Interpolation of Potential Energy Surfaces for Nonadiabatic Simulations of Biological Systems

Abstract

Simulations of photophysical processes in biological systems are essential for understanding the role of molecular environment regarding the utilization of the light energy. However, such simulations are challenging in part due to the associated high computational costs, especially with the often adopted ab initio calculations of excited state potential energy information. Here, an application of a scheme for interpolating diabatic Hamiltonian matrix will be presented. We will show that this method is applicable for a sizeable molecular system (with 21 atoms) with a capability of describing the conical intersection properly and with an extensibility to condensed phase situations, by testing it with a model analytic potential energy surface of the green fluorescent protein chromophore. A procedure for using high-level quantum chemical calculations in the interpolation of diabatic Hamiltonian will also be presented together with the results of trajectory hopping simulations. Finally, we will discuss how this approach can be applied to computational studies of other photobiological systems.