Understanding Protein Folding: Quantitative Connections Between Energy Landscape Theory and Experiments

在过去的几年里，能量景观理论和漏斗概念的成功是巨大的，并改变了对蛋白质折叠问题的普遍理解。它已被证明，拓扑效应是中央在确定过渡态系综的结构细节蛋白质折叠。然而，这些结果中的大多数都是用C-α非晶格模型与能量未受抑序列获得的。虽然这些模型能够预测折叠机制的几何特征，但它们无法确定适当的能量性质，例如折叠势垒高度和原生状态或中间体的稳定性。 在这个项目中，新的模拟和分析方法将开发与一个家庭的帮助下的非格子最低限度的模型与不同层次的详细的蛋白质表示，从简单的C-α链的所有原子的描述，和各种选择的潜力。 通过探索折叠在不同层次的细节，能量和拓扑结构之间的相互作用如何控制折叠机制将获得定量的了解。为了验证这些模型的适用性，一套不同的蛋白质，具有不同程度的复杂性，将进行研究。这些蛋白质中的一些具有相同的天然结构，但显示出不同的折叠机制。蛋白质构成了控制生物体中大部分功能的机制。它们的活性取决于它们的三维结构和动力学，而不是直接取决于它们的氨基酸序列，这一事实为研究蛋白质功能提出了新的概念挑战。 能量景观理论和漏斗概念是定量理解蛋白质折叠问题所需的理论框架的核心。这种理论上的奋进现在已经足够先进，有可能对蛋白质折叠问题建立定量的理解。这种方法和实验之间的初步联系，表明拓扑结构在确定折叠机制中起着核心作用，令人鼓舞。通过进一步提高理论和计算的努力，一个定量的理解之间的相互作用，能量和拓扑结构控制的折叠将获得。 如果人们希望回答一个核心问题，那么就需要这样的进步：在什么水平上，一个模型才能足够好地预测一个没有实验信息的蛋白质的折叠机制？该项目由生物科学理事会分子和细胞生物科学部的分子生物物理学计划以及数学和物理科学理事会的物理学部支持。

OnuchicMCB 0084797 The success of energy landscape theory and the funnel concept during the last several years has been tremendous and has changed the general understanding of the protein folding problem. It has been demonstrated that topological effects are central in determining the structural details of the transition state ensemble for protein folding. Most of these results, however, have been obtained with C-alpha off-lattice models with energetically unfrustrated sequences. Although these models are able to predict the geometrical features of the folding mechanism, they are unable to determine appropriate energetic properties, such as folding barrier heights and stability of the native state or intermediates. In this project, new simulation and analytical methods will be developed with the help of a family of off-lattice minimalist models with different levels of detail in the protein representation, varying from simple C-alpha chains to all-atom descriptions, and various choices of potentials. By exploring the folding at different levels of detail, a quantitative understanding of how the interplay between energetics and topology controls folding mechanisms will be obtained. To verify the applicability of these models, a suite of different proteins, with different levels of complexity, will be studied. Some of these proteins have the same native structure but show distinct folding mechanisms. Proteins comprise the machinery that controls most of the functions in living organisms. The fact that their activity depends on their three-dimensional structure and dynamics and not directly on their amino-acid sequences presents novel conceptual challenges for studying protein function. Energy landscape theory and the funnel concept are at the center of the theoretical framework needed for a quantitative understanding of the protein folding question. This theoretical endeavor is now sufficiently advanced that it is possible to establish a quantitative understanding of the protein folding problem. The initial connections between this approach and experiments, that demonstrate that topology plays a central role in determining the folding mechanism, are encouraging. By further improving the theoretical and computational efforts, a quantitative understanding of how the interplay between energetics and topology controls the folding will be obtained. Such advances are needed, if one hopes to answer a central question: at what level will a model be sufficiently good to predict the folding mechanism of a protein for which no experimental information is available?This project is supported by the Molecular Biophysics Program in the Division of Molecular and Cellular Biosciences in the Directorate for Biological Sciences and the Division of Physics in the Mathematical and Physical Sciences Directorate.