CAREER: Toward Boltzmann-Weighted Protein Ensembles Using Novel Computations

University Of Pittsburgh, Pittsburgh PA

Investigators

Abstract

The objective of this CAREER project, jointly supported by Molecular Biophysics in the Division of Molecular and Cellular Biosciences in the Directorate for Biological Sciences and the Theoretical and Computational Chemistry Program in the Division of Chemistry in the Mathematical and Physical Sciences Directorate, is to continue development and use of novel computational approaches for equilibrium sampling of biomacromoleces, especially proteins. The final goal is to generate ensembles of canonically sampled protein structures, exhibiting full fluctuations. While it is widely appreciated that the full sampling of protein configurations is an extremely challenging problem, recent technical advances suggest the goal may finally be reachable. The Resolution Exchange algorithm and its variants, recently developed by Zuckerman and co-workers, represent a particularly promising class of algorithms for employing coarse-grained models to greatly accelerate rigorous statistical sampling (based on the Boltzmann factor) of standard atomically detailed representations of proteins. The use of coarse-grained protein models is critical, because these can be shown to permit extremely rapid full sampling of configuration space requiring less than one week of single-processor simulation for proteins with fewer than 100 residues. In addition to the Resolution Exchange approach, novel convergence assessment and re-weighting approaches will be employed. High-temperature sampling, moreover, can be directly incorporated into Resolution Exchange simulations. The education plan is to continue writing an introductory text on statistical mechanics for students of biophysics aimed at beginning graduate students or advanced undergraduates. Although statistical mechanics is arguably the fundamental science of molecular biophysics and simulation, there is an outstanding need for a text which is accessible to students from a wide variety of backgrounds (i.e., enrollees in inter-disciplinary graduate programs) and which also maintains the rigor and generality needed for students to grasp the fundamental concepts. The text will therefore focus on the molecular phenomena pertinent to biophysics, avoiding the emphasis on spin systems and phase transitions in many graduate statistical mechanics texts. Further, the text also will rely primarily on basic probability concepts rather than the more abstract terminology of thermodynamics, as has been traditional. The probability concepts are broadly applicable, permitting the student a strong grasp of concepts ranging from entropy and free energy to the connection between dynamics and equilibrium. Throughout the text, the correspondence with traditional nomenclature will be made clear, since this is absolutely necessary for scientific communication and the understanding of the literature.