Molecular Ensemble Modeling: Single-Conformation Property Prediction Is Leaving Signal on the Table for Cyclic Peptides

arXiv 2607.21561·low signal

Aaron Feller, Kris Deibler and Maxim Secor investigate graph learning over conformational ensembles of cyclic peptides, challenging the standard practice of predicting molecular properties from a single representative conformation. Cyclic peptides are a hard case because they genuinely populate multiple conformations in solution. The finding matters for drug-discovery ML teams deciding whether ensemble generation is worth the compute over single-conformer pipelines.