Year: 2026
Type: preprint
Abstract: Motif scaffolding builds a protein around a prescribed structural motif — an active site, a binding epitope, a metal site — so that the motif is presented in its required geometry. The task is usually posed with the motif pinned down: its position along the sequence is given, and several rigid fragments inherit their mutual pose from a native structure. Many applications supply neither. We present NomadFlow , unindexed multi-motif scaffolding on all-atom SE(3) flow matching: the motif enters as a condition, a group projection preserves the internal geometry of each group exactly, and the groups move freely relative to one another until a set time, after which they act only as a condition. We assemble a preliminary benchmark for this setting, varying the granularity of the partition and the structural context around the motif, and obtain unique successes on 19 of 21 tasks. The trained model proposes a diversity of valid mutual poses, and on several tasks the native arrangement is among them. The shape of that solution space, however, varies strongly with the geometry of the condition: across tasks the successful layouts form a wide cloud, collapse onto the native pose, or contract to a connected low-dimensional family — a continuum of poses rather than a set of isolated solutions. Multi-motif methods are therefore better compared by the space of layouts they propose and the successful part of it they retain than by yield or fold diversity alone. Code and weights: https://github.com/ipermyakov/nomadflow . Significance statement A protein built around several functional fragments is given the shape of each piece but not their relative placement. The strongest methods are told what the motif looks like, but not where in the chain it goes. We adapt one such model so each rigid group moves relative to the others. On a preliminary benchmark for this setting it succeeds on 19 of 21 tasks, and the freedom it uses depends sharply on the motif.
Institution: Lomonosov Moscow State University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Award: G4824996115
OpenAlex ID: W7220905495