The energy landscape for folding and function of biomolecules: integrating physical models, genetic information and experiments

本项目由分子与细胞生物科学部的分子生物物理集群、物理部的生命系统物理学和化学部的生命过程化学项目共同资助。细胞的生命是由大量蛋白质和核酸的化学反应网络以及这些分子在细胞间的运输精心安排的。该奖项支持的研究主要集中在生物分子的结构-功能关系上，主要集中在蛋白质上，但也延伸到核酸。利用理论方法的力量，该项目研究蛋白质如何在结构和功能之间分配能量。该项目还通过创建染色质组织的新物理模型来探索基因组的三维组织。这些理论工作可以指导和影响理论界和实验界对折叠和功能的研究。本研究为分子生物物理学高度跨学科领域的学生和博士后提供培训。基于结构的模型（sbm）已被证明是理解控制折叠的全局几何特征的有用工具。基于能量景观理论（ELT）和漏斗概念，这些模型得到了大多数自然产生的蛋白质已经充分减少能量挫折这一事实的支持。基于结构的模型受到结构信息可用性的限制，特别是那些与所有不同功能配置相关的信息。直接偶联分析（DCA）可以预测蛋白质中氨基酸的接触。该研究以sbm为基础，辅以DCA信息，并结合显式溶剂全原子模拟。该项目侧重于蛋白质和几种生物分子机器。最后，受到这种方法在蛋白质和其他分子机器上的早期成功的启发，这个项目的一个重要目标是处理染色体折叠和功能。

This project is jointly funded by the Molecular Biophysics Cluster in the Division of Molecular and Cellular Biosciences, the Physics of Living Systems in the Division of Physics and the Chemistry of Life Processes Program in the Division of Chemistry.The life of cells is orchestrated by a network of chemical reactions involving numerous proteins and nucleic acids, and the transport of these molecules between cellular compartments. The research supported by this award focuses on the structure-function relationship of biomolecules, focusing mostly on proteins but also with extensions to nucleic acids. Using the power of theoretical approaches, this project investigates how proteins distribute their energy between structure and function. The project also explores the three-dimensional organization of the genome by creating new physical models for chromatin organization. The theoretical work may be used to guide and influence the research in folding and function in both theoretical and experimental communities. This research provides training for students and postdoctoral fellows in the highly interdisciplinary field of molecular biophysics.Structure based models (SBMs) have been shown to be a useful tool for understanding the global geometrical features governing folding. Grounded on energy landscape theory (ELT) and the funnel concept, these models are supported by the fact that most naturally occurring proteins have sufficiently reduced energetic frustration. Structure-based models are limited by the availability of structural information, particularly those pertaining to all the different functional configurations. Direct Coupling Analysis (DCA) may predict amino acid contacts in proteins. The research is based on SBMs supplemented by DCA information and integrated with explicit solvent all-atom simulations. The project focuses on proteins and several biomolecular machines. Finally, inspired by the early successes of this approach to proteins and other molecular machines, an important goal of this project deals with chromosome folding and function.