Many proteins function as molecular machines. Understanding the principles that control the machinery of biomolecular systems is a computational challenge in many cases due to the involvement of macromolecular structures composed of multiple subunits and cooperative interactions manifested by allosteric changes in conformations, which are beyond the range of atomic simulations. Our goal in a recently funded R33 has been to develop and utilize low resolution models for exploring the collective dynamics of such complex systems, and bridging between structure and function, based on the paradigm structure-encodes-dynamics-encodes-function. The elastic network models and methods we introduced to this aim have found utility in many applications and helped us gain insights into the intrinsic, structure- encoded ability of proteins to favor the reconfiguration of native structures between functional substates. In the present R01, we are proposing to build on our previous work, to further explore the structure ->dynamics ->function mapping of allosteric and/or multimeric proteins using physically-based and computationally efficient models in collaboration with the NCBC Simbios at Stanford U (PI: Altman). The Simbios group has already started to construct a new simulation package, Simbody, the utility of which is expected to be significantly enhanced by a collaborative work.
Our specific aims are (1) to build models and methods for automated coarse-graining of complex structures at multiple levels of resolution and assessing their collective dynamics, toward using the resulting models (structure) and data (motions) in Simbody;(2) to complement the physics-based approach developed in Aim 1 by information-theoretic approaches toward delineating signal transduction pathways/mechanisms in allosteric systems, and establishing the connection between these pathways and structural dynamics, and (3) to gain insights into the machinery of molecular chaperones, using as prototypes the bacterial chaperonin GroEL-GroES and the DnaK chaperone system, in collaboration with the Gierasch lab currently doing NIH-supported experiments for understanding the allosteric dynamics of the DnaK system. An important outcome of this project will be the establishment of a methodology for simulating the machinery of biomolecular systems on the order of Megadaltons, which will be achieved in collaboration with the Schulten lab, in addition to our partnership with the Simbios team.
Many proteins function as molecular machines. Understanding the dynamics or underlying molecular principles of these machines is a challenge due to the highly cooperative nature of interactions, which simultaneously involve multiple molecules. The aim of this project is twofold: to develop and implement computational models and methods to improve our understanding of the collective dynamics of proteins;and to elucidate the machinery of molecular chaperones - molecular systems that play an essential role in cellular physiology by assisting the folding and assembly/disassembly of proteins and directing them to transport and degradation pathways. These aims will be pursued in collaboration with the National Center for Biomedical Computing Simbios at Stanford U.
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