Liftoff.bio illustration — cat ai models

BoltzGen

Toward universal binder design across modalities

What's new

A generative design counterpart to Boltz covering proteins, peptides, antibodies, nanobodies and small-molecule binders.

BoltzGen aims to be a universal binder-design model. From the authors of Boltz, it supports several design protocols out of the box.

Protocols

  • protein-anything — design proteins to bind arbitrary targets.
  • protein-small_molecule — design proteins to bind small molecules.
  • antibody / nanobody — design CDRs for antibody and nanobody formats.
  • redesign — optimise or redesign existing proteins.

MIT licensed, with high reported hit rates at the cost of more inference compute than fast backbone models.

Related tools

Liftoff.bio illustration — cat ai models
Open source

AI Models

Boltz-2

Open-source structure and binding-affinity prediction, MIT licensed

Python libraryCommand lineModel weights
Liftoff.bio illustration — post structure models
Open source

AI Models

BindCraft

One-shot de novo binder design with AlphaFold2 backpropagation

Python libraryCommand line
Liftoff.bio illustration — cat structural
Open source

AI Models

RFdiffusion

Generative diffusion for de novo protein backbone design

Python libraryCommand lineModel weights