Actin-actin binding protein interfaces

The recent elucidation of the three-dimensional structure of gelsolin segment 1 and profilin provides new insights on how these proteins recognize actin. Although the picture is still incomplete and not all biochemical data are consolidated, the results offer clues on how these proteins exert their effect on actin and how they may modulate the cytoskeleton dynamics. Binding studies on the villin head piece, thymosin β4 and mutants of both peptides allowed to identify critical residues important for actin binding and give the first picture of new actin binding interfaces. The interface of the modelled actomyosin complex is also briefly discussed.     

Protein domain interfaces: characterization and comparison with oligomeric protein interfaces

The physical and chemical properties of domain-domain interactions have been analysed in two-domain proteins selected from the protein classification, CATH. The two-domain structures were divided into those derived from (i) monomeric proteins, or (ii) oligomeric or complexed proteins. The size, polarity, hydrogen bonding and packing of the intra-chain domain interface were calculated for both sets of two-domain structures. The results were compared with inter-chain interface parameters from permanent and non-obligate protein-protein complexes. In general, the intra-chain domain and inter-chain interfaces were remarkably similar. Many of the intra-chain interface properties are intermediate between those calculated for permanent and non-obligate inter-chain complexes. Residue interface propensities were also found to be very similar, with hydrophobic residues playing a major role, together with positively charged arginine residues. In addition, the residue composition of the domain interfaces were found to be more comparable with domain surfaces than domain cores. The implications of these results for domain swapping and protein folding are discussed.     

Interaction modes at protein hetero-dimer interfaces

Hetero dimer (different monomers) interfaces are involved in catalysis and regulation through the formation of interface active sites. This is critical in cell and molecular biology events. The physical and chemical factors determining the formation of the interface active sites is often large in numbers. The combined role of interacting features is frequently combinatorial and additive in nature. Therefore, it is important to determine the physical and chemical features of such interactions. A number of such features have been documented in literature since 1975. However, the use of such interaction features in the prediction of interaction partners and sites given their sequences is still a challenge. In a non-redundant dataset of 156 hetero-dimer structures determined by X-ray crystallography, the interacting partners are often varying in size and thus, size variation between subunits is an important factor in determining the mode of interface formation. The size of protein subunits interacting are either small-small, largelarge, medium-medium, large-small, large-medium and small-medium. It should also be noted that the interface formed between subunits have physical interactions at N terminal (N), C terminal (C) and middle (M) region of the protein with reference to their sequences in one dimension. These features are believed to have application in the prediction of interaction partners and sites from sequences. However, the use of such features for interaction prediction from sequence is not currently clear.     

In silico identification of functional protein interfaces

Proteins perform many of their biological roles through protein-protein, protein-DNA or protein-ligand interfaces. The identification of the amino acids comprising these interfaces often enhances our understanding of the biological function of the proteins. Many methods for the detection of functional interfaces have been developed, and large-scale analyses have provided assessments of their accuracy. Among them are those that consider the size of the protein interface, its amino acid composition and its physicochemical and geometrical properties. Other methods to this effect use statistical potential functions of pairwise interactions, and evolutionary information. The rationale of the evolutionary approach is that functional and structural constraints impose selective pressure; hence, biologically important interfaces often evolve at a slower pace than do other external regions of the protein. Recently, an algorithm, Rate4Site, and a web-server, ConSurf (http://consurf.tau.ac.il/), for the identification of functional interfaces based on the evolutionary relations among homologous proteins as reflected in phylogenetic trees, were developed in our laboratory. The explicit use of the tree topology and branch lengths makes the method remarkably accurate and sensitive. Here we demonstrate its potency in the identification of the functional interfaces of a hypothetical protein, the structure of which was determined as part of the international structural genomics effort. Finally, we propose to combine complementary procedures, in order to enhance the overall performance of methods for the identification of functional interfaces in proteins.     

Interolog interfaces in protein–protein docking

Proteins are essential elements of biological systems, and their function typically relies on their ability to successfully bind to specific partners. Recently, an emphasis of study into protein interactions has been on hot spots, or residues in the binding interface that make a significant contribution to the binding energetics. In this study, we investigate how conservation of hot spots can be used to guide docking prediction. We show that the use of evolutionary data combined with hot spot prediction highlights near‐native structures across a range of benchmark examples. Our approach explores various strategies for using hot spots and evolutionary data to score protein complexes, using both absolute and chemical definitions of conservation along with refinements to these strategies that look at windowed conservation and filtering to ensure a minimum number of hot spots in each binding partner. Finally, structure‐based models of orthologs were generated for comparison with sequence‐based scoring. Using two data sets of 22 and 85 examples, a high rate of top 10 and top 1 predictions are observed, with up to 82% of examples returning a top 10 hit and 35% returning top 1 hit depending on the data set and strategy applied; upon inclusion of the native structure among the decoys, up to 55% of examples yielded a top 1 hit. The 20 common examples between data sets show that more carefully curated interolog data yields better predictions, particularly in achieving top 1 hits. Proteins 2015; 83:1940–1946. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.     

Exploring functional roles of multibinding protein interfaces

Cellular processes are highly interconnected and many proteins are shared in different pathways. Some of these shared proteins or protein families may interact with diverse partners using the same interface regions; such multibinding proteins are the subject of our study. The main goal of our study is to attempt to decipher the mechanisms of specific molecular recognition of multiple diverse partners by promiscuous protein regions. To address this, we attempt to analyze the physicochemical properties of multibinding interfaces and highlight the major mechanisms of functional switches realized through multibinding. We find that only 5% of protein families in the structure database have multibinding interfaces, and multibinding interfaces do not show any higher sequence conservation compared with the background interface sites. We highlight several important functional mechanisms utilized by multibinding families. (a) Overlap between different functional pathways can be prevented by the switches involving nearby residues of the same interfacial region. (b) Interfaces can be reused in pathways where the substrate should be passed from one protein to another sequentially. (c) The same protein family can develop different specificities toward different binding partners reusing the same interface; and finally, (d) inhibitors can attach to substrate binding sites as substrate mimicry and thereby prevent substrate binding.     

Factors affecting protein interaction at sorbent interfaces

Interactions between surfaces and macromolecules are the fundamentals in separation and detection of diverse solutes. In this very brief review the central aspects of protein-surface interactions are discussed with the intention of identifying the important factors influencing such processes and placing them in relation to the established knowledge in this field. Some perspectives of new techniques related to scanning probe microscopy for studying interactions at the nanometer level are also discussed.     

Analysis of homodimeric protein interfaces by graph-spectral methods

The quaternary structures impart structural and functional credibility to proteins. In a multi-subunit protein, it is important to understand the factors that drive the association or dissociation of the subunits. It is a well known fact that both hydrophobic and charged interactions contribute to the stability of the protein interface. The interface residues are also known to be highly conserved. Though they are buried in the oligomer, these residues are either exposed or partially exposed in the monomer. It is felt that a systematic and objective method of identifying interface clusters and their analysis can significantly contribute to the identification of a residue or a collection of residues important for oligomerization. Recently, we have applied the techniques of graph-spectral methods to a variety of problems related to protein structure and folding. A major advantage of this methodology is that the problem is viewed from a global protein topology point of view rather than localized regions of the protein structure. In the present investigation, we have applied the methods of graph-spectral analysis to identify side chain clusters at the interface and the centers of these clusters in a set of homodimeric proteins. These clusters are analyzed in terms of properties such as amino acid composition, accessibility to solvent and conservation of residues. Interesting results such as participation of charged and aromatic residues like arginine, glutamic acid, histidine, phenylalanine and tyrosine, consistent with earlier investigations, have emerged from these analyses. Important additional information is that the residues involved are a part of a cluster(s) and that they are sequentially distant residues which have come closer to each other in the three-dimensional structure of the protein. These residues can easily be detected using our graph-spectral algorithm. This method has also been used to identify important residues ('hot spots') in dimerization and also to detect dimerization sites on the monomer. The residues predicted using the present algorithm have correlated well with the experiments indicating the efficacy of this method in predicting residues involved in dimer stability.     

Cavities and packing at protein interfaces.

An analysis of internal packing defects or "cavities" (both empty and water-containing) within protein structures has been undertaken and includes 3 cavity classes: within domains, between domains, and between protein subunits. We confirm several basic features common to all cavity types but also find a number of new characteristics, including those that distinguish the classes. The total cavity volume remains only a small fraction of the total protein volume and yet increases with protein size. Water-filled "cavities" possess a more polar surface and are typically larger. Their constituent waters are necessary to satisfy the local hydrogen bonding potential. Cavity-surrounding atoms are observed to be, on average, less flexible than their environments. Intersubunit and interdomain cavities are on average larger than the intradomain cavities, occupy a larger fraction of their resident surfaces, and are more frequently water-filled. We observe increased cavity volume at domain-domain interfaces involved with shear type domain motions. The significance of interfacial cavities upon subunit and domain shape complementarity and the protein docking problem, as well as in their structural and functional role in oligomeric proteins, will be discussed. The results concerning cavity size, polarity, solvation, general abundance, and residue type constituency should provide useful guidelines for protein modeling and design.     

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.     

An investigation of protein subunit and domain interfaces

Protein structures were collected from the Brookhaven Database of tertiary architectures that displayed oligomeric association (24 molecules) or whose polypeptide folding revealed domains (34 proteins). The subunit and domain interfaces for these proteins were respectively examined from the following aspects: percentage water-accessible surface area buried by the respective associations, surface compositions and physical characteristics of the residues involved in the subunit and domain contacts, secondary structural state of the interface amino acids, preferred polar and non-polar interactions, spatial distribution of polar and non-polar residues on the interface surface, same residue interactions in the oligomeric contacts, and overall cross-section and shape of the contact surfaces. A general, consistent picture emerged for both the domain and subunit interfaces.     

Exploring protein interfaces with a general photochemical reagent

Protein folding, natural conformational changes, or interaction between partners involved in recognition phenomena brings about differences in the solvent-accessible surface area (SASA) of the polypeptide chain. This primary event can be monitored by the differential chemical reactivity of functional groups along the protein sequence. Diazirine (DZN), a photoreactive gas similar in size to water, generates methylene carbene (:CH(2)). The extreme chemical reactivity of this species allows the almost instantaneous and indiscriminate modification of its immediate molecular cage. (3)H-DZN was successfully used in our laboratory for studying protein structure and folding. Here we address for the first time the usefulness of this probe to examine the area of interaction in protein-protein complexes. For this purpose we chose the complex formed between hen egg white lysozyme (HEWL) and the monoclonal antibody IgG(1) D1.3. :CH(2) labeling of free HEWL or complexed with IgG(1) D1.3 yields 2.76 and 2.32 mmol CH(2) per mole protein at 1 mM DZN concentration, respectively. This reduction (15%) becomes consistent with the expected decrement in the SASA of HEWL occurring upon complexation derived from crystallographic data (11%), in agreement with the known unspecific surface labeling reaction of :CH(2). Further comparative analysis at the level of tryptic peptides led to the identification of the sites involved in the interaction. Remarkably, those peptides implicated in the contact area show the highest differential labeling: H(15)GLDNYR(21), G(117)TDVQAWIR(125), andG(22)YSLGNWVCAAK(33). Thus, protein footprinting with DZN emerges as a feasible methodology useful for mapping contact regions of protein domains involved in macromolecular assemblies.     

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.     

A hidden Markov model for predicting protein interfaces

Protein-protein interactions play a defining role in protein function. Identifying the sites of interaction in a protein is a critical problem for understanding its functional mechanisms, as well as for drug design. To predict sites within a protein chain that participate in protein complexes, we have developed a novel method based on the Hidden Markov Model, which combines several biological characteristics of the sequences neighboring a target residue: structural information, accessible surface area, and transition probability among amino acids. We have evaluated the method using 5-fold cross-validation on 139 unique proteins and demonstrated precision of 66% and recall of 61% in identifying interfaces. These results are better than those achieved by other methods used for identification of interfaces.     

The properties of human disease mutations at protein interfaces

The assembly of proteins into complexes and their interactions with other biomolecules are often vital for their biological function. While it is known that mutations at protein interfaces have a high potential to be damaging and cause human genetic disease, there has been relatively little consideration for how this varies between different types of interfaces. Here we investigate the properties of human pathogenic and putatively benign missense variants at homomeric (isologous and heterologous), heteromeric, DNA, RNA and other ligand interfaces, and at different regions in proteins with respect to those interfaces. We find that different types of interfaces vary greatly in their propensity to be associated with pathogenic mutations, with homomeric heterologous and DNA interfaces being particularly enriched in disease. We also find that residues that do not directly participate in an interface, but are close in three-dimensional space, show a significant disease enrichment. Finally, we observe that mutations at different types of interfaces tend to have distinct property changes when undergoing amino acid substitutions associated with disease, and that this is linked to substantial variability in their identification by computational variant effect predictors.     

Structural motifs in protein cores and at protein–protein interfaces are different

Structures of proteins and protein–protein complexes are determined by the same physical principles and thus share a number of similarities. At the same time, there could be differences because in order to function, proteins interact with other molecules, undergo conformations changes, and so forth, which might impose different restraints on the tertiary versus quaternary structures. This study focuses on structural properties of protein–protein interfaces in comparison with the protein core, based on the wealth of currently available structural data and new structure‐based approaches. The results showed that physicochemical characteristics, such as amino acid composition, residue–residue contact preferences, and hydrophilicity/hydrophobicity distributions, are similar in protein core and protein–protein interfaces. On the other hand, characteristics that reflect the evolutionary pressure, such as structural composition and packing, are largely different. The results provide important insight into fundamental properties of protein structure and function. At the same time, the results contribute to better understanding of the ways to dock proteins. Recent progress in predicting structures of individual proteins follows the advancement of deep learning techniques and new approaches to residue coevolution data. Protein core could potentially provide large amounts of data for application of the deep learning to docking. However, our results showed that the core motifs are significantly different from those at protein–protein interfaces, and thus may not be directly useful for docking. At the same time, such difference may help to overcome a major obstacle in application of the coevolutionary data to docking—discrimination of the intramolecular information not directly relevant to docking.     

An evolution based classifier for prediction of protein interfaces without using protein structures

MOTIVATION: The number of available protein structures still lags far behind the number of known protein sequences. This makes it important to predict which residues participate in protein-protein interactions using only sequence information. Few studies have tackled this problem until now. RESULTS: We applied support vector machines to sequences in order to generate a classification of all protein residues into those that are part of a protein interface and those that are not. For the first time evolutionary information was used as one of the attributes and this inclusion of evolutionary importance rankings improves the classification. Leave-one-out cross-validation experiments show that prediction accuracy reaches 64%.     

Protein–protein interfaces: mimics and inhibitors

Many biological processes are mediated by specific molecular recognition between proteins. However, the thermodynamic and structural 'rules' for such recognition are incompletely understood, as is the potential for inhibition by small molecules. Recent progress has included the discovery of small-molecule inhibitors for several targets important in cancer.