Coarse-grained Simulation data (part 1 of 2) for "Long-chain GM1 gangliosides alter transmembrane domain registration through interdigitation"

Coarse-grained simulation data for the paper "Long-chain GM1 gangliosides alter transmembrane domain registration through interdigitation", Biochimica et Biophysica Acta (BBA) - Biomembrane Volume 1859, Issue 5, May 2017, Pages 870–87, DOI: 10.1016/j.bbamem.2017.01.033

The simulations were performed using GROMACS 5.0.x [1]. The Martini force field [2,3] was employed.

This part (1/2) of the upload contains data for the 10 replica simulations of the system with a larger concentration (6%) of GM1 with an extended tail and for the control system without GM1. Trajectories, each 10 (no GM1) or 20 (6% GM1 with extended tail) microseconds long with frames stored every 1 ns, are given in xtc format. For both systems, a common run input file is given in the tpr format for analysis, although the initial structures of the replicas are different. These files are compatible with GROMACS 5. Common index files for each system type are given in ndx format and common topology files for each system type in top format. Simulation parameters, common for all simulated systems, are given in the mdp file. The simulation parameters for the system without GM1 are identical except for the larger integration time step (25 fs). The itp files can be obtained from the Martini homepage http://cgmartini.nl/ 

The file names denote what kind of tail was used (normal vs. extended), the concentration of GM1 (1.5% (1) vs. 6% (6)), and the replica simulations are numbered from 1 to 10. For the systems without GM1 (NoGM1), the concentration is obviously not given, and there are only 8 replicas.

Note that the NoGM1-2.xtc simulation contains data every 2 ns, while others contain data every 1 ns.

Part 2 of this upload is available at https://doi.org/10.5281/zenodo.831712.

[1] M.J. Abraham et al., GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 2015, 1–2, pp. 19–25, DOI: 10.1016/j.softx.2015.06.001 

[2] S.J. Marrink et al., The MARTINI Force Field:  Coarse Grained Model for Biomolecular Simulations. J. Phys. Chem. B, 2007, 111, pp 7812–7824, DOI: 10.1021/jp071097f

[3] C.A. López et al., Martini Force Field Parameters for Glycolipids. J. Chem. Theory Comput., 2013, 9, pp 1694–1708, DOI: 10.1021/ct3009655