CycPepFlow: Reconciling Ring Coupling and Stereochemical Fidelity in Cyclic Peptide Ensemble Generation

Cyclic peptides are promising therapeutic scaffolds, but generating their conformational ensembles requires capturing long-range ring coupling while preserving local chemical geometry and stereochemistry. We introduce CycPepFlow, an all-atom Cartesian flow model that generates conformers directly from molecular graphs. CycPepFlow combines SO(3)-equivariant local interactions with gated global attention, while atomic chirality conditioning and signed-volume supervision promote tetrahedral stereochemical fidelity. An optional all-pair graph-geodesic attention bias (APG) incorporates pairwise topology into global communication. Evaluated on 1,000 held-out CREMP cyclic peptides containing four to six residues, CycPepFlow-L achieves the highest coverage F1 among the compared methods (76.13%), whereas CycPepFlow APG-L achieves the highest generated-set coverage precision (79.78%) and lowest generated-to-reference matching distance (0.419 Å). On the six-residue subset, APG-L achieves the best coverage F1 (61.61%) together with 99.71% conformer-level tetrahedral accuracy. CycPepFlow thus combines broad reference-ensemble coverage with high generated-set precision and stereochemical fidelity, with its six-mer performance highlighting the potential for extension to larger macrocycles.