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

William Marsh Rice University, Houston TX

Investigators

Abstract

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.