trRosetta is an algorithm for fast and accurate protein structure prediction. It builds the protein structure based on direct energy minimizations with a restrained Rosetta. The restraints include inter-residue distance and orientation distributions, predicted by a deep neural network. Homologous templates are included in the network prediction to improve the accuracy further. In benchmark tests on CASP13 and CAMEO derived sets, trRosetta outperforms all previously described methods. Read more about trRosetta...
The top PDB templates (when detected) and the multiple sequence alignment used trRosetta
09/16/2021, A new paper to summarize the latest development of trRosetta was accepted to Advanced Science. All training codes, training data, pre-trained models and inference codes can be downloaded here.
08/31/2021, A new paper with detailed guidelines for using the trRosetta server and the standalone package was accepted to Nature Protocols.
06/24/2021, A new version of the trRosetta standalone package was released: download here.