Ig-VAE: Generative modeling of protein structure by direct 3D coordinate generation
Fig 3
Analysis of Generative Sampling.
Data for 500 of randomly selected non-redundant training samples and generated structures. (A) Overlays of the pairwise distance and Ramachandran distributions of the real and generated data. (B) A comparison of the real and generated structural ensembles. (C) Overlays of the bond length and bond angle distributions of the real, generated and refined data. (D) The left panel shows a plot of the post-refinement per-residue centroid energy against normalized nearest neighbor distance for the generated structures. The nearest neighbor distance is computed as the minimum Frobenius distance between the generated distance matrix and all distance matrices in the training set. Each point is colored based on whether the nearest neighbor is a heavy or light chain Ig. The center panel shows an overlay of the generated structures (pink) and their nearest neighbors (blue) in the training set. These six structures were selected using a combination of centroid energy, nearest neighbor distance, heavy/light classification, and manual inspection. The right panel shows sequence design results for structures III and VI. The energies in the left panel are centroid energies, while the energies in the right panel are full-atom Rosetta energies using the ref2015 score function.