Representation-aware calibration enables statistically reliable protein structure search

Abstract

Searching large databases of predicted protein structures can reveal remote homologs, but reliable discovery requires accurate significance estimates. We show that native E-values reported by protein structure search tools such as Foldseek and Reseek can be unreliable, leading to false discoveries or missed homologs. To address this problem, we introduce Struct-Caliper, which provides reliable query-specific p-values for protein structure search. The method uses representation-aware query randomization to generate background queries and compares observed alignment scores with the highest scores from randomized searches of the same database. In simulations, SG p-values generally kept reported false positive at or below the chosen cutoff under the evaluated randomization procedures. In searches of 15,177 ASTRAL40 structures, SG p-values increased Foldseek homolog recovery by 18.2% with slightly fewer false discoveries compared with native E-values at a cutoff of 0.01. For Reseek, false discoveries even decreased by 99.5%. Across 73 queries searched against more than two million AlphaFoldDB structures, SG p-values increased the mean recovery of DALI-supported matches by 23.5% at the same cutoff. These results show that Struct-Caliper can improve the reliability of structure searches and help prioritize discoveries for further biological analysis.