2021/03/01 by Tingyu Wang, Wang, Tingyu, Christopher D. Cooper +5
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · Environmental Science · #Bacteriophages and microbial interactions #Biological Physics (physics.bio-ph) #Computational Engineering #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Finance #Plant Virus Research Studies #Protein Structure and Dynamics #and Science (cs.CE)
paper · pdf · doi:10.48550/arxiv.2103.01048
openalex publication_date 2021/03/01 · openalex created_date 2021/03/15 · openalex updated_date 2026/07/28
Biomolecular electrostatics is key in protein function and the chemical processes affecting it. Implicit-solvent models via the Poisson-Boltzmann (PB) equation provide insights with less computational cost than atomistic models, making large-system studies -- at the scale of viruses -- accessible to more researchers. Here we present a high-productivity and high-performance linear PB solver based on Exafmm, a fast multipole method library, and Bempp, a Galerkin boundary element method package. The workflow integrates an easy-to-use Python interface with optimized computational kernels, and can be run interactively via Jupyter notebooks, for faster prototyping. Our results show the capability of the software, confirm code correctness, and assess performance with between 8,000 and 2 million elements. Showcasing the power of this interactive computing platform, we study the conditioning of two variants of the boundary integral formulation with just a few lines of code. Mesh-refinement studies confirm convergence as 1/N, for N boundary elements, and a comparison with results from the trusted APBS code using various proteins shows agreement. Our binding energy calculations using 9 various complexes align with the results from using five other grid-based PB solvers. Performance results include timings, breakdowns, and computational complexity. Exafmm offers evaluation speeds of just a few seconds for tens of millions of points, and O(N) scaling. The trend observed in our performance comparison with APBS demonstrates the advantage of Bempp-Exafmm in applications involving larger structures or requiring higher accuracy. Computing the solvation free energy of a Zika virus, represented by 1.6 million atoms and 10 million boundary elements, took 80-min runtime on a single compute node (dual 20-core).