Saving Significant Amount of Time in MD Simulations by Using an Implicit Solvent Model and Elevated Temperatures

Molecular dynamic simulations are used for investigating various aspects of biological processes. Such simulations often require intensive computer power; therefore several solutions were developed to minimize the computer power needed, including the usage of elevated temperatures. Yet, such simulations are still not commonly used by the wide scientific community of chemists and biochemists. For about two years now, the molecular simulations suite GROMACS enables conducting simulations using implicit solvent models to further decrease runtimes. In order to quantify the saving in computer power, and to confirm the validity of the models, we followed the simple dissolution process of a single NaCl molecule. The results reveal approximately 350-fold decrease in real-world runtime when using an implicit solvent model and an elevated temperature, compared to using explicit water molecules and simulating at room temperature. In addition, in a wide range of temperatures, the dissolution times of NaCl are distributed, as expected, exponentially, both in explicit and in implicit solvent models, hence confirming the validity of the simulation approach. Hopefully, our findings will encourage many scientists to take advantage of the recent progress in the molecular dynamics field for various applications. 1. Introduction Molecular dynamics (MD) is the computer simulation of the physical movements of molecules. The molecules’ atoms are allowed to interact for a period of time, and the trajectories of the motion of the system are followed. In order for an MD simulation to be meaningful, the run has to be long enough for the system to visit all the energetically relevant conformations; that is, the system has to be ergodic in the timescale of the simulation [1]. An important benefit of the ergodicity of the system is that it allows MD to follow only one copy of the molecule instead of looking at a snapshot of many copies of the molecule. On the other hand, very long runtimes are required in order to achieve ergodicity, since the time step of the simulation has to be short enough to allow following the fastest motion of the system, namely, bond stretching and bond bending. These short time steps impose working in femtosecond resolution. However, “interesting” biochemical processes typically take at least microseconds and sometimes even milliseconds. Therefore, MD simulations of biochemical processes require intensive calculations and thus depend on expensive and hard-to-achieve hardware. To resolve this, various approaches were developed ranging from special-purpose