Published December 1, 2020 | Version v1

256 DPPC Molecules bilayer in pure Water, simulated at 288K (gel) or 358K (fluid)

  • 1. King's College London (UK)
  • 2. Institut Charles Sadron (FR)

Description

Publication: MLLPA: A Machine Learning-assisted Python module to study phase-specific events in lipid membranes

Published on: 08 April 2021

Journal: J Comp Chem, 2021, DOI: 10.1002/jcc.26508

Description: Simulation files used to train our Python module to identify the thermodynamic phase of individual lipid molecules in a bilayer, as well as the simulation files analysed by the machine learning models. More information on the module can be found on its website.

The training files are named dppc_gel.gro and dppc_fluid.gro. They respectively correspond to the final frame of the systems simulated at 288K and 358K. All other files are the files analysed by the module.

System composition:

  • DPPC molecules: 256 with 130 atoms each
  • Water molecules:  42,492 with 3 atoms each 
  • Simulation box dimensions (approx.): 9 x 9 x 20 nm

Simulation details:

  • Software: Gromacs (v. 2020)
  • Forcefield: Charmm36 (v. June 2015) - Water: TIP3P
  • Thermostat: Nose-hoover (0.4ps, 2 groups)
  • Barostat: Parrinello-Rahman semi-isotropic (2.0ps, 1.0 bar on each axis, 4.5e-5 bar-1)
  • Duration: 25 ns (after stabilisation)

Files

Files (6.0 GB)

Name Size
md5:1886d2656b4667ea8766123609be21c0
11.1 MB Download
md5:2b6744855e6d1fdac692811c7f6fd405
4.6 MB Download
md5:3cc027a3c568291c56c7215e7d054d4e
3.0 GB Download
md5:a7144e8c7f79743f7a4dc432e5e3e6c1
11.1 MB Download
md5:74ea8c7047a4de641c7ed66184c1dd0a
4.6 MB Download
md5:043b4ddde6fe1ea50152489fd1b68954
3.0 GB Download