Collaborative Research: On-The-Fly free Energy Parameterization in Molecular Aimulations

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TECHNICAL SUMMARYThis award supports computational and theoretical research and education with an aim to develop a new method for extracting free energies from molecular dynamics simulations. The method is based on temperature-acceleration, wherein free energy gradients in some desired set of collective variables are sampled in a running molecular dynamics simulation while simultaneously driving those collective variables over free energy barriers that would otherwise render traditional molecular dynamics ineffective. These gradients are used as inputs into an optimization procedure that minimizes the error associated with gradients of an analytical free energy.The major thrusts of the research are: (1) benchmark the performance of the method against alternative approaches for computing coarse grained potentials, such as iterative Boltzmann inversion and force-matching, (2) developing the method as a tool for deriving potentials of mean force for multiscale polymer molecular simulations, and (3) developing the method as a means of statistical evaluation of large-scale protein conformational sampling.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. All simulation codes developed in this project will be made freely available to the community.This award also supports training and mentoring of underrepresented students in state of the art computational and numerical methods.NON-TECHNICAL SUMMARYThis award supports computational and theoretical research and education with an aim to develop a new method of extracting information from computer simulations. 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 molecular-level understanding into the realm of everyday perception requires statistical approaches that are not always straightforward and often computationally quite expensive. This award supports developing a new statistical method for extracting information from molecular-level simulations. The method is potentially much more efficient than existing approaches. The research 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. All simulation codes developed in this project will be made freely available to the community.This award also supports training and mentoring of underrepresented students in state of the art computational and numerical methods.