EnsembleEGNN: Set-Based Graph Learning for Thermodynamic Ensembles of Cyclic Peptides

Excerpt

arXiv:2607.21561v2 Announce Type: replace Abstract: Molecular graph encoding often relies on a single, static structure, ignoring the thermodynamic ensemble of molecules that are present in solution. Here, we introduce EnsembleEGNN, a foundation model that encodes structural ensembles by processing individual conformers through shared equivariant graph neural network layers, pooled with a set attention block, to make property predictions from the whole ensemble. Pretrained on the CREMP cyclic pe