Grid convergence of PyGBe with immunoglobulin G near a charged surface
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Reproducibility package containing data, running script, plotting script and final plot of grid-convergence study for immunoglobulin G near a charged surface.
The running script invokes the open-source bioelectrostatics solver PyGBe with the given input data, computes the extrapolated value of solvation plus surface energy (with Richardson extrapolation), and plots the final result of convergence.
This result is part of the publication:
—"Probing protein orientation near charged nanosurfaces for simulation-assisted biosensor design," Christopher D. Cooper, Natalia C. Clementi, Lorena A. Barba; J. Chem. Phys., Vol. 143: 124709 (2015)
PyGBe solves biomolecular electrostatics problems using an implicit-solvent model (Poisson-Boltzmann) and it uses GPU hardware for fast execution. It is written in Python, PyCUDA and CUDA.
More information about the PyGBe code in:
—"Validation of the PyGBe code for Poisson-Boltzmann equation with boundary element methods," Christopher Cooper, Lorena A. Barba. figshare.
—"A biomolecular electrostatics solver using Python, GPUs and boundary elements that can handle solvent-filled cavities and Stern layers", Christopher D. Cooper, Jaydeep P. Bardhan, L. A. Barba. Comput. Phys. Comm., 185(3):720–729 (March 2014). 10.1016/j.cpc.2013.10.028 // Preprint arXiv:1309.4018
This research is made possible by support from the Office of Naval Research, Applied Computational Analysis Program, N00014-11-1-0356. LAB also acknowledges support from NSF CAREER award OCI-1149784.