Simbios group has already started to construct a new simulation package, Simbody, the utility of which is expected to be significantly enhanced by a collaborative work. Our specific aims are (1) to build models and methods for automated coarse-graining of complex structures at multiple levels of resolution and assessing their collective dynamics, toward using the resulting models (structure) and data (motions) in Simbody; (2) to complement the physics-based approach developed in Aim 1 by information-theoretic approaches toward delineating signal transduction pathways/mechanisms in allosteric systems, and establishing the connection between these pathways and structural dynamics, and (3) to gain insights into the machinery of molecular chaperones, using as prototypes the bacterial chaperonin GroEL-GroES and the DnaK chaperone system, in collaboration with the Gierasch lab currently doing NIH-supported experiments for understanding the allosteric dynamics of the DnaK system. An important outcome of this project will be the establishment of a methodology for simulating the machinery of biomolecular systems on the order of Megadaltons, which will be achieved in collaboration with the Schulten lab, in addition to our partnership with the Simbios team.