trFlow: ultrafast all-atom protein conformational ensemble generation via conditional flow matching

Abstract

Generating diverse, all-atom protein conformations remains challenging, especially for recovering alternative functional states and modeling conformational ensembles. We present trFlow, an ultrafast approach for generating all-atom conformations using geometry-guided flow matching. trFlow leverages three core innovations: (1) a hybrid single- and multi-step sampling scheme that balances accuracy and speed; (2) a decoupled representation-generation architecture that maximizes computational efficiency; and (3) fine-tuning on NMR ensembles to better capture conformational heterogeneity. Extensive benchmarking across dual-conformation proteins, NMR ensembles, and a CASP16 dynamic target shows that trFlow outperforms competing methods in recovering challenging states and reproducing experimental heterogeneity, while being an order of magnitude faster than existing all-atom approaches. These results establish trFlow as a practical and scalable framework for large-scale generation of all-atom conformational ensembles.