CODD: Co-Occurent Domain Discovery

Motivation : Hidden Markov Models (HMMs) have proved to be a powerful tool for protein domain identification in new sequenced organisms. However, numerous domains may be missed in highly divergent proteins. This is the case for Plasmodium falciparum proteins, the main causal agent of human malaria.

Results : Here we propose a method to improve the sensitivity of HMM domain detection by exploiting the tendency of the domains to appear preferentially with a few other favorite domains in a protein. When sequence information alone is not sufficient to warrant the presence of a particular domain, our method enables its detection on the basis of the presence of other Pfam or InterPro domains. Moreover, a dedicated statistical procedure allows us to estimate the false discovery rate associated with the results. Applied to P. falciparum, our method identifies 585 new Pfam domains (versus the 3 683 already known domains in the Pfam database) with an estimated error rate below 20%. These new domains provide 387 new Gene Ontology annotations to the P. falciparum proteome. Analogous and congruent results are obtained when applying the method to the related Plasmodium species P. vivax and P. yoelii.