In the PDZ domain, DCA-inferred couplings correlate with measured epistasis more strongly at short range (ρ=0.69) than long range (ρ=0.48)

The distance-dependent failure that Bravi, Ravasio, Brito, and Wyart derived in their in-silico allosteric networks (claim-dca-underestimates-long-range-epistasis-in-allosteric-materials) reproduces in real protein data. The authors compared Direct Coupling Analysis against Salinas & Ranganathan's (2018, eLife) deep-mutational-scan measurements of energetic epistasis in the α2-helix of the PDZ domain (9 residues), setting the experimentally measured epistasis |∆∆G| against DCA-inferred couplings |∆∆E| computed from an alignment of 1,656 eukaryotic PDZ domains.

The result matches the model's prediction: "We find a stronger correlation between |∆∆G| and |∆∆E| for short range pairs (Pearson correlation ρ = 0.69), than for long range pairs (ρ = 0.48), as the long-range strong epistatic interaction between residues 1 and 8 is not captured by the DCA-inferred energetic couplings." The specific residue-1/residue-8 coupling — real, strong, and long-range — is precisely the kind of interaction the synthetic-network analysis said would go missing, and it goes missing.

This is the external, real-protein confirmation that closes the loop opened in claim-bravi-2020-applies-dca-to-evolved-allosteric-networks-as-synthetic-msa: a prediction generated inside an evolved mechanical-network model, then validated against a measured mutational landscape of an actual protein family. It is a data point in the vault's entity-direct-coupling-analysis cluster on where sequence-based coevolution inference stops tracking function.