Predicting binding sites of hydrolase-inhibitor complexes by combining several methods

Background

Protein-protein interactions play a critical role in protein function. Completion of many genomes is being followed rapidly by major efforts to identify interacting protein pairs experimentally in order to decipher the networks of interacting, coordinated-in-action proteins. Identification of protein-protein interaction sites and detection of specific amino acids that contribute to the specificity and the strength of protein interactions is an important problem with broad applications ranging from rational drug design to the analysis of metabolic and signal transduction networks.

Results

In order to increase the power of predictive methods for protein-protein interaction sites, we have developed a consensus methodology for combining four different methods. These approaches include: data mining using Support Vector Machines, threading through protein structures, prediction of conserved residues on the protein surface by analysis of phylogenetic trees, and the Conservatism of Conservatism method of Mirny and Shakhnovich. Results obtained on a dataset of hydrolase-inhibitor complexes demonstrate that the combination of all four methods yield improved predictions over the individual methods.

Conclusions

We developed a consensus method for predicting protein-protein interface residues by combining sequence and structure-based methods. The success of our consensus approach suggests that similar methodologies can be developed to improve prediction accuracies for other bioinformatic problems.     

Prediction of protein-protein interactions using distant conservation of sequence patterns and structure relationships

MOTIVATION: Given that association and dissociation of protein molecules is crucial in most biological processes several in silico methods have been recently developed to predict protein-protein interactions. Structural evidence has shown that usually interacting pairs of close homologs (interologs) physically interact in the same way. Moreover, conservation of an interaction depends on the conservation of the interface between interacting partners. In this article we make use of both, structural similarities among domains of known interacting proteins found in the Database of Interacting Proteins (DIP) and conservation of pairs of sequence patches involved in protein-protein interfaces to predict putative protein interaction pairs. RESULTS: We have obtained a large amount of putative protein-protein interaction (approximately 130,000). The list is independent from other techniques both experimental and theoretical. We separated the list of predictions into three sets according to their relationship with known interacting proteins found in DIP. For each set, only a small fraction of the predicted protein pairs could be independently validated by cross checking with the Human Protein Reference Database (HPRD). The fraction of validated protein pairs was always larger than that expected by using random protein pairs. Furthermore, a correlation map of interacting protein pairs was calculated with respect to molecular function, as defined in the Gene Ontology database. It shows good consistency of the predicted interactions with data in the HPRD database. The intersection between the lists of interactions of other methods and ours produces a network of potentially high-confidence interactions.     

Mapping of protein-protein interaction sites by the 'absence of interference' approach

Protein-protein interactions are critical to most biological processes, and locating protein-protein interfaces on protein structures is an important task in molecular biology. We developed a new experimental strategy called the ‘absence of interference’ approach to determine surface residues involved in protein-protein interaction of established yeast two-hybrid pairs of interacting proteins. One of the proteins is subjected to high-level randomization by error-prone PCR. The resulting library is selected by yeast two-hybrid system for interacting clones that are isolated and sequenced. The interaction region can be identified by an absence or depletion of mutations. For data analysis and presentation, we developed a Web interface that analyzes the mutational spectrum and displays the mutational frequency on the surface of the structure (or a structural model) of the randomized protein†. Additionally, this interface might be of use for the display of mutational distributions determined by other types of random mutagenesis experiments. We applied the approach to map the interface of the catalytic domain of the DNA methyltransferase Dnmt3a with its regulatory factor Dnmt3L. Dnmt3a was randomized with high mutational load. A total of 76 interacting clones were isolated and sequenced, and 648 mutations were identified. The mutational pattern allowed to identify a unique interaction region on the surface of Dnmt3a, which comprises about 500-600 Å². The results were confirmed by site-directed mutagenesis and structural analysis. The absence-of-interference approach will allow high-throughput mapping of protein interaction sites suitable for functional studies and protein docking.     

Recurrence quantification analysis reveals interaction partners in paramyxoviridae envelope glycoproteins.

The paramyxovirus envelope fuses with the host cell membrane by cooperative interaction of two transmembrane glycoproteins: the hemagglutinin neuraminidase (HN) and the fusion (F) glycoprotein. The interaction appears to be finely regulated, as both proteins must derive from the same viral species to obtain a functional interaction. Because HN and F do not form stable complexes, this interaction is poorly characterized. This article demonstrates that a modification of a classical bioinformatic method based on the co-evolution of interacting partners can detect the specificity of the HN and F interaction. The proposed approach relies on a relatively new nonlinear signal analysis technique, recurrence quantification analysis (RQA), applied to the hydrophobicity sequences of viral proteins. This technique is able to shed light on the interaction between HN and F proteins in the virus-cell fusion and, more generally, permits the quantitative comparison of nonhomologue protein systems. On the contrary, the same co-evolution approach, based on the classical sequence alignment procedure, was unable to discriminate interacting partners from the general strict correlation existing between the evolution of viral proteins as a whole. The cooperation between HN and F in the fusion process is thus demonstrated by a bioinformatic, purely sequence-dependent, perspective.     

Coarse-grained strategy for modeling protein stability in concentrated solutions

We present a coarse-grained approach for modeling the thermodynamic stability of single-domain globular proteins in concentrated aqueous solutions. Our treatment derives effective protein-protein interactions from basic structural and energetic characteristics of the native and denatured states. These characteristics, along with the intrinsic (i.e., infinite dilution) thermodynamics of folding, are calculated from elementary sequence information using a heteropolymer collapse theory. We integrate this information into Reactive Canonical Monte Carlo simulations to investigate the connections between protein sequence hydrophobicity, protein-protein interactions, protein concentration, and the thermodynamic stability of the native state. The model predicts that sequence hydrophobicity can affect how protein concentration impacts native-state stability in solution. In particular, low hydrophobicity proteins are primarily stabilized by increases in protein concentration, whereas high hydrophobicity proteins exhibit richer nonmonotonic behavior. These trends appear qualitatively consistent with the available experimental data. Although factors such as pH, salt concentration, and protein charge are also important for protein stability, our analysis suggests that some of the nontrivial experimental trends may be driven by a competition between destabilizing hydrophobic protein-protein attractions and entropic crowding effects.     

Predicting the structure of the light-harvesting complex II of Rhodospirillum molischianum.

We attempted to predict through computer modeling the structure of the light-harvesting complex II (LH-II) of Rhodospirillum molischianum, before the impending publication of the structure of a homologous protein solved by means of X-ray diffraction. The protein studied is an integral membrane protein of 16 independent polypeptides, 8 alpha-apoproteins and 8 beta-apoproteins, which aggregate and bind to 24 bacteriochlorophyll-a's and 12 lycopenes. Available diffraction data of a crystal of the protein, which could not be phased due to a lack of heavy metal derivatives, served to test the predicted structure, guiding the search. In order to determine the secondary structure, hydropathy analysis was performed to identify the putative transmembrane segments and multiple sequence alignment propensity analyses were used to pinpoint the exact sites of the 20-residue-long transmembrane segment and the 4-residue-long terminal sequence at both ends, which were independently verified and improved by homology modeling. A consensus assignment for the secondary structure was derived from a combination of all the prediction methods used. Three-dimensional structures for the alpha- and the beta-apoprotein were built by comparative modeling. The resulting tertiary structures are combined, using X-PLOR, into an alpha beta dimer pair with bacteriochlorophyll-a's attached under constraints provided by site-directed mutagenesis and spectral data. The alpha beta dimer pairs were then aggregated into a quaternary structure through further molecular dynamics simulations and energy minimization. The structure of LH-II so determined is an octamer of alpha beta heterodimers forming a ring with a diameter of 70 A.     

Protein-protein interactions more conserved within species than across species

Experimental high-throughput studies of protein-protein interactions are beginning to provide enough data for comprehensive computational studies. Today, about ten large data sets, each with thousands of interacting pairs, coarsely sample the interactions in fly, human, worm, and yeast. Another about 55,000 pairs of interacting proteins have been identified by more careful, detailed biochemical experiments. Most interactions are experimentally observed in prokaryotes and simple eukaryotes; very few interactions are observed in higher eukaryotes such as mammals. It is commonly assumed that pathways in mammals can be inferred through homology to model organisms, e.g. the experimental observation that two yeast proteins interact is transferred to infer that the two corresponding proteins in human also interact. Two pairs for which the interaction is conserved are often described as interologs. The goal of this investigation was a large-scale comprehensive analysis of such inferences, i.e. of the evolutionary conservation of interologs. Here, we introduced a novel score for measuring the overlap between protein-protein interaction data sets. This measure appeared to reflect the overall quality of the data and was the basis for our two surprising results from our large-scale analysis. Firstly, homology-based inferences of physical protein-protein interactions appeared far less successful than expected. In fact, such inferences were accurate only for extremely high levels of sequence similarity. Secondly, and most surprisingly, the identification of interacting partners through sequence similarity was significantly more reliable for protein pairs within the same organism than for pairs between species. Our analysis underlined that the discrepancies between different datasets are large, even when using the same type of experiment on the same organism. This reality considerably constrains the power of homology-based transfer of interactions. In particular, the experimental probing of interactions in distant model organisms has to be undertaken with some caution. More comprehensive images of protein-protein networks will require the combination of many high-throughput methods, including in silico inferences and predictions. http://www.rostlab.org/results/2006/ppi_homology/     

ISIS: interaction sites identified from sequence

MOTIVATION: Large-scale experiments reveal pairs of interacting proteins but leave the residues involved in the interactions unknown. These interface residues are essential for understanding the mechanism of interaction and are often desired drug targets. Reliable identification of residues that reside in protein-protein interface typically requires analysis of protein structure. Therefore, for the vast majority of proteins, for which there is no high-resolution structure, there is no effective way of identifying interface residues. RESULTS: Here we present a machine learning-based method that identifies interacting residues from sequence alone. Although the method is developed using transient protein-protein interfaces from complexes of experimentally known 3D structures, it never explicitly uses 3D information. Instead, we combine predicted structural features with evolutionary information. The strongest predictions of the method reached over 90% accuracy in a cross-validation experiment. Our results suggest that despite the significant diversity in the nature of protein-protein interactions, they all share common basic principles and that these principles are identifiable from sequence alone.     

Six new candidate members of the alpha/beta twisted open-sheet family detected by sequence similarity to flavodoxin.

Strong sequence similarity has been reported among WrbA (the Trp repressor-binding protein of Escherichia coli); Ycp4, a protein of unknown function from the budding yeast Saccharomyces cerevisiae; P25, the pap1-dependent protein of the fission yeast Schizosaccharomyces pombe; and the translation product of a partial cDNA sequence from rice seedling root (Oryza sativa, locus Ricr02421a; here referred to as RicR). Further homology search with the profile method indicates that all the above sequences are related to the flavodoxin family and, in turn, allows detection of the recently proposed flavodoxin-like proteins from E. coli, MioC and the hypothetical protein YihB. We discuss sequence conservation with reference to the known 3-dimensional structures of flavodoxins. Conserved sequence and hydrophobicity patterns, as well as residue-pair interaction potentials, strongly support the hypothesis that these proteins share the alpha/beta twisted open-sheet fold typical of flavodoxins, with an additional alpha/beta unit in the WrbA family. On the basis of the proposed structural homology, we discuss the details of the putative FMN-binding sites. Our analysis also suggests that the helix-turn-helix motif we identified previously in the C-terminal region of the WrbA family is unlikely to reflect a DNA-binding function of this new protein family.     

Computational redesign of protein-protein interaction specificity

We developed a 'computational second-site suppressor' strategy to redesign specificity at a protein-protein interface and applied it to create new specifically interacting DNase-inhibitor protein pairs. We demonstrate that the designed switch in specificity holds in in vitro binding and functional assays. We also show that the designed interfaces are specific in the natural functional context in living cells, and present the first high-resolution X-ray crystallographic analysis of a computer-redesigned functional protein-protein interface with altered specificity. The approach should be applicable to the design of interacting protein pairs with novel specificities for delineating and re-engineering protein interaction networks in living cells.     

Fast and accurate modeling of protein-protein interactions by combining template-interface-based docking with flexible refinement

The similarity between folding and binding led us to posit the concept that the number of protein-protein interface motifs in nature is limited, and interacting protein pairs can use similar interface architectures repeatedly, even if their global folds completely vary. Thus, known protein-protein interface architectures can be used to model the complexes between two target proteins on the proteome scale, even if their global structures differ. This powerful concept is combined with a flexible refinement and global energy assessment tool. The accuracy of the method is highly dependent on the structural diversity of the interface architectures in the template dataset. Here, we validate this knowledge-based combinatorial method on the Docking Benchmark and show that it efficiently finds high-quality models for benchmark complexes and their binding regions even in the absence of template interfaces having sequence similarity to the targets. Compared to "classical" docking, it is computationally faster; as the number of target proteins increases, the difference becomes more dramatic. Further, it is able to distinguish binders from nonbinders. These features allow performing large-scale network modeling. The results on an independent target set (proteins in the p53 molecular interaction map) show that current method can be used to predict whether a given protein pair interacts. Overall, while constrained by the diversity of the template set, this approach efficiently produces high-quality models of protein-protein complexes. We expect that with the growing number of known interface architectures, this type of knowledge-based methods will be increasingly used by the broad proteomics community.     

Biological units and their effect upon the properties and prediction of protein-protein interactions

Structural data as collated in the Protein Data Bank (PDB) have been widely applied in the study and prediction of protein-protein interactions. However, since the basic PDB Entries contain only the contents of the asymmetric unit rather than the biological unit, some key interactions may be missed by analysing only the PDB Entry. A total of 69,054 SCOP (Structural Classification of Proteins) domains were examined systematically to identify the number of additional novel interacting domain pairs and interfaces found by considering the biological unit as stored in the PQS (Protein Quaternary Structure) database. The PQS data adds 25,965 interacting domain pairs to those seen in the PDB Entries to give a total of 61,783 redundant interacting domain pairs. Redundancy filtering at the level of the SCOP family shows PQS to increase the number of novel interacting domain-family pairs by 302 (13.3%) from 2277, but only 16/302 (1.4%) of the interacting domain pairs have the two domains in different SCOP families. This suggests the biological units add little to the elucidation of novel biological interaction networks. However, when the orientation of the domain pairs is considered, the PQS data increases the number of novel domain-domain interfaces observed by 1455 (34.5%) to give 5677 non-redundant domain-domain interfaces. In all, 162/1455 novel domain-domain interfaces are between domains from different families, an increase of 8.9% over the PDB Entries. Overall, the PQS biological units provide a rich source of novel domain-domain interfaces that are not seen in the studied PDB Entries, and so PQS domain-domain interaction data should be exploited wherever possible in the analysis and prediction of protein-protein interactions.     

Design of a heterospecific, tetrameric, 21-residue miniprotein with mixed alpha/beta structure

The study of short, autonomously folding peptides, or "miniproteins," is important for advancing our understanding of protein stability and folding specificity. Although many examples of synthetic alpha-helical structures are known, relatively few mixed alpha/beta structures have been successfully designed. Only one mixed-secondary structure oligomer, an alpha/beta homotetramer, has been reported thus far. In this report, we use structural analysis and computational design to convert this homotetramer into the smallest known alpha/beta-heterotetramer. Computational screening of many possible sequence/structure combinations led efficiently to the design of short, 21-residue peptides that fold cooperatively and autonomously into a specific complex in solution. A 1.95 A crystal structure reveals how steric complementarity and charge patterning encode heterospecificity. The first- and second-generation heterotetrameric miniproteins described here will be useful as simple models for the analysis of protein-protein interaction specificity and as structural platforms for the further elaboration of folding and function.     

Coordinated folding and association of the LIN-2, -7 (L27) domain. An obligate heterodimerization involved in assembly of signaling and cell polarity complexes

LIN-2, -7 (L27) homology domains are putative protein-protein interaction modules found in several scaffold proteins involved in the assembly of polarized cell-signaling structures. These specific interaction pairs are well conserved across metazoan species, from worms to man. We have expressed and purified L27 domains from multiple species and find that certain domains from proteins such as Caenorhabditis elegans LIN-2 and LIN-7 can specifically heterodimerize. Biophysical analysis of interacting L27 domains demonstrates that the domains interact with a 1:1 stoichiometry. Circular dichroism studies reveal that the domains appear to function as an obligate heterodimer; individually the domains are largely unfolded, but when associated they show a significant increase in helicity, as well as a cooperative unfolding transition. These novel obligate interacting pairs are likely to play a key role in regulating the organization of signaling proteins at polarized cell structures.     

Analysis of hydrophobicity in the alpha and beta chemokine families and its relevance to dimerization.

The chemokine family of chemotactic cytokines plays a key role in orchestrating the immune response. The family has been divided into 2 subfamilies, alpha and beta, based on the spacing of the first 2 cysteine residues, function, and chromosomal location. Members within each subfamily have 25-70% sequence identity, whereas the amino acid identity between members of the 2 subfamilies ranges from 20 to 40%. A quantitative analysis of the hydrophobic properties of 11 alpha and 9 beta chemokine sequences, based on the coordinates of the prototypic alpha and beta chemokines, interleukin-8 (IL-8), and human macrophage inflammatory protein-1 beta (hMIP-1 beta), respectively, is presented. The monomers of the alpha and beta chemokines have their strongest core hydrophobic cluster at equivalent positions, consistent with their similar tertiary structures. In contrast, the pattern of monomer surface hydrophobicity between the alpha and beta chemokines differs in a manner that is fully consistent with the observed differences in quaternary structure. The most hydrophobic surface clusters on the monomer subunits are located in very different regions of the alpha and beta chemokines and comprise in each case the amino acids that are buried at the interface of their respective dimers. The theoretical analysis of hydrophobicity strongly supports the hypothesis that the distinct dimers observed for IL-8 and hMIP-1 beta are preserved for all the alpha and beta chemokines, respectively. This provides a rational explanation for the lack of receptor crossbinding and reactivity between the alpha and beta chemokine subfamilies.     

Solution structure of the Ras binding domain of the protein kinase Byr2 from Schizosaccharomyces pombe.

BACKGROUND: After activation, small GTPases such as Ras transfer the incoming signal to effectors by specifically interacting with the binding domain of these proteins. Structural details of the binding domain of different effectors determine which pathway is predominantly activated. Byr2 from fission yeast is a functional homolog of Raf, which is the direct downstream target of Ras in mammalians that initiates a protein kinase cascade. The amino acid sequence of Byr2's Ras binding domain is only weakly related to that of Raf, and Byr2's three-dimensional structure is unknown. RESULTS: We have solved the 3D structure of the Ras binding domain of Byr2 (Byr2RBD) from Schizosaccharomyces pombe in solution. The structure consists of three alpha helices and a mixed five-stranded beta pleated sheet arranged in the topology betabetaalphabetabetaalphabetaalpha with the first seven canonic secondary structure elements forming a ubiquitin superfold. 15N-(1)H-TROSY-HSQC spectroscopy of the complex of Byr2RBD with Ras*Mg(2+)*GppNHp reveals that the first and second beta strands and the first alpha helix of Byr2 are mainly involved in the protein-protein interaction as observed in other Ras binding domains. Although the putative interaction site of H-Ras from human and Ras1 from S. pombe are identical in sequence, binding to Byr2 leads to small but significant differences in the NMR spectra, indicating a slightly different binding mode. CONCLUSIONS: The ubiquitin superfold appears to be the general structural motif for Ras binding domains even in cases with vanishing sequence identity. However, details of the 3D structure and the interacting interface are different, thereby determining the specifity of the recognition of Ras and Ras-related proteins.     

Secondary structure based analysis and classification of biological interfaces: identification of binding motifs in protein-protein interactions

MOTIVATION: The increasing amount of data on protein-protein interaction needs to be rationalized for deriving guidelines for the alteration or design of an interface between two proteins. RESULTS: We present a detaild structural analysis and comparison of homo- versus heterodimeric protein-protein interfaces. Regular secondary structures (helices and strands) are the main components of the former, whereas non-regular structures (turns, loops, etc.) frequently mediate interactions in the latter. Interface helices get longer with increasing interface area, but only in heterocomplexes. On average, the homodimers have longer helical segments and prominent helix-helix pairs. There is a surprising distinction in the relative orientation of interface helices, with a tendency for aligned packing in homodimers and a clear preference for packing at 90 degrees in heterodimers. Arg and the aromatic residues have a higher preference to occur in all secondary structural elements (SSEs) in the interface. Based on the dominant SSE, the interfaces have been grouped into four classes: alpha, beta, alphabeta and non-regular. Identity between protein and interface classes is the maximum for alpha proteins, but rather mediocre for the other protein classes. The interface classes of the two chains forming a heterodimer are often dissimilar. Eleven binding motifs can capture the prominent architectural features of most of the interfaces.     

3D structure and significance of the GPhiXXG helix packing motif in tetramers of the E1beta subunit of pyruvate dehydrogenase from the archeon Pyrobaculum aerophilum.

As part of a structural genomics project, we have determined the 2.0 A structure of the E1beta subunit of pyruvate dehydrogenase from Pyrobaculum aerophilum (PA), a thermophilic archaeon. The overall fold of E1beta from PA is closely similar to the previously determined E1beta structures from humans (HU) and P. putida (PP). However, unlike the HU and PP structures, the PA structure was determined in the absence of its partner subunit, E1alpha. Significant structural rearrangements occur in E1beta when its E1alpha partner is absent, including rearrangement of several secondary structure elements such as helix C. Helix C is buried by E1alpha in the HU and PP structures, but makes crystal contacts in the PA structure that lead to an apparent beta(4) tetramer. Static light scattering and sedimentation velocity data are consistent with the formation of PA E1beta tetramers in solution. The interaction of helix C with its symmetry-related counterpart stabilizes the tetrameric interface, where two glycine residues on the same face of one helix create a packing surface for the other helix. This GPhiXXG helix-helix interaction motif has previously been found in interacting transmembrane helices, and is found here at the E1alpha-E1beta interface for both the HU and PP alpha(2)beta(2) tetramers. As a case study in structural genomics, this work illustrates that comparative analysis of protein structures can identify the structural significance of a sequence motif.