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. 2022 Aug 3;122(18):14085–14179. doi: 10.1021/acs.chemrev.1c00757

Figure 34.

Figure 34

Network architecture and performance of RoseTTAFold. (A) RoseTTAFold architecture with 1D, 2D, and 3D attention tracks. Multiple connections between tracks allow the network to simultaneously learn relationships within and between sequences, distances, and coordinates. (B) Average template modeling score of prediction methods on CASP14 targets. Zhang-server and BAKER-ROSETTASERVER were the top 2 server groups, while AlphaFold2 and BAKER were the top 2 human groups in CASP14; BAKER-ROSETTASERVER and BAKER predictions were based on trRosetta. Predictions with the two-track model and RoseTTAFold (both end-to-end and pyRosetta version) were completely automated. (C) Blind benchmark results on CAMEO medium and hard targets; model accuracies are template modeling score values from the CAMEO Web site. Reprinted with permission from ref (400). Copyright 2021 The American Association for the Advancement of Science.