Please use this identifier to cite or link to this item:http://hdl.handle.net/20.500.12105/7879
Conservation of coevolving protein interfaces bridges prokaryote-eukaryote homologies in the twilight zone
Proc Natl Acad Sci U S A. 2016;113(52):15018-15023
Protein-protein interactions are fundamental for the proper functioning of the cell. As a result, protein interaction surfaces are subject to strong evolutionary constraints. Recent developments have shown that residue coevolution provides accurate predictions of heterodimeric protein interfaces from sequence information. So far these approaches have been limited to the analysis of families of prokaryotic complexes for which large multiple sequence alignments of homologous sequences can be compiled. We explore the hypothesis that coevolution points to structurally conserved contacts at protein-protein interfaces, which can be reliably projected to homologous complexes with distantly related sequences. We introduce a domain-centered protocol to study the interplay between residue coevolution and structural conservation of protein-protein interfaces. We show that sequence-based coevolutionary analysis systematically identifies residue contacts at prokaryotic interfaces that are structurally conserved at the interface of their eukaryotic counterparts. In turn, this allows the prediction of conserved contacts at eukaryotic protein-protein interfaces with high confidence using solely mutational patterns extracted from prokaryotic genomes. Even in the context of high divergence in sequence (the twilight zone), where standard homology modeling of protein complexes is unreliable, our approach provides sequence-based accurate information about specific details of protein interactions at the residue level. Selected examples of the application of prokaryotic coevolutionary analysis to the prediction of eukaryotic interfaces further illustrate the potential of this approach.
coevolution | contact prediction | homology modeling | protein complex | protein–protein interaction
Biological Evolution | Catalytic Domain | Computational Biology | Databases, Protein | Eukaryota | Humans | Models, Statistical | Prokaryotic Cells | Protein Binding | Protein Interaction Mapping | Protein Multimerization | Proteins | Reproducibility of Results | Sequence Alignment | Sequence Homology | Evolution, Molecular | Mutation
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