Computing Electrostatics of COVID-19 Proteins with Parallelized Boundary Integral Poisson-Boltzmann Solvers

The Poisson-Boltzmann (PB) model governs the electrostatics of solvated biomolecules, i.e., potential, field, energy, and force. These quantities can provide useful information about protein properties, functions, and dynamics. In this project, we investigate the practical application of the PB model on selected proteins that play significant roles in the spread, treatment, and prevention of COVID-19 virus diseases. To this end, we solved the boundary integral form of the PB equation on the molecular surfaces of the selected proteins. For each selected protein, the simulation produces the electrostatic solvation energy as a global measurement and electrostatic surface potential for local details. By considering the advantages of current algorithms and computer hardware, we focus on the parallelization of the treecode-accelerated boundary integral (TABI) solver using the Message Passing Interface (MPI) on CPUs and the parallelized direct-sum boundary integral (DSBI) solver using KOKKOS on GPUs. We provide guidance for users when the DSBI solver on GPU or the TABI solver with MPI on CPU should be used depending on the size of the problem. Specifically, when the number of unknowns is smaller than a predetermined threshold, the GPU-accelerated DSBI solver converges rapidly thus has the potential to perform PB model-based molecular dynamics or Monte Carlo simulation.