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July 18th, 2025
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CBI-LMGM, CNRS, Universite Toulouse
bioinformatics
biorxiv

Fast parameterization of Martini3 models for fragments and small molecules

Szczuka, M.Open in Google Scholar•pereira, g. P.Open in Google Scholar•Walter, L. J.Open in Google Scholar•Gueroult, M.Open in Google Scholar•Poulain, P.Open in Google Scholar•Bereau, T.Open in Google Scholar•De Souza, P. T.Open in Google Scholar•Chavent, M.Open in Google Scholar

Coarse-grained molecular dynamics simulations, such as those performed with the recently parametrized Martini 3 force field, simplify molecular models and enable the study of larger systems over longer timescales. With this new implementation, Martini 3 allows more bead types and sizes, becoming more amenable to study dynamical phenomena involving small molecules such as protein-ligand interactions and membrane permeation. However, while there were some solutions to automatically model small molecules using the previous iteration of Martini force field, there is no simple way to generate such molecules for Martini 3 yet. Here, we introduce Auto-MartiniM3, an advanced and updated version of the Auto-Martini program, designed to automate the coarse-graining of small molecules to be used with the Martini 3 force field. We validated our approach by modeling 81 small molecules from the Martini Database and comparing their structural and thermodynamic properties with ones obtained from models designed by Martini experts. Additionally, we assessed the behavior of Auto-MartiniM3-generated models by calculating solute translocation and free energy across lipid bilayers. We also evaluated more complex molecules such as caffeine by testing its binding to the adenosine A2A receptor. Finally, our results from deploying Auto-MartiniM3 on a large dataset of molecular fragments demonstrate that this program can become a tool of choice for fast high-throughput creation of coarse-grained models of small molecules, offering a good balance between automation and accuracy. Auto-MartiniM3 source code is freely available at https://github.com/Martini-Force-Field-Initiative/Automartini_M3

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