Motivation: It has recently become possible to build reliable de novo models of proteins if a multiple sequence alignment (MSA) of at least 1000 homologous sequences can be built. Methods of global statistical network analysis can explain the observed correlations between columns in the MSA by a small set of directly coupled pairs of columns. Strong couplings are indicative of residue-residue contacts, and from the predicted contacts a structure can be computed. Here, we exploit the structural regularity of paired β-strands that leads to characteristic patterns in the noisy matrices of couplings. The β–β contacts should be detected more reliably than single contacts, reducing the required number of sequences in the MSAs.

Results: bbcontacts predicts β–β contacts by detecting these characteristic patterns in the 2D map of coupling scores using two hidden Markov models (HMMs), one for parallel and one for antiparallel contacts. β-bulges are modelled as indel states. In contrast to existing methods, bbcontacts uses predicted instead of true secondary structure. On a standard set of 916 test proteins, 34% of which have MSAs with < 1000 sequences, bbcontacts achieves 50% precision for contacting β–β residue pairs at 50% recall using predicted secondary structure and 64% precision at 64% recall using true secondary structure, while existing tools achieve around 45% precision at 45% recall using true secondary structure.

Availability and implementation: bbcontacts is open source software (GNU Affero GPL v3) available at https://bitbucket.org/soedinglab/bbcontacts

Contact: jessica.andreani@mines.org or soeding@mpibpc.mpg.de

Supplementary information: Supplementary data are available at Bioinformatics online.