ABSTRACT
Interacting proteins and protein domains coevolve on multiple scales, from their correlated presence across species, to correlations in amino-acid usage. Genomic databases provide rapidly growing data for variability in genomic protein content and in protein sequences, calling for computational predictions of unknown interactions. We first introduce the concept of direct phyletic couplings, based on global statistical models of phylogenetic profiles. They strongly increase the accuracy of predicting pairs of related protein domains beyond simpler correlation-based approaches like phylogenetic profiling (80% vs. 30-50% positives out of the 1000 highest-scoring pairs). Combined with the direct coupling analysis of inter-protein residue-residue coevolution, we provide multi-scale evidence for direct but unknown interaction between protein families. An in-depth discussion shows these to be biologically sensible and directly experimentally testable. Negative phyletic couplings highlight alternative solutions for the same functionality, including documented cases of convergent evolution. Thereby our work proves the strong potential of global statistical modeling approaches to genome-wide coevolutionary analysis, far beyond the established use for individual protein complexes and domain-domain interactions.
Subject(s)
Computational Biology/methods , Protein Interaction Domains and Motifs/physiology , Protein Interaction Mapping/methods , Algorithms , Amino Acids/metabolism , Animals , Biophysical Phenomena , Evolution, Molecular , Humans , Models, Statistical , Phylogeny , Protein Binding/physiology , Protein Domains/physiology , Proteins/chemistryABSTRACT
Two-component systems (TCS) comprising sensor histidine kinases and response regulator proteins are among the most important players in bacterial and archaeal signal transduction and also occur in reduced numbers in some eukaryotic organisms. Given their importance to cellular survival, virulence, and cellular development, these systems are among the most scrutinized bacterial proteins. In the recent years, a flurry of bioinformatics, genetic, biochemical, and structural studies have provided detailed insights into many molecular mechanisms that underlie the detection of signals and the generation of the appropriate response by TCS. Importantly, it has become clear that there is significant diversity in the mechanisms employed by individual systems. This review discusses the current knowledge on common themes and divergences from the paradigm of TCS signaling. An emphasis is on the information gained by a flurry of recent structural and bioinformatics studies.
