  Motif scaffolding seeks to design scaffold structures for constructing
proteins with functions derived from the desired motif, which is crucial for
the design of vaccines and enzymes. Previous works approach the problem by
inpainting or conditional generation. Both of them can only scaffold motifs
with fixed positions, and the conditional generation cannot guarantee the
presence of motifs. However, prior knowledge of the relative motif positions in
a protein is not readily available, and constructing a protein with multiple
functions in one protein is more general and significant because of the
synergies between functions. We propose a Floating Anchor Diffusion (FADiff)
model. FADiff allows motifs to float rigidly and independently in the process
of diffusion, which guarantees the presence of motifs and automates the motif
position design. Our experiments demonstrate the efficacy of FADiff with high
success rates and designable novel scaffolds. To the best of our knowledge,
FADiff is the first work to tackle the challenge of scaffolding multiple motifs
without relying on the expertise of relative motif positions in the protein.
Code is available at https://github.com/aim-uofa/FADiff.
