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Protein orientation near a charged surface using PyGBe and protein G B1 D4

Version 6 2015-09-21, 18:06
Version 5 2015-09-21, 18:06
Version 4 2015-03-25, 14:25
dataset
posted on 2015-09-21, 18:06 authored by Christopher D. Cooper, Lorena A. BarbaLorena A. Barba

Reproducibility package containing data, running script, plotting script and final plot of the protein-orientation study for protein G B1 D4' near a charged surface.

The running script invokes the open-source bioelectrostatics solver PyGBe with the given input data, computes the orientation probability distribution and plots the final result.

The file set includes:

—1 mesh, 2 bodies
—PQR file
—mesh-generation script for sensor surface
—input parameters and running script for mesher
—input file for PyGBe and running script
—CSV file of output (tilt, rotation, energy)
—Figure 11 of the paper and plotting script 

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.

http://dx.doi.org/10.6084/m9.figshare.154331

—"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

 

Acknowledgement:

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.

Funding

ONR N00014-11-1-0356

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