All Competitors

Transformer-based protein language diffusion model generating all-atom intrinsically disordered protein conformational ensembles, validated against experimental NMR and SAXS data.

A sequence-to-ensemble predictor that generates experiment-consistent conformational ensembles of intrinsically disordered proteins by pairing deep-learning fragment prediction with physics-aware assembly.

Rigidity-aware geometric pretraining framework that front-loads SE(3) geometry learning to improve protein backbone generation, motif scaffolding, and conformational ensemble modeling.

Lightweight variant of AlphaFlow achieving ~47x faster conformational ensemble sampling by fine-tuning only AlphaFold's structure module with frozen Evoformer.

AlphaFold fine-tuned with flow matching to generate conformational ensembles, capturing protein dynamics and flexibility beyond single static structures.