The Journal of Chemical PhysicsBiophysicsPeer-reviewed journal article
Tutorial on quantifying and sampling biomolecular ensembles with ShapeGMM
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Abstract
Here we present a detailed workflow for clustering and enhanced sampling of biomolecular conformations using the ShapeGMM methodology. This approach fits a probabilistic model of biomolecular conformations rooted in the idea that the free energy can expressed in terms of local fluctuations in atomic positions around metastable states. We demonstrate using a single model system how to generate and fit equilibrium molecular dynamics simulation data. We then show how to use the resulting model to generate a reaction coordinate between two states, how to sample along that coordinate using Metadynamics using our size-and-shape PLUMED module, and how to cluster those biased conformations to give a refined equilibrium ShapeGMM model.
- assay: multiome
- research focus: trajectory inference
- approach: deep learning
- approach: statistical model
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