Nature Communications · 2025 · 52 citations · 102 references
Natural SciencesBiochemistryBiophysicsComputational BiophysicsStructural BiologyStructural BiophysicsCoarse-grained ModelingConformational SamplingMolecular DynamicsProtein DynamicsProtein StructureProtein Structure ModelingCoarse-grained SimulationComputational EfficiencyEnvironmental BiasMolecular Dynamics Of ProteinsProtein Coarse-grainingProtein Conformational ChangesProtein Dynamics ModelingVirtual Site Simulation
Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The GōMartini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced GōMartini model, which combines a virtual-site implementation of Gō models with Martini 3. The implementation has been extensively tested by the community since the release of the reparametrized version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with Gō models. This work presents GōMartini 3, an improved coarse-grained protein model combining physics- and structure-based approaches. It boosts computational efficiency and accuracy for structured soluble and membrane as well as disordered peptides/proteins.
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Canonical sampling through velocity rescaling
Giovanni Bussi, Davide Donadio, Michele Parrinello · The Journal of Chemical Physics · 2007 · 18.4K citations · Full text
Natural Sciences, Chemistry, Physics +17