Hydrophobic folding units at protein-protein interfaces: implications to protein folding and to protein-protein association.

A hydrophobic folding unit cutting algorithm, originally developed for dissecting single-chain proteins, has been applied to a dataset of dissimilar two-chain protein-protein interfaces. Rather than consider each individual chain separately, the two-chain complex has been treated as a single chain. The two-chain parsing results presented in this work show hydrophobicity to be a critical attribute of two-state versus three-state protein-protein complexes. The hydrophobic folding units at the interfaces of two-state complexes suggest that the cooperative nature of the two-chain protein folding is the outcome of the hydrophobic effect, similar to its being the driving force in a single-chain folding. In analogy to the protein-folding process, the two-chain, two-state model complex may correspond to the formation of compact, hydrophobic nuclei. On the other hand, the three-state model complex involves binding of already folded monomers, similar to the association of the hydrophobic folding units within a single chain. The similarity between folding entities in protein cores and in two-state protein-protein interfaces, despite the absence of some chain connectivities in the latter, indicates that chain linkage does not necessarily affect the native conformation. This further substantiates the notion that tertiary, non-local interactions play a critical role in protein folding. These compact, hydrophobic, two-chain folding units, derived from structurally dissimilar protein-protein interfaces, provide a rich set of data useful in investigations of the role played by chain connectivity and by tertiary interactions in studies of binding and of folding. Since they are composed of non-contiguous pieces of protein backbones, they may also aid in defining folding nuclei.     

Studies of protein-protein interfaces: a statistical analysis of the hydrophobic effect.

Data sets of 362 structurally nonredundant protein-protein interfaces and of 57 symmetry-related oligomeric interfaces have been used to explore whether the hydrophobic effect that guides protein folding is also the main driving force for protein-protein associations. The buried nonpolar surface area has been used to measure the hydrophobic effect. Our analysis indicates that, although the hydrophobic effect plays a dominant role in protein-protein binding, it is not as strong as that observed in the interior of protein monomers. Comparison of interiors of the monomers with those of the interfaces reveals that, in general, the hydrophobic amino acids are more frequent in the interior of the monomers than in the interior of the protein-protein interfaces. On the other hand, a higher proportion of charged and polar residues are buried at the interfaces, suggesting that hydrogen bonds and ion pairs contribute more to the stability of protein binding than to that of protein folding. Moreover, comparison of the interior of the interfaces to protein surfaces indicates that the interfaces are poorer in polar/charged than the surfaces and are richer in hydrophobic residues. The interior of the interfaces appears to constitute a compromise between the stabilization contributed by the hydrophobic effect on the one hand and avoiding patches on the protein surfaces that are too hydrophobic on the other. Such patches would be unfavorable for the unassociated monomers in solution. We conclude that, although the types of interactions are similar between protein-protein interfaces and single-chain proteins overall, the contribution of the hydrophobic effect to protein-protein associations is not as strong as to protein folding. This implies that packing patterns and interatom, or interresidue, pairwise potential functions, derived from monomers, are not ideally suited to predicting and assessing ligand associations or design. These would perform adequately only in cases where the hydrophobic effect at the binding site is substantial.     

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.     

Insights from the structural analysis of protein heterodimer interfaces

Protein heterodimer complexes are often involved in catalysis, regulation, assembly, immunity and inhibition. This involves the formation of stable interfaces between the interacting partners. Hence, it is of interest to describe heterodimer interfaces using known structural complexes. We use a non-redundant dataset of 192 heterodimer complex structures from the protein databank (PDB) to identify interface residues and describe their interfaces using amino-acids residue property preference. Analysis of the dataset shows that the heterodimer interfaces are often abundant in polar residues. The analysis also shows the presence of two classes of interfaces in heterodimer complexes. The first class of interfaces (class A) with more polar residues than core but less than surface is known. These interfaces are more hydrophobic than surfaces, where protein-protein binding is largely hydrophobic. The second class of interfaces (class B) with more polar residues than core and surface is shown. These interfaces are more polar than surfaces, where binding is mainly polar. Thus, these findings provide insights to the understanding of protein-protein interactions.     

Molecular principles of the interactions of disordered proteins

Thorough knowledge of the molecular principles of protein-protein recognition is essential to our understanding of protein function at the cellular level. Whereas interactions of ordered proteins have been analyzed in great detail, complexes of intrinsically unstructured/disordered proteins (IUPs) have hardly been addressed so far. Here, we have collected a database of 39 complexes of experimentally verified IUPs, and compared their interfaces with those of 72 complexes of ordered, globular proteins. The characteristic differences found between the two types of complexes suggest that IUPs represent a distinct molecular implementation of the principles of protein-protein recognition. The interfaces do not differ in size, but those of IUPs cover a much larger part of the surface of the protein than for their ordered counterparts. Moreover, IUP interfaces are significantly more hydrophobic relative to their overall amino acid composition, but also in absolute terms. They rely more on hydrophobic-hydrophobic than on polar-polar interactions. Their amino acids in the interface realize more intermolecular contacts, which suggests a better fit with the partner due to induced folding upon binding that results in a better adaptation to the partner. The two modes of interaction also differ in that IUPs usually use only a single continuous segment for partner binding, whereas the binding sites of ordered proteins are more segmented. Probably, all these features contribute to the increased evolutionary conservation of IUP interface residues. These noted molecular differences are also manifested in the interaction energies of IUPs. Our approximation of these by low-resolution force-fields shows that IUPs gain much more stabilization energy from intermolecular contacts, than from folding, i.e. they use their binding energy for folding. Overall, our findings provide a structural rationale to the prior suggestions that many IUPs are specialized for functions realized by protein-protein interactions.     

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.     

Predicting protein-protein interactions on a proteome scale by matching evolutionary and structural similarities at interfaces using PRISM

Prediction of protein-protein interactions at the structural level on the proteome scale is important because it allows prediction of protein function, helps drug discovery and takes steps toward genome-wide structural systems biology. We provide a protocol (termed PRISM, protein interactions by structural matching) for large-scale prediction of protein-protein interactions and assembly of protein complex structures. The method consists of two components: rigid-body structural comparisons of target proteins to known template protein-protein interfaces and flexible refinement using a docking energy function. The PRISM rationale follows our observation that globally different protein structures can interact via similar architectural motifs. PRISM predicts binding residues by using structural similarity and evolutionary conservation of putative binding residue 'hot spots'. Ultimately, PRISM could help to construct cellular pathways and functional, proteome-scale annotation. PRISM is implemented in Python and runs in a UNIX environment. The program accepts Protein Data Bank-formatted protein structures and is available at http://prism.ccbb.ku.edu.tr/prism_protocol/.     

Structural segments and residue propensities in protein-RNA interfaces: comparison with protein-protein and protein-DNA complexes

The interface of a protein molecule that is involved in binding another protein, DNA or RNA has been characterized in terms of the number of unique secondary structural segments (SSSs), made up of stretches of helix, strand and non-regular (NR) regions. On average 10-11 segments define the protein interface in protein-protein (PP) and protein-DNA (PD) complexes, while the number is higher (14) for protein-RNA (PR) complexes. While the length of helical segments in PP interaction increases with the interface area, this is not the case in PD and PR complexes. The propensities of residues to occur in the three types of secondary structural elements (SSEs) in the interface relative to the corresponding elements in the protein tertiary structures have been calculated. Arg, Lys, Asn, Tyr, His and Gln are preferred residues in PR complexes; in addition, Ser and Thr are also favoured in PD interfaces.     

Structural characterisation and functional significance of transient protein-protein interactions

Protein-protein complexes that dissociate and associate readily, often depending on the physiological condition or environment, play an important role in many biological processes. In order to characterise these "transient" protein-protein interactions, two sets of complexes were collected and analysed. The first set consists of 16 experimentally validated "weak" transient homodimers, which are known to exist as monomers and dimers at physiological concentration, with dissociation constants in the micromolar range. A set of 23 functionally validated transient (i.e. intracellular signalling) heterodimers comprise the second set. This set includes complexes that are more stable, with nanomolar binding affinities, and require a molecular trigger to form and break the interaction. In comparison to more stable homodimeric complexes, the weak homodimers demonstrate smaller contact areas between protomers and the interfaces are more planar and polar on average. The physicochemical and geometrical properties of these weak homodimers more closely resemble those of non-obligate hetero-oligomeric complexes, whose components can exist either as monomers or as complexes in vivo. In contrast to the weak transient dimers, "strong" transient dimers often undergo large conformational changes upon association/dissociation and are characterised with larger, less planar and sometimes more hydrophobic interfaces. From sequence alignments we find that the interface residues of the weak transient homodimers are generally more conserved than surface residues, consistent with being constrained to maintain the protein-protein interaction during evolution. Protein families that include members with different oligomeric states or structures are identified, and found to exhibit a lower sequence conservation at the interface. The results are discussed in terms of the physiological function and evolution of protein-protein interactions.     

Structural similarity and classification of protein interaction interfaces

Interactions between proteins play a key role in many cellular processes. Studying protein-protein interactions that share similar interaction interfaces may shed light on their evolution and could be helpful in elucidating the mechanisms behind stability and dynamics of the protein complexes. When two complexes share structurally similar subunits, the similarity of the interaction interfaces can be found through a structural superposition of the subunits. However, an accurate detection of similarity between the protein complexes containing subunits of unrelated structure remains an open problem. Here, we present an alignment-free machine learning approach to measure interface similarity. The approach relies on the feature-based representation of protein interfaces and does not depend on the superposition of the interacting subunit pairs. Specifically, we develop an SVM classifier of similar and dissimilar interfaces and derive a feature-based interface similarity measure. Next, the similarity measure is applied to a set of 2,806×2,806 binary complex pairs to build a hierarchical classification of protein-protein interactions. Finally, we explore case studies of similar interfaces from each level of the hierarchy, considering cases when the subunits forming interactions are either homologous or structurally unrelated. The analysis has suggested that the positions of charged residues in the homologous interfaces are not necessarily conserved and may exhibit more complex conservation patterns.     

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.     

The many faces of protein-protein interactions: A compendium of interface geometry

A systematic classification of protein-protein interfaces is a valuable resource for understanding the principles of molecular recognition and for modelling protein complexes. Here, we present a classification of domain interfaces according to their geometry. Our new algorithm uses a hybrid approach of both sequential and structural features. The accuracy is evaluated on a hand-curated dataset of 416 interfaces. Our hybrid procedure achieves 83% precision and 95% recall, which improves the earlier sequence-based method by 5% on both terms. We classify virtually all domain interfaces of known structure, which results in nearly 6,000 distinct types of interfaces. In 40% of the cases, the interacting domain families associate in multiple orientations, suggesting that all the possible binding orientations need to be explored for modelling multidomain proteins and protein complexes. In general, hub proteins are shown to use distinct surface regions (multiple faces) for interactions with different partners. Our classification provides a convenient framework to query genuine gene fusion, which conserves binding orientation in both fused and separate forms. The result suggests that the binding orientations are not conserved in at least one-third of the gene fusion cases detected by a conventional sequence similarity search. We show that any evolutionary analysis on interfaces can be skewed by multiple binding orientations and multiple interaction partners. The taxonomic distribution of interface types suggests that ancient interfaces common to the three major kingdoms of life are enriched by symmetric homodimers. The classification results are online at http://www.scoppi.org.     

Identification of protein-protein interaction sites from docking energy landscapes

Protein recognition is one of the most challenging and intriguing problems in structural biology. Despite all the available structural, sequence and biophysical information about protein-protein complexes, the physico-chemical patterns, if any, that make a protein surface likely to be involved in protein-protein interactions, remain elusive. Here, we apply protein docking simulations and analysis of the interaction energy landscapes to identify protein-protein interaction sites. The new protocol for global docking based on multi-start global energy optimization of an all-atom model of the ligand, with detailed receptor potentials and atomic solvation parameters optimized in a training set of 24 complexes, explores the conformational space around the whole receptor without restrictions. The ensembles of the rigid-body docking solutions generated by the simulations were subsequently used to project the docking energy landscapes onto the protein surfaces. We found that highly populated low-energy regions consistently corresponded to actual binding sites. The procedure was validated on a test set of 21 known protein-protein complexes not used in the training set. As much as 81% of the predicted high-propensity patch residues were located correctly in the native interfaces. This approach can guide the design of mutations on the surfaces of proteins, provide geometrical details of a possible interaction, and help to annotate protein surfaces in structural proteomics.     

Structural and thermodynamic strategies for site-specific DNA binding proteins

BACKGROUND: Site-specific protein-DNA complexes vary greatly in structural properties and in the thermodynamic strategy for achieving an appropriate binding free energy. A better understanding of the structural and energetic engineering principles might lead to rational methods for modification or design of such proteins. RESULTS: A novel analysis of ten site-specific protein-DNA complexes reveals a striking correspondence between the degree of imposed DNA distortion and the thermodynamic parameters of each system. For complexes with relatively undistorted DNA, favorable enthalpy change drives unfavorable entropy change, whereas for complexes with highly distorted DNA, unfavorable DeltaH degrees is driven by favorable DeltaS degrees. We show for the first time that protein-DNA associations have isothermal enthalpy-entropy compensation, distinct from temperature-dependent compensation, so DeltaH degrees and DeltaS degrees do not vary independently. All complexes have favorable DeltaH degrees from direct protein-DNA recognition interactions and favorable DeltaS degrees from water release. Systems that strongly distort the DNA nevertheless have net unfavorable DeltaH degrees as the result of molecular strain, primarily associated with the base pair destacking. These systems have little coupled protein folding and the strained interface suffers less immobilization, so DeltaS degrees is net favorable. By contrast, systems with little DNA distortion have net favorable DeltaH degrees, which must be counterbalanced by net unfavorable DeltaS degrees, derived from loss of vibrational entropy (a result of isothermal enthalpy-entropy compensation) and from coupling between DNA binding and protein folding. CONCLUSIONS: Isothermal enthalpy-entropy compensation implies that a structurally optimal, unstrained fit is achieved only at the cost of entropically unfavorable immobilization, whereas an enthalpically weaker, strained interface entails smaller entropic penalties.     

Peptide segments in protein-protein interfaces

An important component of functional genomics involves the understanding of protein association. The interfaces resulting from protein-protein interactions - (i) specific, as represented by the homodimeric quaternary structures and the complexes formed by two independently occurring protein components, and (ii) non-specific, as observed in the crystal lattice of monomeric proteins - have been analysed on the basis of the length and the number of peptide segments. In 1000 A2 of the interface area, contributed by a polypeptide chain, there would be 3.4 segments in homodimers, 5.6 in complexes and 6.3 in crystal contacts. Concomitantly, the segments are the longest (with 8.7 interface residues) in homodimers. Core segments (likely to contribute more towards binding) are more in number in homodimers (1.7) than in crystal contacts (0.5), and this number can be used as one of the parameters to distinguish between the two types of interfaces. Dominant segments involved in specific interactions, along with their secondary structural features, are enumerated.     

Geometric Similarities of Protein-Protein Interfaces at Atomic Resolution Are Only Observed within Homologous Families: An Exhaustive Structural Classification Study

To elucidate the structural basis of the diversity and universality in protein-protein interactions, an exhaustive all-against-all structural comparison of all known protein interfaces in the Protein Data Bank was performed at atomic resolution. After similar interfaces were clustered, approximately 20,000 structural motifs with at least two members were identified, out of which 3678 motifs consisted of at least 10 interfaces. Except for some trivial interfaces involving single α helices, almost all motifs were found to be confined within single protein families. Furthermore, the interaction partners of each motif were found to be very limited, and, accordingly, the interaction networks of the motifs tend to be small and are much more restricted than the binding sites for small ligand molecules. These findings suggest that, at the level of atomic structures, protein-protein interactions are precisely designed; hence, protein interfaces with multiple interacting partners should involve incompletely overlapping multiple interfaces and/or accommodate structural changes upon binding to their targets.     

A dissection of specific and non-specific protein-protein interfaces

We compare the geometric and physical-chemical properties of interfaces involved in specific and non-specific protein-protein interactions in crystal structures reported in the Protein Data Bank. Specific interactions are illustrated by 70 protein-protein complexes and by subunit contacts in 122 homodimeric proteins; non-specific interactions are illustrated by 188 pairs of monomeric proteins making crystal-packing contacts selected to bury more than 800 A2 of protein surface. A majority of these pairs have 2-fold symmetry and form "crystal dimers" that cannot be distinguished from real dimers on the basis of the interface size or symmetry. The chemical and amino acid compositions of the large crystal-packing interfaces resemble the protein solvent-accessible surface. These interfaces are less hydrophobic than in homodimers and contain much fewer fully buried atoms. We develop a residue propensity score and a hydrophobic interaction score to assess preferences seen in the chemical and amino acid compositions of the different types of interfaces, and we derive indexes to evaluate the atomic packing, which we find to be less compact at non-specific than at specific interfaces. We test the capacity of these parameters to identify homodimeric proteins in crystal structures, and show that a simple combination of the non-polar interface area and the fraction of buried interface atoms assigns the quaternary structure of 88% of the homodimers and 77% of the monomers in our data set correctly. These success rates increase to 93-95% when the residue propensity score of the interfaces is taken into consideration.