Dissecting protein-protein recognition sites

The recognition sites in 70 pairwise protein-protein complexes of known three-dimensional structure are dissected in a set of surface patches by clustering atoms at the interface. When the interface buries <2000 A2 of protein surface, the recognition sites usually form a single patch on the surface of each component protein. In contrast, larger interfaces are generally multipatch, with at least one pair of patches that are equivalent in size to a single-patch interface. Each recognition site, or patch within a site, contains a core made of buried interface atoms, surrounded by a rim of atoms that remain accessible to solvent in the complex. A simple geometric model reproduces the number and distribution of atoms within a patch. The rim is similar in composition to the rest of the protein surface, but the core has a distinctive amino acid composition, which may help in identifying potential protein recognition sites on single proteins of known structures.     

Dissecting subunit interfaces in homodimeric proteins

The subunit interfaces of 122 homodimers of known three-dimensional structure are analyzed and dissected into sets of surface patches by clustering atoms at the interface; 70 interfaces are single-patch, the others have up to six patches, often contributed by different structural domains. The average interface buries 1,940 A2 of the surface of each monomer, contains one or two patches burying 600-1,600 A2, is 65% nonpolar and includes 18 hydrogen bonds. However, the range of size and of hydrophobicity is wide among the 122 interfaces. Each interface has a core made of residues with atoms buried in the dimer, surrounded by a rim of residues with atoms that remain accessible to solvent. The core, which constitutes 77% of the interface on average, has an amino acid composition that resembles the protein interior except for the presence of arginine residues, whereas the rim is more like the protein surface. These properties of the interfaces in homodimers, which are permanent assemblies, are compared to those of protein-protein complexes where the components associate after they have independently folded. On average, subunit interfaces in homodimers are twice larger than in complexes, and much less polar due to the large fraction belonging to the core, although the amino acid compositions of the cores are similar in the two types of interfaces.     

Protein-protein crystal-packing contacts.

Protein-protein contacts in monomeric protein crystal structures have been analyzed and compared to the physiological protein-protein contacts in oligomerization. A number of features differentiate the crystal-packing contacts from the natural contacts occurring in multimeric proteins. The area of the protein surface patches involved in packing contacts is generally smaller and its amino acid composition is indistinguishable from that of the protein surface accessible to the solvent. The fraction of protein surface in crystal contacts is very variable and independent of the number of packing contacts. The thermal motion at the crystal packing interface and that of the protein core, even for large packing interfaces, though the tendency is to be closer to that of the core. These results suggest that protein crystallization depends on random protein-protein interactions, which have little in common with physiological protein-protein recognition processes, and that the possibility of engineering macromolecular crystallization to improve crystal quality could be widened.     

Optimal docking area: a new method for predicting protein-protein interaction sites

Understanding energetics and mechanism of protein-protein association remains one of the biggest theoretical problems in structural biology. It is assumed that desolvation must play an essential role during the association process, and indeed protein-protein interfaces in obligate complexes have been found to be highly hydrophobic. However, the identification of protein interaction sites from surface analysis of proteins involved in non-obligate protein-protein complexes is more challenging. Here we present Optimal Docking Area (ODA), a new fast and accurate method of analyzing a protein surface in search of areas with favorable energy change when buried upon protein-protein association. The method identifies continuous surface patches with optimal docking desolvation energy based on atomic solvation parameters adjusted for protein-protein docking. The procedure has been validated on the unbound structures of a total of 66 non-homologous proteins involved in non-obligate protein-protein hetero-complexes of known structure. Optimal docking areas with significant low-docking surface energy were found in around half of the proteins. The 'ODA hot spots' detected in X-ray unbound structures were correctly located in the known protein-protein binding sites in 80% of the cases. The role of these low-surface-energy areas during complex formation is discussed. Burial of these regions during protein-protein association may favor the complexed configurations with near-native interfaces but otherwise arbitrary orientations, thus driving the formation of an encounter complex. The patch prediction procedure is freely accessible at http://www.molsoft.com/oda and can be easily scaled up for predictions in structural proteomics.     

Are protein–protein interfaces more conserved in sequence than the rest of the protein surface?

Protein interfaces are thought to be distinguishable from the rest of the protein surface by their greater degree of residue conservation. We test the validity of this approach on an expanded set of 64 protein-protein interfaces using conservation scores derived from two multiple sequence alignment types, one of close homologs/orthologs and one of diverse homologs/paralogs. Overall, we find that the interface is slightly more conserved than the rest of the protein surface when using either alignment type, with alignments of diverse homologs showing marginally better discrimination. However, using a novel surface-patch definition, we find that the interface is rarely significantly more conserved than other surface patches when using either alignment type. When an interface is among the most conserved surface patches, it tends to be part of an enzyme active site. The most conserved surface patch overlaps with 39% (+/- 28%) and 36% (+/- 28%) of the actual interface for diverse and close homologs, respectively. Contrary to results obtained from smaller data sets, this work indicates that residue conservation is rarely sufficient for complete and accurate prediction of protein interfaces. Finally, we find that obligate interfaces differ from transient interfaces in that the former have significantly fewer alignment gaps at the interface than the rest of the protein surface, as well as having buried interface residues that are more conserved than partially buried interface residues.     

Surface, subunit interfaces and interior of oligomeric proteins

The solvent-accessible surface area (As) of 23 oligomeric proteins is calculated using atomic co-ordinates from high-resolution and well-refined crystal structures. As is correlated with the protein molecular weight, and a power law predicts its value to within 5% on average. The accessible surface of the average oligomer is similar to that of monomeric proteins in its hydropathy and amino acid composition. The distribution of the 20 amino acid types between the protein surface and its interior is also the same as in monomers. Interfaces, i.e. surfaces involved in subunit contacts, differ from the rest of the subunit surface. They are enriched in hydrophobic side-chains, yet they contain a number of charged groups, especially from Arg residues, which are the most abundant residues at interfaces except for Leu. Buried Arg residues are involved in H-bonds between subunits. We counted H-bonds at interfaces and found that several have none, others have one H-bond per 200 A2 of interface area on average (1 A = 0.1 nm). A majority of interface H-bonds involve charged donor or acceptor groups, which should make their contribution to the free energy of dissociation significant, even when they are few. The smaller interfaces cover about 700 A2 of the subunit surface. The larger ones cover 3000 to 10,000 A2, up to 40% of the subunit surface area in catalase. The lower value corresponds to an estimate of the accessible surface area loss required for stabilizing subunit association through the hydrophobic effect alone. Oligomers with small interfaces have globular subunits with accessible surface areas similar to those of monomeric proteins. We suggest that these oligomers assemble from preformed monomers with little change in conformation. In oligomers with large interfaces, isolated subunits should be unstable given their excessively large accessible surface, and assembly is expected to require major structural changes.     

Assessment of protein side‐chain conformation prediction methods in different residue environments

Computational prediction of side‐chain conformation is an important component of protein structure prediction. Accurate side‐chain prediction is crucial for practical applications of protein structure models that need atomic‐detailed resolution such as protein and ligand design. We evaluated the accuracy of eight side‐chain prediction methods in reproducing the side‐chain conformations of experimentally solved structures deposited to the Protein Data Bank. Prediction accuracy was evaluated for a total of four different structural environments (buried, surface, interface, and membrane‐spanning) in three different protein types (monomeric, multimeric, and membrane). Overall, the highest accuracy was observed for buried residues in monomeric and multimeric proteins. Notably, side‐chains at protein interfaces and membrane‐spanning regions were better predicted than surface residues even though the methods did not all use multimeric and membrane proteins for training. Thus, we conclude that the current methods are as practically useful for modeling protein docking interfaces and membrane‐spanning regions as for modeling monomers. Proteins 2014; 82:1971–1984. © 2014 Wiley Periodicals, Inc.     

Folding of beta/alpha-unit scrambled forms of S. cerevisiae triosephosphate isomerase: Evidence for autonomy of substructure formation and plasticity of hydrophobic and hydrogen bonding interactions in core of (beta/alpha)8-barrel

We show that residues at the interfaces of protein-protein complexes have higher side-chain energy than other surface residues. Eight different sets of protein complexes were analyzed. For each protein pair, the complex structure was used to identify the interface residues in the unbound monomer structures. Side-chain energy was calculated for each surface residue in the unbound monomer using our previously developed scoring function.1 The mean energy was calculated for the interface residues and the other surface residues. In 15 of the 16 monomers, the mean energy of the interface residues was higher than that of other surface residues. By decomposing the scoring function, we found that the energy term of the buried surface area of non-hydrogen-bonded hydrophilic atoms is the most important factor contributing to the high energy of the interface regions. In spite of lacking hydrophilic residues, the interface regions were found to be rich in buried non-hydrogen-bonded hydrophilic atoms. Although the calculation results could be affected by the inaccuracy of the scoring function, patch analysis of side-chain energy on the surface of an isolated protein may be helpful in identifying the possible protein-protein interface. A patch was defined as 20 residues surrounding the central residue on the protein surface, and patch energy was calculated as the mean value of the side-chain energy of all residues in the patch. In 12 of the studied monomers, the patch with the highest energy overlaps with the observed interface. The results are more remarkable when only three residues with the highest energy in a patch are averaged to derive the patch energy. All three highest-energy residues of the top energy patch belong to interfacial residues in four of the eight small protomers. We also found that the residue with the highest energy score on the surface of a small protomer is very possibly the key interaction residue.     

Hydrophobic patches on the surfaces of protein structures

A survey of hydrophobic patches on the surface of 112 soluble, monomeric proteins is presented. The largest patch on each individual protein averages around 400 Ų but can range from 200 to 1,200 Ų. These areas are not correlated to the sizes of the proteins and only weakly to their apolar surface fraction. Ala, Lys, and Pro have dominating contributions to the apolar surface for smaller patches, while those of the hydrophobic amino acids become more important as the patch size Increases. The hydrophilic amino acids expose an approximately constant fraction of their apolar area independent of patch size; the hydrophobic residue types reach similar exposure only in the larger patches. Though the mobility of residues on the surface is generally higher, it decreases for hydrophilic residues with Increasing patch size. Several characteristics of hydrophobic patches catalogued here should prove useful in the design and engineering of proteins. © 1996 Wiley-Liss, Inc.     

Amino acid architecture and the distribution of polar atoms on the surfaces of proteins

We propose that a necessary condition for a protein to be soluble is the absence of large hydrophobic patches on its solvent-accessible surface, which can cause aggregation to occur. We note that the polar nature of the backbone of all amino acids guarantees a minimum polar content and hence can interrupt such patches. As a result, a carefully conserved detailed atomic placement of residues on the protein surface is not necessary for solubility. In order to demonstrate this, we construct a measure based on the average hydrophobicity of a simply defined patch. We use this measurement to compare surfaces that exhibit a clear difference in their solubility properties, namely, a) the solvent accessible surfaces for a set of homo-dimers and the surfaces buried in their interfaces and b) for a set of monomers the surfaces of fragments of secondary structure which are solvent accessible/inaccessible. Having demonstrated a difference in the first set of distributions, we characterize the solvent accessible surfaces of monomeric proteins. To test if cooperative behavior occurs between the atoms for these surfaces, we construct a set of randomized surfaces, which obey a very simple stereochemical constraint. We find that the observed and randomized distributions are much more similar than the previous sets we examined. This implies that while surfaces of soluble proteins must have sufficient polar content, the relative placement of atoms of one amino acid with respect to the atoms of neighboring amino acid need not be finely tuned, which provides an innate robustness for protein design and folding.     

Predicting nucleic acid binding interfaces from structural models of proteins

The function of DNA‐ and RNA‐binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure‐based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high‐resolution three‐dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I‐TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high‐resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I‐TASSER produces high‐quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low‐resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Proteins 2012. © 2011 Wiley Periodicals, Inc.     

Predicting where Small Molecules Bind at Protein-Protein Interfaces

Small molecules that bind at protein-protein interfaces may either block or stabilize protein-protein interactions in cells. Thus, some of these binding interfaces may turn into prospective targets for drug design. Here, we collected 175 pairs of protein-protein (PP) complexes and protein-ligand (PL) complexes with known three-dimensional structures for which (1) one protein from the PP complex shares at least 40% sequence identity with the protein from the PL complex, and (2) the interface regions of these proteins overlap at least partially with each other. We found that those residues of the interfaces that may bind the other protein as well as the small molecule are evolutionary more conserved on average, have a higher tendency of being located in pockets and expose a smaller fraction of their surface area to the solvent than the remaining protein-protein interface region. Based on these findings we derived a statistical classifier that predicts patches at binding interfaces that have a higher tendency to bind small molecules. We applied this new prediction method to more than 10 000 interfaces from the protein data bank. For several complexes related to apoptosis the predicted binding patches were in direct contact to co-crystallized small molecules.     

Cavities in protein–DNA and protein–RNA interfaces

An analysis of cavities present in protein–DNA and protein–RNA complexes is presented. In terms of the number of cavities and their total volume, the interfaces formed in these complexes are akin to those in transient protein–protein heterocomplexes. With homodimeric proteins protein–DNA interfaces may contain cavities involving both the protein subunits and DNA, and these are more than twice as large as cavities involving a single protein subunit and DNA. A parameter, cavity index, measuring the degree of surface complementarity, indicates that the packing of atoms in protein–protein/DNA/RNA is very similar, but it is about two times less efficient in the permanent interfaces formed between subunits in homodimers. As within the tertiary structure and protein–protein interfaces, protein–DNA interfaces have a higher inclination to be lined by β-sheet residues; from the DNA side, base atoms, in particular those in minor grooves, have a higher tendency to be located in cavities. The larger cavities tend to be less spherical and solvated. A small fraction of water molecules are found to mediate hydrogen-bond interactions with both the components, suggesting their primary role is to fill in the void left due to the local non-complementary nature of the surface patches.     

Characteristics of super alphaA-crystallin, a product of in vitro exon shuffling

alphaA-Crystallin, a small heat shock protein with chaperone-like activity, forms dynamic multimeric complexes. Recently we described the spontaneous generation of a mutant protein (super alphaA-crystallin) by exon duplication arisen via exon shuffling confirming a classic hypothesis by Gilbert [Nature 271 (1978) 501]. Comparison of super alphaA-crystallin, which is viable in a mouse skeletal muscle cell line, with normal alphaA-crystallin shows that it has diminished thermostability, increased exposure of hydrophobic patches, a larger complex size and lost its chaperone activity. However, super alphaA-crystallin subunits exchange as readily between complexes as does normal alphaA-crystallin. These data indicate that chaperone-like activity may vanish independent of subunit hydrophobicity and exchangeability.     

Conservation of substructures in proteins: interfaces of secondary structural elements in proteasomal subunits

It is observed that during divergent evolution of two proteins with a common phylogenetic origin, the structural similarity of their backbones is often preserved even when the sequence similarity between them decreases to a virtually undetectable level. Here we analyzed, whether the conservation of structure along evolution involves also the local atomic structures in the interfaces between secondary structural elements. We have used as study case one protein family, the proteasomal subunits, for which 17 crystal structures are known. These include 14 different subunits of Saccharomyces cerevisiae, 2 subunits of Thermoplasma acidophilum and one subunit of Escherichia coli. The structural core of the 17 proteasomal subunits has 23 secondary structural elements. Any two adjacent secondary structural elements form a molecular interface consisting of two molecular patches. We found 61 interfaces that occurred in all 17 subunits. The 3D shape of equivalent molecular patches from different proteasomal subunits were compared by superposition. Our results demonstrate that pairs of equivalent molecular patches show an RMSD which is lower than that of randomly chosen patches from unrelated proteins. This is true even when patch comparisons with identical residues were excluded from the analysis. Furthermore it is known that the sequential dissimilarity is correlated to the RMSD between the backbones of the members of protein families. The question arises whether this is also true for local atomic structures. The results show that the correlation of individual patch RMSD values and local sequence dissimilarities is low and has a wide range from 0 to 0.41, however, it is surprising that there is a good correlation between the average RMSD of all corresponding patches and the global sequence dissimilarity. This average patch RMSD correlates slightly stronger than the C(alpha)-trace RMSD to the global sequence dissimilarity.     

In silico analysis of the two tandem somatomedin B domains of ENPP1 reveals hints on the homodimerization of the protein

The homodimerization of ENPP1 is mediated by the two somatomedin B (SMB) domains of the protein through a mechanism that is yet unknown at the atomistic level. The tandem arrangement of these domains without an intermediate spacer implies their possible packing into a functional assembly, which we explored by rigid docking. To exclude potential bias in the docking search we assessed the absence of flexible protein regions by evaluating the normalized B-factors calculated from the Cα atom displacements derived from molecular dynamics simulations. After filtering the docking results exploiting the criterion that residues located at the inter-domain interfaces are more conserved than non-interface residues, the resulting best model of the tandem SMB domains revealed the presence of two large conserved surface patches not engaged in the inter-domain contact. The largest patch is flat and contains all the invariant positively charged residues characterized by fully solvent-exposed side chains within the tandem SMB domains, suggesting as a possible role its interaction with the negative phospholipids on the cell surface. We envisage that an ENPP1 monomer bound to the cell membrane via the transmembrane segment can also interact with the cell surface through the largest conserved patch favoring a specific geometry of the tandem SMB module on the cell that optimally exposes the second conserved patch for the symmetric interaction with another membrane-bound ENPP1 monomer, finally promoting the homodimerization. Biological implications of this model and insights into the effects of the K173Q variant associated with insulin resistance and related abnormalities are presented.     

Structure and assembly of the RNA binding domain of bluetongue virus non-structural protein 2

Bluetongue virus non-structural protein 2 belongs to a class of highly conserved proteins found in orbiviruses of the Reoviridae family. Non-structural protein 2 forms large multimeric complexes and localizes to cytoplasmic inclusions in infected cells. It is able to bind single-stranded RNA non-specifically, and it has been suggested that the protein is involved in the selection and condensation of the Bluetongue virus RNA segments prior to genome encapsidation. We have determined the x-ray structure of the N-terminal domain (sufficient for the RNA binding ability of non-structural protein 2) to 2.4 A resolution using anomalous scattering methods. Crystals of this apparently insoluble domain were obtained by in situ proteolysis of a soluble construct. The asymmetric unit shows two monomers related by non-crystallographic symmetry, with each monomer folded as a beta sandwich with a unique topology. The crystal structure reveals extensive monomer-monomer interactions, which explain the ability of the protein to self-assemble into large homomultimeric complexes. Of the entire surface area of the monomer, one-third is used to create the interfaces of the curved multimeric assembly observed in the x-ray structure. The structure reported here shows how the N-terminal domain would be able to bind single-stranded RNA non-specifically protecting the bound regions in a heterogeneous multimeric but not polymeric complex.     

Analysis and prediction of carbohydrate binding sites

An analysis of the characteristic properties of sugar binding sites was performed on a set of 19 sugar binding proteins. For each site six parameters were evaluated: solvation potential, residue propensity, hydrophobicity, planarity, protrusion and relative accessible surface area. Three of the parameters were found to distinguish the observed sugar binding sites from the other surface patches. These parameters were then used to calculate the probability for a surface patch to be a carbohydrate binding site. The prediction was optimized on a set of 19 non-homologous carbohydrate binding structures and a test prediction was carried out on a set of 40 protein-carbohydrate complexes. The overall accuracy of prediction achieved was 65%. Results were in general better for carbohydrate-binding enzymes than for the lectins, with a rate of success of 87%.     

SHARP2: protein-protein interaction predictions using patch analysis

SHARP2 is a flexible web-based bioinformatics tool for predicting potential protein-protein interaction sites on protein structures. It implements a predictive algorithm that calculates multiple parameters for overlapping patches of residues on the surface of a protein. Six parameters are calculated: solvation potential, hydrophobicity, accessible surface area, residue interface propensity, planarity and protrusion (SHARP2). Parameter scores for each patch are combined, and the patch with the highest combined score is predicted as a potential interaction site. SHARP2 enables users to upload 3D protein structure files in PDB format, to obtain information on potential interaction sites as downloadable HTML tables and to view the location of the sites on the 3D structure using Jmol. The server allows for the input of multiple structures and multiple combinations of parameters. Therefore predictions can be made for complete datasets, as well as individual structures. AVAILABILITY: http://www.bioinformatics.sussex.ac.uk/SHARP2.