trFlow: ultrafast all-atom protein conformational ensemble generation via conditional flow matching
- 1Shandong University
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.
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BibTeX
@misc{xiang2026trflow,
title = {{trFlow: ultrafast all-atom protein conformational ensemble generation via conditional flow matching}},
author = {C. Xiang and K. Zhao and Z. Peng and W. Wang and J. Yang},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.03.756422},
url = {https://www.biorxiv.org/content/10.64898/2026.10.03.756422v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - trFlow: ultrafast all-atom protein conformational ensemble generation via conditional flow matching
AU - C. Xiang
AU - K. Zhao
AU - Z. Peng
AU - W. Wang
AU - J. Yang
PY - 2026
DA - 2026/10/03
PB - bioRxiv
DO - 10.64898/2026.10.03.756422
UR - https://www.biorxiv.org/content/10.64898/2026.10.03.756422v1
AB - 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.
ER -