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Article Dans Une Revue Journal of Computational Chemistry Année : 2021

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

Céline Ruscher
Olivier Benzerara
Fabrice Thalmann

Résumé

MLLPA is a new Python 3 module developed to analyse phase domains in a lipid membrane based on lipid molecular states. Reading standard simulation coordinate and trajectory files, the software first analyse the phase composition of the lipid membrane by using Machine Learning tools to label each individual molecules with respect to their state, and then decompose the simulation box using Voronoi tessellations to analyse the local environment of all the molecules of interest. MLLPA is versatile as it can read from multiple format (e.g. GROMACS, LAMMPS) and from either all-atom (e.g. CHARMM36) or coarse-grain models (e.g. Martini). It can also analyse multiple geometries of membranes (e.g. bilayers, vesicles). Finally, the software allows for training with more than two phases, allowing for multiple phase coexistence analysis.
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Dates et versions

hal-03597389 , version 1 (04-03-2022)

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Vivien Walter, Céline Ruscher, Olivier Benzerara, Fabrice Thalmann. MLLPA: A Machine Learning-assisted Python module to study phase-specific events in lipid membranes. Journal of Computational Chemistry, 2021, ⟨10.1002/jcc.26508⟩. ⟨hal-03597389⟩
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