In this project, funded by the Condensed Matter and Materials Theory Program, a new method is proposed for extracting free energies from molecular dynamics (MD) simulations. The method is based on temperature-acceleration, wherein free energy gradients in some desired set of collective variables are sampled in a running MD simulation while simultaneously driving those collective variables over free energy barriers that would otherwise render traditional MD hopeless at such sampling. These gradients are used as inputs into an optimization that minimizes the error associated with gradients of an analytical free energy by evolving that free energy?s parameters. The method therefore takes as input an MD system, the definitions of whatever collective variables in which one would like to know the free energy, and a functional form for that free energy, and then the method produces the optimal set of parameters. The method is formulated in a general way and is therefore expected to be applicable broadly to almost any desired collective variables. This project will be devoted to developing this method particularly for applications involving deriving effective coarse-grained potentials for multiscale simulations and to the study of conformational statistics of large biomolecules. The project will also provide training and mentoring of underrepresented students in state of the art computational and numerical methods

NON-TECHNICAL SUMMARY

Whether in designing new drugs or new materials, or simply trying to understand how Nature works, computer simulations are important in understanding how matter behaves at the molecular level. Bringing such molecular-level understanding into the realm of everyday perception requires statistical approaches that are not always straightforward and often quite expensive. This project proposes a new statistical method for extracting information from molecular-level simulations. The method is potentially much more efficient than existing approaches. The research undertaken in this project will develop and apply this method to test systems relevant for biological and materials applications. The project could significantly reduce the cost associated with obtaining high-quality information from simulations at the molecular level that at the intersections of chemistry, physics, and biology. The project will also provide training and mentoring of underrepresented students in state of the art computational and numerical methods. This work is supported by the Condensed Matter and Materials Theory Program.

Agency
National Science Foundation (NSF)
Institute
Division of Materials Research (DMR)
Type
Standard Grant (Standard)
Application #
1207432
Program Officer
Daryl W. Hess
Project Start
Project End
Budget Start
2012-09-01
Budget End
2015-08-31
Support Year
Fiscal Year
2012
Total Cost
$198,411
Indirect Cost
Name
New York University
Department
Type
DUNS #
City
New York
State
NY
Country
United States
Zip Code
10012