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Title: Robust and accurate prediction of residue–residue interactions across protein interfaces using evolutionary information}
Article:
Abstract:
Do the amino acid sequence identities of residues that make contact across protein interfaces covary during evolution? If so, such covariance could be used to predict contacts across interfaces and assemble models of biological complexes. We find that residue pairs identified using a pseudo-likelihood-based method to covary across protein–protein interfaces in the 50S ribosomal unit and 28 additional bacterial protein complexes with known structure are almost always in contact in the complex, provided that the number of aligned sequences is greater than the average length of the two proteins. We use this method to make subunit contact predictions for an additional 36 protein complexes with unknown structures, and present models based on these predictions for the tripartite ATP-independent periplasmic( TRAP) transporter, the tripartite efflux system, the pyruvate formate lyase-activating enzyme complex, and the methionine ABC transporter.
Introduction:
Recent work has demonstrated the accuracy of coevolution-based contact prediction for monomeric proteins using a global statistical model( Thomas et al., 2008) to distinguish between direct and indirect couplings( Marks et al., 2011; Morcos et al., 2011; Hopf et al., 2012; Nugent and Jones, 2012; Jones et al., 2012; Lapedes et al., 2012; Marks et al., 2012; Sułkowska et al., 2012; Kamisetty et al., 2013). While early approaches relied on estimating an inverse covariance matrix( Marks et al., 2011; Morcos et al., 2011; Jones et al., 2012), more recent studies have shown that a pseudo-likelihood-based approach( Balakrishnan et al., 2011) results in more accurate predictions( Ekeberg et al., 2013; Kamisetty et al., 2013) for a range of alignment sizes and protein lengths. In contrast to this rich body of work for monomeric proteins, relatively little is known about the utility of such statistical models in predicting protein–protein interactions. The more general problem of predicting if two proteins interact with each other has been studied extensively using a wide variety of approaches( de Juan et al., 2013; Hosur et al., 2012; Zhang et al., 2012; Shoemaker and Panchenko, 2007, Valencia and Pazos, 2002, Ochoa and Pazos, 2010). Amino acid residue coevolution has been used to predict residue–residue interactions across interfaces with local statistical models( Pazos et al., 1997; Halperin et al., 2006). As noted above, the accuracy of these models is reduced by the confounding of direct and indirect correlations( Lapedes et al., 1999; Weigt et al., 2009); the application of global statistical models to coevolution-based contact prediction across interfaces has been limited to the case of the histidine-kinase/response-regulator two component system( Burger and van Nimwegen, 2008; Weigt et al., 2009; Schug et al., 2009; Dago et al., 2012). In this study, we examine residue–residue covariation across protein–protein interfaces using a pseudo-likelihood-based statistical method. In a large set of complexes of known structure, we find that covarying pairs of positions are almost always in contact in the three-dimensional structure, provided there are sufficient aligned sequences. We find further that significant residue–residue covariance occurs frequently between physically interacting protein pairs but very rarely between non-interacting pairs, and hence should be useful for predicting whether two proteins interact. We use the pseudo-likelihood method to predict contacts across protein-interfaces for 36 evolutionarily conserved complexes of unknown structure and present structure models for four of the complexes particularly well constrained by these data.
Discussion:
Our results demonstrate unequivocally that there is strong selective pressure at protein–protein interfaces beyond simple residue conservation, and that co-evolving residue pairs are nearly always in contact in the protein complex. Not all contacting residues across protein interfaces likely co-evolve nor all protein–protein interfaces. Nevertheless, as illustrated in Figures 1 and 2, there is clearly sufficient coevolutionary signal to significantly constrain models of a large number of protein complexes. There is a notable contrast in the utility of intra-monomer and intersubunit predicted contacts for structure modeling. We found previously( Kamisetty et al., 2013) that contacts could be predicted with high accuracy for monomeric proteins, provided there were sufficient aligned sequences, but in such cases there was almost always already a structure of a family member from which comparative models could be built, limiting the utility of the predicted contacts in structure prediction( Though predicted contacts can be useful in modeling allosteric changes in protein structures[Hopf et al., 2012; Morcos et al., 2013]). In contrast, here we find that more than half of the complexes for which the protein families of the constituent subunits are sufficiently large for accurate contact prediction do not currently have three-dimensional structures. Hence, while predicted contacts can be very accurate for both monomeric globular proteins and for protein–protein complexes, they are more useful for structure modeling for the latter due to the much poorer representation of protein complexes in the PDB. While our approach of constructing a global statistical model from paired sequence alignments is generally applicable to any taxa, the current study focuses on prokaryotes and mitochondria. Doing so allows us to largely avoid the problem of distinguishing between paralogs by exploiting the operon architecture of bacterial genomes( Jacob et al., 2005). Constructing paired-sequence alignments for more complex genomic architectures is more involved and requires the ability to distinguish orthologs from paralogs, the subject of active research( Remm et al., 2001; Datta et al., 2009). Protocols for generating paired sequence alignments more generally are an important area for development in this area.
Proteins are considered the ‘workhorse molecules’ of life and they are involved in virtually everything that cells do . Proteins are strings of amino acids that have folded into a specific three-dimensional shape . Proteins must have the correct shape to function properly , as they often work by binding to other proteins or molecules—much like a key fitting into a lock . Working out the structure of a protein can , therefore , provide major insights into how the protein does its job . Two or more proteins can bind together and form a complex to perform various tasks; and solving the structures of these complexes can be challenging , even if the structures of the protein subunits are known . Now , Ovchinnikov , Kamisetty , and Baker have developed a method for predicting which parts of the proteins make contact with each other in a two-protein complex . Different species can have copies of the same proteins; but a copy from one species might have different amino acids at certain positions when compared to a related copy from another species . As such , when pairs of interacting proteins from different species are compared , there will be many positions in the two proteins that vary . However , if the amino acid at a position in one protein ( let's call it ‘X’ ) varies , and the amino acid at , say , position ‘Y’ in the other protein also varies such that for any given amino acid at position Y there is often a specific amino acid at position X; positions X and Y are said to ‘co-vary’ . Ovchinnikov et al . noticed that when a pair of amino acids ( one from each protein in a two-protein complex ) co-varied , these two amino acids tended to make contact with each other at the protein–protein interface . Ovchinnikov et al . used the new method to make predictions about the protein–protein interfaces in 28 protein complexes found in bacteria , and also to make a prediction about the interface between protein subunits in the bacterial ribosome . When these predictions were checked against the actual structures , which were all known beforehand , they were found to be accurate if the number of copies of each protein being compared is greater than the average length of the two proteins . Ovchinnikov et al . went on to predict the amino acids on the protein–protein interfaces for another 36 bacterial protein complexes with unknown structures , and to present models for four larger complexes . The next challenge is to extend the method to protein complexes that are found only in eukaryotes ( i . e . , not in bacteria ) . Since the number of related copies for eukaryotic proteins tends to be smaller , there are fewer proteins to compare and it is therefore harder to detect ‘covariation’ when it occurs .