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Martini developer trying to make CG models more useful for molecular design and drug/vaccine delivery 🖥️+🍸=💊💉 | Group leader at CBPsmn/ENS de Lyon | CNRS Researcher at DAMM team of LBMC/ENS de Lyon | Scientific consultant

🚀 Sponsorship opportunities still available 📍 Lyon, France | 14–16 October 2026 Registration opening soon. Stay tuned for further announcements! #CGML2026 #MachineLearning #MolecularModeling #CoarseGrained #DrugDiscovery #Formulations #MaterialsScience

Our paper on [Bentopy](doi.org/10.1002/pro....) is out in Protein Science! We developed Bentopy to make assembling large-scale MD models more accessible, building on what we learned from trying to simulate whole-cell models. Here's our updated Martini JCVI-syn3A cell model👇

Our collective work with @tbereau.bsky.social and @pauloctsouza.bsky.social labs to automatically parametrize CG models of small molecules is now published in JCTC! Nice Christmas present for 1st author @szczukam.bsky.social and all the coauthors! pubs.acs.org/doi/full/10....

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 time scales. With this new implementation, Martini 3 allows more bead types and sizes, becoming more amenable to studying dynamical phenomena involving small molecules such as protein–ligand interactions and membrane permeation. However, while solutions existed to automatically model small molecules using the previous iteration of the 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 simple molecules from the Martini Database and comparing their structural and thermodynamic properties with those 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 data set 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.

Looking forward to #acsfall2025! Hoping to finally meet in person the colleagues I’ve long admired at the @acscomp.bsky.social reception Sunday as well. 😄🍸

🔬 Coarse-Grained Modeling @ ACS Fall 2025 — Program Out Now! 🚀 📍 Washington DC | Aug 17–21 - Wed, Aug 20 AM: LNPs — nucleic acid delivery → viral entry simulations - Wed, Aug 20 PM: Proteins & multiscale modeling - Thu, Aug 21 AM: Methods & industry