EvoDiff

Sequence-space diffusion: Operates directly in protein-sequence space rather than structure space, enabling generation of proteins that structure-based models can't reach.

Evolutionary-scale training: Trains on massive evolutionary protein datasets, leveraging the diverse biological sequence space as learning signal.

Controllable generation: Supports conditional generation on function, family, or motif constraints, giving researchers practical design levers.

Beyond structure-based models: Generates proteins that are inaccessible to structure-based generators (e.g., those without well-defined folds), expanding the design space.