Extended Data Fig. 3. AF-Cluster sampling detects KaiB^TE ground state in evolutionary couplings.

a) Contacts under 5 Å that correspond uniquely to the FS state (left) or ground state (right). Boxed features correspond to features unique to both states. b) AUC scores to both states of contact maps predicted by MSA transformer, a method trained by unsupervised learning. Randomly-subsampled MSAs have higher score to the FS state, and AF-Cluster contacts have higher score to ground state. c) Contact maps of sampled MSAs with the highest AUC to the ground state from (i) AF-Cluster and (ii) random sampling. The best-scoring random sample does not include the beta-strand unique to the ground state (boxed in blue in i). (iii) Contacts calculated from the whole MSA show features corresponding the FS state: beta-strands (orange, magenta) and the helix-helix interaction (red) boxed in (A). d) Contact map scores for both states correlate to the AF2 prediction RMSD for each state (Ground state: Spearman R = −0.32, p = 2e-09, FS state: Spearman R = −0.34, p = 4e-10 via a two-sided statistical test. No adjustment for multiple comparisons was made). Error bands for the linear trendline are 95% confidence intervals obtained via bootstrapping.