Extended Data Fig. 8: Additional motif scaffolding performance metrics.
From: Efficient protein structure generation with sparse denoising models
(a) Number of unique scaffolds out of n = 1,000 generated per motif-scaffolding problem using backbone atom (N, CA, C, O) RMSD (bb) and CA RMSD (CA) as a threshold for success. Results are shown for both structure-editing (salad+edit) and motif conditioned models (salad+cond). (b) Percentage of successful designs for each motif-scaffolding problem. (c) Scatter plots comparing the number of unique successful scaffolds for all single (n = 24) and multi-motif (n = 6) scaffolding tasks between salad models and state-of-the-art diffusion models (Genie2, RFdiffusion). The x and y axes show the number of unique scaffolds for each model. Points on the dashed line correspond to motifs with an equal number of designs for both methods. For points above the line, salad is better; for points below the line RFdiffusion/Genie2 is better. The number of points above and below the line is listed in the upper left and lower right corners.
