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

<p><strong>Publication:</strong>&nbsp;MLLPA: A Machine Learning-assisted Python module to study phase-specific events in lipid membranes</p> <p><strong>Published on:</strong>&nbsp;08 April 2021</p> <p><strong>Journal</strong>: <em><a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.26508">J Comp Chem</a>, </em>2021, DOI:&nbsp;10.1002/jcc.26508</p> <p><strong>Description</strong>: Simulation files used to train our Python module&nbsp;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&nbsp;<a href="https://vivien-walter.github.io/mllpa/">its website</a>.</p> <p>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.</p> <p><strong>System composition:</strong></p> <ul> <li>DPPC molecules:&nbsp;256 with 130 atoms each</li> <li>Water molecules:&nbsp; 42,492 with 3&nbsp;atoms each&nbsp;</li> <li>Simulation box dimensions (approx.): 9&nbsp;x 9&nbsp;x 20 nm</li> </ul> <p><strong>Simulation details:</strong></p> <ul> <li>Software: Gromacs (v. 2020)</li> <li>Forcefield: Charmm36 (v. June 2015) - Water: TIP3P</li> <li>Thermostat: Nose-hoover (0.4ps, 2 groups)</li> <li>Barostat: Parrinello-Rahman semi-isotropic (2.0ps, 1.0 bar on each axis, 4.5e-5 bar-1)</li> <li>Duration: 25&nbsp;ns (after stabilisation)</li> </ul>