REINVENT4

GPT-style model trained on SAFE (fragment-based) molecular representation. Enables fragment-constrained design including scaffold decoration and linker generation.

Flow-based generative model that creates novel small molecule ligands for a target binding pocket. Generates hundreds of candidates in minutes.

Diffusion-based generative model for de novo protein backbone design. Generates novel protein structures conditioned on binding targets, symmetry, or functional sites.

Successor to RFdiffusion using flow matching. Designs enzymes directly from active site geometry (theozyme) specifications.

Inverse folding model: generates amino acid sequences predicted to fold into a target 3D backbone structure. Standard component of all modern protein design pipelines.