Neural relational inference to learn long-range allosteric interactions in proteins from molecular dynamics simulations

Abstract

Here, the authors apply a neural relational inference model to infer dynamic networks of interacting residues in protein molecular dynamics simulations. The model can predict allosteric communication pathways and relative free energy changes upon mutations.