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

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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.