Efficient Parallel Computation of Molecular Potential Energy Surfaces for the Study of Light-Induced Transition Dynamics in Multiple Coordinates

The conformational dynamics of molecules that arise due to light-induced transitions are critically important in many biochemical reactions, and therefore dictate the functionality of many types of biological sensors. Therefore, researchers of biological science and biological-inspired technology often need to prescribe the molecular geometry of the stable states and the associated transition trajectories that occur as a result of external excitation, e.g., light-induced transitions from the ground state to the excited states. The traditional approach to study this type of phenomenology is to limit the number of varying molecular coordinates to one or a few due to the considerable computational expense of the required physically modeling required for generating an accurate physical model for analysis. While the conformational dynamics for some types of simple molecules (e.g., retinal) are known to be adequately described by one or few numbers of molecular coordinates, light-induced transitions in arbitrarily complex molecules can be expected to involve the influence of multiple coordinates, and their influence can be expected to vary as a function of time. The research reported here will address the development of parallel computational algorithms that allow for the highly efficient study of molecular conformational dynamics over multiple numbers of multidimensional energy surfaces. Here, the goal is the development of a simulation tool that is capable of: constructing physically accurate multidimensional potential energy surfaces (i.e., from first-principle physical modeling codes); deriving the natural trajectories to local minima within individual surfaces; and that allows for dynamics human interfacing for specifying the transition between energy surfaces and the number of coordinates to be used for the optimization within a particular energy surface. As will be illustrated, this type of physics-based simulation tool will allow researchers to efficiently explore the light-induced conformation dynamics associated with complex biomolecules, and therefore, be a useful tool for the design of biological-sensing processes in the future.