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The ensembles were generated by running the six individual clusterings, each with the six distance measures.
The non-homologous X-ray β-sheet ensemble was generated by selecting from the PDB protein-only structures with a sequence longer than 50 residues and a minimum resolution of 2.5 Å.
First, during an exhaustive docking, a pose ensemble is generated by rigidly rotating and translating each conformer within the active site.
The ensemble is generated by assigning randomly sampled values of kinetic rate constants and copy numbers of regulatory proteins to each cell in the ensemble.
By construction, the three ensembles were generated so that A and C would both be more similar to ensemble B than to each other.
NOE-based structural ensembles were generated using the csrosetta3 toolbox integrated within the Rosetta3 software suite.
Using this method to compare the three test ensembles we find that both ensembles A and C are significantly more similar to ensemble B than to each other, in full agreement with the way the ensembles were generated.
For the test ensembles A C we find that the method can rank the similarities, and that the results are in accordance with how the ensembles were generated.
The homologous ensembles (Supplementary Fig. 2) were generated by selecting sequence homologous NMR ensembles and X-ray structures to 1cbs (78 structures), 1mvg (60 structures), 2axf (80 structures), 1rkm (32 structures), 1s2h (33 structures) and 1szv (56 structures).
The ensembles are generated via a Monte Carlo procedure by selecting snap-shot from an MD trajectory that reproduce experimentally measured RDCs.
The gene orthology predictions were generated by the Ensemble Gene Tree method [ 63], which is based on the PHYML algorithm for multiple protein sequence alignments, and uses MUSCLE for each gene family that contains sequences from all five species (A. sinensis, A. gambiae, Ae. aegypti, C. quinquefasciatus and D. melanogaster).
