Heteronuclear NMR and soft docking: an experimental approach for a structural model of the cytochrome c553-ferredoxin complex

The combination of docking algorithms with NMR data has been developed extensively for the studies of protein-ligand interactions. However, to extend this development for the studies of protein-protein interactions, the intermolecular NOE constraints, which are needed, are more difficult to access. In the present work, we describe a new approach that combines an ab initio docking calculation and the mapping of an interaction site using chemical shift variation analysis. The cytochrome c553-ferredoxin complex is used as a model of numerous electron-transfer complexes. The 15N-labeling of both molecules has been obtained, and the mapping of the interacting site on each partner, respectively, has been done using HSQC experiments. 1H and 15N chemical shift analysis defines the area of both molecules involved in the recognition interface. Models of the complex were generated by an ab initio docking software, the BiGGER program (bimolecular complex generation with global evaluation and ranking). This program generates a population of protein-protein docked geometries ranked by a scoring function, combining relevant stabilization parameters such as geometric complementarity surfaces, electrostatic interactions, desolvation energy, and pairwise affinities of amino acid side chains. We have implemented a new module that includes experimental input (here, NMR mapping of the interacting site) as a filter to select the accurate models. Final structures were energy minimized using the X-PLOR software and then analyzed. The best solution has an interface area (1037.4 A2) falling close to the range of generally observed recognition interfaces, with a distance of 10.0 A between the redox centers.     

Structural evidence that colicin A protein binds to a novel binding site of TolA protein in Escherichia coli periplasm

The Tol assembly of proteins is an interacting network of proteins located in the Escherichia coli cell envelope that transduces energy and contributes to cell integrity. TolA is central to this network linking the inner and outer membranes by interactions with TolQ, TolR, TolB, and Pal. Group A colicins, such as ColA, parasitize the Tol network through interactions with TolA and/or TolB to facilitate translocation through the cell envelope to reach their cytotoxic site of action. We have determined the first structure of the C-terminal domain of TolA (TolAIII) bound to an N-terminal ColA polypeptide (TA(53-107)). The interface region of the TA(53-107)-TolAIII complex consists of polar contacts linking residues Arg-92 to Arg-96 of ColA with residues Leu-375-Pro-380 of TolA, which constitutes a β-strand addition commonly seen in more promiscuous protein-protein contacts. The interface region also includes three cation-π interactions (Tyr-58-Lys-368, Tyr-90-Lys-379, Phe-94-Lys-396), which have not been observed in any other colicin-Tol protein complex. Mutagenesis of the interface residues of ColA or TolA revealed that the effect on the interaction was cumulative; single mutations of either partner had no effect on ColA activity, whereas mutations of three or more residues significantly reduced ColA activity. Mutagenesis of the aromatic ring component of the cation-π interacting residues showed Tyr-58 of ColA to be essential for the stability of complex formation. TA(53-107) binds on the opposite side of TolAIII to that used by g3p, ColN, or TolB, illustrating the flexible nature of TolA as a periplasmic hub protein.     

Structural determination of biomolecular interfaces by nuclear magnetic resonance of proteins with reduced proton density

Protein interactions are important for understanding many molecular mechanisms underlying cellular processes. So far, interfaces between interacting proteins have been characterized by NMR spectroscopy mostly by using chemical shift perturbations and cross-saturation via intermolecular cross-relaxation. Although powerful, these techniques cannot provide unambiguous estimates of intermolecular distances between interacting proteins. Here, we present an alternative approach, called REDSPRINT (REDduced/Standard PRoton density INTerface identification), to map protein interfaces with greater accuracy by using multiple NMR probes. Our approach is based on monitoring the cross-relaxation from a source protein (or from an arbitrary ligand that need not be a protein) with high proton density to a target protein (or other biomolecule) with low proton density by using isotope-filtered nuclear Overhauser spectroscopy (NOESY). This methodology uses different isotropic labeling for the source and target proteins to identify the source-target interface and also determine the proton density of the source protein at the interface for protein-protein or protein-ligand docking. Simulation indicates significant gains in sensitivity because of the resultant relaxation properties, and the utility of this technique, including a method for direct determination of the protein interface, is demonstrated for two different protein–protein complexes.     

Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer

Blocking specific protein interactions can lead to human diseases. Accordingly, protein interactions and the structural knowledge on interacting surfaces of proteins (interfaces) have an important role in predicting the genotype-phenotype relationship. We have built the phenotype specific sub-networks of protein-protein interactions (PPIs) involving the relevant genes responsible for lung and brain metastasis from primary tumor in breast cancer. First, we selected the PPIs most relevant to metastasis causing genes (seed genes), by using the “guilt-by-association” principle. Then, we modeled structures of the interactions whose complex forms are not available in Protein Databank (PDB). Finally, we mapped mutations to interface structures (real and modeled), in order to spot the interactions that might be manipulated by these mutations. Functional analyses performed on these sub-networks revealed the potential relationship between immune system-infectious diseases and lung metastasis progression, but this connection was not observed significantly in the brain metastasis. Besides, structural analyses showed that some PPI interfaces in both metastasis sub-networks are originating from microbial proteins, which in turn were mostly related with cell adhesion. Cell adhesion is a key mechanism in metastasis, therefore these PPIs may be involved in similar molecular pathways that are shared by infectious disease and metastasis. Finally, by mapping the mutations and amino acid variations on the interface regions of the proteins in the metastasis sub-networks we found evidence for some mutations to be involved in the mechanisms differentiating the type of the metastasis.     

Site-directed spin labeling study of subunit interactions in the alpha-crystallin domain of small heat-shock proteins. Comparison of the oligomer symmetry in alphaA-crystallin, HSP 27, and HSP 16.3

Site-directed spin labeling was used to investigate quaternary interactions along a conserved sequence in the alpha-crystallin domain of alphaA-crystallin, heat-shock protein 27 (HSP 27), and Mycobacterium tuberculosis heat-shock protein (HSP 16.3). In previous work, it was demonstrated that this sequence in alphaA-crystallin and HSP 27 forms a beta-strand involved in subunit contacts. In this study, the symmetry and geometry of the resulting interface were investigated. For this purpose, the pattern of spin-spin interactions was analyzed, and the number of interacting spins was determined in alphaA-crystallin and HSP 27. The results reveal a 2-fold symmetric interface consisting of two beta-strands interacting near their N termini in an antiparallel fashion. Remarkably, subunit interactions along this interface persist when the alpha-crystallin domains are expressed in isolation. Because this domain in alphaA-crystallin forms dimers and tetramers, it is inferred that interactions along this interface mediate the formation of a basic dimeric unit. In contrast, in HSP 16.3, spin-spin interactions are observed at only one site near the C terminus of the sequence. Furthermore, cysteine substitutions at residues flanking the N terminus resulted in the dissociation of the oligomeric structure. Analysis of the spin-spin interactions and size exclusion chromatography indicates a 3-fold symmetric interface. Taken together, our results demonstrate that subunit interactions in the alpha-crystallin domain of mammalian small heat-shock proteins assemble a basic building block of the oligomeric structure. Sequence divergence in this domain results in variations in the size and symmetry of the quaternary structure between distant members of the small heat-shock protein family.     

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.     

PICK1：一个功能多样的药靶蛋白

蛋白质是生命功能的执行者.生命体中某些关键蛋白的功能异常往往是导致疾病发生的根本原因.这些疾病相关蛋白极有可能成为药物靶点,为新药研发和疾病治疗提供重要线索. PICK1蛋白（protein interacting with Cα kinase 1）结合能力广泛、功能多样以及在多种重要疾病（如：癌症、精神分裂症、疼痛、帕金森综合症等）的发生发展过程中发挥潜在的作用,使其成为一个可能的药靶蛋白. PICK1与绝大多数配体蛋白的相互作用是通过其PDZ结构域与配体C末端区域的结合介导的,使PICK1的PDZ结构域成为一个潜在的药物靶点.因此,可以利用生物小分子物质特异性地结合PICK1的PDZ结构域,干扰或阻断PICK1与配体蛋白的天然相互作用,最终达到治疗相关疾病的目的.     

Transmembrane domains interactions within the membrane milieu: Principles, advances and challenges

Protein-protein interactions within the membrane are involved in many vital cellular processes. Consequently, deficient oligomerization is associated with known diseases. The interactions can be partially or fully mediated by transmembrane domains (TMD). However, in contrast to soluble regions, our knowledge of the factors that control oligomerization and recognition between the membrane-embedded domains is very limited. Due to the unique chemical and physical properties of the membrane environment, rules that apply to interactions between soluble segments are not necessarily valid within the membrane. This review summarizes our knowledge on the sequences mediating TMD-TMD interactions which include conserved motifs such as the GxxxG, QxxS, glycine and leucine zippers, and others. The review discusses the specific role of polar, charged and aromatic amino acids in the interface of the interacting TMD helices. Strategies to determine the strength, dynamics and specificities of these interactions by experimental (ToxR, TOXCAT, GALLEX and FRET) or various computational approaches (molecular dynamic simulation and bioinformatics) are summarized. Importantly, the contribution of the membrane environment to the TMD-TMD interaction is also presented. Studies utilizing exogenously added TMD peptides have been shown to influence in vivo the dimerization of intact membrane proteins involved in various diseases. The chirality independent TMD-TMD interactions allows for the design of novel short d- and l-amino acids containing TMD peptides with advanced properties. Overall these studies shed light on the role of specific amino acids in mediating the assembly of the TMDs within the membrane environment and their contribution to protein function. This article is part of a Special Issue entitled: Protein Folding in Membranes.     

Non‐interacting surface solvation and dynamics in protein–protein interactions

Protein–protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure‐based drug design methods, as well as design of de novo binders with preferred interaction properties. At a structural and molecular level, interface and rim regions are not enough to fully account for the energetics of protein–protein binding, even for simple lock‐and‐key rigid binders. As we have recently shown, properties of the global surface might also play a role in protein–protein interactions. Here, we report on molecular dynamics simulations performed to understand solvent effects on protein–protein surfaces. We compare properties of the interface, rim, and non‐interacting surface regions for five different complexes and their free components. Interface and rim residues become, as expected, less mobile upon complexation. However, non‐interacting surface appears more flexible in the complex. Fluctuations of polar residues are always lower compared with charged ones, independent of the protein state. Further, stable water molecules are often observed around polar residues, in contrast to charged ones. Our analysis reveals that (a) upon complexation, the non‐interacting surface can have a direct entropic compensation for the lower interface and rim entropy and (b) the mobility of the first hydration layer, which is linked to the stability of the protein–protein complex, is influenced by the local chemical properties of the surface. These findings corroborate previous hypotheses on the role of the hydration layer in shielding protein–protein complexes from unintended protein–protein interactions. Proteins 2015; 83:445–458. © 2014 Wiley Periodicals, Inc.     

Insights into protein-DNA interactions through structure network analysis

Protein-DNA interactions are crucial for many cellular processes. Now with the increased availability of structures of protein-DNA complexes, gaining deeper insights into the nature of protein-DNA interactions has become possible. Earlier, investigations have characterized the interface properties by considering pairwise interactions. However, the information communicated along the interfaces is rarely a pairwise phenomenon, and we feel that a global picture can be obtained by considering a protein-DNA complex as a network of noncovalently interacting systems. Furthermore, most of the earlier investigations have been carried out from the protein point of view (protein-centric), and the present network approach aims to combine both the protein-centric and the DNA-centric points of view. Part of the study involves the development of methodology to investigate protein-DNA graphs/networks with the development of key parameters. A network representation provides a holistic view of the interacting surface and has been reported here for the first time. The second part of the study involves the analyses of these graphs in terms of clusters of interacting residues and the identification of highly connected residues (hubs) along the protein-DNA interface. A predominance of deoxyribose-amino acid clusters in beta-sheet proteins, distinction of the interface clusters in helix-turn-helix, and the zipper-type proteins would not have been possible by conventional pairwise interaction analysis. Additionally, we propose a potential classification scheme for a set of protein-DNA complexes on the basis of the protein-DNA interface clusters. This provides a general idea of how the proteins interact with the different components of DNA in different complexes. Thus, we believe that the present graph-based method provides a deeper insight into the analysis of the protein-DNA recognition mechanisms by throwing more light on the nature and the specificity of these interactions.     

Structural consequences of anesthetic and nonimmobilizer interaction with gramicidin A channels

Although interactions of general anesthetics with soluble proteins have been studied, the specific interactions with membrane bound-proteins that characterize general anesthesia are largely unknown. The structural modulations of anesthetic interactions with synaptic ion channels have not been elucidated. Using gramicidin A as a simplified model for transmembrane ion channels, we have recently demonstrated that a pair of structurally similar volatile anesthetic and nonimmobilizer, 1-chloro-1,2,2-trifluorocyclobutane (F3) and 1,2-dichlorohexafluorocyclobutane (F6), respectively, have distinctly different effects on the channel function. Using high-resolution NMR structural analysis, we show here that neither F3 nor F6 at pharmacologically relevant concentrations can significantly affect the secondary structure of the gramicidin A channel. Although both the anesthetic F3 and the nonimmobilizer F6 can perturb residues at the middle section of the channel deep inside the hydrophobic region in the sodium dodecyl sulfate micelles, only F3, but not F6, can significantly alter the chemical shifts of the tryptophan indole N-H protons near the channel entrances. The results are consistent with the notion that anesthetics cause functional change of the channel by interacting with the amphipathic domains at the peptide-lipid-water interface.     

A Frustrated Binding Interface for Intrinsically Disordered Proteins

Intrinsically disordered proteins are very common in the eukaryotic proteome, and many of them are associated with diseases. Disordered proteins usually undergo a coupled binding and folding reaction and often interact with many different binding partners. Using double mutant cycles, we mapped the energy landscape of the binding interface for two interacting disordered domains and found it to be largely suboptimal in terms of interaction free energies, despite relatively high affinity. These data depict a frustrated energy landscape for interactions involving intrinsically disordered proteins, which is likely a result of their functional promiscuity.     

Discovery of multiple interacting partners of gankyrin,a proteasomal chaperone and an oncoprotein—Evidence for a common hot spot site at the interface and its functional relevance

Gankyrin, a non‐ATPase component of the proteasome and a chaperone of proteasome assembly, is also an oncoprotein. Gankyrin regulates a variety of oncogenic signaling pathways in cancer cells and accelerates degradation of tumor suppressor proteins p53 and Rb. Therefore gankyrin may be a unique hub integrating signaling networks with the degradation pathway. To identify new interactions that may be crucial in consolidating its role as an oncogenic hub, crystal structure of gankyrin‐proteasome ATPase complex was used to predict novel interacting partners. EEVD, a four amino acid linear sequence seems a hot spot site at this interface. By searching for EEVD in exposed regions of human proteins in PDB database, we predicted 34 novel interactions. Eight proteins were tested and seven of them were found to interact with gankyrin. Affinity of four interactions is high enough for endogenous detection. Others require gankyrin overexpression in HEK 293 cells or occur endogenously in breast cancer cell line‐ MDA‐MB‐435, reflecting lower affinity or presence of a deregulated network. Mutagenesis and peptide inhibition confirm that EEVD is the common hot spot site at these interfaces and therefore a potential polypharmacological drug target. In MDA‐MB‐231 cells in which the endogenous CLIC1 is silenced, trans‐expression of Wt protein (CLIC1_EEVD) and not the hot spot site mutant (CLIC1_AAVA) resulted in significant rescue of the migratory potential. Our approach can be extended to identify novel functionally relevant protein‐protein interactions, in expansion of oncogenic networks and in identifying potential therapeutic targets. Proteins 2014; 82:1283–1300. © 2013 Wiley Periodicals, Inc.     

Physical and genetic interactions of yeast Cwc21p,an ortholog of human SRm300/SRRM2, suggest a role at the catalytic center of the spliceosome

In Saccharomyces cerevisiae, Cwc21p is a protein of unknown function that is associated with the NineTeen Complex (NTC), a group of proteins involved in activating the spliceosome to promote the pre-mRNA splicing reaction. Here, we show that Cwc21p binds directly to two key splicing factors—namely, Prp8p and Snu114p—and becomes the first NTC-related protein known to dock directly to U5 snRNP proteins. Using a combination of proteomic techniques we show that the N-terminus of Prp8p contains an intramolecular fold that is a Snu114p and Cwc21p interacting domain (SCwid). Cwc21p also binds directly to the C-terminus of Snu114p. Complementary chemical cross-linking experiments reveal reciprocal protein footprints between the interacting Prp8 and Cwc21 proteins, identifying the conserved cwf21 domain in Cwc21p as a Prp8p binding site. Genetic and functional interactions between Cwc21p and Isy1p indicate that they have related functions at or prior to the first catalytic step of splicing, and suggest that Cwc21p functions at the catalytic center of the spliceosome, possibly in response to environmental or metabolic changes. We demonstrate that SRm300, the only SR-related protein known to be at the core of human catalytic spliceosomes, is a functional ortholog of Cwc21p, also interacting directly with Prp8p and Snu114p. Thus, the function of Cwc21p is likely conserved from yeast to humans.     

A quantitative analysis of interfacial amino acid conservation in protein-protein hetero complexes

A long-standing question in molecular biology is whether interfaces of protein-protein complexes are more conserved than the rest of the protein surfaces. Although it has been reported that conservation can be used as an indicator for predicting interaction sites on proteins, there are recent reports stating that the interface regions are only slightly more conserved than the rest of the protein surfaces, with conservation signals not being statistically significant enough for predicting protein-protein binding sites. In order to properly address these controversial reports we have studied a set of 28 well resolved hetero complex structures of proteins that consists of transient and non-transient complexes. The surface positions were classified into four conservation classes and the conservation index of the surface positions was quantitatively analyzed. The results indicate that the surface density of highly conserved positions is significantly higher in the protein-protein interface regions compared with the other regions of the protein surface. However, the average conservation index of the patches in the interface region is not significantly higher compared with other surface regions of the protein structures. This finding demonstrates that the number of conserved residue positions is a more appropriate indicator for predicting protein-protein binding sites than the average conservation index in the interacting region. We have further validated our findings on a set of 59 benchmark complex structures. Furthermore, an analysis of 19 complexes of antigen-antibody interactions shows that there is no conservation of amino acid positions in the interacting regions of these complexes, as expected, with the variable region of the immunoglobulins interacting mostly with the antigens. Interestingly, antigen interacting regions also have a higher number of non-conserved residue positions in the interacting region than the rest of the protein surface.     

Characterization of protein hubs by inferring interacting motifs from protein interactions

The characterization of protein interactions is essential for understanding biological systems. While genome-scale methods are available for identifying interacting proteins, they do not pinpoint the interacting motifs (e.g., a domain, sequence segments, a binding site, or a set of residues). Here, we develop and apply a method for delineating the interacting motifs of hub proteins (i.e., highly connected proteins). The method relies on the observation that proteins with common interaction partners tend to interact with these partners through a common interacting motif. The sole input for the method are binary protein interactions; neither sequence nor structure information is needed. The approach is evaluated by comparing the inferred interacting motifs with domain families defined for 368 proteins in the Structural Classification of Proteins (SCOP). The positive predictive value of the method for detecting proteins with common SCOP families is 75% at sensitivity of 10%. Most of the inferred interacting motifs were significantly associated with sequence patterns, which could be responsible for the common interactions. We find that yeast hubs with multiple interacting motifs are more likely to be essential than hubs with one or two interacting motifs, thus rationalizing the previously observed correlation between essentiality and the number of interacting partners of a protein. We also find that yeast hubs with multiple interacting motifs evolve slower than the average protein, contrary to the hubs with one or two interacting motifs. The proposed method will help us discover unknown interacting motifs and provide biological insights about protein hubs and their roles in interaction networks.     

Generation and analysis of a protein-protein interface data set with similar chemical and spatial patterns of interactions

Protein-protein interfaces are regions between 2 polypeptide chains that are not covalently connected. Here, we have created a nonredundant interface data set generated from all 2-chain interfaces in the Protein Data Bank. This data set is unique, since it contains clusters of interfaces with similar shapes and spatial organization of chemical functional groups. The data set allows statistical investigation of similar interfaces, as well as the identification and analysis of the chemical forces that account for the protein-protein associations. Toward this goal, we have developed I2I-SiteEngine (Interface-to-Interface SiteEngine) [Data set available at http://bioinfo3d.cs.tau.ac.il/Interfaces; Web server: http://bioinfo3d.cs.tau.ac.il/I2I-SiteEngine]. The algorithm recognizes similarities between protein-protein binding surfaces. I2I-SiteEngine is independent of the sequence or the fold of the proteins that comprise the interfaces. In addition to geometry, the method takes into account both the backbone and the side-chain physicochemical properties of the interacting atom groups. Its high efficiency makes it suitable for large-scale database searches and classifications. Below, we briefly describe the I2I-SiteEngine method. We focus on the classification process and the obtained nonredundant protein-protein interface data set. In particular, we analyze the biological significance of the clusters and present examples which illustrate that given constellations of chemical groups in protein-protein binding sites may be preferred, and are observed in proteins with different structures and different functions. We expect that these would yield further information regarding the forces stabilizing protein-protein interactions.     

Investigation at residue level of the early steps during the assembly of two proteins into supramolecular objects

Understanding the driving forces governing protein assembly requires the characterization of interactions at molecular level. We focus on two homologous oppositely charged proteins, lysozyme and α-lactalbumin, which can assemble into microspheres. The assembly early steps were characterized through the identification of interacting surfaces monitored at residue level by NMR chemical shift perturbations by titrating one (15)N-labeled protein with its unlabeled partner. While α-lactalbumin has a narrow interacting site, lysozyme has interacting sites scattered on a broad surface. The further assembly of these rather unspecific heterodimers into tetramers leads to the establishment of well-defined interaction sites. Within the tetramers, most of the electrostatic charge patches on the protein surfaces are shielded. Then, hydrophobic interactions, which are possible because α-lactalbumin is in a partially folded state, become preponderant, leading to the formation of larger oligomers. This approach will be particularly useful for rationalizing the design of protein assemblies as nanoscale devices.     

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.