LaCPlow: Geometry-Preserving Partially Latent Flow Matching for Cyclic Peptide Generation

Cyclic peptides share much of their local stereochemistry with linear peptides, but cyclization alters their covalent topology and reshapes their global conformations through sparse, nonlocal chemical constraints. Satisfying these constraints depends on the relative placement and orientation of linked residues. We propose LaCPlow, a target-conditioned partially latent flow model that explicitly transports residue frames while encoding sequence and residue-local atom coordinates in a continuous latent representation. A representation-aligned joint vector field couples these components by predicting rotational, translational, and latent velocities. Because chemistry-specific specialization depends on the capabilities of its substrate, we first evaluate LaCPlow-Base without cyclization-specific supervision to assess its geometric modeling capacity. We then introduce LaCPlow-Cyc, which incorporates cyclization-specific supervision. LaCPlow-Cyc improves bond-forming geometry while largely preserving the stereochemical quality of the base model.