2 papers
physics.chem-ph2026
Machine Learning Interatomic Potentials: Advancing Open-Source Software for Efficient and Scalable Molecular Simulation
Christoph Brunken, Titouan Cormier, Lucien Walewski +15
Machine learning interatomic potentials (MLIPs) enable atomistic simulations with near ab initio accuracy at significantly reduced computational cost, but their broader adoption is…
q-bio.BM2025
GeoGraph: Geometric and Graph-based Ensemble Descriptors for Intrinsically Disordered Proteins
Eoin Quinn, Marco Carobene, Jean Quentin +3
While deep learning has revolutionized the prediction of rigid protein structures, modelling the conformational ensembles of Intrinsically Disordered Proteins (IDPs) remains a key…