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Compare Conformation Ensembles
g_dice is a tool written using GROMACS APIs to quantify differences between two conformational ensembles. Quanitification is in terms of a true metric that satisfies the conditions set forth by the zeroth law of thermodynamics. The metric is normalized and takes up a value closer to unity as the difference between the ensembles increases. The two ensembles are provided as two trajectory files (supported formats=xtc,trr,pdb). Consult the README file in the package for installation and usage instructions.
v3.0.0
Jan 09, 2017

- Added residue eta calculation (average eta per residue). - New struct-based API. - Cache optimized svm training data (svm problems structs). - Fixed memory leaks in svm training. - Added -nthreads option to set the number of threads to use at runtime. - Atom IDs are output next to eta values. - Shows progress while constructing svm problem structs (can take a long time for large trajectories). - Added failure handling to large memory allocations. - Added functions for freeing svm data. - Added regression test.  View License

PLEASE CITE THESE PAPERS

S. Varma, M. Botlani and R.E. Leighty, Discerning intersecting fusion-activation pathways in the Nipah virus using machine learning. Proteins. 82: 3241-3254 (2014) View

R.E. Leighty and S. Varma, Quantifying changes in intrinsic molecular motion using support vector machines. J Chem. Theory and Comput. 9: 868-875 (2013) View

ADDITIONAL PAPERS

P. Dutta, A. Siddiqui, M. Botlani and S. Varma, Stimulation of Nipah Fusion: Small Intradomain Changes Trigger Extensive Interdomain Rearrangements. Biophys. J. 111: 1621–1630 (2016) View

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Tessellated surface area
g_tessellate_area is a code written using GROMACS APIs that calculates 3-d surface areas using Delaunay tessellation. It reads in a trajectory file through the -f option (supported formats=xtc,trr,pdb). The set of points for tessellation, such as the coordinates of phosphorous atoms, are specified using an index file by the -n option. Areas can be calculated individually for each frame in which case the output is dumped into an ASCII file specified by the -o option. This code can also be used for calculating the surface areas of lipid bilayers. In such a calculation, the lipid bilayer normal is assumed to be parallel to the z-axis. This assumption is made to include in the surface area the space between the atoms lying at the periphery of the unit cell and the boundary of the unit cell. The correction is performed by inserting points at regular intervals along the edges of the simulation box. To use this correction, set the boolean -corr. The -2d option will yield 2D projections on the XY plane - for a lipid bilayer perpendicular to the z-axis, the 2D projected area along with the -corr option will essentially yield the 2D area of the simulation cell. You can also set -espace X, where X is the desired spacing in nanometers of the edge correction point intervals (default = 0.8). An alternative way to calculate lipid surface areas is to map the coordinates on to a weighted 3D grid and tessellate the highest weight z-coordinates along the horizontal plane. The latter method is, however, still experimental and not supported. To use the experimental weighted grid method, set the -dense option. The tessellated surface can be visualized using the -print option. The resulting .node and .ele files are numbered by frame, and can be viewed by Jonathan R. Shewchuck''s program showme (found here: https://www.cs.cmu.edu/~quake/showme.html). WARNING, the -print option produces a .node and .ele file for EVERY frame AND disables parallelization! (So don''t be surprised when you come back hours later and see a hundred thousand new files in your current directory). If you build g_tessellate_area with OPENMP, you can set the number of threads to use with -nthreads X, where X is the number of threads to use. The default is to use the maximum number of cores available.
v1.0.0
Feb 18, 2016

First stable release.  View License

PLEASE CITE THESE PAPERS

N. Duro, M. Gjika, A. Siddiqui, H.L. Scott and S. Varma, POPC bilayers supported on nanoporous substrates: specific effects of silica-type surface hydroxylation and charge density. Langmuir. 32: 6766–6774 (2016) View


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