Structural Dynamics of Biomolecular Systems

许多蛋白质的功能是分子机器。理解控制生物分子系统的机制的原理在许多情况下是一个计算挑战，因为涉及由多个亚基组成的大分子结构和构象变构变化所表现出的合作相互作用，这超出了原子模拟的范围。在最近资助的R33项目中，我们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，并基于结构-编码-动力学-编码-功能的范式在结构和功能之间架起桥梁。我们为此目的引入的弹性网络模型和方法在许多应用中已经发现了实用性，并帮助我们深入了解蛋白质的内在结构编码能力，以促进功能子状态之间的天然结构的重新配置。在目前的R 01中，我们建议在我们以前的工作基础上，与斯坦福大学U的NCBC Simbios合作，使用基于物理和计算效率的模型进一步探索变构和/或多聚体蛋白质的结构->动力学->功能映射（PI：Altman）。Simbios小组已经开始构建一个新的模拟包Simbody，预计通过合作将大大提高其效用。我们的具体目标是（1）建立模型和方法，用于在多个分辨率水平上自动粗粒化复杂结构，并评估其集体动态，以使用所产生的模型Simbody中的数据（结构）和数据（运动）;（2）通过信息理论方法来补充目标1中开发的基于物理学的方法，以描绘变构系统中的信号转导途径/机制，并建立这些途径和结构动力学之间的联系，以及（3）深入了解分子伴侣的机制，使用细菌伴侣蛋白GroEL-GroES和DnaK伴侣系统作为原型，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方法，用于模拟兆道尔顿量级的生物分子系统的机械，这将与Schulten实验室合作实现，此外我们还与Simbios团队合作。

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.