Fig. 1: Sparse model architecture.
From: Efficient protein structure generation with sparse denoising models
a, Schematic of the basic block of our architecture. b, Schematic of neighbour selection using residue index, nearest and random neighbours. c, Architecture of our sparse protein autoencoder. d, Sparse model performance on an autoencoding task. Box plots of scRMSD between the ground-truth and decoded structures for multiple sparse architectures: equivariant (EQ) and non-equivariant (NEQ). Optionally, we use predicted distograms for neighbour selection (dgram) and vector quantization (VQ). Measures of reconstruction performance are shown per number of model recycling iterations. The dotted line indicates the threshold of 1 Å for reconstruction at atomic precision. The box centre line indicates the median, the boundaries indicate the 1st and 3rd quartiles, and whiskers show the 1st or 3rd quartile + 1.5 times the interquartile range based on n = 34 CASP14 test structures and n = 45 CASP15 test structures.
