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

<strong>Publication:</strong> MLLPA: A Machine Learning-assisted Python module to study phase-specific events in lipid membranes <strong>Published on:</strong> 08 April 2021 <strong>Journal</strong>: <em>J Comp Chem, </em>2021, DOI: 10.1002/jcc.26508 <strong>Description</strong>: 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. <strong>System composition:</strong> 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 <strong>Simulation details:</strong> 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)