PT  - JOURNAL ARTICLE
AU  - Miguel Correa Marrero
AU  - Richard G.H. Immink
AU  - Dick de Ridder
AU  - Aalt D.J van Dijk
TI  - Improving intermolecular contact prediction through protein-protein interaction prediction using coevolutionary analysis with expectation-maximization
AID  - 10.1101/254789
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 254789
4099  - http://biorxiv.org/content/early/2018/01/28/254789.short
4100  - http://biorxiv.org/content/early/2018/01/28/254789.full
AB  - Predicting residue-residue contacts between interacting proteins is an important problem in bioinformatics. The growing wealth of sequence data can be used to infer these contacts through correlated mutation analysis on multiple sequence alignments of interacting homologs of the proteins of interest. This requires correct identification of pairs of interacting proteins for many species, in order to avoid introducing noise (i.e. non-interacting sequences) in the analysis that will decrease predictive performance. We have designed Ouroboros, a novel algorithm to reduce such noise in intermolecular contact prediction. Our method iterates between weighting proteins according to how likely they are to interact based on the correlated mutations signal, and predicting correlated mutations based on the weighted sequence alignment. We show that this approach accurately discriminates between protein interaction versus noninteraction and simultaneously improves the prediction of intermolecular contact residues compared to a naive application of correlated mutation analysis. Furthermore, the method relaxes the assumption of one-to-one interaction of previous approaches, allowing for the study of many-to-many interactions. Source code and test data are available at www.bif.wur.nl/