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