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

OnuchicMCB 0084797能量景观理论和漏斗概念在过去的几年中取得了巨大的成功，并改变了人们对蛋白质折叠问题的一般理解。已经证明，拓扑效应是决定蛋白质折叠过渡态系综结构细节的核心。然而，这些结果中的大多数都是用具有能量不受挫序列的C-α非晶格模型获得的。尽管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，如折叠势垒高度和天然状态或中间体的稳定性。在这个项目中，将在一系列非晶格极简模型的帮助下开发新的模拟和分析方法，这些模型在蛋白质表示中具有不同程度的细节，从简单的C-阿尔法链到全原子描述，以及各种势的选择。通过探索不同细节水平的折叠，将获得对能量学和拓扑之间的相互作用如何控制折叠机制的定量理解。为了验证这些模型的适用性，将研究一组不同复杂程度的不同蛋白质。其中一些蛋白质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大部分功能的机械。它们的活性依赖于它们的三维结构和动力学，而不是直接依赖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中心。这一理论努力现在已经足够先进，有可能建立对蛋白质折叠问题的定量理解。这种方法与实验之间的初步联系令人鼓舞，这些实验表明，拓扑在决定折叠机制中发挥着核心作用。通过进一步改进理论和计算工作，将获得对能量学和拓扑学之间的相互作用如何控制折叠的定量理解。如果人们希望回答一个核心问题，就需要这样的进展：在什么水平上，一个模型将足够好地预测蛋白质的折叠机制，而目前还没有实验信息？这个项目得到了生物科学局分子和细胞生物科学部的分子生物学计划和数学和物理科学局物理部的支持。

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.