Grid convergence of PyGBe with immunoglobulin G near a charged surface

2015-03-25T14:28:54Z (GMT) by Christopher D. Cooper Lorena A. Barba
<p>Reproducibility package containing data, running script, plotting script and final plot of grid-convergence study for immunoglobulin G near a charged surface.</p><p>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.</p> <p>This result is part of the publication:</p><p>—<strong>"Probing protein orientation near charged nanosurfaces for simulation-assisted biosensor design,"</strong> Christopher D. Cooper, Natalia C. Clementi, Lorena A. Barba; <i>J. Chem. Phys</i>., Vol. 143: 124709 (2015)</p> <p>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.</p> <p> </p> <p>More information about the PyGBe code in:</p> <p><em>—"Validation of the PyGBe code for Poisson-Boltzmann equation with boundary element methods,"</em> Christopher Cooper, Lorena A. Barba. figshare.<br></p> <p>—</p> <p>—"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. <em>Comput. Phys. Comm.</em>, <strong>185(</strong>3):720–729 (March 2014). 10.1016/j.cpc.2013.10.028 // Preprint arXiv:1309.4018</p> <p><strong>Acknowledgement:</strong><br>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.</p> <p> </p>