A strategy for grafting protein-protein binding sites is described. Firstly, key interaction residues at the interface of ligand protein to be grafted are identified and suitable positions in scaffold protein for grafting these key residues are sought. Secondly, the scaffold proteins are superposed onto the ligand protein based on the corresponding Ca and Cb atoms. The complementarity between the scaffold protein and the receptor protein is evaluated and only matches with high score are accepted. The relative position between scaffold and receptor proteins is adjusted so that the interface has a reasonable packing density. Then the scaffold protein is mutated to corresponding residues in ligand protein at each candidate position. And the residues having bad steric contacts with the receptor proteins, or buried charged residues not involved in the formation of any salt bridge are mutated. Finally, the mutated scaffold protein in complex with receptor protein is co-minimized by Charmm. In addition, we deduce a scoring function to evaluate the affinity between mutated scaffold protein and receptor protein by statistical analysis of rigid binding data sets.
The selection and study of descriptive variables of protein-protein complex interface is a major question that many biologists come across when the research of protein-protein recognition is concerned. Several variables have been proposed to understand the structural or energetic features of complex interfaces. Here a systematic study of some of these "traditional" variables, as well as a few new ones, is introduced. With the values of these variables extracted from 42 PDB samples with real or false complex interfaces, a binary logistic regression analysis is performed, which results in an effective empirical model for the evaluation of binding probabilities of protein-protein interfaces. The model is validated with 12 samples, and satisfactory results are obtained for both the training and validation sets. Meanwhile, three potential dimeric interfaces of staphylokinase have been investigated and one with the best suitability to our model is proposed.
Full Text Available The yeast two-hybrid (Y2H system exploits host cell genetics in order to display binary protein-protein interactions (PPIs via defined and selectable phenotypes. Numerous improvements have been made to this method, adapting the screening principle for diverse applications, including drug discovery and the scale-up for proteome wide interaction screens in human and other organisms. Here we discuss a systematic workflow and analysis scheme for screening data generated by Y2H and related assays that includes high-throughput selection procedures, readout of comprehensive results via next-generation sequencing (NGS, and the interpretation of interaction data via quantitative statistics. The novel assays and tools will serve the broader scientific community to harness the power of NGS technology to address PPI networks in health and disease. We discuss examples of how this next-generation platform can be applied to address specific questions in diverse fields of biology and medicine.
Letteboer, S.J.F.; Roepman, R.
Identification of binary protein-protein interactions is a crucial step in determining the molecular context and functional pathways of proteins. State-of-the-art proteomics techniques provide high-throughput information on the content of proteomes and protein complexes, but give little information
Li, Yan; Liu, Zhihai; Han, Li; Li, Chengke; Wang, Renxiao
Protein-protein interactions are observed in various biological processes. They are important for understanding the underlying molecular mechanisms and can be potential targets for developing small-molecule regulators of such processes. Previous studies suggest that certain residues on protein-protein binding interfaces are "hot spots". As an extension to this concept, we have developed a residue-based method to identify the characteristic interaction patterns (CIPs) on protein-protein binding interfaces, in which each pattern is a cluster of four contacting residues. Systematic analysis was conducted on a nonredundant set of 1,222 protein-protein binding interfaces selected out of the entire Protein Data Bank. Favored interaction patterns across different protein-protein binding interfaces were retrieved by considering both geometrical and chemical conservations. As demonstrated on two test tests, our method was able to predict hot spot residues on protein-protein binding interfaces with good recall scores and acceptable precision scores. By analyzing the function annotations and the evolutionary tree of the protein-protein complexes in our data set, we also observed that protein-protein interfaces sharing common characteristic interaction patterns are normally associated with identical or similar biological functions. PMID:23930922
Emperador, Agustí; Orozco, Modesto
We are optimizing a force-field to be used with our coarsegrained protein model for the recognition of protein -protein binding. We have found that, apart from ranking correctly the ligand-receptor conformations generated in a protein-protein docking algorithm, our model is able to distinguish binding (experimental structure) from nonbinding (false positive) conformations for many complexes. This suggests us that the model could have a good performance in complete cross-d...
Gao, Mu; Skolnick, Jeffrey
Protein-protein and protein-ligand interactions are ubiquitous in a biological cell. Here, we report a comprehensive study of the distribution of protein-ligand interaction sites, namely ligand-binding pockets, around protein-protein interfaces where protein-protein interactions occur. We inspected a representative set of 1,611 representative protein-protein complexes and identified pockets with a potential for binding small molecule ligands. The majority of these pockets are within a 6 Å dis...
Andberg, Tor Arne Heim
Absolute binding free energies for the third domain of the turkey ovomucoid inhibitor in complex with Streptomyces griseus proteinase B and porcine pancreatic elastase has been calculated using the linear interaction energy method.
Selvaraj S; Jayaram B; Saranya N; Gromiha M; Fukui Kazuhiko
Abstract Background Protein-protein interactions are important for several cellular processes. Understanding the mechanism of protein-protein recognition and predicting the binding sites in protein-protein complexes are long standing goals in molecular and computational biology. Methods We have developed an energy based approach for identifying the binding site residues in protein–protein complexes. The binding site residues have been analyzed with sequence and structure based parameters such...
Bertonati, Claudia; Honig, Barry; Alexov, Emil
The salt dependence of the binding free energy of five protein-protein hetero-dimers and two homo-dimers/tetramers was calculated from numerical solutions to the Poisson-Boltzmann equation. Overall, the agreement with experimental values is very good. In all cases except one involving the highly charged lactoglobulin homo-dimer, increasing the salt concentration is found both experimentally and theoretically to decrease the binding affinity. To clarify the source of salt effects, the salt-dep...
Full Text Available Abstract Background Protein-protein interactions are important for several cellular processes. Understanding the mechanism of protein-protein recognition and predicting the binding sites in protein-protein complexes are long standing goals in molecular and computational biology. Methods We have developed an energy based approach for identifying the binding site residues in protein–protein complexes. The binding site residues have been analyzed with sequence and structure based parameters such as binding propensity, neighboring residues in the vicinity of binding sites, conservation score and conformational switching. Results We observed that the binding propensities of amino acid residues are specific for protein-protein complexes. Further, typical dipeptides and tripeptides showed high preference for binding, which is unique to protein-protein complexes. Most of the binding site residues are highly conserved among homologous sequences. Our analysis showed that 7% of residues changed their conformations upon protein-protein complex formation and it is 9.2% and 6.6% in the binding and non-binding sites, respectively. Specifically, the residues Glu, Lys, Leu and Ser changed their conformation from coil to helix/strand and from helix to coil/strand. Leu, Ser, Thr and Val prefer to change their conformation from strand to coil/helix. Conclusions The results obtained in this study will be helpful for understanding and predicting the binding sites in protein-protein complexes.
Li, Minghui; Petukh, Marharyta; Alexov, Emil; Panchenko, Anna R
The crucial prerequisite for proper biological function is the protein's ability to establish highly selective interactions with macromolecular partners. A missense mutation that alters the protein binding affinity may cause significant perturbations or complete abolishment of the function, potentially leading to diseases. The availability of computational methods to evaluate the impact of mutations on protein-protein binding is critical for a wide range of biomedical applications. Here, we report an efficient computational approach for predicting the effect of single and multiple missense mutations on protein-protein binding affinity. It is based on a well-tested simulation protocol for structure minimization, modified MM-PBSA and statistical scoring energy functions with parameters optimized on experimental sets of several thousands of mutations. Our simulation protocol yields very good agreement between predicted and experimental values with Pearson correlation coefficients of 0.69 and 0.63 and root-mean-square errors of 1.20 and 1.90 kcal mol(-1) for single and multiple mutations, respectively. Compared with other available methods, our approach achieves high speed and prediction accuracy and can be applied to large datasets generated by modern genomics initiatives. In addition, we report a crucial role of water model and the polar solvation energy in estimating the changes in binding affinity. Our analysis also reveals that prediction accuracy and effect of mutations on binding strongly depends on the type of mutation and its location in a protein complex. PMID:24803870
Cao, Huaiqing; Huang, Yongqi; Liu, Zhirong
To clarify the interplay between the binding affinity and kinetics of protein-protein interactions, and the possible role of intrinsically disordered proteins in such interactions, molecular simulations were carried out on 20 protein complexes. With bias potential and reweighting techniques, the free energy profiles were obtained under physiological affinities, which showed that the bound-state valley is deep with a barrier height of 12 - 33 RT. From the dependence of the affinity on interface interactions, the entropic contribution to the binding affinity is approximated to be proportional to the interface area. The extracted dissociation rates based on the Arrhenius law correlate reasonably well with the experimental values (Pearson correlation coefficient R = 0.79). For each protein complex, a linear free energy relationship between binding affinity and the dissociation rate was confirmed, but the distribution of the slopes for intrinsically disordered proteins showed no essential difference with that observed for ordered proteins. A comparison with protein folding was also performed. Proteins 2016; 84:920-933. © 2016 Wiley Periodicals, Inc. PMID:27018856
Metz, Alexander; Pfleger, Christopher; Kopitz, Hannes; Pfeiffer-Marek, Stefania; Baringhaus, Karl-Heinz; Gohlke, Holger
Protein-protein interfaces are considered difficult targets for small-molecule protein-protein interaction modulators (PPIMs ). Here, we present for the first time a computational strategy that simultaneously considers aspects of energetics and plasticity in the context of PPIM binding to a protein interface. The strategy aims at identifying the determinants of small-molecule binding, hot spots, and transient pockets, in a protein-protein interface in order to make use of this knowledge for predicting binding modes of and ranking PPIMs with respect to their affinity. When applied to interleukin-2 (IL-2), the computationally inexpensive constrained geometric simulation method FRODA outperforms molecular dynamics simulations in sampling hydrophobic transient pockets. We introduce the PPIAnalyzer approach for identifying transient pockets on the basis of geometrical criteria only. A sequence of docking to identified transient pockets, starting structure selection based on hot spot information, RMSD clustering and intermolecular docking energies, and MM-PBSA calculations allows one to enrich IL-2 PPIMs from a set of decoys and to discriminate between subgroups of IL-2 PPIMs with low and high affinity. Our strategy will be applicable in a prospective manner where nothing else than a protein-protein complex structure is known; hence, it can well be the first step in a structure-based endeavor to identify PPIMs. PMID:22087639
Salcini, A E; Confalonieri, S; Doria, M;
EH is a recently identified protein-protein interaction domain found in the signal transducers Eps15 and Eps15R and several other proteins of yeast nematode. We show that EH domains from Eps15 and Eps15R bind in vitro to peptides containing an asparagine-proline-phenylalanine (NPF) motif. Direct...... screening of expression libraries with EH domains yielded a number of putative EH interactors, all of which possessed NPF motifs that were shown to be responsible for the interaction. Among these interactors were the human homolog of NUMB, a developmentally reguated gene of Drosophila, and RAB, the cellular...... cofactor of the HIV REV protein. We demonstrated coimmunoprecipitation of Eps15 with NUMB and RAB. Finally, in vitro binding of NPF-containing peptides to cellular proteins and EST database screening established the existence of a family of EH-containing proteins in mammals. Based on the characteristics of...
Canino, Lawrence S.; Shen, Tongye; McCammon, J. Andrew
We extend the self-consistent pair contact probability method to the evaluation of the partition function for a protein complex at thermodynamic equilibrium. Specifically, we adapt the method for multichain models and introduce a parametrization for amino acid-specific pairwise interactions. This method is similar to the Gaussian network model but allows for the adjusting of the strengths of native state contacts. The method is first validated on a high resolution x-ray crystal structure of bovine Pancreatic Phospholipase A2 by comparing calculated B-factors with reported values. We then examine binding-induced changes in flexibility in protein-protein complexes, comparing computed results with those obtained from x-ray crystal structures and molecular dynamics simulations. In particular, we focus on the mouse acetylcholinesterase:fasciculin II and the human α-thrombin:thrombomodulin complexes.
Rozinek, Sarah C.; Glickman, Randolph D.; Thomas, Robert J.; Brancaleon, Lorenzo
Bioeffects of directed-optical-energy encompass a wide range of applications. One aspect of photochemical interactions involves irradiating a photosensitizer with visible light in order to induce protein unfolding and consequent changes in function. In the past, irradiation of several dye-protein combinations has revealed effects on protein structure. Beta lactoglobulin, human serum albumin (HSA) and tubulin have all been photo-modified with meso-tetrakis(4- sulfonatophenyl)porphyrin (TSPP) bound, but only in the case of tubulin has binding caused a verified loss of biological function (loss of ability to form microtubules) as a result of this light-induced structural change. The current work questions if the photo-induced structural changes that occur to HSA, are sufficient to disable its biological function of binding to osteonectin. The albumin-binding protein, osteonectin, is about half the molecular weight of HSA, so the two proteins and their bound product can be separated and quantified by size exclusion high performance liquid chromatography. TSPP was first bound to HSA and irradiated, photo-modifying the structure of HSA. Then native HSA or photo-modified HSA (both with TSPP bound) were compared, to assess loss in HSA's innate binding ability as a result of light-induced structure modification.
Full Text Available Abstract Background The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate interaction information in the literature. We present an information extraction system that was designed to locate protein-protein interaction data in the literature and present these data to curators and the public for review and entry into BIND. Results Cross-validation estimated the support vector machine's test-set precision, accuracy and recall for classifying abstracts describing interaction information was 92%, 90% and 92% respectively. We estimated that the system would be able to recall up to 60% of all non-high throughput interactions present in another yeast-protein interaction database. Finally, this system was applied to a real-world curation problem and its use was found to reduce the task duration by 70% thus saving 176 days. Conclusions Machine learning methods are useful as tools to direct interaction and pathway database back-filling; however, this potential can only be realized if these techniques are coupled with human review and entry into a factual database such as BIND. The PreBIND system described here is available to the public at http://bind.ca. Current capabilities allow searching for human, mouse and yeast protein-interaction information.
Chen, Wentao; Dong, Jiajia; Plate, Lars; Mortenson, David E; Brighty, Gabriel J; Li, Suhua; Liu, Yu; Galmozzi, Andrea; Lee, Peter S; Hulce, Jonathan J; Cravatt, Benjamin F; Saez, Enrique; Powers, Evan T; Wilson, Ian A; Sharpless, K Barry; Kelly, Jeffery W
Arylfluorosulfates have appeared only rarely in the literature and have not been explored as probes for covalent conjugation to proteins, possibly because they were assumed to possess high reactivity, as with other sulfur(VI) halides. However, we find that arylfluorosulfates become reactive only under certain circumstances, e.g., when fluoride displacement by a nucleophile is facilitated. Herein, we explore the reactivity of structurally simple arylfluorosulfates toward the proteome of human cells. We demonstrate that the protein reactivity of arylfluorosulfates is lower than that of the corresponding aryl sulfonyl fluorides, which are better characterized with regard to proteome reactivity. We discovered that simple hydrophobic arylfluorosulfates selectively react with a few members of the intracellular lipid binding protein (iLBP) family. A central function of iLBPs is to deliver small-molecule ligands to nuclear hormone receptors. Arylfluorosulfate probe 1 reacts with a conserved tyrosine residue in the ligand-binding site of a subset of iLBPs. Arylfluorosulfate probes 3 and 4, featuring a biphenyl core, very selectively and efficiently modify cellular retinoic acid binding protein 2 (CRABP2), both in vitro and in living cells. The X-ray crystal structure of the CRABP2-4 conjugate, when considered together with binding site mutagenesis experiments, provides insight into how CRABP2 might activate arylfluorosulfates toward site-specific reaction. Treatment of breast cancer cells with probe 4 attenuates nuclear hormone receptor activity mediated by retinoic acid, an endogenous client lipid of CRABP2. Our findings demonstrate that arylfluorosulfates can selectively target single iLBPs, making them useful for understanding iLBP function. PMID:27191344
Craig, Tim J; Ciufo, Leonora F; Morgan, Alan
Protein-protein interactions, and the factors affecting them, are of fundamental importance to all biological systems. Surface plasmon resonance (SPR) and isothermal titration calorimetry (ITR) are powerful methods for assaying such interactions, but are expensive to implement. In contrast, bead-based pull-down assays using affinity tags such as glutathione-S-transferase (GST), require no specialist equipment. As a result, such assays are the most popular method for analysing protein-protein interactions, despite being time-consuming and prone to variability. In respect of these problems, we have modified this form of binding assay, using glutathione-coated 96-well plates rather than glutathione-Sepharose beads to bind the primary bait protein. Quantitation of bound protein utilises ELISA for purified proteins and scintillation counting for in vitro translated proteins, rather than the SDS-PAGE-based detection methods used in traditional bead-based assays. These modifications result in an approximately 10-fold increase in the number of samples that can be assayed daily, and allow results to be obtained within hours as opposed to days. We validate the modified assay by analysing the equilibrium binding of Munc18 and syntaxin, and also demonstrate that association and dissociation kinetics may be measured using this approach. The method we describe is generally applicable to any protein-protein interaction assay based on affinity tags and is amenable to automation, and so should benefit a wide range of biochemical research. PMID:15236910
Kastritis, Panagiotis L.; Garcia Lopes Maia Rodrigues, João; Bonvin, Alexandre M J J
The HADDOCK score, a scoring function for both protein-protein and protein-nucleic acid modeling, has been successful in selecting near-native docking poses in a variety of cases, including those of the CAPRI blind prediction experiment. However, it has yet to be optimized for small molecules, and i
Feliu, Elisenda; Aloy, Patrick; Oliva, Baldo
results were compared with a residue-pair potential scoring function (RPScore) and an atomic-detailed scoring function (Zrank). We have combined knowledge-based potentials to score protein-protein poses of decoys of complexes classified either as transient or as permanent protein-protein interactions......Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions for...... selecting rigid-body docking poses. These potentials include the energetic component that provides the residues with a particular secondary structure and surface accessibility. These scoring functions have been tested on a state-of-art benchmark dataset and on a decoy dataset of permanent interactions. Our...
Baskin Berivan; Zhang Shudong; Tuekam Brigitte; Lay Vicki; Wolting Cheryl; de Bruijn Berry; Martin Joel; Donaldson Ian; Bader Gary D; Michalickova Katerina; Pawson Tony; Hogue Christopher WV
Abstract Background The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND) seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate inte...
Jia, Jianhua; Liu, Zi; Xiao, Xuan; Liu, Bingxiang; Chou, Kuo-Chen
With the explosive growth of protein sequences entering into protein data banks in the post-genomic era, it is highly demanded to develop automated methods for rapidly and effectively identifying the protein-protein binding sites (PPBSs) based on the sequence information alone. To address this problem, we proposed a predictor called iPPBS-PseAAC, in which each amino acid residue site of the proteins concerned was treated as a 15-tuple peptide segment generated by sliding a window along the protein chains with its center aligned with the target residue. The working peptide segment is further formulated by a general form of pseudo amino acid composition via the following procedures: (1) it is converted into a numerical series via the physicochemical properties of amino acids; (2) the numerical series is subsequently converted into a 20-D feature vector by means of the stationary wavelet transform technique. Formed by many individual "Random Forest" classifiers, the operation engine to run prediction is a two-layer ensemble classifier, with the 1st-layer voting out the best training data-set from many bootstrap systems and the 2nd-layer voting out the most relevant one from seven physicochemical properties. Cross-validation tests indicate that the new predictor is very promising, meaning that many important key features, which are deeply hidden in complicated protein sequences, can be extracted via the wavelets transform approach, quite consistent with the facts that many important biological functions of proteins can be elucidated with their low-frequency internal motions. The web server of iPPBS-PseAAC is accessible at http://www.jci-bioinfo.cn/iPPBS-PseAAC , by which users can easily acquire their desired results without the need to follow the complicated mathematical equations involved. PMID:26375780
Full Text Available Abstract Background Signal transduction events often involve transient, yet specific, interactions between structurally conserved protein domains and polypeptide sequences in target proteins. The identification and validation of these associating domains is crucial to understand signal transduction pathways that modulate different cellular or developmental processes. Bioinformatics strategies to extract and integrate information from diverse sources have been shown to facilitate the experimental design to understand complex biological events. These methods, primarily based on information from high-throughput experiments, have also led to the identification of new connections thus providing hypothetical models for cellular events. Such models, in turn, provide a framework for directing experimental efforts for validating the predicted molecular rationale for complex cellular processes. In this context, it is envisaged that the rational design of peptides for protein-peptide binding studies could substantially facilitate the experimental strategies to evaluate a predicted interaction. This rational design procedure involves the integration of protein-protein interaction data, gene ontology, physico-chemical calculations, domain-domain interaction data and information on functional sites or critical residues. Results Here we describe an integrated approach called "PeptideMine" for the identification of peptides based on specific functional patterns present in the sequence of an interacting protein. This approach based on sequence searches in the interacting sequence space has been developed into a webserver, which can be used for the identification and analysis of peptides, peptide homologues or functional patterns from the interacting sequence space of a protein. To further facilitate experimental validation, the PeptideMine webserver also provides a list of physico-chemical parameters corresponding to the peptide to determine the feasibility of
Ming Yang; Yan Ge; Jiayan Wu; Jingfa Xiao; Jun Yu
Coevolution can be seen as the interdependency between evolutionary histories. In the context of protein evolution, functional correlation proteins are ever-present coordinated evolutionary characters without disruption of organismal integrity. As to complex system, there are two forms of protein-protein interactions in vivo, which refer to inter-complex interaction and intra-complex interaction. In this paper, we studied the difference of coevolution characters between inter-complex interaction and intra-complex interaction using "Mirror tree" method on the respiratory chain (RC) proteins. We divided the correlation coefficients of every pairwise RC proteins into two groups corresponding to the binary protein-protein interaction in intra-complex and the binary protein-protein interaction in inter-complex, respectively. A dramatical discrepancy is detected between the coevolution characters of the two sets of protein interactions (Wilcoxon test, p-value = 4.4 x 10-6). Our finding reveals some critical information on coevolutionary study and assists the mechanical investigation of protein-protein interaction.Furthermore, the results also provide some unique clue for supramolecular organization of protein complexes in the mitochondrial inner membrane. More detailed binding sites map and genome information of nuclear encoded RC proteins will be extraordinary valuable for the further mitochondria dynamics study.
Byron, Olwyn; Vestergaard, Bente
Responsive formation of protein:protein interaction (PPI) upon diverse stimuli is a fundament of cellular function. As a consequence, PPIs are complex, adaptive entities, and exist in structurally heterogeneous interplays defined by the energetic states of the free and complexed protomers. The...
Del Bene, Janet E.; Alkorta, Ibon; Sanchez-Sanz, Goar; Elguero, José
Ab initio MP2/aug'-cc-pVTZ calculations have been carried out to determine the structures and binding energies of binary complexes formed by HBO with a series of small molecules A. Three different types of structures have been identified, which depend on the nature of A. In one structure A:HBO, HBO acts as a weak proton donor. In the second HBO:A, HBO is a relatively strong base. The third type of complex A||HBO has HBO and A in an approximately parallel arrangement. The dipole moment of A influences both the type of complex formed and its binding energy.
The UvrA protein is the DNA binding and damage recognition subunit of the damage-specific UvrABC endonuclease. In addition, it is an ATPase/GTPase, and the binding energy of ATP is linked to dimerization of the UvrA protein. Furthermore, the UvrA protein interacts with the UvrB protein to modulate its activities, both in solution and in association with DNA, where the UvrAB complex possesses a helicase activity. The domains of the UvrA protein that sponsor each of these activities were localized within the protein by studying the in vitro properties of a set of purified deletion mutants of the UvrA protein. A region located within the first 230 amino acids was found to contain the minimal region necessary for interactions with UvrB, the UvrA dimerization interface was localized to within the first 680 amino acids, and the DNA binding domain lies within the first 900 amino acids of the 940-amino acid UvrA protein. Two damage recognition domains were detected. The first domain, which coincides with the DNA binding region, is required to detect the damage. The second domain, located on or near the C-terminal 40 amino acids, stabilizes the protein-DNA complex when damage is encountered
Langdon, Blake B.; Kastantin, Mark; Walder, Robert; Schwartz, Daniel K.
While traditional models of protein adsorption focus primarily on direct protein-surface interactions, recent findings suggest that protein-protein interactions may play a central role. Using high-throughput intermolecular resonance energy transfer (RET) tracking, we directly observed dynamic, protein-protein associations of bovine serum albumin on poly(ethylene glycol) modified surfaces. The associations were heterogeneous and reversible, and associating molecules resided on the surface for ...
Full Text Available A binding event between two proteins typically consists of a diffusional search of binding partners for one another, followed by a specific recognition of the compatible binding sites resulting in the formation of the complex. However, it is unclear how binding partners find each other in the context of the crowded, constantly fluctuating, and interaction-rich cellular environment. Here we examine the non-specific component of protein-protein interactions, which refers to those physicochemical properties of the binding partners that are independent of the exact details of their binding sites, but which can affect their localization or diffusional search for one another. We show that, for a large set of high-resolution experimental 3D structures of binary, transient protein complexes taken from the DOCKGROUND database, the binding partners display a surprising, statistically significant similarity in terms of their total hydration free energies normalized by a size-dependent variable. We hypothesize that colocalization of binding partners, even within individual cellular compartments such as the cytoplasm, may be influenced by their relative hydrophilicity, potentially in response to local hydrophilic gradients.
Full Text Available Abstract Background Since proteins perform their functions by interacting with one another and with other biomolecules, reconstructing a map of the protein-protein interactions of a cell, experimentally or computationally, is an important first step toward understanding cellular function and machinery of a proteome. Solely derived from the Gene Ontology (GO, we have defined an effective method of reconstructing a yeast protein interaction network by measuring relative specificity similarity (RSS between two GO terms. Description Based on the RSS method, here, we introduce a predicted Saccharomyces protein-protein interaction database called SPIDer. It houses a gold standard positive dataset (GSP with high confidence level that covered 79.2% of the high-quality interaction dataset. Our predicted protein-protein interaction network reconstructed from the GSPs consists of 92 257 interactions among 3600 proteins, and forms 23 connected components. It also provides general links to connect predicted protein-protein interactions with three other databases, DIP, BIND and MIPS. An Internet-based interface provides users with fast and convenient access to protein-protein interactions based on various search features (searching by protein information, GO term information or sequence similarity. In addition, the RSS value of two GO terms in the same ontology, and the inter-member interactions in a list of proteins of interest or in a protein complex could be retrieved. Furthermore, the database presents a user-friendly graphical interface which is created dynamically for visualizing an interaction sub-network. The database is accessible at http://cmb.bnu.edu.cn/SPIDer/index.html. Conclusion SPIDer is a public database server for protein-protein interactions based on the yeast genome. It provides a variety of search options and graphical visualization of an interaction network. In particular, it will be very useful for the study of inter-member interactions
Szklarczyk, Damian; Jensen, Lars Juhl
of research are explored. Here we present an overview of the most widely used protein-protein interaction databases and the methods they employ to gather, combine, and predict interactions. We also point out the trade-off between comprehensiveness and accuracy and the main pitfall scientists have to be aware...
Nussinov, Ruth; Tsai, Chung-Jung
Proteins are the `workhorses' of the cell. Their roles span functions as diverse as being molecular machines and signalling. They carry out catalytic reactions, transport, form viral capsids, traverse membranes and form regulated channels, transmit information from DNA to RNA, making possible the synthesis of new proteins, and they are responsible for the degradation of unnecessary proteins and nucleic acids. They are the vehicles of the immune response and are responsible for viral entry into the cell. Given their importance, considerable effort has been centered on the prediction of protein function. A prime way to do this is through identification of binding partners. If the function of at least one of the components with which the protein interacts is known, that should let us assign its function(s) and the pathway(s) in which it plays a role. This holds since the vast majority of their chores in the living cell involve protein-protein interactions. Hence, through the intricate network of these interactions we can map cellular pathways, their interconnectivities and their dynamic regulation. Their identification is at the heart of functional genomics; their prediction is crucial for drug discovery. Knowledge of the pathway, its topology, length, and dynamics may provide useful information for forecasting side effects. The goal of predicting protein-protein interactions is daunting. Some associations are obligatory, others are continuously forming and dissociating. In principle, from the physical standpoint, any two proteins can interact, but under what conditions and at which strength? The principles of protein-protein interactions are general: the non-covalent interactions of two proteins are largely the outcome of the hydrophobic effect, which drives the interactions. In addition, hydrogen bonds and electrostatic interactions play important roles. Thus, many of the interactions observed in vitro are the outcome of experimental overexpression. Protein disorder
La, David; Kihara, Daisuke
Protein-protein binding events mediate many critical biological functions in the cell. Typically, functionally important sites in proteins can be well identified by considering sequence conservation. However, protein-protein interaction sites exhibit higher sequence variation than other functional regions, such as catalytic sites of enzymes. Consequently, the mutational behavior leading to weak sequence conservation poses significant challenges to the protein-protein interaction site predicti...
Identification of AML-1 and the (8;21) translocation protein (AML-1/ETO) as sequence-specific DNA-binding proteins: the runt homology domain is required for DNA binding and protein-protein interactions.
Meyers, S; Downing, J R; Hiebert, S W
The AML1 gene on chromosome 21 is disrupted in the (8;21)(q22;q22) translocation associated with acute myelogenous leukemia and encodes a protein with a central 118-amino-acid domain with 69% homology to the Drosophila pair-rule gene, runt. We demonstrate that AML-1 is a DNA-binding protein which specifically interacts with a sequence belonging to the group of enhancer core motifs, TGT/cGGT. Electrophoretic mobility shift analysis of cell extracts identified two AML-1-containing protein-DNA c...
Full Text Available Abstract Over the past few years, the number of known protein-protein interactions has increased substantially. To make this information more readily available, a number of publicly available databases have set out to collect and store protein-protein interaction data. Protein-protein interactions have been retrieved from six major databases, integrated and the results compared. The six databases (the Biological General Repository for Interaction Datasets [BioGRID], the Molecular INTeraction database [MINT], the Biomolecular Interaction Network Database [BIND], the Database of Interacting Proteins [DIP], the IntAct molecular interaction database [IntAct] and the Human Protein Reference Database [HPRD] differ in scope and content; integration of all datasets is non-trivial owing to differences in data annotation. With respect to human protein-protein interaction data, HPRD seems to be the most comprehensive. To obtain a complete dataset, however, interactions from all six databases have to be combined. To overcome this limitation, meta-databases such as the Agile Protein Interaction Database (APID offer access to integrated protein-protein interaction datasets, although these also currently have certain restrictions.
Schulte, Roberta; Talamas, Jessica; Doucet, Christine; Hetzer, Martin W.
We present a miniaturized pull-down method for the detection of protein-protein interactions using standard affinity chromatography reagents. Binding events between different proteins, which are color-coded with quantum dots (QDs), are visualized on single affinity chromatography beads by fluorescence microscopy. The use of QDs for single molecule detection allows the simultaneous analysis of multiple protein-protein binding events and reduces the amount of time and material needed to perform...
Jones, S; Thornton, J. M.
This review examines protein complexes in the Brookhaven Protein Databank to gain a better understanding of the principles governing the interactions involved in protein-protein recognition. The factors that influence the formation of protein-protein complexes are explored in four different types of protein-protein complexes--homodimeric proteins, heterodimeric proteins, enzyme-inhibitor complexes, and antibody-protein complexes. The comparison between the complexes highlights differences tha...
Liu, Zhu; Gong, Zhou; Dong, Xu; Tang, Chun
Proteins interact with each other to establish their identities in cell. The affinities for the interactions span more than ten orders of magnitude, and KD values in μM-mM regimen are considered transient and are important in cell signaling. Solution NMR including diamagnetic and paramagnetic techniques has enabled atomic-resolution depictions of transient protein-protein interactions. Diamagnetic NMR allows characterization of protein complexes with KD values up to several mM, whereas ultraweak and fleeting complexes can be modeled with the use of paramagnetic NMR especially paramagnetic relaxation enhancement (PRE). When tackling ever-larger protein complexes, PRE can be particularly useful in providing long-range intermolecular distance restraints. As NMR measurements are averaged over the ensemble of complex structures, structural information for dynamic protein-protein interactions besides the stereospecific one can often be extracted. Herein the protein interaction dynamics are exemplified by encounter complexes, alternative binding modes, and coupled binding/folding of intrinsically disordered proteins. Further integration of NMR with other biophysical techniques should allow better visualization of transient protein-protein interactions. In particular, single-molecule data may facilitate the interpretation of ensemble-averaged NMR data. Though same structures of proteins and protein complexes were found in cell as in diluted solution, we anticipate that the dynamics of transient protein protein-protein interactions be different, which awaits awaits exploration by NMR. This article is part of a Special Issue entitled: Physiological Enzymology and Protein Functions. This article is part of a Special Issue entitled: Physiological Enzymology and Protein Functions. PMID:25896389
Surya, Sukumaran; Abhilash, Joseph; Geethanandan, Krishnan; Sadasivan, Chittalakkottu; Haridas, Madhathilkovilakathu
Proteins may utilize complex networks of interactions to create/proceed signaling pathways of highly adaptive responses such as programmed cell death. Direct binary interactions study of proteins may help propose models for protein-protein interaction. Towards this goal we applied a combination of thermodynamic kinetics and crystal structure analyses to elucidate the complexity and diversity in such interactions. By determining the heat change on the association of two galactose-specific legume lectins from Butea monosperma (BML) and Spatholobus parviflorus (SPL) belonging to Fabaceae family helped to compute the binding equilibrium. It was extended further by X-ray structural analysis of BML-SPL binary complex. In order to chart the proteins interacting mainly through their interfaces, identification of the nature of forces which stabilized the association of the lectin-lectin complex was examined. Comprehensive analysis of the BMLSPL complex by isothermal titration calorimetry and X-ray crystal structure threw new light on the lectin-lectin interactions suggesting of their use in diverse areas of glycobiology. PMID:26945504
Haruki Nakamura; Kengo Kinoshita; Ashwini Patil
Hubs are proteins with a large number of interactions in a protein-protein interaction network. They are the principal agents in the interaction network and affect its function and stability. Their specific recognition of many different protein partners is of great interest from the structural viewpoint. Over the last few years, the structural properties of hubs have been extensively studied. We review the currently known features that are particular to hubs, possibly affecting their binding ...
Lecornet Hélène; Regad Leslie; Martin Juliette; Camproux Anne-Claude
Abstract Background In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. Results In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backb...
Cell-free protein synthesis systems provide facile access to proteins in a nascent state that enables formation of soluble, native protein-protein complexes even if one of the protein components is prone to self-aggregation and precipitation. Combined with selective isotope-labeling, this allows the rapid analysis of protein-protein interactions with few 15N-HSQC spectra. The concept is demonstrated with binary and ternary complexes between the χ, ψ and γ subunits of Escherichia coli DNA polymerase III: nascent, selectively 15N-labeled ψ produced in the presence of χ resulted in a soluble, correctly folded χ-ψ complex, whereas ψ alone precipitated irrespective of whether γ was present or not. The 15N-HSQC spectra showed that the N-terminal segment of ψ is mobile in the χ-ψ complex, yet important for its binding to γ. The sample preparation was greatly enhanced by an autoinduction strategy, where the T7 RNA polymerase needed for transcription of a gene in a T7-promoter vector was produced in situ
Regulation of ryanodine receptor RyR2 by protein-protein interactions: prediction of a PKA binding site on the N-terminal domain of RyR2 and its relation to disease causing mutations [v1; ref status: indexed, http://f1000r.es/4tw
Belinda Nazan Walpoth
Full Text Available Protein-protein interactions are the key processes responsible for signaling and function in complex networks. Determining the correct binding partners and predicting the ligand binding sites in the absence of experimental data require predictive models. Hybrid models that combine quantitative atomistic calculations with statistical thermodynamics formulations are valuable tools for bioinformatics predictions. We present a hybrid prediction and analysis model for determining putative binding partners and interpreting the resulting correlations in the yet functionally uncharacterized interactions of the ryanodine RyR2 N-terminal domain. Using extensive docking calculations and libraries of hexameric peptides generated from regulator proteins of the RyR2 channel, we show that the residues 318-323 of protein kinase A, PKA, have a very high affinity for the N-terminal of RyR2. Using a coarse grained Elastic Net Model, we show that the binding site lies at the end of a pathway of evolutionarily conserved residues in RyR2. The two disease causing mutations are also on this path. The program for the prediction of the energetically responsive residues by the Elastic Net Model is freely available on request from the corresponding author.
Titushin, Maxim S.; Feng, Yingang; Lee, John; Vysotski, Eugene S.; Liu, Zhi-jie
In this review we summarize the progress made towards understanding the role of protein-protein interactions in the function of various bioluminescence systems of marine organisms, including bacteria, jellyfish and soft corals, with particular focus on methodology used to detect and characterize these interactions. In some bioluminescence systems, protein-protein interactions involve an “accessory protein” whereby a stored substrate is efficiently delivered to the bioluminescent enzyme lucife...
Stephan Ederer; Florian Fink; Wolfram Gronwald
Based on a protein-protein docking approach we have developed a procedure to verify or falsify protein-protein interactions that were proposed by other methods such as yeast-2-hybrid assays. Our method currently utilizes intermolecular energies but can be expanded to incorporate additional terms such as amino acid based pair-potentials. We show some early results that demonstrate the general applicability of our approach.
A holistic protein-protein molecular docking approach,HoDock,was established,composed of such steps as binding site prediction,initial complex structure sampling,refined complex structure sampling,structure clustering,scoring and final structure selection.This article explains the detailed steps and applications for CAPRI Target 39.The CAPRI result showed that three predicted binding site residues,A191HIS,B512ARG and B531ARG,were correct,and there were five submitted structures with a high fraction of correct receptor-ligand interface residues,indicating that this docking approach may improve prediction accuracy for protein-protein complex structures.
Paul A. Bates
Full Text Available Here is presented an investigation of the use of normal modes in protein-protein docking, both in theory and in practice. Upper limits of the ability of normal modes to capture the unbound to bound conformational change are calculated on a large test set, with particular focus on the binding interface, the subset of residues from which the binding energy is calculated. Further, the SwarmDock algorithm is presented, to demonstrate that the modelling of conformational change as a linear combination of normal modes is an effective method of modelling flexibility in protein-protein docking.
Full Text Available Quantitative proteome research is greatly promoted by high-resolution parallel format assays. A characterization of protein complexes based on binding forces offers an unparalleled dynamic range and allows for the effective discrimination of non-specific interactions. Here we present a DNA-based Molecular Force Assay to quantify protein-protein interactions, namely the bond between different variants of GFP and GFP-binding nanobodies. We present different strategies to adjust the maximum sensitivity window of the assay by influencing the binding strength of the DNA reference duplexes. The binding of the nanobody Enhancer to the different GFP constructs is compared at high sensitivity of the assay. Whereas the binding strength to wild type and enhanced GFP are equal within experimental error, stronger binding to superfolder GFP is observed. This difference in binding strength is attributed to alterations in the amino acids that form contacts according to the crystal structure of the initial wild type GFP-Enhancer complex. Moreover, we outline the potential for large-scale parallelization of the assay.
Amin R Mazloom
Full Text Available Coregulator proteins (CoRegs are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP followed by mass spectrometry (MS applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/.
Planas-Iglesias, Joan; Bonet, Jaume; García-García, Javier;
Protein-protein interactions (PPIs) play a relevant role among the different functions of a cell. Identifying the PPI network of a given organism (interactome) is useful to shed light on the key molecular mechanisms within a biological system. In this work, we show the role of structural features...... interacting and non-interacting protein pairs to classify the structural features that sustain the binding (or non-binding) behavior. Our study indicates that not only the interacting region but also the rest of the protein surface are important for the interaction fate. The interpretation of this...... classification suggests that the balance between favoring and disfavoring structural features determines if a pair of proteins interacts or not. Our results are in agreement with previous works and support the funnel-like intermolecular energy landscape theory that explains PPIs. We have used these features to...
Blagoev, B.; Kratchmarova, I.; Ong, S.E.;
Mass spectrometry-based proteomics can reveal protein-protein interactions on a large scale, but it has been difficult to separate background binding from functionally important interactions and still preserve weak binders. To investigate the epidermal growth factor receptor (EGFR) pathway, we em...
Dengjel, Joern; Kratchmarova, Irina; Blagoev, Blagoy
Proteins exert their function inside a cell generally in multiprotein complexes. These complexes are highly dynamic structures changing their composition over time and cell state. The same protein may thereby fulfill different functions depending on its binding partners. Quantitative mass...... spectrometry (MS)-based proteomics in combination with affinity purification protocols has become the method of choice to map and track the dynamic changes in protein-protein interactions, including the ones occurring during cellular signaling events. Different quantitative MS strategies have been used to...... characterize protein interaction networks. In this chapter we describe in detail the use of stable isotope labeling by amino acids in cell culture (SILAC) for the quantitative analysis of stimulus-dependent dynamic protein interactions....
Martin, Shawn Bryan; Sale, Kenneth L.; Faulon, Jean-Loup Michel; Roe, Diana C.
The goal of this project was to examine the protein-protein docking problem, especially as it relates to homology-based structures, identify the key bottlenecks in current software tools, and evaluate and prototype new algorithms that may be developed to improve these bottlenecks. This report describes the current challenges in the protein-protein docking problem: correctly predicting the binding site for the protein-protein interaction and correctly placing the sidechains. Two different and complementary approaches are taken that can help with the protein-protein docking problem. The first approach is to predict interaction sites prior to docking, and uses bioinformatics studies of protein-protein interactions to predict theses interaction site. The second approach is to improve validation of predicted complexes after docking, and uses an improved scoring function for evaluating proposed docked poses, incorporating a solvation term. This scoring function demonstrates significant improvement over current state-of-the art functions. Initial studies on both these approaches are promising, and argue for full development of these algorithms.
Melody G Campbell
Full Text Available Ribosome assembly in eukaryotic organisms requires more than 200 assembly factors to facilitate and coordinate rRNA transcription, processing, and folding with the binding of the ribosomal proteins. Many of these assembly factors bind and dissociate at defined times giving rise to discrete assembly intermediates, some of which have been partially characterized with regards to their protein and RNA composition. Here, we have analyzed the protein-protein interactions between the seven assembly factors bound to late cytoplasmic pre-40S ribosomes using recombinant proteins in binding assays. Our data show that these factors form two modules: one comprising Enp1 and the export adaptor Ltv1 near the beak structure, and the second comprising the kinase Rio2, the nuclease Nob1, and a regulatory RNA binding protein Dim2/Pno1 on the front of the head. The GTPase-like Tsr1 and the universally conserved methylase Dim1 are also peripherally connected to this second module. Additionally, in an effort to further define the locations for these essential proteins, we have analyzed the interactions between these assembly factors and six ribosomal proteins: Rps0, Rps3, Rps5, Rps14, Rps15 and Rps29. Together, these results and previous RNA-protein crosslinking data allow us to propose a model for the binding sites of these seven assembly factors. Furthermore, our data show that the essential kinase Rio2 is located at the center of the pre-ribosomal particle and interacts, directly or indirectly, with every other assembly factor, as well as three ribosomal proteins required for cytoplasmic 40S maturation. These data suggest that Rio2 could play a central role in regulating cytoplasmic maturation steps.
Mahmood; A.; Mahdavi; Yen-Han; Lin
Protein domains are conserved and functionally independent structures that play an important role in interactions among related proteins. Domain-domain inter- actions have been recently used to predict protein-protein interactions (PPI). In general, the interaction probability of a pair of domains is scored using a trained scoring function. Satisfying a threshold, the protein pairs carrying those domains are regarded as "interacting". In this study, the signature contents of proteins were utilized to predict PPI pairs in Saccharomyces cerevisiae, Caenorhabditis ele- gans, and Homo sapiens. Similarity between protein signature patterns was scored and PPI predictions were drawn based on the binary similarity scoring function. Results show that the true positive rate of prediction by the proposed approach is approximately 32% higher than that using the maximum likelihood estimation method when compared with a test set, resulting in 22% increase in the area un- der the receiver operating characteristic (ROC) curve. When proteins containing one or two signatures were removed, the sensitivity of the predicted PPI pairs in- creased significantly. The predicted PPI pairs are on average 11 times more likely to interact than the random selection at a confidence level of 0.95, and on aver- age 4 times better than those predicted by either phylogenetic profiling or gene expression profiling.
Lehne Benjamin; Schlitt Thomas
Abstract Over the past few years, the number of known protein-protein interactions has increased substantially. To make this information more readily available, a number of publicly available databases have set out to collect and store protein-protein interaction data. Protein-protein interactions have been retrieved from six major databases, integrated and the results compared. The six databases (the Biological General Repository for Interaction Datasets [BioGRID], the Molecular INTeraction ...
Teilum, Kaare; Olsen, Johan G.; Kragelund, Birthe B.
In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein...
Chen Yung-Chiang; Lo Yu-Shu; Yang Jinn-Moon
Abstract Background Comprehensive exploration of protein-protein interactions is a challenging route to understand biological processes. For efficiently enlarging protein interactions annotated with residue-based binding models, we proposed a new concept "3D-domain interolog mapping" with a scoring system to explore all possible protein pairs between the two homolog families, derived from a known 3D-structure dimmer (template), across multiple species. Each family consists of homologous prote...
Abstract Background Protein-protein docking is a challenging computational problem in functional genomics, particularly when one or both proteins undergo conformational change(s) upon binding. The major challenge is to define a scoring function soft enough to tolerate these changes and specific enough to distinguish between near-native and "misdocked" conformations. Results Using a linear programming (LP) technique, we developed two types of potentials: (i) Side chain-based and (ii) Heavy ato...
Colantoni, Alessio; Bianchi, Valerio; Gherardini, Pier Federico; Scalia Tomba, Gianpaolo; Ausiello, Gabriele; Helmer-Citterich, Manuela; Ferrè, Fabrizio
Background Anecdotal evidence of the involvement of alternative splicing (AS) in the regulation of protein-protein interactions has been reported by several studies. AS events have been shown to significantly occur in regions where a protein interaction domain or a short linear motif is present. Several AS variants show partial or complete loss of interface residues, suggesting that AS can play a major role in the interaction regulation by selectively targeting the protein binding sites. In t...
Yogurtcu, Osman N.; Erdemli, S. Bora; Nussinov, Ruth; Turkay, Metin; Keskin, Ozlem
Conserved residues in protein-protein interfaces correlate with residue hot-spots. To obtain insight into their roles, we have studied their mobility. We have performed 39 explicit solvent simulations of 15 complexes and their monomers, with the interfaces varying in size, shape, and function. The dynamic behavior of conserved residues in unbound monomers illustrates significantly lower flexibility as compared to their environment, suggesting that already before binding they are constrained i...
Kalyan S. Chakrabarti
Full Text Available Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection or are caused in response to ligand binding (induced fit. Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here, we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsin kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using nuclear magnetic resonance (NMR spectroscopy, stopped-flow kinetics, and isothermal titration calorimetry, we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Protein dynamics in free recoverin limits the overall rate of binding.
Chakrabarti, Kalyan S; Agafonov, Roman V; Pontiggia, Francesco; Otten, Renee; Higgins, Matthew K; Schertler, Gebhard F X; Oprian, Daniel D; Kern, Dorothee
Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection) or are caused in response to ligand binding (induced fit). Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here, we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsin kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using nuclear magnetic resonance (NMR) spectroscopy, stopped-flow kinetics, and isothermal titration calorimetry, we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Protein dynamics in free recoverin limits the overall rate of binding. PMID:26725117
Kapadia, Shasvath J; Ajith, Parameswaran
In the adiabatic post-Newtonian (PN) approximation, the phase evolution of gravitational waves (GWs) from inspiralling compact binaries in quasicircular orbits is computed by equating the change in binding energy with the GW flux. This energy balance equation can be solved in different ways, which result in multiple approximants of the PN waveforms. Due to the poor convergence of the PN expansion, these approximants tend to differ from each other during the late inspiral. Which of these approximants should be chosen as templates for detection and parameter estimation of GWs from inspiraling compact binaries is not obvious. In this paper, we present estimates of the effective higher order (beyond the currently available 4PN and 3.5PN) non-spinning terms in the PN expansion of the binding energy and the GW flux that minimize the difference of multiple PN approximants (TaylorT1, TaylorT2, TaylorT4, TaylorF2) with effective one body waveforms calibrated to numerical relativity (EOBNR). We show that PN approximant...
Roberts, D; Keeling, R; Tracka, M; van der Walle, C F; Uddin, S; Warwicker, J; Curtis, R
Better predictive ability of salt and buffer effects on protein-protein interactions requires separating out contributions due to ionic screening, protein charge neutralization by ion binding, and salting-in(out) behavior. We have carried out a systematic study by measuring protein-protein interactions for a monoclonal antibody over an ionic strength range of 25 to 525 mM at 4 pH values (5, 6.5, 8, and 9) in solutions containing sodium chloride, calcium chloride, sodium sulfate, or sodium thiocyante. The salt ions are chosen so as to represent a range of affinities for protein charged and noncharged groups. The results are compared to effects of various buffers including acetate, citrate, phosphate, histidine, succinate, or tris. In low ionic strength solutions, anion binding affinity is reflected by the ability to reduce protein-protein repulsion, which follows the order thiocyanate > sulfate > chloride. The sulfate specific effect is screened at the same ionic strength required to screen the pH dependence of protein-protein interactions indicating sulfate binding only neutralizes protein charged groups. Thiocyanate specific effects occur over a larger ionic strength range reflecting adsorption to charged and noncharged regions of the protein. The latter leads to salting-in behavior and, at low pH, a nonmonotonic interaction profile with respect to sodium thiocyanate concentration. The effects of thiocyanate can not be rationalized in terms of only neutralizing double layer forces indicating the presence of an additional short-ranged protein-protein attraction at moderate ionic strength. Conversely, buffer specific effects can be explained through a charge neutralization mechanism, where buffers with greater valency are more effective at reducing double layer forces at low pH. Citrate binding at pH 6.5 leads to protein charge inversion and the formation of attractive electrostatic interactions. Throughout the report, we highlight similarities in the measured
Jillian L Blatti
Full Text Available Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP and thioesterase (TE govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr as a model, a structural simulation of docking CrACP to CrTE identifies a protein-protein recognition surface between the two domains. A virtual screen reveals plant TEs with similar in silico binding to CrACP. Employing an activity-based crosslinking probe designed to selectively trap transient protein-protein interactions between the TE and ACP, we demonstrate in vitro that CrTE must functionally interact with CrACP to release fatty acids, while TEs of vascular plants show no mechanistic crosslinking to CrACP. This is recapitulated in vivo, where overproduction of the endogenous CrTE increased levels of short-chain fatty acids and engineering plant TEs into the C. reinhardtii chloroplast did not alter the fatty acid profile. These findings highlight the critical role of protein-protein interactions in manipulating fatty acid biosynthesis for algae biofuel engineering as illuminated by activity-based probes.
Full Text Available BACKGROUND: The study and comparison of protein-protein interfaces is essential for the understanding of the mechanisms of interaction between proteins. While there are many methods for comparing protein structures and protein binding sites, so far no methods have been reported for comparing the geometry of non-covalent interactions occurring at protein-protein interfaces. METHODOLOGY/PRINCIPAL FINDINGS: Here we present a method for aligning non-covalent interactions between different protein-protein interfaces. The method aligns the vector representations of van der Waals interactions and hydrogen bonds based on their geometry. The method has been applied to a dataset which comprises a variety of protein-protein interfaces. The alignments are consistent to a large extent with the results obtained using two other complementary approaches. In addition, we apply the method to three examples of protein mimicry. The method successfully aligns respective interfaces and allows for recognizing conserved interface regions. CONCLUSIONS/SIGNIFICANCE: The Galinter method has been validated in the comparison of interfaces in which homologous subunits are involved, including cases of mimicry. The method is also applicable to comparing interfaces involving non-peptidic compounds. Galinter assists users in identifying local interface regions with similar patterns of non-covalent interactions. This is particularly relevant to the investigation of the molecular basis of interaction mimicry.
Quang, Leigh J; Sandler, Stanley I; Lenhoff, Abraham M
The anisotropy of shape and functionality of proteins complicates the prediction of protein-protein interactions. We examine the distribution of electrostatic and nonelectrostatic contributions to these interactions for two globular proteins, lysozyme and chymosin B, which differ in molecular weight by about a factor of 2. The interaction trends for these proteins are computed in terms of contributions to the osmotic second virial coefficient that are evaluated using atomistic models of the proteins. Our emphasis is on identifying the orientational configurations that contribute most strongly to the overall interactions due to high-complementarity interactions, and on calculating the effect of ionic strength on such interactions. The results emphasize the quantitative importance of several features of protein interactions, notably that despite differences in their frequency of occurrence, configurations differing appreciably in interaction energy can contribute meaningfully to overall interactions. However, relatively small effects due to charge anisotropy or specific hydration can affect the overall interaction significantly only if they contribute to strongly attractive configurations. The results emphasize the necessity of accounting for detailed anisotropy to capture actual experimental trends, and the sensitivity of even very detailed atomistic models to subtle solution contributions. PMID:26580057
Haasl Ryan J
Full Text Available Abstract Background The development of high-throughput technologies such as yeast two-hybrid systems and mass spectrometry technologies has made it possible to generate large protein-protein interaction (PPI datasets. Mining these datasets for underlying biological knowledge has, however, remained a challenge. Results A total of 3108 sequence signatures were found, each of which was shared by a set of guest proteins interacting with one of 944 host proteins in Saccharomyces cerevisiae genome. Approximately 94% of these sequence signatures matched entries in InterPro member databases. We identified 84 distinct sequence signatures from the remaining 172 unknown signatures. The signature sharing information was then applied in predicting sub-cellular localization of yeast proteins and the novel signatures were used in identifying possible interacting sites. Conclusion We reported a method of PPI data mining that facilitated the discovery of novel sequence signatures using a large PPI dataset from S. cerevisiae genome as input. The fact that 94% of discovered signatures were known validated the ability of the approach to identify large numbers of signatures from PPI data. The significance of these discovered signatures was demonstrated by their application in predicting sub-cellular localizations and identifying potential interaction binding sites of yeast proteins.
Hayes, Sheri; Malacrida, Beatrice; Kiely, Maeve; Kiely, Patrick A
Signalling proteins are intrinsic to all biological processes and interact with each other in tightly regulated and orchestrated signalling complexes and pathways. Characterization of protein binding can help to elucidate protein function within signalling pathways. This information is vital for researchers to gain a more comprehensive knowledge of cellular networks which can then be used to develop new therapeutic strategies for disease. However, studying protein-protein interactions (PPIs) can be challenging as the interactions can be extremely transient downstream of specific environmental cues. There are many powerful techniques currently available to identify and confirm PPIs. Choosing the most appropriate range of techniques merits serious consideration. The aim of this review is to provide a starting point for researchers embarking on a PPI study. We provide an overview and point of reference for some of the many methods available to identify interactions from in silico analysis and large scale screening tools through to the methods used to validate potential PPIs. We discuss the advantages and disadvantages of each method and we also provide a workflow chart to highlight the main experimental questions to consider when planning cell lysis to maximize experimental success. PMID:27528744
Chamani, J., E-mail: Chamani@ibb.ut.ac.i [Department of Biology, Faculty of Sciences, Islamic Azad University-Mashhad Branch, Mashhad (Iran, Islamic Republic of); Asoodeh, A. [Department of Chemistry, Faculty of Sciences, Ferdowsi University of Mashhad, Mashhad (Iran, Islamic Republic of); Homayoni-Tabrizi, M. [Department of Biology, Faculty of Sciences, Islamic Azad University-Mashhad Branch, Mashhad (Iran, Islamic Republic of); Amiri Tehranizadeh, Z.; Baratian, A.; Saberi, M.R. [Medical Chemistry Department, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad (Iran, Islamic Republic of); Gharanfoli, M. [Department of Development Biology, Culture and Science University, Tehran (Iran, Islamic Republic of)
Combination of several drugs is often necessary especially during long-term therapy. The competitive binding drugs can cause a decrease in the amount of drug bound to protein and increase the biological active fraction of the drug. The aim of this study is to analyze the interactions of Lomefloxacin (LMF) and Colchicine (COL) with human serum albumin (HSA) and to evaluate the mechanism of simultaneous binding of LMF and COL to protein. Fluorescence analysis was used to estimate the effect of drugs on the protein fluorescence and to define the binding and quenching properties of drugs-HSA complexes. The binding sites for LMF and COL were identified in tertiary structure of HSA with the use of spectrofluorescence analysis. The analysis of fluorescence quenching of HSA in the binary and ternary systems show that LMF does not affect the complex formed between COL and HSA. On the contrary, COL decreases the interaction between LMF and HSA. The results of synchronous fluorescence, resonance light scattering and circular dichroism spectra of binary and ternary systems show that binding of LMF and COL to HSA can induce micro-environmental and conformational changes in HSA. The simultaneous presence of LMF and COL in binding to HSA should be taken into account in the multi-drug therapy, and necessity of using a monitoring therapy owning to the possible increase of the uncontrolled toxic effects. Molecular modeling of the possible binding sites of LMF and COL in binary and ternary systems to HSA confirms the spectroscopic results.
Combination of several drugs is often necessary especially during long-term therapy. The competitive binding drugs can cause a decrease in the amount of drug bound to protein and increase the biological active fraction of the drug. The aim of this study is to analyze the interactions of Lomefloxacin (LMF) and Colchicine (COL) with human serum albumin (HSA) and to evaluate the mechanism of simultaneous binding of LMF and COL to protein. Fluorescence analysis was used to estimate the effect of drugs on the protein fluorescence and to define the binding and quenching properties of drugs-HSA complexes. The binding sites for LMF and COL were identified in tertiary structure of HSA with the use of spectrofluorescence analysis. The analysis of fluorescence quenching of HSA in the binary and ternary systems show that LMF does not affect the complex formed between COL and HSA. On the contrary, COL decreases the interaction between LMF and HSA. The results of synchronous fluorescence, resonance light scattering and circular dichroism spectra of binary and ternary systems show that binding of LMF and COL to HSA can induce micro-environmental and conformational changes in HSA. The simultaneous presence of LMF and COL in binding to HSA should be taken into account in the multi-drug therapy, and necessity of using a monitoring therapy owning to the possible increase of the uncontrolled toxic effects. Molecular modeling of the possible binding sites of LMF and COL in binary and ternary systems to HSA confirms the spectroscopic results.
Peri, Claudio; Morra, Giulia; Colombo, Giorgio
Understanding protein-protein interactions (PPI) at the molecular level is a fundamental task in the design of new drugs, the prediction of protein function and the clarification of the mechanisms of (dis)regulation of biochemical pathways. In this study, we use a novel computational approach to investigate the energetics of aminoacid networks located on the surface of proteins, isolated and in complex with their respective partners. Interestingly, the analysis of individual proteins identifies patches of surface residues that, when mapped on the structure of their respective complexes, reveal regions of residue-pair couplings that extend across the binding interfaces, forming continuous motifs. An enhanced effect is visible across the proteins of the dataset forming larger quaternary assemblies. The method indicates the presence of energetic signatures in the isolated proteins that are retained in the bound form, which we hypothesize to determine binding orientation upon complex formation. We propose our method, BLUEPRINT, as a complement to different approaches ranging from the ab-initio characterization of PPIs, to protein-protein docking algorithms, for the physico-chemical and functional investigation of protein-protein interactions. PMID:27050828
Full Text Available Abstract Background The study of protein-protein interactions is becoming increasingly important for biotechnological and therapeutic reasons. We can define two major areas therein: the structural prediction of protein-protein binding mode, and the identification of the relevant residues for the interaction (so called 'hot-spots'. These hot-spot residues have high interest since they are considered one of the possible ways of disrupting a protein-protein interaction. Unfortunately, large-scale experimental measurement of residue contribution to the binding energy, based on alanine-scanning experiments, is costly and thus data is fairly limited. Recent computational approaches for hot-spot prediction have been reported, but they usually require the structure of the complex. Results We have applied here normalized interface propensity (NIP values derived from rigid-body docking with electrostatics and desolvation scoring for the prediction of interaction hot-spots. This parameter identifies hot-spot residues on interacting proteins with predictive rates that are comparable to other existing methods (up to 80% positive predictive value, and the advantage of not requiring any prior structural knowledge of the complex. Conclusion The NIP values derived from rigid-body docking can reliably identify a number of hot-spot residues whose contribution to the interaction arises from electrostatics and desolvation effects. Our method can propose residues to guide experiments in complexes of biological or therapeutic interest, even in cases with no available 3D structure of the complex.
Teilum, Kaare; Olsen, Johan G; Kragelund, Birthe B
In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1). PMID:26217672
Full Text Available Protein-protein interactions (PPIs play a major role in many biological processes and they represent an important class of targets for therapeutic intervention. However, targeting PPIs is challenging because often no convenient natural substrates are available as starting point for small-molecule design. Here, we explored the characteristics of protein interfaces in five non-redundant datasets of 174 protein-protein (PP complexes, and 161 protein-ligand (PL complexes from the ABC database, 436 PP complexes, and 196 PL complexes from the PIBASE database and a dataset of 89 PL complexes from the Timbal database. In all cases, the small molecule ligands must bind at the respective PP interface. We observed similar amino acid frequencies in all three datasets. Remarkably, also the characteristics of PP contacts and overlapping PL contacts are highly similar.
Teilum, Kaare; Olsen, Johan Gotthardt; Kragelund, Birthe Brandt
In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs) and other proteins rely on changes in flexibility and this is seen as a...... strong determinant for their function. This has fostered the notion that IDP's bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those...... of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non-identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol(-1)....
代启国; 郭茂祖; 刘晓燕; 滕志霞; 王春宇
Proteins usually bind together to form complexes, which play an important role in cellular activities. Many graph clustering methods have been proposed to identify protein complexes by finding dense regions in protein-protein interaction networks. We present a novel framework (CPL) that detects protein complexes by propagating labels through interactions in a network, in which labels denote complex identifiers. With proper propagation in CPL, proteins in the same complex will be assigned with the same labels. CPL does not make any strong assumptions about the topological structures of the complexes, as in previous methods. The CPL algorithm is tested on several publicly available yeast protein-protein interaction networks and compared with several state-of-the-art methods. The results suggest that CPL performs better than the existing methods. An analysis of the functional homogeneity based on a gene ontology analysis shows that the detected complexes of CPL are highly biologically relevant.
Full Text Available In biology proteins from different structural classes interact across and within classes in ways that are optimized to achieve balanced functional outputs. The interactions between intrinsically disordered proteins (IDPs and other proteins rely on changes in flexibility and this is seen as a strong determinant for their function. This has fostered the notion that IDP’s bind with low affinity but high specificity. Here we have analyzed available detailed thermodynamic data for protein-protein interactions to put to the test if the thermodynamic profiles of IDP interactions differ from those of other protein-protein interactions. We find that ordered proteins and the disordered ones act as non identical twins operating by similar principles but where the disordered proteins complexes are on average less stable by 2.5 kcal mol-1.
Full Text Available Protein-Protein interactions are deregulated or disrupted; it’s a new target for an anti-cancer agent development. In this work, the protein-protein interfaces mimics on a small molecule inhibitors of a molecular combinatorial ligand library (as a similar structure of protein-protein interfaces was designed for disruption of NcoRSIN3- HDAC3 complexes. And molecular docking study was performed with Schrodinger-Maestro-9.3.5-Version, the designed five Ligands was shown good binding interactions and their docking score was around -11.9, As a result of five ligand of a novel analogue is showing superior anti- cancerous histone deacetylase inhibitor caused by the disruption of HDAC-3.
@@ Protein-protein interactions (PPIs) are of vital importance for virtually all processes of a living cell. The study of these associations of protein molecules could improve people's understanding of diseases and provide basis for therapeutic approaches.
Chowdhury, Saiful M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Shi, Liang [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Yoon, Hyunjin [Dartmouth College, Hanover, NH (United States); Ansong, Charles [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Rommereim, Leah M. [Dartmouth College, Hanover, NH (United States); Norbeck, Angela D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Auberry, Kenneth J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Moore, R. J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Adkins, Joshua N. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Heffron, Fred [Oregon Health and Science Univ., Portland, OR (United States); Smith, Richard D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
We successfully modified an existing method to investigate protein-protein interactions in the pathogenic bacterium Salmonella typhimurium (STM). This method includes i) addition of a histidine-biotin-histidine tag to the bait proteins via recombinant DNA techniques; ii) in vivo cross-linking with formaldehyde; iii) tandem affinity purification of bait proteins under fully denaturing conditions; and iv) identification of the proteins cross-linked to the bait proteins by liquid-chromatography in conjunction with tandem mass-spectrometry. In vivo cross-linking stabilized protein interactions permitted the subsequent two-step purification step conducted under denaturing conditions. The two-step purification greatly reduced nonspecific binding of non-cross-linked proteins to bait proteins. Two different negative controls were employed to reduce false-positive identification. In an initial demonstration of this approach, we tagged three selected STM proteins- HimD, PduB and PhoP- with known binding partners that ranged from stable (e.g., HimD) to transient (i.e., PhoP). Distinct sets of interacting proteins were identified with each bait protein, including the known binding partners such as HimA for HimD, as well as anticipated and unexpected binding partners. Our results suggest that novel protein-protein interactions may be critical to pathogenesis by Salmonella typhimurium. .
Kuchaiev, Oleksii; Rasajski, Marija; Higham, Desmond J.; Przul, Natasa; Przytycka, Teresa Maria
Understanding complex networks of protein-protein interactions (PPIs) is one of the foremost challenges of the post-genomic era. Due to the recent advances in experimental bio-technology, including yeast-2-hybrid (Y2H), tandem affinity purification (TAP) and other high-throughput methods for protein-protein interaction (PPI) detection, huge amounts of PPI network data are becoming available. Of major concern, however, are the levels of noise and incompleteness. For example, for Y2H screens, i...
Understanding how proteins interact with each other is of fundamental importance and is one of the most important goals of molecular biology. In order to study the characteristics of protein-protein interaction sites datasets of non-homologous protein-complexes have been compiled. These datasets include 142 obligate homocomplexes, 20 obligate hetero-complexes, 20 enzyme-inhibitor complexes, 15 antibody-antigen complexes, and 10 signaling complexes. Overall, the protein-protein interfaces of o...
Garma, Leonardo; Mukherjee, Srayanta; Mitra, Pralay; Zhang, Yang
“Protein quaternary structure universe” refers to the ensemble of all protein-protein complexes across all organisms in nature. The number of quaternary folds thus corresponds to the number of ways proteins physically interact with other proteins. This study focuses on answering two basic questions: Whether the number of protein-protein interactions is limited and, if yes, how many different quaternary folds exist in nature. By all-to-all sequence and structure comparisons, we grouped the pro...
Jie Song; Jiaxing Cheng; Xiuquan Du
Identification of protein-protein interface residues is crucial for structural biology. This paper proposes a covering algorithm for predicting protein-protein interface residues with features including protein sequence profile and residue accessible area. This method adequately utilizes the characters of a covering algorithm which have simple, lower complexity and high accuracy for high dimension data. The covering algorithm can achieve a comparable performance (69.62%, Complete dataset; 60....
Leonardo Garma; Srayanta Mukherjee; Pralay Mitra; Yang Zhang
"Protein quaternary structure universe" refers to the ensemble of all protein-protein complexes across all organisms in nature. The number of quaternary folds thus corresponds to the number of ways proteins physically interact with other proteins. This study focuses on answering two basic questions: Whether the number of protein-protein interactions is limited and, if yes, how many different quaternary folds exist in nature. By all-to-all sequence and structure comparisons, we grouped the pro...
Full Text Available Abstract Background In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. Results In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%. This proportion is even greater in the interface regions (41%. Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins. Conclusion Our study provides qualitative information about induced fit. These results could be of help for flexible docking.
Dukare, Sandeep; Klempnauer, Karl-Heinz
The transcription factor c-Myb plays a key role in the control of proliferation and differentiation in hematopoietic progenitor cells and has been implicated in the development of leukemia and certain non-hematopoietic tumors. c-Myb activity is highly dependent on the interaction with the coactivator p300 which is mediated by the transactivation domain of c-Myb and the KIX domain of p300. We have previously observed that conservative valine-to-isoleucine amino acid substitutions in a conserved stretch of hydrophobic amino acids have a profound effect on Myb activity. Here, we have explored the function of the hydrophobic region as a mediator of protein-protein interactions. We show that the hydrophobic region facilitates Myb self-interaction and binding of the histone acetyl transferase Tip60, a previously identified Myb interacting protein. We show that these interactions are affected by the valine-to-isoleucine amino acid substitutions and suppress Myb activity by interfering with the interaction of Myb and the KIX domain of p300. Taken together, our work identifies the hydrophobic region in the Myb transactivation domain as a binding site for homo- and heteromeric protein interactions and leads to a picture of the c-Myb transactivation domain as a composite protein binding region that facilitates interdependent protein-protein interactions of Myb with regulatory proteins. PMID:27080133
Cole, D. J.; Skylaris, C.-K.; Rajendra, E.; Venkitaraman, A. R.; Payne, M. C.
A modification of the MM-PBSA technique for calculating binding affinities of biomolecular complexes is presented. Classical molecular dynamics is used to explore the motion of the extended interface between two peptides derived from the BRC4 repeat of BRCA2 and the eukaryotic recombinase RAD51. The resulting trajectory is sampled using the linear-scaling density functional theory code, onetep, to determine from first principles, and with high computational efficiency, the relative free energies of binding of the ~2800 atom receptor-ligand complexes. This new method provides the basis for computational interrogation of protein-protein and protein-ligand interactions within fields ranging from chemical biological studies to small-molecule binding behaviour, with both unprecedented chemical accuracy and affordable computational expense.
Cole, Daniel; Skylaris, Chris-Kriton; Rajendra, Eeson; Venkitaraman, Ashok; Payne, Mike
A modification of the MM-PBSA technique for calculating binding affinities of biomolecular complexes is presented. Classical molecular dynamics is used to explore the motion of the extended interface between two peptides derived from the BRC4 repeat of BRCA2 and the eukaryotic recombinase RAD51. The resulting trajectory is sampled using the linear-scaling density functional theory code, onetep, to determine from first principles, and with high computational efficiency, the relative free energies of binding of the ˜2800 atom receptor-ligand complexes. This new method provides the basis for computational interrogation of protein-protein and protein-ligand interactions, within fields ranging from chemical biological studies to small molecule binding behaviour, with both unprecedented chemical accuracy and affordable computational expense.
Yeh, Hsin-Sung; Chang, Jae-Woong; Yong, Jeongsik
Characterizing protein-protein and protein-RNA interaction networks is a fundamental step to understanding the function of an RNA-binding protein. In many cases, these interactions are transient and highly dynamic. Therefore, capturing stable as well as transient interactions in living cells for the identification of protein-binding partners and the mapping of RNA-binding sequences is key to a successful establishment of the molecular interaction network. In this chapter, we will describe a method for capturing the molecular interactions in living cells using formaldehyde as a crosslinker and enriching a specific RNA-protein complex from cell extracts followed by mass spectrometry and Next-Gen sequencing analyses. PMID:26965265
Tang, HaiLin; Zhong, Fan; Liu, Wei; He, FuChu; Xie, HongWei
Integration of pathway and protein-protein interaction (PPI) data can provide more information that could lead to new biological insights. PPIs are usually represented by a simple binary model, whereas pathways are represented by more complicated models. We developed a series of rules for transforming protein interactions from pathway to binary model, and the protein interactions from seven pathway databases, including PID, BioCarta, Reactome, NetPath, INOH, SPIKE and KEGG, were transformed based on these rules. These pathway-derived binary protein interactions were integrated with PPIs from other five PPI databases including HPRD, IntAct, BioGRID, MINT and DIP, to develop integrated dataset (named PathPPI). More detailed interaction type and modification information on protein interactions can be preserved in PathPPI than other existing datasets. Comparison analysis results indicate that most of the interaction overlaps values (O AB) among these pathway databases were less than 5%, and these databases must be used conjunctively. The PathPPI data was provided at http://proteomeview.hupo.org.cn/PathPPI/PathPPI.html. PMID:25591449
Rajagopala, Seesandra Venkatappa
The yeast two-hybrid system (Y2H) is a powerful method to identify binary protein-protein interactions in vivo. Here we describe Y2H screening strategies that use defined libraries of open reading frames (ORFs) and cDNA libraries. The array-based Y2H system is well suited for interactome studies of small genomes with an existing ORFeome clones preferentially in a recombination based cloning system. For large genomes, pooled library screening followed by Y2H pairwise retests may be more efficient in terms of time and resources, but multiple sampling is necessary to ensure comprehensive screening. While the Y2H false positives can be efficiently reduced by using built-in controls, retesting, and evaluation of background activation; implementing the multiple variants of the Y2H vector systems is essential to reduce the false negatives and ensure comprehensive coverage of an interactome. PMID:26621469
Cellular functions, either under the normal or pathological conditions or under different stresses, are the results of the coordinated action of multiple proteins interacting in macromolecular complexes or assemblies. The precise determination of the specific composition of protein complexes, especially using scalable and high-throughput methods, represents a systematic approach toward revealing particular cellular biological functions. In this regard, the direct profiling protein-protein interactions (PPIs) represent an efficient way to dissect functional pathways for revealing novel protein functions. In this review, we illustrate the technological evolution for the large-scale and precise identification of PPIs toward higher physiologically relevant accuracy. These techniques aim at improving the efficiency of complex pull-down, the signal specificity and accuracy in distinguishing specific PPIs, and the accuracy of identifying physiological relevant PPIs. A newly developed streamline proteomic approach for mapping the binary relationship of PPIs in a protein complex is introduced.
Full Text Available Abstract Background Identifying protein-protein interactions is fundamental for understanding the molecular machinery of the cell. Proteome-wide studies of protein-protein interactions are of significant value, but the high-throughput experimental technologies suffer from high rates of both false positive and false negative predictions. In addition to high-throughput experimental data, many diverse types of genomic data can help predict protein-protein interactions, such as mRNA expression, localization, essentiality, and functional annotation. Evaluations of the information contributions from different evidences help to establish more parsimonious models with comparable or better prediction accuracy, and to obtain biological insights of the relationships between protein-protein interactions and other genomic information. Results Our assessment is based on the genomic features used in a Bayesian network approach to predict protein-protein interactions genome-wide in yeast. In the special case, when one does not have any missing information about any of the features, our analysis shows that there is a larger information contribution from the functional-classification than from expression correlations or essentiality. We also show that in this case alternative models, such as logistic regression and random forest, may be more effective than Bayesian networks for predicting interactions. Conclusions In the restricted problem posed by the complete-information subset, we identified that the MIPS and Gene Ontology (GO functional similarity datasets as the dominating information contributors for predicting the protein-protein interactions under the framework proposed by Jansen et al. Random forests based on the MIPS and GO information alone can give highly accurate classifications. In this particular subset of complete information, adding other genomic data does little for improving predictions. We also found that the data discretizations used in the
Frank, Andreas O.; Feldkamp, Michael D.; Kennedy, J. Phillip; Waterson, Alex G.; Pelz, Nicholas F.; Patrone, James D.; Vangamudi, Bhavatarini; Camper, DeMarco V.; Rossanese, Olivia W.; Chazin, Walter J.; Fesik, Stephen W.
Replication protein A (RPA), the major eukaryotic single-stranded DNA (ssDNA) binding protein, is involved in nearly all cellular DNA transactions. The RPA N-terminal domain (RPA70N) is a recruitment site for proteins involved in DNA damage response and repair. Selective inhibition of these protein-protein interactions has the potential to inhibit the DNA damage response and sensitize cancer cells to DNA-damaging agents without affecting other functions of RPA. To discover a potent, selective...
Zhe Zhang; Schindler, Christina E. M.; Lange, Oliver F.; Martin Zacharias
The high-resolution refinement of docked protein-protein complexes can provide valuable structural and mechanistic insight into protein complex formation complementing experiment. Monte Carlo (MC) based approaches are frequently applied to sample putative interaction geometries of proteins including also possible conformational changes of the binding partners. In order to explore efficiency improvements of the MC sampling, several enhanced sampling techniques, including temperature or Hamilto...
Zhang, Yu; Fu, Jing; Chee, Sze Y; Ang, Emmiline X W; Orner, Brendan P.
DNA-binding protein from starved cells (DPS), a mini-ferritin capable of self-assembling into a 12-meric nano-cage, was chosen as the basis for an alanine-shaving mutagenesis study to investigate the importance of key amino acid residues, located at symmetry-related protein-protein interfaces, in controlling protein stability and self-assembly. Nine mutants were designed through simple inspection, synthesized, and subjected to transmission electron microscopy, circular dichroism, size exclusi...
Lopes, Anne; Sacquin-Mora, Sophie; Dimitrova, Viktoriya; Laine, Elodie; Ponty, Yann; Carbone, Alessandra
Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information sh...
Schildbach, Stefan; Blumert, Conny; Horn, Friedemann; von Bergen, Martin; Labudde, Dirk
The functionality of most proteins is regulated by protein-protein interactions. Hence, the comprehensive characterization of the interactome is the next milestone on the path to understand the biochemistry of the cell. A powerful method to detect protein-protein interactions is a combination of coimmunoprecipitation or affinity purification with quantitative mass spectrometry. Nevertheless, both methods tend to precipitate a high number of background proteins due to nonspecific interactions. To address this challenge the software Protein-Protein-Interaction-Optimizer (PIPINO) was developed to perform an automated data analysis, to facilitate the selection of bona fide binding partners, and to compare the dynamic of interaction networks. In this study we investigated the STAT1 interaction network and its activation dependent dynamics. Stable isotope labeling by amino acids in cell culture (SILAC) was applied to analyze the STAT1 interactome after streptavidin pull-down of biotagged STAT1 from human embryonic kidney 293T cells with and without activation. Starting from more than 2,000 captured proteins 30 potential STAT1 interaction partners were extracted. Interestingly, more than 50% of these were already reported or predicted to bind STAT1. Furthermore, 16 proteins were found to affect the binding behavior depending on STAT1 phosphorylation such as STAT3 or the importin subunits alpha 1 and alpha 6. PMID:26966684
Gottschalk, Marie; Bach, Anders; Hansen, Jakob Lerche;
to the endogenous C-terminal peptide of the NMDA receptor, as evaluated by a cell-free protein-protein interaction assay. However, it is important to address both membrane permeability and effect in living cells. Therefore a bioluminescence resonance energy transfer (BRET) assay was established, where the C...
Gerding, Dale N.; Johnson, Stuart; Rupnik, Maja; Aktories, Klaus
Binary toxin (CDT) is frequently observed in Clostridium difficile strains associated with increased severity of C. difficile infection (CDI). CDT belongs to the family of binary ADP-ribosylating toxins consisting of two separate toxin components: CDTa, the enzymatic ADP-ribosyltransferase which modifies actin, and CDTb which binds to host cells and translocates CDTa into the cytosol. CDTb is activated by serine proteases and binds to lipolysis stimulated lipoprotein receptor. ADP-ribosylatio...
Bowler, Emily H; Wang, Zhenghe; Ewing, Rob M
The acquisition of mutations that activate oncogenes or inactivate tumor suppressors is a primary feature of most cancers. Mutations that directly alter protein sequence and structure drive the development of tumors through aberrant expression and modification of proteins, in many cases directly impacting components of signal transduction pathways and cellular architecture. Cancer-associated mutations may have direct or indirect effects on proteins and their interactions and while the effects of mutations on signaling pathways have been widely studied, how mutations alter underlying protein-protein interaction networks is much less well understood. Systematic mapping of oncoprotein protein interactions using proteomics techniques as well as computational network analyses is revealing how oncoprotein mutations perturb protein-protein interaction networks and drive the cancer phenotype. PMID:26325016
Rheinstadter, Maikel; Schmalzl, Karin; Wood, Kathleen; Strauch, Dieter
We present experimental evidence for a long-range protein-protein interaction in purple membrane (PM). The interprotein dynamics were quantified by measuring the spectrum of the acoustic phonons in the 2D bacteriorhodopsin (BR) protein lattice using inelastic neutron scattering. Phonon energies of about 1 meV were determined. The data are compared to an analytical model, and the effective spring constant for the interaction between neighboring protein trimers are determined to be k=53 N/m. Ad...
Szilagyi, Andras; Zhang, Yang
The structure of protein-protein complexes can be constructed by using the known structure of other protein complexes as a template. The complex structure templates are generally detected either by homology-based sequence alignments or, given the structure of monomer components, by structure-based comparisons. Critical improvements have been made in recent years by utilizing interface recognition and by recombining monomer and complex template libraries. Encouraging progress has also been wit...
Jonnalagadda, Siddhartha; Gonzalez, Graciela
Accurate systems for extracting Protein-Protein Interactions (PPIs) automatically from biomedical articles can help accelerate biomedical research. Biomedical Informatics researchers are collaborating to provide metaservices and advance the state-of-art in PPI extraction. One problem often neglected by current Natural Language Processing systems is the characteristic complexity of the sentences in biomedical literature. In this paper, we report on the impact that automatic simplification of s...
V. Srinivasa Rao; Srinivas, K.; Sujini, G. N.; G. N. Sunand Kumar
Protein-protein interaction plays key role in predicting the protein function of target protein and drug ability of molecules. The majority of genes and proteins realize resulting phenotype functions as a set of interactions. The in vitro and in vivo methods like affinity purification, Y2H (yeast 2 hybrid), TAP (tandem affinity purification), and so forth have their own limitations like cost, time, and so forth, and the resultant data sets are noisy and have more false positives to annotate t...
Nepusz, Tamás; Yu, Haiyuan; Paccanaro, Alberto
We introduce clustering with overlapping neighborhood expansion (ClusterONE), a method for detecting potentially overlapping protein complexes from protein-protein interaction data. ClusterONE-derived complexes for several yeast data sets showed better correspondence with reference complexes in the Munich Information Center for Protein Sequence (MIPS) catalog and complexes derived from the Saccharomyces Genome Database (SGD) than the results of seven popular methods. The results also showed a...
Ivanov, Andrei A.; Khuri, Fadlo R.; Fu, Haian
The emergence and convergence of cancer genomics, targeted therapies, and network oncology have significantly expanded the landscape of protein-protein interaction (PPI) networks in cancer for therapeutic discovery. Extensive biological and clinical investigations have led to the identification of protein interaction hubs and nodes that are critical for the acquisition and maintaining characteristics of cancer essential for cell transformation. Such cancer enabling PPIs have become promising ...
Full Text Available The Arenaviridae family includes widely distributed pathogens that cause severe hemorrhagic fever in humans. Replication and packaging of their single-stranded RNA genome involve RNA recognition by viral proteins and a number of key protein-protein interactions. Viral RNA synthesis is directed by the virus-encoded RNA dependent-RNA polymerase (L protein and requires viral RNA encapsidation by the Nucleoprotein. In addition to the role that the interaction between L and the Nucleoprotein may have in the replication process, polymerase activity appears to be modulated by the association between L and the small multifunctional Z protein. Z is also a structural component of the virions that plays an essential role in viral morphogenesis. Indeed, interaction of the Z protein with the Nucleoprotein is critical for genome packaging. Furthermore, current evidence suggests that binding between Z and the viral envelope glycoprotein complex is required for virion infectivity, and that Z homo-oligomerization is an essential step for particle assembly and budding. Efforts to understand the molecular basis of arenavirus life cycle have revealed important details on these viral protein-protein interactions that will be reviewed in this article.
Full Text Available Abstract Background Atomic Solvation Parameters (ASP model has been proven to be a very successful method of calculating the binding free energy of protein complexes. This suggests that incorporating it into docking algorithms should improve the accuracy of prediction. In this paper we propose an FFT-based algorithm to calculate ASP scores of protein complexes and develop an ASP-based protein-protein docking method (ASPDock. Results The ASPDock is first tested on the 21 complexes whose binding free energies have been determined experimentally. The results show that the calculated ASP scores have stronger correlation (r ≈ 0.69 with the binding free energies than the pure shape complementarity scores (r ≈ 0.48. The ASPDock is further tested on a large dataset, the benchmark 3.0, which contain 124 complexes and also shows better performance than pure shape complementarity method in docking prediction. Comparisons with other state-of-the-art docking algorithms showed that ASP score indeed gives higher success rate than the pure shape complementarity score of FTDock but lower success rate than Zdock3.0. We also developed a softly restricting method to add the information of predicted binding sites into our docking algorithm. The ASP-based docking method performed well in CAPRI rounds 18 and 19. Conclusions ASP may be more accurate and physical than the pure shape complementarity in describing the feature of protein docking.
Two Excel Spreadsheet files are offered to help calibrate telescope or camera image scale and orientation with binary stars for any time. One is a personally selected list of fixed position binaries and binaries with well-determined orbits, and the other contains all binaries with published orbits. Both are derived from the web site of the Washington Double Star Library. The spreadsheets give the position angle and separation of the binaries for any entered time by taking advantage of Excel's built in iteration function to solve Kepler's transcendental equation.
A central question in molecular biology is what structural features are common at protein-protein interfaces and what energetic factors define the affinity and specificity of protein-protein association. Analysis of structural and mutational data on protein-protein interfaces revealed that protein-protein interfaces of different functional classes contain many more energetically important charged and polar residues than was previously thought. Since, in the context of protein folding studies, polar interactions are believed to destabilize the folded proteins, this observation raised the question as to the forces that determine the stability of protein complexes. To investigate this issue in detail, the authors developed a number of partitioning schemes that allowed them to investigate the role of selected residues, ion pairs, and networks of polar interactions in protein-protein association. The methods developed were applied to the analysis of four different protein-protein interfaces: the ribonuclease barnase and its inhibitor barstar, the human growth hormone and its receptor, subtype N9 influenze virus neuraminidase and NC41 antibody, and the Ras Binding Domain of kinase cRaf and a Ras homologue Rap1A. The calculations revealed a surprising variability in how polar interactions affect the stability of different complexes. The finding that positions of charged and polar residues on protein-protein interfaces are optimized with respect to electrostatic interactions suggests that this property can be employed for the discrimination between native conformations and trial complexes generated by a docking algorithm. Analysis indicated the presence of SH2 domains in Janus family of non-receptor protein tyrosine kinases.
Bimlesh Ojha; Cirantan Kar; Gopal Das
There is a great deal of interest in developing small molecule inhibitors of protein misfolding and aggregation due to a growing number of pathologic states known as amyloid disorders. In searching for alternative ways to reduce protein-protein interactions or to inhibit the amyloid formation, the inhibitory effects of cationic amphiphile viz. -methyl-8-(alkoxy)quinolinium iodide on aggregation behaviour of hen egg white lysozyme (HEWL) at alkaline pH has been studied. Even though the compounds did not protect native HEWL from conformational changes, they were effective in diminishing HEWL amyloid formation, delaying both nucleation and elongation phases. It is likely that strong binding in the HEWL compound complex, raises the activation energy barrier for protein misfolding and subsequent aggregation, thereby retarding the aggregation kinetics substantially.
Full Text Available Understanding complex networks of protein-protein interactions (PPIs is one of the foremost challenges of the post-genomic era. Due to the recent advances in experimental bio-technology, including yeast-2-hybrid (Y2H, tandem affinity purification (TAP and other high-throughput methods for protein-protein interaction (PPI detection, huge amounts of PPI network data are becoming available. Of major concern, however, are the levels of noise and incompleteness. For example, for Y2H screens, it is thought that the false positive rate could be as high as 64%, and the false negative rate may range from 43% to 71%. TAP experiments are believed to have comparable levels of noise.We present a novel technique to assess the confidence levels of interactions in PPI networks obtained from experimental studies. We use it for predicting new interactions and thus for guiding future biological experiments. This technique is the first to utilize currently the best fitting network model for PPI networks, geometric graphs. Our approach achieves specificity of 85% and sensitivity of 90%. We use it to assign confidence scores to physical protein-protein interactions in the human PPI network downloaded from BioGRID. Using our approach, we predict 251 interactions in the human PPI network, a statistically significant fraction of which correspond to protein pairs sharing common GO terms. Moreover, we validate a statistically significant portion of our predicted interactions in the HPRD database and the newer release of BioGRID. The data and Matlab code implementing the methods are freely available from the web site: http://www.kuchaev.com/Denoising.
Accurate systems for extracting Protein-Protein Interactions (PPIs) automatically from biomedical articles can help accelerate biomedical research. Biomedical Informatics researchers are collaborating to provide metaservices and advance the state-of-art in PPI extraction. One problem often neglected by current Natural Language Processing systems is the characteristic complexity of the sentences in biomedical literature. In this paper, we report on the impact that automatic simplification of sentences has on the performance of a state-of-art PPI extraction system, showing a substantial improvement in recall (8%) when the sentence simplification method is applied, without significant impact to precision.
Mishra, Vibhor; Kumar, Ashutosh; Ali, Vahab; Nozaki, Tomoyoshi; Zhang, Kam Y J; Bhakuni, Vinod
Physical interactions between d-phosphoglycerate dehydrogenase (EhPGDH) and phosphoserine aminotransferase (EhPSAT) from an enteric human parasite Entamoeba histolytica was observed by pull-down assay, gel filtration chromatography, chemical cross-linking, emission anisotropy, molecular docking and molecular dynamic simulations. The protein-protein complex had a 1:1 stochiometry with a dissociation constant of 3.453 × 10(-7) M. Ionic interactions play a significant role in complex formation and stability. Analysis of the energy minimized average simulated model of the protein complex show that the nucleotide binding domain of EhPGDH specifically interacts with EhPSAT. Denaturation studies suggest that the nucleotide binding domain (Nbd) and substrate binding domain (Sbd) of EhPGDH are independent folding/unfolding units. Thus the Nbd-EhPGDH was separately cloned over-expressed and purified to homogeneity. Fluorescence anisotropy study show that the purified Nbd interacts with EhPSAT. Forward enzyme catalyzed reaction for the EhPGDH-PSAT complex showed efficient Km values for 3-phosphoglyceric acid as compared to only EhPGDH suggesting a possibility of substrate channelling in the protein complex. PMID:22386871
Full Text Available RPGR-interacting protein 1 (RPGRIP1 is mutated in the eye disease Leber congenital amaurosis (LCA and its structural homolog, RPGRIP1-like (RPGRIP1L, is mutated in many different ciliopathies. Both are multidomain proteins that are predicted to interact with retinitis pigmentosa G-protein regulator (RPGR. RPGR is mutated in X-linked retinitis pigmentosa and is located in photoreceptors and primary cilia. We solved the crystal structure of the complex between the RPGR-interacting domain (RID of RPGRIP1 and RPGR and demonstrate that RPGRIP1L binds to RPGR similarly. RPGRIP1 binding to RPGR affects the interaction with PDEδ, the cargo shuttling factor for prenylated ciliary proteins. RPGRIP1-RID is a C2 domain with a canonical β sandwich structure that does not bind Ca2+ and/or phospholipids and thus constitutes a unique type of protein-protein interaction module. Judging from the large number of C2 domains in most of the ciliary transition zone proteins identified thus far, the structure presented here seems to constitute a cilia-specific module that is present in multiprotein transition zone complexes.
Feng, Mei; Kang, Hongsuk; Yang, Zaixing; Luan, Binquan; Zhou, Ruhong
Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.
Full Text Available Understanding the mechanisms of protein-protein interaction is a fundamental problem with many practical applications. The fact that different proteins can bind similar partners suggests that convergently evolved binding interfaces are reused in different complexes. A set of protein complexes composed of non-homologous domains interacting with homologous partners at equivalent binding sites was collected in 2006, offering an opportunity to investigate this point. We considered 433 pairs of protein-protein complexes from the ABAC database (AB and AC binary protein complexes sharing a homologous partner A and analyzed the extent of physico-chemical similarity at the atomic and residue level at the protein-protein interface. Homologous partners of the complexes were superimposed using Multiprot, and similar atoms at the interface were quantified using a five class grouping scheme and a distance cut-off. We found that the number of interfacial atoms with similar properties is systematically lower in the non-homologous proteins than in the homologous ones. We assessed the significance of the similarity by bootstrapping the atomic properties at the interfaces. We found that the similarity of binding sites is very significant between homologous proteins, as expected, but generally insignificant between the non-homologous proteins that bind to homologous partners. Furthermore, evolutionarily conserved residues are not colocalized within the binding sites of non-homologous proteins. We could only identify a limited number of cases of structural mimicry at the interface, suggesting that this property is less generic than previously thought. Our results support the hypothesis that different proteins can interact with similar partners using alternate strategies, but do not support convergent evolution.
Ouimet, Claire M; Shao, Hao; Rauch, Jennifer N; Dawod, Mohamed; Nordhues, Bryce; Dickey, Chad A; Gestwicki, Jason E; Kennedy, Robert T
Capillary electrophoresis (CE) has been identified as a useful platform for detecting, quantifying, and screening for modulators of protein-protein interactions (PPIs). In this method, one protein binding partner is labeled with a fluorophore, the protein binding partners are mixed, and then, the complex is separated from free protein to allow direct determination of bound to free ratios. Although it possesses many advantages for PPI studies, the method is limited by the need to have separation conditions that both prevent protein adsorption to capillary and maintain protein interactions during the separation. In this work, we use protein cross-linking capillary electrophoresis (PXCE) to overcome this limitation. In PXCE, the proteins are cross-linked under binding conditions and then separated. This approach eliminates the need to maintain noncovalent interactions during electrophoresis and facilitates method development. We report PXCE methods for an antibody-antigen interaction and heterodimer and homodimer heat shock protein complexes. Complexes are cross-linked by short treatments with formaldehyde after reaching binding equilibrium. Cross-linked complexes are separated by electrophoretic mobility using free solution CE or by size using sieving electrophoresis of SDS complexes. The method gives good quantitative results; e.g., a lysozyme-antibody interaction was found to have Kd = 24 ± 3 nM by PXCE and Kd = 17 ± 2 nM using isothermal calorimetry (ITC). Heat shock protein 70 (Hsp70) in complex with bcl2 associated athanogene 3 (Bag3) was found to have Kd = 25 ± 5 nM by PXCE which agrees with Kd values reported without cross-linking. Hsp70-Bag3 binding site mutants and small molecule inhibitors of Hsp70-Bag3 were characterized by PXCE with good agreement to inhibitory constants and IC50 values obtained by a bead-based flow cytometry protein interaction assay (FCPIA). PXCE allows rapid method development for quantitative analysis of PPIs. PMID:27434096
Bier, David; Thiel, Philipp; Briels, Jeroen; Ottmann, Christian
More than 300,000 Protein-Protein Interactions (PPIs) can be found in human cells. This number is significantly larger than the number of single proteins, which are the classical targets for pharmacological intervention. Hence, specific and potent modulation of PPIs by small, drug-like molecules would tremendously enlarge the "druggable genome" enabling novel ways of drug discovery for essentially every human disease. This strategy is especially promising in diseases with difficult targets like intrinsically disordered proteins or transcription factors, for example neurodegeneration or metabolic diseases. Whereas the potential of PPI modulation has been recognized in terms of the development of inhibitors that disrupt or prevent a binary protein complex, the opposite (or complementary) strategy to stabilize PPIs has not yet been realized in a systematic manner. This fact is rather surprising given the number of impressive natural product examples that confer their activity by stabilizing specific PPIs. In addition, in recent years more and more examples of synthetic molecules are being published that work as PPI stabilizers, despite the fact that in the majority they initially have not been designed as such. Here, we describe examples from both the natural products as well as the synthetic molecules advocating for a stronger consideration of the PPI stabilization approach in chemical biology and drug discovery. PMID:26093250
Nourani, Esmaeil; Khunjush, Farshad; Durmuş, Saliha
Pathogenic microorganisms exploit host cellular mechanisms and evade host defense mechanisms through molecular pathogen-host interactions (PHIs). Therefore, comprehensive analysis of these PHI networks should be an initial step for developing effective therapeutics against infectious diseases. Computational prediction of PHI data is gaining increasing demand because of scarcity of experimental data. Prediction of protein-protein interactions (PPIs) within PHI systems can be formulated as a classification problem, which requires the knowledge of non-interacting protein pairs. This is a restricting requirement since we lack datasets that report non-interacting protein pairs. In this study, we formulated the "computational prediction of PHI data" problem using kernel embedding of heterogeneous data. This eliminates the abovementioned requirement and enables us to predict new interactions without randomly labeling protein pairs as non-interacting. Domain-domain associations are used to filter the predicted results leading to 175 novel PHIs between 170 human proteins and 105 viral proteins. To compare our results with the state-of-the-art studies that use a binary classification formulation, we modified our settings to consider the same formulation. Detailed evaluations are conducted and our results provide more than 10 percent improvements for accuracy and AUC (area under the receiving operating curve) results in comparison with state-of-the-art methods. PMID:27072625
Shore, S N; van den Heuvel, EPJ
This volume contains lecture notes presented at the 22nd Advanced Course of the Swiss Society for Astrophysics and Astronomy. The contributors deal with symbiotic stars, cataclysmic variables, massive binaries and X-ray binaries, in an attempt to provide a better understanding of stellar evolution.
Full Text Available Introduction: The spatiotemporal order plays an important role in cell functioning and is affected in many pathologies such as cancer and neurodegenerative diseases. One of the ultimate goals of molecular biology is reconstruction of the spatiotemporal structure of a living cell at the molecular level. This task includes determination of proximities between different molecular components in the cell and monitoring their time- and physiological state-dependent changes. In many cases, proximity between macromolecules arises due to their interactions; however, the contribution of dynamic self-organization in generation of spatiotemporal order is emerging as another viable possibility. Specifically, in proteomics, this implies that the detection of protein-protein proximity is a more general task than gaining information about physical interactions between proteins, as it could detail aspects of spatial order in vivo that are challenging to reconstitute in binding experiments in vitro. Methods: In this work, we have developed a method of monitoring protein-protein proximity in vivo. For this purpose, the BirA was fused to one of the interaction partners, whereas the BAP was modified to make the detection of its biotinylation possible by mass spectrometry. Results: Using several experimental systems, we showed that the biotinylation is interaction dependent. In addition, we demonstrated that BAP domains with different primary amino acid structures and thus with different molecular weights can be used in the same experiment, providing the possibility of multiplexing. Alternatively to the changes in primary amino acid structure, the stable isotope format can also be used, providing another way to perform multiplexing experiments. Finally, we also demonstrated that our system could help to overcome another limitation of current methodologies to detect protein-protein proximity. For example, one can follow the state of a protein of interest at a defined
Frystyk, Jan; Højlund, Kurt; Rasmussen, Kirsten Nyborg; Jørgensen, Søren Peter; Wildner-Christensen, Mette; Ørskov, Hans
IGFBP-2, -3, -4, nor IGF-II caused any cross-reaction. The linear standard curve covered 3 orders of magnitude, and within and in-between assay coefficients of variation were less than 5 and 15%, respectively. To study the dynamic relationship between free IGF-I and binary complex formation, seven......-I correlated inversely with IGFBP-1 (-0.81 < or = r < or = -0.48; 0.0001 < or = P < or = 0.05) and the binary complex (-0.79 < or = r < or = -0.41; 0.0001 < or = P < or = 0.05). To study overnight fasting levels, we compared healthy controls and patients with type 1 diabetes and chronic renal failure (n = 10...
Lua, Rhonald C; Marciano, David C; Katsonis, Panagiotis; Adikesavan, Anbu K; Wilkins, Angela D; Lichtarge, Olivier
Understanding the molecular basis of protein function remains a central goal of biology, with the hope to elucidate the role of human genes in health and in disease, and to rationally design therapies through targeted molecular perturbations. We review here some of the computational techniques and resources available for characterizing a critical aspect of protein function - those mediated by protein-protein interactions (PPI). We describe several applications and recent successes of the Evolutionary Trace (ET) in identifying molecular events and shapes that underlie protein function and specificity in both eukaryotes and prokaryotes. ET is a part of analytical approaches based on the successes and failures of evolution that enable the rational control of PPI. PMID:24878423
Friedhoff, Peter; Li, Pingping; Gotthardt, Julia
The principal DNA mismatch repair proteins MutS and MutL are versatile enzymes that couple DNA mismatch or damage recognition to other cellular processes. Besides interaction with their DNA substrates this involves transient interactions with other proteins which is triggered by the DNA mismatch or damage and controlled by conformational changes. Both MutS and MutL proteins have ATPase activity, which adds another level to control their activity and interactions with DNA substrates and other proteins. Here we focus on the protein-protein interactions, protein interaction sites and the different levels of structural knowledge about the protein complexes formed with MutS and MutL during the mismatch repair reaction. PMID:26725162
SUN Jingchun; XU Jinlin; LI Yixue; SHI Tieliu
Protein-protein interactions play key roles in cells. Lots of experimental approaches and in silico methods have been developed to identify and predict large-scale protein-protein interactions. However, compared with the traditionally experimental results, the high-throughput protein-protein interaction data often contain the false positives in high probability. In order to fully utilize the large-scale data, it is necessary to develop bioinformatic methods for systematically evaluating those data in order to further improve the data reliability and mine biological information. This review summarizes the methodologies of analysis and application of high-throughput protein-protein interaction data, including the evaluation methods, the relationship between protein-protein interaction data and other protein biological information, and their applications in biological study. In addition, this paper also suggests some interesting topics on mining high-throughput protein-protein interaction data.
Wan Kyu Kim
Full Text Available 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.
Heo, Lim; Lee, Hasup; Seok, Chaok
Protein-protein docking methods have been widely used to gain an atomic-level understanding of protein interactions. However, docking methods that employ low-resolution energy functions are popular because of computational efficiency. Low-resolution docking tends to generate protein complex structures that are not fully optimized. GalaxyRefineComplex takes such low-resolution docking structures and refines them to improve model accuracy in terms of both interface contact and inter-protein orientation. This refinement method allows flexibility at the protein interface and in the overall docking structure to capture conformational changes that occur upon binding. Symmetric refinement is also provided for symmetric homo-complexes. This method was validated by refining models produced by available docking programs, including ZDOCK and M-ZDOCK, and was successfully applied to CAPRI targets in a blind fashion. An example of using the refinement method with an existing docking method for ligand binding mode prediction of a drug target is also presented. A web server that implements the method is freely available at http://galaxy.seoklab.org/refinecomplex. PMID:27535582
Kuenemann, Mélaine A.; Labbé, Céline M.; Cerdan, Adrien H.; Sperandio, Olivier
Protein-protein interactions (PPIs) play vital roles in life and provide new opportunities for therapeutic interventions. In this large data analysis, 3,300 inhibitors of PPIs (iPPIs) were compared to 17 reference datasets of collectively ~566,000 compounds (including natural compounds, existing drugs, active compounds on conventional targets, etc.) using a chemoinformatics approach. Using this procedure, we showed that comparable classes of PPI targets can be formed using either the similarity of their ligands or the shared properties of their binding cavities, constituting a proof-of-concept that not only can binding pockets be used to group PPI targets, but that these pockets certainly condition the properties of their corresponding ligands. These results demonstrate that matching regions in both chemical space and target space can be found. Such identified classes of targets could lead to the design of PPI-class-specific chemical libraries and therefore facilitate the development of iPPIs to the stage of drug candidates.
Peng Liu; Lei Yang; Daming Shi; Xianglong Tang
A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction net...
Maroun, M; Aronheim, A
The Ras Recruitment System (RRS) is a method for identification and isolation of protein-protein interaction. The method is based on translocation of cytoplasmic mammalian Ras protein to the inner leaflet of the plasma membrane through protein-protein interaction. The system is studied in a temperature-sensitive yeast strain where the yeast Ras guanyl nucleotide exchange factor is inactive at 36 degrees C. Protein-protein interaction results in cell growth at the restrictive temperature. We d...
Lee, Wan-Hung; Xu, Zhili; Ashpole, Nicole M; Hudmon, Andy; Kulkarni, Pushkar M; Thakur, Ganesh A; Lai, Yvonne Y; Hohmann, Andrea G
Aberrant increases in NMDA receptor (NMDAR) signaling contributes to central nervous system sensitization and chronic pain by activating neuronal nitric oxide synthase (nNOS) and generating nitric oxide (NO). Because the scaffolding protein postsynaptic density 95kDA (PSD95) tethers nNOS to NMDARs, the PSD95-nNOS complex represents a therapeutic target. Small molecule inhibitors IC87201 (EC5O: 23.94 μM) and ZL006 (EC50: 12.88 μM) directly inhibited binding of purified PSD95 and nNOS proteins in AlphaScreen without altering binding of PSD95 to ErbB4. Both PSD95-nNOS inhibitors suppressed glutamate-induced cell death with efficacy comparable to MK-801. IC87201 and ZL006 preferentially suppressed phase 2A pain behavior in the formalin test and suppressed allodynia induced by intraplantar complete Freund's adjuvant administration. IC87201 and ZL006 suppressed mechanical and cold allodynia induced by the chemotherapeutic agent paclitaxel (ED50s: 2.47 and 0.93 mg/kg i.p. for IC87201 and ZL006, respectively). Efficacy of PSD95-nNOS disruptors was similar to MK-801. Motor ataxic effects were induced by MK-801 but not by ZL006 or IC87201. Finally, MK-801 produced hyperalgesia in the tail-flick test whereas IC87201 and ZL006 did not alter basal nociceptive thresholds. Our studies establish the utility of using AlphaScreen and purified protein pairs to establish and quantify disruption of protein-protein interactions. Our results demonstrate previously unrecognized antinociceptive efficacy of ZL006 and establish, using two small molecules, a broad application for PSD95-nNOS inhibitors in treating neuropathic and inflammatory pain. Collectively, our results demonstrate that disrupting PSD95-nNOS protein-protein interactions is effective in attenuating pathological pain without producing unwanted side effects (i.e. motor ataxia) associated with NMDAR antagonists. PMID:26071110
Full Text Available Abstract Background Many recent studies have investigated modularity in biological networks, and its role in functional and structural characterization of constituent biomolecules. A technique that has shown considerable promise in the domain of modularity detection is the Newman and Girvan (NG algorithm, which relies on the number of shortest-paths across pairs of vertices in the network traversing a given edge, referred to as the betweenness of that edge. The edge with the highest betweenness is iteratively eliminated from the network, with the betweenness of the remaining edges recalculated in every iteration. This generates a complete dendrogram, from which modules are extracted by applying a quality metric called modularity denoted by Q. This exhaustive computation can be prohibitively expensive for large networks such as Protein-Protein Interaction Networks. In this paper, we present a novel optimization to the modularity detection algorithm, in terms of an efficient termination criterion based on a target edge betweenness value, using which the process of iterative edge removal may be terminated. Results We validate the robustness of our approach by applying our algorithm on real-world protein-protein interaction networks of Yeast, C.Elegans and Drosophila, and demonstrate that our algorithm consistently has significant computational gains in terms of reduced runtime, when compared to the NG algorithm. Furthermore, our algorithm produces modules comparable to those from the NG algorithm, qualitatively and quantitatively. We illustrate this using comparison metrics such as module distribution, module membership cardinality, modularity Q, and Jaccard Similarity Coefficient. Conclusions We have presented an optimized approach for efficient modularity detection in networks. The intuition driving our approach is the extraction of holistic measures of centrality from graphs, which are representative of inherent modular structure of the
Jessica B Hostetler
Full Text Available A vaccine targeting Plasmodium vivax will be an essential component of any comprehensive malaria elimination program, but major gaps in our understanding of P. vivax biology, including the protein-protein interactions that mediate merozoite invasion of reticulocytes, hinder the search for candidate antigens. Only one ligand-receptor interaction has been identified, that between P. vivax Duffy Binding Protein (PvDBP and the erythrocyte Duffy Antigen Receptor for Chemokines (DARC, and strain-specific immune responses to PvDBP make it a complex vaccine target. To broaden the repertoire of potential P. vivax merozoite-stage vaccine targets, we exploited a recent breakthrough in expressing full-length ectodomains of Plasmodium proteins in a functionally-active form in mammalian cells and initiated a large-scale study of P. vivax merozoite proteins that are potentially involved in reticulocyte binding and invasion.We selected 39 P. vivax proteins that are predicted to localize to the merozoite surface or invasive secretory organelles, some of which show homology to P. falciparum vaccine candidates. Of these, we were able to express 37 full-length protein ectodomains in a mammalian expression system, which has been previously used to express P. falciparum invasion ligands such as PfRH5. To establish whether the expressed proteins were correctly folded, we assessed whether they were recognized by antibodies from Cambodian patients with acute vivax malaria. IgG from these samples showed at least a two-fold change in reactivity over naïve controls in 27 of 34 antigens tested, and the majority showed heat-labile IgG immunoreactivity, suggesting the presence of conformation-sensitive epitopes and native tertiary protein structures. Using a method specifically designed to detect low-affinity, extracellular protein-protein interactions, we confirmed a predicted interaction between P. vivax 6-cysteine proteins P12 and P41, further suggesting that the proteins
Full Text Available WSSV is one of the most dangerous pathogens in shrimp aquaculture. However, the molecular mechanism of how WSSV interacts with shrimp is still not very clear. In the present study, bioinformatic approaches were used to predict interactions between proteins from WSSV and shrimp. The genome data of WSSV (NC_003225.1 and the constructed transcriptome data of F. chinensis were used to screen potentially interacting proteins by searching in protein interaction databases, including STRING, Reactome, and DIP. Forty-four pairs of proteins were suggested to have interactions between WSSV and the shrimp. Gene ontology analysis revealed that 6 pairs of these interacting proteins were classified into “extracellular region” or “receptor complex” GO-terms. KEGG pathway analysis showed that they were involved in the “ECM-receptor interaction pathway.” In the 6 pairs of interacting proteins, an envelope protein called “collagen-like protein” (WSSV-CLP encoded by an early virus gene “wsv001” in WSSV interacted with 6 deduced proteins from the shrimp, including three integrin alpha (ITGA, two integrin beta (ITGB, and one syndecan (SDC. Sequence analysis on WSSV-CLP, ITGA, ITGB, and SDC revealed that they possessed the sequence features for protein-protein interactions. This study might provide new insights into the interaction mechanisms between WSSV and shrimp.
Corbi-Verge, Carles; Kim, Philip M
Protein-protein interactions (PPI) are involved in virtually every cellular process and thus represent an attractive target for therapeutic interventions. A significant number of protein interactions are frequently formed between globular domains and short linear peptide motifs (DMI). Targeting these DMIs has proven challenging and classical approaches to inhibiting such interactions with small molecules have had limited success. However, recent new approaches have led to the discovery of potent inhibitors, some of them, such as Obatoclax, ABT-199, AEG-40826 and SAH-p53-8 are likely to become approved drugs. These novel inhibitors belong to a wide range of different molecule classes, ranging from small molecules to peptidomimetics and biologicals. This article reviews the main reasons for limited success in targeting PPIs, discusses how successful approaches overcome these obstacles to discovery promising inhibitors for human protein double minute 2 (HDM2), B-cell lymphoma 2 (Bcl-2), X-linked inhibitor of apoptosis protein (XIAP), and provides a summary of the promising approaches currently in development that indicate the future potential of PPI inhibitors in drug discovery. PMID:26936767
Full Text Available Abstract Background Protein-protein interaction (PPI is essential to most biological processes. Abnormal interactions may have implications in a number of neurological syndromes. Given that the association and dissociation of protein molecules is crucial, computational tools capable of effectively identifying PPI are desirable. In this paper, we propose a simple yet effective method to detect PPI based on pairwise similarity and using only the primary structure of the protein. The PPI based on Pairwise Similarity (PPI-PS method consists of a representation of each protein sequence by a vector of pairwise similarities against large subsequences of amino acids created by a shifting window which passes over concatenated protein training sequences. Each coordinate of this vector is typically the E-value of the Smith-Waterman score. These vectors are then used to compute the kernel matrix which will be exploited in conjunction with support vector machines. Results To assess the ability of the proposed method to recognize the difference between "interacted" and "non-interacted" proteins pairs, we applied it on different datasets from the available yeast saccharomyces cerevisiae protein interaction. The proposed method achieved reasonable improvement over the existing state-of-the-art methods for PPI prediction. Conclusion Pairwise similarity score provides a relevant measure of similarity between protein sequences. This similarity incorporates biological knowledge about proteins and it is extremely powerful when combined with support vector machine to predict PPI.
Alfaras-Melainis, Konstantinos; Gomes, Ivone; Rozenfeld, Raphael; Zachariou, Venetia; Devi, Lakshmi
Opioid receptors, MORP, DORP and KORP, belong to the family A of G protein coupled receptors (GPCR), and have been found to modulate a large number of physiological functions, including mood, stress, appetite, nociception and immune responses. Exogenously applied opioid alkaloids produce analgesia, hedonia and addiction. Addiction is linked to alterations in function and responsiveness of all three opioid receptors in the brain. Over the last few years, a large number of studies identified protein-protein interactions that play an essential role in opioid receptor function and responsiveness. Here, we summarize interactions shown to affect receptor biogenesis and trafficking, as well as those affecting signal transduction events following receptor activation. This article also examines protein interactions modulating the rate of receptor endocytosis and degradation, events that play a major role in opiate analgesia. Like several other GPCRs, opioid receptors may form homo or heterodimers. The last part of this review summarizes recent knowledge on proteins known to affect opioid receptor dimerization. PMID:19273296
Sánchez Claros, Carmen
Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.
Witherow, D. Scott; Carson, Sue
The study of protein-protein interactions is important to scientists in a wide range of disciplines. We present here the assessment of a lab-intensive course that teaches students techniques used to identify and further study protein-protein interactions. One of the unique elements of the course is that students perform a yeast two-hybrid screen…
Somireddy Venkata, Bharat Kumar Reddy
Protein-protein interactions play an important role in all cellular processes such as signal transduction, electron transfer, gene regulation, transcription, and translation. Understanding these protein-protein interactions at the molecular level, is an important aim in structural biology. The prote
De Las Rivas, Javier; Fontanillo, Celia
Mapping and understanding of the protein interaction networks with their key modules and hubs can provide deeper insights into the molecular machinery underlying complex phenotypes. In this article, we present the basic characteristics and definitions of protein networks, starting with a distinction of the different types of associations between proteins. We focus the review on protein-protein interactions (PPIs), a subset of associations defined as physical contacts between proteins that occur by selective molecular docking in a particular biological context. We present such definition as opposed to other types of protein associations derived from regulatory, genetic, structural or functional relations. To determine PPIs, a variety of binary and co-complex methods exist; however, not all the technologies provide the same information and data quality. A way of increasing confidence in a given protein interaction is to integrate orthogonal experimental evidences. The use of several complementary methods testing each single interaction assesses the accuracy of PPI data and tries to minimize the occurrence of false interactions. Following this approach there have been important efforts to unify primary databases of experimentally proven PPIs into integrated databases. These meta-databases provide a measure of the confidence of interactions based on the number of experimental proofs that report them. As a conclusion, we can state that integrated information allows the building of more reliable interaction networks. Identification of communities, cliques, modules and hubs by analysing the topological parameters and graph properties of the protein networks allows the discovery of central/critical nodes, which are candidates to regulate cellular flux and dynamics. PMID:22908212
Full Text Available Protein-protein interactions (PPIs constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.
Full Text Available BACKGROUND: The exponential increase of published biomedical literature prompts the use of text mining tools to manage the information overload automatically. One of the most common applications is to mine protein-protein interactions (PPIs from PubMed abstracts. Currently, most tools in mining PPIs from literature are using co-occurrence-based approaches or rule-based approaches. Hybrid methods (frame-based approaches by combining these two methods may have better performance in predicting PPIs. However, the predicted PPIs from these methods are rarely evaluated by known PPI databases and co-occurred terms in Gene Ontology (GO database. METHODOLOGY/PRINCIPAL FINDINGS: We here developed a web-based tool, PPI Finder, to mine human PPIs from PubMed abstracts based on their co-occurrences and interaction words, followed by evidences in human PPI databases and shared terms in GO database. Only 28% of the co-occurred pairs in PubMed abstracts appeared in any of the commonly used human PPI databases (HPRD, BioGRID and BIND. On the other hand, of the known PPIs in HPRD, 69% showed co-occurrences in the literature, and 65% shared GO terms. CONCLUSIONS: PPI Finder provides a useful tool for biologists to uncover potential novel PPIs. It is freely accessible at http://liweilab.genetics.ac.cn/tm/.
Rooklin, David; Wang, Cheng; Katigbak, Joseph; Arora, Paramjit S; Zhang, Yingkai
Inhibition of protein-protein interactions (PPIs) is emerging as a promising therapeutic strategy despite the difficulty in targeting such interfaces with drug-like small molecules. PPIs generally feature large and flat binding surfaces as compared to typical drug targets. These features pose a challenge for structural characterization of the surface using geometry-based pocket-detection methods. An attractive mapping strategy--that builds on the principles of fragment-based drug discovery (FBDD)--is to detect the fragment-centric modularity at the protein surface and then characterize the large PPI interface as a set of localized, fragment-targetable interaction regions. Here, we introduce AlphaSpace, a computational analysis tool designed for fragment-centric topographical mapping (FCTM) of PPI interfaces. Our approach uses the alpha sphere construct, a geometric feature of a protein's Voronoi diagram, to map out concave interaction space at the protein surface. We introduce two new features--alpha-atom and alpha-space--and the concept of the alpha-atom/alpha-space pair to rank pockets for fragment-targetability and to facilitate the evaluation of pocket/fragment complementarity. The resulting high-resolution interfacial map of targetable pocket space can be used to guide the rational design and optimization of small molecule or biomimetic PPI inhibitors. PMID:26225450
Full Text Available Increasing evidence suggests that protein-protein interaction is essential in many biological processes including epithelial transport. In this report, we discuss the significance of protein interactions to HCO(3(- secretion in pancreatic duct cells. In pancreatic ducts HCO(3(- secretion is mediated by cystic fibrosis transmembrane conductance regulator (CFTR activated luminal Cl(-/HCO(3(- exchange activity and HCO(3(- absorption is achieved by Na(+-dependent mechanisms including Na(+/H(+ exchanger 3 (NHE3. We found biochemical and functional association between CFTR and NHE3. In addition, protein binding through PDZ modules is needed for this regulatory interaction. CFTR affected NHE3 activities in two ways. Acutely, CFTR augmented the cAMP-dependent inhibition of NHE3. In a chronic mechanism, CFTR increases the luminal expression of Na(+/H(+ exchange in pancreatic duct cells. These findings reveal that protein complexes in the plasma membrane of pancreatic duct cells are highly organized for efficient HCO(3(- secretion.
Murilo S. Alves
Full Text Available Responses to biotic stress in plants lead to dramatic reprogramming of gene expression, favoring stress responses at the expense of normal cellular functions. Transcription factors are master regulators of gene expression at the transcriptional level, and controlling the activity of these factors alters the transcriptome of the plant, leading to metabolic and phenotypic changes in response to stress. The functional analysis of interactions between transcription factors and other proteins is very important for elucidating the role of these transcriptional regulators in different signaling cascades. In this review, we present an overview of protein-protein interactions for the six major families of transcription factors involved in plant defense: basic leucine zipper containing domain proteins (bZIP, amino-acid sequence WRKYGQK (WRKY, myelocytomatosis related proteins (MYC, myeloblastosis related proteins (MYB, APETALA2/ ETHYLENE-RESPONSIVE ELEMENT BINDING FACTORS (AP2/EREBP and no apical meristem (NAM, Arabidopsis transcription activation factor (ATAF, and cup-shaped cotyledon (CUC (NAC. We describe the interaction partners of these transcription factors as molecular responses during pathogen attack and the key components of signal transduction pathways that take place during plant defense responses. These interactions determine the activation or repression of response pathways and are crucial to understanding the regulatory networks that modulate plant defense responses.
Christina M Taylor
Full Text Available Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank. EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite and B. malayi (H. sapiens parasite, which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly
Hong, Jongsuk; Vesperini, Enrico; Sollima, Antonio; McMillan, Stephen L. W.; D'Antona, Franca; D'Ercole, Annibale
We present the results of a survey of N-body simulations aimed at exploring the evolution of compact binaries in multiple-population globular clusters. We show that as a consequence of the initial differences in the structural properties of the first-generation (FG) and the second-generation (SG) populations and the effects of dynamical processes on binary stars, the SG binary fraction decreases more rapidly than that of the FG population. The difference between the FG and SG binary fraction is qualitatively similar to but quantitatively smaller than that found for wider binaries in our previous investigations. The evolution of the radial variation of the binary fraction is driven by the interplay between binary segregation, ionization and ejection. Ionization and ejection counteract in part the effects of mass segregation but for compact binaries the effects of segregation dominate and the inner binary fraction increases during the cluster evolution. We explore the variation of the difference between the FG and the SG binary fraction with the distance from the cluster centre and its dependence on the binary binding energy and cluster structural parameters. The difference between the binary fraction in the FG and the SG populations found in our simulations is consistent with the results of observational studies finding a smaller binary fraction in the SG population.
Bartlett, Madelaine; Thompson, Beth; Brabazon, Holly; Del Gizzi, Robert; Zhang, Thompson; Whipple, Clinton
Protein-protein interactions (PPIs) have widely acknowledged roles in the regulation of development, but few studies have addressed the timing and mechanism of shifting PPIs over evolutionary history. The B-class MADS-box transcription factors, PISTILLATA (PI) and APETALA3 (AP3) are key regulators of floral development. PI-like (PI(L)) and AP3-like (AP3(L)) proteins from a number of plants, including Arabidopsis thaliana (Arabidopsis) and the grass Zea mays (maize), bind DNA as obligate heterodimers. However, a PI(L) protein from the grass relative Joinvillea can bind DNA as a homodimer. To ascertain whether Joinvillea PI(L) homodimerization is an anomaly or indicative of broader trends, we characterized PI(L) dimerization across the Poales and uncovered unexpected evolutionary lability. Both obligate B-class heterodimerization and PI(L) homodimerization have evolved multiple times in the order, by distinct molecular mechanisms. For example, obligate B-class heterodimerization in maize evolved very recently from PI(L) homodimerization. A single amino acid change, fixed during domestication, is sufficient to toggle one maize PI(L) protein between homodimerization and obligate heterodimerization. We detected a signature of positive selection acting on residues preferentially clustered in predicted sites of contact between MADS-box monomers and dimers, and in motifs that mediate MADS PPI specificity in Arabidopsis. Changing one positively selected residue can alter PI(L) dimerization activity. Furthermore, ectopic expression of a Joinvillea PI(L) homodimer in Arabidopsis can homeotically transform sepals into petals. Our results provide a window into the evolutionary remodeling of PPIs, and show that novel interactions have the potential to alter plant form in a context-dependent manner. PMID:26908583
Ryan, Keegan; Nakajima, Miki; Stevenson, David J.
Can a bound pair of similar mass terrestrial planets exist? We are interested here in bodies with a mass ratio of ~ 3:1 or less (so Pluto/Charon or Earth/Moon do not qualify) and we do not regard the absence of any such discoveries in the Kepler data set to be significant since the tidal decay and merger of a close binary is prohibitively fast well inside of 1AU. SPH simulations of equal mass “Earths” were carried out to seek an answer to this question, assuming encounters that were only slightly more energetic than parabolic (zero energy). We were interested in whether the collision or near collision of two similar mass bodies would lead to a binary in which the two bodies remain largely intact, effectively a tidal capture hypothesis though with the tidal distortion being very large. Necessarily, the angular momentum of such an encounter will lead to bodies separated by only a few planetary radii if capture occurs. Consistent with previous work, mostly by Canup, we find that most impacts are disruptive, leading to a dominant mass body surrounded by a disk from which a secondary forms whose mass is small compared to the primary, hence not a binary planet by our adopted definition. However, larger impact parameter “kissing” collisions were found to produce binaries because the dissipation upon first encounter was sufficient to provide a bound orbit that was then rung down by tides to an end state where the planets are only a few planetary radii apart. The long computational times for these simulation make it difficult to fully map the phase space of encounters for which this outcome is likely but the indications are that the probability is not vanishingly small and since planetary encounters are a plausible part of planet formation, we expect binary planets to exist and be a non-negligible fraction of the larger orbital radius exoplanets awaiting discovery.
Hong, Jongsuk; Sollima, Antonio; McMillan, Stephen L W; D'Antona, Franca; D'Ercole, Annibale
The discovery of multiple stellar populations in globular clusters has implications for all the aspects of the study of these stellar systems. In this paper, by means of N-body simulations, we study the evolution of binary stars in multiple-population clusters and explore the implications of the initial differences in the spatial distribution of different stellar populations for the evolution and survival of their binary stars. Our simulations show that initial differences between the spatial distribution of first-generation (FG) and second-generation (SG) stars can leave a fingerprint in the current properties of the binary population. SG binaries are disrupted more efficiently than those of the FG population resulting in a global SG binary fraction smaller than that of the FG. As for surviving binaries, dynamical evolution produces a difference between the SG and the FG binary binding energy distribution with the SG population characterized by a larger fraction of high binding energy (more bound) binaries. ...
Davis Melissa J
Full Text Available Abstract Background Many biological processes are mediated by dynamic interactions between and among proteins. In order to interact, two proteins must co-occur spatially and temporally. As protein-protein interactions (PPIs and subcellular location (SCL are discovered via separate empirical approaches, PPI and SCL annotations are independent and might complement each other in helping us to understand the role of individual proteins in cellular networks. We expect reliable PPI annotations to show that proteins interacting in vivo are co-located in the same cellular compartment. Our goal here is to evaluate the potential of using PPI annotation in determining SCL of proteins in human, mouse, fly and yeast, and to identify and quantify the factors that contribute to this complementarity. Results Using publicly available data, we evaluate the hypothesis that interacting proteins must be co-located within the same subcellular compartment. Based on a large, manually curated PPI dataset, we demonstrate that a substantial proportion of interacting proteins are in fact co-located. We develop an approach to predict the SCL of a protein based on the SCL of its interaction partners, given sufficient confidence in the interaction itself. The frequency of false positive PPIs can be reduced by use of six lines of supporting evidence, three based on type of recorded evidence (empirical approach, multiplicity of databases, and multiplicity of literature citations and three based on type of biological evidence (inferred biological process, domain-domain interactions, and orthology relationships, with biological evidence more-effective than recorded evidence. Our approach performs better than four existing prediction methods in identifying the SCL of membrane proteins, and as well as or better for soluble proteins. Conclusion Understanding cellular systems requires knowledge of the SCL of interacting proteins. We show how PPI data can be used more effectively to
Romina Oliva; Edrisse Chermak; Luigi Cavallo
In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a ...
Bier, David; Bartel, Maria; Sies, Katharina; Halbach, Sebastian; Higuchi, Yusuke; Haranosono, Yu; Brummer, Tilman; Kato, Nobuo; Ottmann, Christian
Small-molecule modulation of protein-protein interactions (PPIs) is one of the most promising new areas in drug discovery. In the vast majority of cases only inhibition or disruption of PPIs is realized, whereas the complementary strategy of targeted stabilization of PPIs is clearly under-represented. Here, we report the example of a semi-synthetic natural product derivative--ISIR-005--that stabilizes the cancer-relevant interaction of the adaptor protein 14-3-3 and Gab2. The crystal structure of ISIR-005 in complex with 14-3-3 and the binding motif of Gab2 comprising two phosphorylation sites (Gab2pS210pT391) showed how the stabilizing molecule binds to the rim-of-the-interface of the protein complex. Only in the direct vicinity of 14-3-3/Gab2pT391 site is a pre-formed pocket occupied by ISIR-005; binding of the Gab2pS210 motif to 14-3-3 does not create an interface pocket suitable for the molecule. Accordingly, ISIR-005 only stabilizes the binding of the Gab2pT391 but not the Gab2pS210 site. This study represents structural and biochemical proof of the druggability of the 14-3-3/Gab2 PPI interface with important implications for the development of PPI stabilizers. PMID:26644359
Rani, Shilpa; Park, Chang Sik; Sreenivasaiah, Pradeep Kumar; Kim, Do Han
In the heart, excitation-contraction (E-C) coupling is mediated by Ca2+ release from sarcoplasmic reticulum (SR) through the interactions of proteins forming the Ca2+ release unit (CRU). Among them, calsequestrin (CSQ) and histidine-rich Ca2+ binding protein (HRC) are known to bind the charged luminal region of triadin (TRN) and thus directly or indirectly regulate ryanodine receptor 2 (RyR2) activity. However, the mechanisms of CSQ and HRC mediated regulation of RyR2 activity through TRN have remained unclear. We first examined the minimal KEKE motif of TRN involved in the interactions with CSQ2, HRC and RyR2 using TRN deletion mutants and in vitro binding assays. The results showed that CSQ2, HRC and RyR2 share the same KEKE motif region on the distal part of TRN (aa 202–231). Second, in vitro binding assays were conducted to examine the Ca2+ dependence of protein-protein interactions (PPI). The results showed that TRN-HRC interaction had a bell-shaped Ca2+ dependence, which peaked at pCa4, whereas TRN-CSQ2 or TRN-RyR2 interaction did not show such Ca2+ dependence pattern. Third, competitive binding was conducted to examine whether CSQ2, HRC, or RyR2 affects the TRN-HRC or TRN-CSQ2 binding at pCa4. Among them, only CSQ2 or RyR2 competitively inhibited TRN-HRC binding, suggesting that HRC can confer functional refractoriness to CRU, which could be beneficial for reloading of Ca2+ into SR at intermediate Ca2+ concentrations. PMID:26674963
Juettemann, Thomas; Gerloff, Dietlind L
Binary subcomplexes in proteins database (BISC) is a new protein-protein interaction (PPI) database linking up the two communities most active in their characterization: structural biology and functional genomics researchers. The BISC resource offers users (i) a structural perspective and related information about binary subcomplexes (i.e. physical direct interactions between proteins) that are either structurally characterized or modellable entries in the main functional genomics PPI databases BioGRID, IntAct and HPRD; (ii) selected web services to further investigate the validity of postulated PPI by inspection of their hypothetical modelled interfaces. Among other uses we envision that this resource can help identify possible false positive PPI in current database records. BISC is freely available at http://bisc.cse.ucsc.edu. PMID:21081561
Full Text Available The high-resolution refinement of docked protein-protein complexes can provide valuable structural and mechanistic insight into protein complex formation complementing experiment. Monte Carlo (MC based approaches are frequently applied to sample putative interaction geometries of proteins including also possible conformational changes of the binding partners. In order to explore efficiency improvements of the MC sampling, several enhanced sampling techniques, including temperature or Hamiltonian replica exchange and well-tempered ensemble approaches, have been combined with the MC method and were evaluated on 20 protein complexes using unbound partner structures. The well-tempered ensemble method combined with a 2-dimensional temperature and Hamiltonian replica exchange scheme (WTE-H-REMC was identified as the most efficient search strategy. Comparison with prolonged MC searches indicates that the WTE-H-REMC approach requires approximately 5 times fewer MC steps to identify near native docking geometries compared to conventional MC searches.
Zhang, Zhe; Schindler, Christina E M; Lange, Oliver F; Zacharias, Martin
The high-resolution refinement of docked protein-protein complexes can provide valuable structural and mechanistic insight into protein complex formation complementing experiment. Monte Carlo (MC) based approaches are frequently applied to sample putative interaction geometries of proteins including also possible conformational changes of the binding partners. In order to explore efficiency improvements of the MC sampling, several enhanced sampling techniques, including temperature or Hamiltonian replica exchange and well-tempered ensemble approaches, have been combined with the MC method and were evaluated on 20 protein complexes using unbound partner structures. The well-tempered ensemble method combined with a 2-dimensional temperature and Hamiltonian replica exchange scheme (WTE-H-REMC) was identified as the most efficient search strategy. Comparison with prolonged MC searches indicates that the WTE-H-REMC approach requires approximately 5 times fewer MC steps to identify near native docking geometries compared to conventional MC searches. PMID:26053419
Martell, Jeffrey D; Yamagata, Masahito; Deerinck, Thomas J; Phan, Sébastien; Kwa, Carolyn G; Ellisman, Mark H; Sanes, Joshua R; Ting, Alice Y
Intercellular protein-protein interactions (PPIs) enable communication between cells in diverse biological processes, including cell proliferation, immune responses, infection, and synaptic transmission, but they are challenging to visualize because existing techniques have insufficient sensitivity and/or specificity. Here we report a split horseradish peroxidase (sHRP) as a sensitive and specific tool for the detection of intercellular PPIs. The two sHRP fragments, engineered through screening of 17 cut sites in HRP followed by directed evolution, reconstitute into an active form when driven together by an intercellular PPI, producing bright fluorescence or contrast for electron microscopy. Fusing the sHRP fragments to the proteins neurexin (NRX) and neuroligin (NLG), which bind each other across the synaptic cleft, enabled sensitive visualization of synapses between specific sets of neurons, including two classes of synapses in the mouse visual system. sHRP should be widely applicable to studying mechanisms of communication between a variety of cell types. PMID:27240195
Li, Ye; Zhang, Xianren; Cao, Dapeng
We use a dissipative particle dynamic simulation to investigate the effects of shape complementarity on the protein-protein interactions. By monitoring different kinds of protein shape-complementarity modes, we gave a clear mechanism to reveal the role of the shape complementarity in the protein-protein interactions, i.e., when the two proteins with shape complementarity approach each other, the conformation of lipid chains between two proteins would be restricted significantly. The lipid molecules tend to leave the gap formed by two proteins to maximize the configuration entropy, and therefore yield an effective entropy-induced protein-protein attraction, which enhances the protein aggregation. In short, this work provides an insight into understanding the importance of the shape complementarity in the protein-protein interactions especially for protein aggregation and antibody-antigen complexes. Definitely, the shape complementarity is the third key factor affecting protein aggregation and complex, besides the electrostatic-complementarity and hydrophobic complementarity. PMID:24253561
Cotecchia, Susanna; Stanasila, Laura; Diviani, Dario
The adrenergic receptors are among the best characterized G protein-coupled receptors (GPCRs) and knowledge on this receptor family has provided several important paradigms about GPCR function and regulation. One of the most recent paradigms initially supported by studies on adrenergic receptors is that both βarrestins and G protein-coupled receptors themselves can act as scaffolds binding a variety of proteins and this can result in growing complexity of the receptor-mediated cellular effect...
Simonson Thomas; Noirel Josselin
Abstract Background Protein-protein interactions are central to cellular organization, and must have appeared at an early stage of evolution. To understand better their role, we consider a simple model of protein evolution and determine the effect of an explicit selection for Protein-protein interactions. Results In the model, viable sequences all have the same fitness, following the neutral evolution theory. A very simple, two-dimensional lattice representation of the protein structures is u...
Li, Bohua; Zhao, Lei; Wang, Chong; Guo, Huaizu; Wu, Lan; Zhang, Xunming; Qian, Weizhu; Wang, Hao; Guo, Yajun
Understanding the evolutionary mechanism that acts at the interfaces of protein-protein complexes is a fundamental issue with high interest for delineating the macromolecular complexes and networks responsible for regulation and complexity in biological systems. To investigate whether the evolution of protein-protein interface acts in a similar way as antibody affinity maturation, we incorporated evolutionary information derived from antibody affinity maturation with common simulation techniq...
Wei, Yang; Thyparambil, Aby A.; Latour, Robert A.
While protein-surface interactions have been widely studied, relatively little is understood at this time regarding how protein-surface interaction effects are influenced by protein-protein interactions and how these effects combine with the internal stability of a protein to influence its adsorbed-state structure and bioactivity. The objectives of this study were to develop a method to study these combined effects under widely varying protein-protein interaction conditions using hen egg-whit...
Sun Zhirong; Liu Ke; Chen Hu; Zhang Song
Abstract Background Genome sequencing projects generate massive amounts of sequence data but there are still many proteins whose functions remain unknown. The availability of large scale protein-protein interaction data sets makes it possible to develop new function prediction methods based on protein-protein interaction (PPI) networks. Although several existing methods combine multiple information resources, there is no study that integrates protein domain information and PPI networks to pre...
Farid Amir-Ghiasvand; Abbas Nowzari-Dalini; Vida Momenzadeh
To date, few tools for aligning protein-protein interaction networks have been suggested. These tools typically find conserved interaction patterns using various local or global alignment algorithms. However, the improvement of the speed, scalability, simplification, and accuracy of network alignment tools is still the target of new researches. In this paper, we introduce Pin-Align, a new tool for local alignment of protein-protein interaction networks. Pin-Align accuracy is tested on protein...
Iyer, Lavanya K.; Moorthy, Balakrishnan S.; Topp, Elizabeth M.
Protein structure and local environment in lyophilized formulations were probed using high-resolution solid-state photolytic crosslinking with mass spectrometric analysis (ssPC-MS). In order to characterize structure and microenvironment, protein-protein, protein-excipient and protein-water interactions in lyophilized powders were identified. Myoglobin (Mb) was derivatized in solution with the heterobifunctional probe succinimidyl 4,4’-azipentanoate (SDA) and the structural integrity of the l...
Eishingdrelo, Haifeng; Cai, Jidong; Weissensee, Paul; Sharma, Praveen; Tocci, Michael J; Wright, Paul S
We have developed a novel cell-based protein-protein interaction assay method. The method relies on conversion of an inactive permuted luciferase containing a Tobacco Etch Virus protease (TEV) cleavage sequence fused onto protein (A) to an active luciferase upon interaction and cleavage by another protein (B) fused with the TEV protease. We demonstrate assay applicability for ligand-induced protein-protein interactions including G-protein coupled receptors, receptor tyrosine kinases and nucle...
Vincent Vagenende; Han, Alvin X.; Han B Pek; Bernard L W Loo
Although the nature of solvent-protein interactions is generally weak and non-specific, addition of cosolvents such as denaturants and osmolytes strengthens protein-protein interactions for some proteins, whereas it weakens protein-protein interactions for others. This is exemplified by the puzzling observation that addition of glycerol oppositely affects the association constants of two antibodies, D1.3 and D44.1, with lysozyme. To resolve this conundrum, we develop a methodology based on th...
Li, Ye; Zhang, Xianren; Cao, Dapeng
We use a dissipative particle dynamic simulation to investigate the effects of shape complementarity on the protein-protein interactions. By monitoring different kinds of protein shape-complementarity modes, we gave a clear mechanism to reveal the role of the shape complementarity in the protein-protein interactions, i.e., when the two proteins with shape complementarity approach each other, the conformation of lipid chains between two proteins would be restricted significantly. The lipid mol...
Full Text Available Abstract Background Protein-protein docking is a challenging computational problem in functional genomics, particularly when one or both proteins undergo conformational change(s upon binding. The major challenge is to define a scoring function soft enough to tolerate these changes and specific enough to distinguish between near-native and "misdocked" conformations. Results Using a linear programming (LP technique, we developed two types of potentials: (i Side chain-based and (ii Heavy atom-based. To achieve this we considered a set of 161 transient complexes and generated a large set of putative docked structures (decoys, based on a shape complementarity criterion, for each complex. The demand on the potentials was to yield, for the native (correctly docked structure, a potential energy lower than those of any of the non-native (misdocked structures. We show that the heavy atom-based potentials were able to comply with this requirement but not the side chain-based one. Thus, despite the smaller number of parameters, the capability of heavy atom-based potentials to discriminate between native and "misdocked" conformations is improved relative to those of the side chain-based potentials. The performance of the atom-based potentials was evaluated by a jackknife test on a set of 50 complexes taken from the Zdock2.3 decoys set. Conclusions Our results show that, using the LP approach, we were able to train our potentials using a dataset of transient complexes only the newly developed potentials outperform three other known potentials in this test.
Swapna Lakshmipuram S
Full Text Available Abstract Background The correlation of genetic distances between pairs of protein sequence alignments has been used to infer protein-protein interactions. It has been suggested that these correlations are based on the signal of co-evolution between interacting proteins. However, although mutations in different proteins associated with maintaining an interaction clearly occur (particularly in binding interfaces and neighbourhoods, many other factors contribute to correlated rates of sequence evolution. Proteins in the same genome are usually linked by shared evolutionary history and so it would be expected that there would be topological similarities in their phylogenetic trees, whether they are interacting or not. For this reason the underlying species tree is often corrected for. Moreover processes such as expression level, are known to effect evolutionary rates. However, it has been argued that the correlated rates of evolution used to predict protein interaction explicitly includes shared evolutionary history; here we test this hypothesis. Results In order to identify the evolutionary mechanisms giving rise to the correlations between interaction proteins, we use phylogenetic methods to distinguish similarities in tree topologies from similarities in genetic distances. We use a range of datasets of interacting and non-interacting proteins from Saccharomyces cerevisiae. We find that the signal of correlated evolution between interacting proteins is predominantly a result of shared evolutionary rates, rather than similarities in tree topology, independent of evolutionary divergence. Conclusions Since interacting proteins do not have tree topologies that are more similar than the control group of non-interacting proteins, it is likely that coevolution does not contribute much to, if any, of the observed correlations.
Verhoef, Lisette G G C; Mattioli, Michela; Ricci, Fernanda; Li, Yao-Cheng; Wade, Mark
Cell-based assays of protein-protein interactions (PPIs) using split reporter proteins can be used to identify PPI agonists and antagonists. Generally, such assays measure one PPI at a time, and thus counterscreens for on-target activity must be run in parallel or at a subsequent stage; this increases both the cost and time during screening. Split luciferase systems offer advantages over those that use split fluorescent proteins (FPs). This is since split luciferase offers a greater signal:noise ratio and, unlike split FPs, the PPI can be reversed upon small molecule treatment. While multiplexed PPI assays using luciferase have been reported, they suffer from low signal:noise and require fairly complex spectral deconvolution during analysis. Furthermore, the luciferase enzymes used are large, which limits the range of PPIs that can be interrogated due to steric hindrance from the split luciferase fragments. Here, we report a multiplexed PPI assay based on split luciferases from Photinus pyralis (firefly luciferase, FLUC) and the deep-sea shrimp, Oplophorus gracilirostris (NanoLuc, NLUC). Specifically, we show that the binding of the p53 tumor suppressor to its two major negative regulators, MDM2 and MDM4, can be simultaneously measured within the same sample, without the requirement for complex filters or deconvolution. We provide chemical and genetic validation of this system using MDM2-targeted small molecules and mutagenesis, respectively. Combined with the superior signal:noise and smaller size of split NanoLuc, this multiplexed PPI assay format can be exploited to study the induction or disruption of pairwise interactions that are prominent in many cell signaling pathways. PMID:26646257
Synthesis, characterization and thermal studies of binary and/or mixed ligand complexes of Cd(II), Cu(II), Ni(II) and Co(III) based on 2-(Hydroxybenzylidene) thiosemicarbazone: DNA binding affinity of binary Cu(II) complex
Saif, M.; Mashaly, Mahmoud M.; Eid, Mohamed F.; Fouad, R.
A new series of metal complexes of Cd(II), Cu(II), Ni(II) and Co(III) with Schiff base ligand, H2L, 2-(Hydroxybenzylidene) thiosemicarbazone were synthesized. The mixed ligand complexes were prepared by using glycine (Gly), 2-aminopyridine (2-Ampy) and 1,10-phenanthroline (Phen) as secondary ligands. The structure of these complexes was identified and confirmed by elemental analysis, molar conductivity, UV-Vis, FT-IR and 1H NMR spectroscopy and magnetic moment measurements as well as TG-DSC technique. The discussions of the prepared complexes indicate that the ligand behaves as a monoanionic tridentate ligand through ONS donor sites. Thermal studies suggested a mechanism for the degradation of the metal complexes as a function of temperature supporting the chelation modes and showed the possibility of obtaining new complexes pyrolytically in the solid state which cannot be synthesized from the solution. The absorption studies support that the binary Cu(II) complex exhibits a significant binding affinity to HS-DNA through intercalative mode.
Luo, Lin; King, Nathan P; Yeo, Jeremy C; Jones, Alun; Stow, Jennifer L
The study of protein-protein interactions is a major theme in biological disciplines. Pull-down or affinity-precipitation assays using GST fusion proteins have become one of the most common and valuable approaches to identify novel binding partners for proteins of interest (bait). Non-specific binding of prey proteins to the beads or to GST itself, however, inevitably complicates and impedes subsequent analysis of pull-down results. A variety of measures, each with inherent advantages and limitations, can minimise the extent of the background. This technical brief details and tests a modification of established GST pull-down protocols. By specifically eluting only the bait (minus the GST tag) and the associated non-specific binding proteins with a simple, single-step protease cleavage, a cleaner platform for downstream protein identification with MS is established. We present a proof of concept for this method, as evidenced by a GST pull-down/MS case study of the small guanosine triphosphatase (GTPase) Rab31 in which: (i) sensitivity was enhanced, (ii) a reduced level of background was observed, (iii) distinguishability of non-specific contaminant proteins from genuine binders was improved and (iv) a putative new protein-protein interaction was discovered. Our protease cleavage step is readily applicable to all further affinity tag pull-downs. PMID:24259493
Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identifi cation of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifi es and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At fi rst, IRO is applied in a binary classifi er to determine whether sentences contain a relation or not. Then, IRO is taken to guide PPI extraction by building sentence dependency parse tree. Comprehensive and quantitative evaluations and detailed analyses are used to demonstrate the signifi cant performance of IRO on relation sentences classifi cation and PPI extraction. Our PPI extraction method yielded a recall of around 80% and 90% and an F1 of around 54% and 66% on corpora of AIMed and Bioinfer, respectively, which are superior to most existing extraction methods. Copyright © 2014 Inderscience Enterprises Ltd.
Protein-protein interactions are essential biological reactions occurring at inter- and intra-cellular levels. The analysis of their mechanism is generally required in order link to understand their various cellular functions. Bioluminescence resonance energy transfer (BRET), which is based on an enzymatic activity of luciferase, is a useful tool for investigating protein-protein interactions in live cells. The combination of the BRET system and biomolecular fluorescence complementation (BiFC) would provide us a better understanding of the hetero-oligomeric structural states of protein complexes. In this review, we discuss the application of BRET to the protein-protein interactions of mitochondrial-associated proteins and discuss its physiological relevance. PMID:27493852
Becirovic, Elvir; Böhm, Sybille; Nguyen, Ong N. P.; Riedmayr, Lisa M.; Hammelmann, Verena; Schön, Christian; Butz, Elisabeth S.; Wahl-Schott, Christian; Biel, Martin; Michalakis, Stylianos
Fluorescence resonance energy transfer (FRET) is a powerful method for the detection and quantification of stationary and dynamic protein-protein interactions. Technical limitations have hampered systematic in vivo FRET experiments to study protein-protein interactions in their native environment. Here, we describe a rapid and robust protocol that combines adeno-associated virus (AAV) vector-mediated in vivo delivery of genetically encoded FRET partners with ex vivo FRET measurements. The method was established on acutely isolated outer segments of murine rod and cone photoreceptors and relies on the high co-transduction efficiency of retinal photoreceptors by co-delivered AAV vectors. The procedure can be used for the systematic analysis of protein-protein interactions of wild type or mutant outer segment proteins in their native environment. Conclusively, our protocol can help to characterize the physiological and pathophysiological relevance of photoreceptor specific proteins and, in principle, should also be transferable to other cell types. PMID:27516733
Cau, Ylenia; Fiorillo, Annarita; Mori, Mattia; Ilari, Andrea; Botta, Maurizo; Lalle, Marco
Giardiasis is a gastrointestinal diarrheal illness caused by the protozoan parasite Giardia duodenalis, which affects annually over 200 million people worldwide. The limited antigiardial drug arsenal and the emergence of clinical cases refractory to standard treatments dictate the need for new chemotherapeutics. The 14-3-3 family of regulatory proteins, extensively involved in protein-protein interactions (PPIs) with pSer/pThr clients, represents a highly promising target. Despite homology with human counterparts, the single 14-3-3 of G. duodenalis (g14-3-3) is characterized by a constitutive phosphorylation in a region critical for target binding, thus affecting the function and the conformation of g14-3-3/clients interaction. However, to approach the design of specific small molecule modulators of g14-3-3 PPIs, structural elucidations are required. Here, we present a detailed computational and crystallographic study exploring the implications of g14-3-3 phosphorylation on protein structure and target binding. Self-Guided Langevin Dynamics and classical molecular dynamics simulations show that phosphorylation affects locally and globally g14-3-3 conformation, inducing a structural rearrangement more suitable for target binding. Profitable features for g14-3-3/clients interaction were highlighted using a hydrophobicity-based descriptor to characterize g14-3-3 client peptides. Finally, the X-ray structure of g14-3-3 in complex with a mode-1 prototype phosphopeptide was solved and combined with structure-based simulations to identify molecular features relevant for clients binding to g14-3-3. The data presented herein provide a further and structural understanding of g14-3-3 features and set the basis for drug design studies. PMID:26551337
van Dieck, Jan; Schmid, Volker; Heindl, Dieter; Dziadek, Sebastian; Schraeml, Michael; Gerg, Michael; Massoner, Petra; Engel, Alfred M; Tiefenthaler, Georg; Vural, Serhat; Stritt, Simon; Tetzlaff, Fabian; Soukupova, Monika; Kopetzki, Erhard; Bossenmaier, Birgit; Thomas, Marlene; Klein, Christian; Mertens, Alfred; Heller, Astrid; Tacke, Michael
Investigation of protein-protein interactions (PPIs) and protein phosphorylation in clinical tissue samples can offer valuable information about the activation status and function of proteins involved in disease progression. However, existing antibody-based methods for phosphorylation detection have been found to lack specificity, and methods developed for examining PPIs in vitro cannot be easily adapted for tissues samples. In this study, we eliminated some of these limitations by developing a specific immunohistochemical staining method that uses "dual binders" (DBs), which are bispecific detection agents consisting of two Fab fragment molecules joined by a flexible linker, to detect PPIs and protein phosphorylation. We engineered DBs by selecting Fab fragments with fast off-rate kinetics, which allowed us to demonstrate that stable target binding was achieved only upon simultaneous, cooperative binding to both epitopes. We show that DBs specifically detect the activated HER2/HER3 complex in formalin-fixed, paraffin-embedded cancer cells and exhibit superior detection specificity for phospho-HER3 compared to the corresponding monoclonal antibody. Overall, the performance of DBs makes them attractive tools for future development for clinical applications. PMID:24529991
Full Text Available Apoptosis and autophagy are distinct biological processes, each driven by a different set of protein-protein interactions, with significant crosstalk via direct interactions among apoptotic and autophagic proteins. To measure the global profile of these interactions, we adapted the Gaussia luciferase protein-fragment complementation assay (GLuc PCA, which monitors binding between proteins fused to complementary fragments of a luciferase reporter. A library encompassing 63 apoptotic and autophagic proteins was constructed for the analysis of ∼3,600 protein-pair combinations. This generated a detailed landscape of the apoptotic and autophagic modules and points of interface between them, identifying 46 previously unknown interactions. One of these interactions, between DAPK2, a Ser/Thr kinase that promotes autophagy, and 14-3-3τ, was further investigated. We mapped the region responsible for 14-3-3τ binding and proved that this interaction inhibits DAPK2 dimerization and activity. This proof of concept underscores the power of the GLuc PCA platform for the discovery of biochemical pathways within the cell death network.
LIU Xiang; WANG Yifei
Proteins are fundamental components of all living cells and the protein-protein interaction plays an important role in vital movement.This paper briefly introduced the original Resonant Recognition Model (RRM),and then modified it by using the wavelet transform to acquire the Modified Resonant Recognition Model (MRRM).The key characteristic of the new model is that it can predict directly the proteinprotein interaction from the primary sequence,and the MRRM is more suitable than the RRM for this prediction.The results of numerical experiments show that the MRRM is effective for predicting the protein-protein interaction.
Full Text Available Protein-protein interactions are important for biochemical processes in biological systems. The 3D structure of the macromolecular complex resulting from the protein-protein association is a very useful source to understand its specific functions. This work focuses on computational study for protein-protein docking, where the individually crystallized structures of interacting proteins are treated as rigid, and the conformational space generated by the two interacting proteins is explored extensively. The energy function consists of intermolecular electrostatic potential, desolvation free energy represented by empirical contact potential, and simple repulsive energy terms. The conformational space is six dimensional, represented by translational vectors and rotational angles formed between two interacting proteins. The conformational sampling is carried out by the search algorithms such as simulated annealing (SA, conformational space annealing (CSA, and CSA combined with SA simulations (combined CSA/SA. Benchmark tests are performed on a set of 18 protein-protein complexes selected from various protein families to examine feasibility of these search methods coupled with the energy function above for protein docking study.
Zhang, Shu-Bo; Tang, Qiang-Rong
Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction. PMID:27117309
Hartmann-Petersen, Rasmus; Gordon, Colin
The commercial availability of instruments, such as Biacore, that are capable of monitoring surface plasmon resonance (SPR) has greatly simplified the quantification of protein-protein interactions. Already, this technique has been used for some studies of the ubiquitin-proteasome system. Here we...
Nazar Zaki; Elfadil A. Mohamed; Antonio Mora
The identification and characterization of protein complexes implicated in protein-protein interaction data are crucial to the understanding of the molecular events under normal and abnormal physiological conditions. This paper provides a novel characterization of subcomplexes in protein interaction databases, stressing definition and representation issues, quantification, biological validation, network metrics, motifs, modularity, and gene ontology (GO) terms. The paper introduces the concep...
CAI Lun; XUE Hong; LU Hongchao; ZHAO Yi; ZHU Xiaopeng; BU Dongbo; LING Lunjiang; CHEN Runsheng
Protein-protein interaction is a physical interaction of two proteins in living cells. In budding yeast Saccharomyces cerevisiae, large-scale protein-protein interaction data have been obtained through high-throughput yeast two-hybrid systems (Y2H) and protein complex purification techniques based on mass-spectrometry. Here, we collect 11855 interactions between total 2617 proteins. Through seriate genome-wide mRNA expression data, similarity between two genes could be measured. Protein complex data can also be obtained publicly and can be translated to pair relationship that any two proteins can only exist in the same complex or not. Analysis of protein complex data, protein-protein interaction data and mRNA expression data can elucidate correlations between them. The results show that proteins that have interactions or similar expression patterns have a higher possibility to be in the same protein complex than randomized selected proteins, and proteins which have interactions and similar expression patterns are even more possible to exist in the same protein complex. The work indicates that comprehensive integration and analysis of public large-scale bioinformatical data, such as protein complex data, protein-protein interaction data and mRNA expression data, may help to uncover their relationships and common biological information underlying these data. The strategies described here may help to integrate and analyze other functional genomic and proteomic data, such as gene expression profiling, protein-localization mapping and large-scale phenotypic data, both in yeast and in other organisms.
Huisman, I.H.; Prádanos, P.; Hernández, A.
It was studied how protein-protein and protein-membrane interactions influence the filtration performance during the ultrafiltration of protein solutions over polymeric membranes. This was done by measuring flux, streaming potential, and protein transmission during filtration of bovine serum albumin
Full Text Available Abstract Background Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual amino-acids are systematically mutated to alanine and changes in free energy of binding (ΔΔG measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots" at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition. Results We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which ΔΔG ≥ 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%. Conclusion We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been
Full Text Available Creatine kinase (CK; EC 184.108.40.206 is related to several skin diseases such as psoriasis and dermatomyositis. CK is important in skin energy homeostasis because it catalyzes the reversible transfer of a phosphoryl group from MgATP to creatine. In this study, we predicted CK binding proteins via the use of bioinformatic tools such as protein-protein interaction (PPI mappings and suggest the putative hub proteins for CK interactions. We obtained 123 proteins for brain type CK and 85 proteins for muscle type CK in the interaction networks. Among them, several hub proteins such as NFKB1, FHL2, MYOC, and ASB9 were predicted. Determination of the binding factors of CK can further promote our understanding of the roles of CK in physiological conditions.
Full Text Available Large-scale analyses of protein-protein interactions based on coarse-grain molecular docking simulations and binding site predictions resulting from evolutionary sequence analysis, are possible and realizable on hundreds of proteins with variate structures and interfaces. We demonstrated this on the 168 proteins of the Mintseris Benchmark 2.0. On the one hand, we evaluated the quality of the interaction signal and the contribution of docking information compared to evolutionary information showing that the combination of the two improves partner identification. On the other hand, since protein interactions usually occur in crowded environments with several competing partners, we realized a thorough analysis of the interactions of proteins with true partners but also with non-partners to evaluate whether proteins in the environment, competing with the true partner, affect its identification. We found three populations of proteins: strongly competing, never competing, and interacting with different levels of strength. Populations and levels of strength are numerically characterized and provide a signature for the behavior of a protein in the crowded environment. We showed that partner identification, to some extent, does not depend on the competing partners present in the environment, that certain biochemical classes of proteins are intrinsically easier to analyze than others, and that small proteins are not more promiscuous than large ones. Our approach brings to light that the knowledge of the binding site can be used to reduce the high computational cost of docking simulations with no consequence in the quality of the results, demonstrating the possibility to apply coarse-grain docking to datasets made of thousands of proteins. Comparison with all available large-scale analyses aimed to partner predictions is realized. We release the complete decoys set issued by coarse-grain docking simulations of both true and false interacting partners, and
Full Text Available Protein-protein interactions forming dominant signalling events are providing ever-growing platforms for the development of novel Biologic tools for controlling cell growth. Casein Kinase 1 α (CK1α forms a genetic and physical interaction with the murine double minute chromosome 2 (MDM2 oncoprotein resulting in degradation of the p53 tumour suppressor. Pharmacological inhibition of CK1 increases p53 protein level and induces cell death, whilst small interfering RNA-mediated depletion of CK1α stabilizes p53 and induces growth arrest. We mapped the dominant protein-protein interface that stabilizes the MDM2 and CK1α complex in order to determine whether a peptide derived from the core CK1α-MDM2 interface form novel Biologics that can be used to probe the contribution of the CK1-MDM2 protein-protein interaction to p53 activation and cell viability. Overlapping peptides derived from CK1α were screened for dominant MDM2 binding sites using (i ELISA with recombinant MDM2; (ii cell lysate pull-down towards endogenous MDM2; (iii MDM2-CK1α complex-based competition ELISA; and (iv MDM2-mediated ubiquitination. One dominant peptide, peptide 35 was bioactive in all four assays and its transfection induced cell death/growth arrest in a p53-independent manner. Ectopic expression of flag-tagged peptide 35 induced a novel ubiquitin and NEDD8 modification of CK1α, providing one of the first examples whereby NEDDylation of a protein kinase can be induced. These data identify an MDM2 binding motif in CK1α which when isolated as a small peptide can (i function as a dominant negative inhibitor of the CK1α-MDM2 interface, (ii be used as a tool to study NEDDylation of CK1α, and (iii reduce cell growth. Further, this approach provides a technological blueprint, complementing siRNA and chemical biology approaches, by exploiting protein-protein interactions in order to develop Biologics to manipulate novel types of signalling pathways such as cross
Mostafa H Ahmed
Full Text Available BACKGROUND: There is a great interest in understanding and exploiting protein-protein associations as new routes for treating human disease. However, these associations are difficult to structurally characterize or model although the number of X-ray structures for protein-protein complexes is expanding. One feature of these complexes that has received little attention is the role of water molecules in the interfacial region. METHODOLOGY: A data set of 4741 water molecules abstracted from 179 high-resolution (≤ 2.30 Å X-ray crystal structures of protein-protein complexes was analyzed with a suite of modeling tools based on the HINT forcefield and hydrogen-bonding geometry. A metric termed Relevance was used to classify the general roles of the water molecules. RESULTS: The water molecules were found to be involved in: a (bridging interactions with both proteins (21%, b favorable interactions with only one protein (53%, and c no interactions with either protein (26%. This trend is shown to be independent of the crystallographic resolution. Interactions with residue backbones are consistent for all classes and account for 21.5% of all interactions. Interactions with polar residues are significantly more common for the first group and interactions with non-polar residues dominate the last group. Waters interacting with both proteins stabilize on average the proteins' interaction (-0.46 kcal mol(-1, but the overall average contribution of a single water to the protein-protein interaction energy is unfavorable (+0.03 kcal mol(-1. Analysis of the waters without favorable interactions with either protein suggests that this is a conserved phenomenon: 42% of these waters have SASA ≤ 10 Å(2 and are thus largely buried, and 69% of these are within predominantly hydrophobic environments or "hydrophobic bubbles". Such water molecules may have an important biological purpose in mediating protein-protein interactions.
The objectives of this report are to: Develop novel site-specific protein labeling chemistries for assaying protein-protein interactions in MR-1; and development of a novel optical acquisition and data analysis method for characterizing protein-protein interactions in MR-1 model systems. Our work on analyzing protein-protein interactions in MR-1 is divided in four areas: (1) expression and labeling of MR-1 proteins; (2) general scheme for site-specific fluorescent labeling of expressed proteins; (3) methodology development for monitoring protein-protein interactions; and (4) study of protein-protein interactions in MR-1. In this final report, we give an account for our advances in all areas.
Hain, Adelaide U P; Miller, Alexia S; Levitskaya, Jelena; Bosch, Jürgen
New therapies are needed against malaria, a parasitic infection caused by Plasmodium falciparum, as drug resistance emerges against the current treatment, artemisinin. We previously characterized the Atg8-Atg3 protein-protein interaction (PPI), which is essential for autophagy and parasite survival. Herein we illustrate the use of virtual library screening to selectively block the PPI in the parasite without inhibiting the homologous interaction in humans by targeting the A-loop of PfAtg8. This A-loop is important for Atg3 binding in Plasmodium, but is absent from the human Atg8 homologues. In this proof-of-concept study, we demonstrate a shift in lipidation state of PfAtg8 and inhibition of P. falciparum growth in both blood- and liver-stage cultures upon drug treatment. Our results illustrate how in silico screening and structure-aided drug design against a PPI can be used to identify new hits for drug development. Additionally, as we targeted a region of Atg8 that is conserved within apicomplexans, we predict that our small molecule will have cross-reactivity against other disease-causing apicomplexans, such as Toxoplasma, Cryptosporidium, Theileria, Neospora, Eimeria, and Babesia. PMID:26748931
Keiding, Hans; Peleg, Bezalel
Abstract A social choice rule (SCR) is a collection of social choice correspondences, one for each agenda. An effectivity rule is a collection of effectivity functions, one for each agenda. We prove that every monotonic and superadditive effectivity rule is the effectivity rule of some SCR. A SCR...... is binary if it is rationalized by an acyclic binary relation. The foregoing result motivates our definition of a binary effectivity rule as the effectivity rule of some binary SCR. A binary SCR is regular if it satisfies unanimity, monotonicity, and independence of infeasible alternatives. A binary...... effectivity rule is regular if it is the effectivity rule of some regular binary SCR. We characterize completely the family of regular binary effectivity rules. Quite surprisingly, intrinsically defined von Neumann-Morgenstern solutions play an important role in this characterization...
Southworth, John; Clausen, J.V.
Stars: fundamental parameters - Stars : binaries : eclipsing - Stars: Binaries: spectroscopic - Open clusters and ass. : general Udgivelsesdato: 5 August......Stars: fundamental parameters - Stars : binaries : eclipsing - Stars: Binaries: spectroscopic - Open clusters and ass. : general Udgivelsesdato: 5 August...
Podgornaia, Anna I; Casino, Patricia; Marina, Alberto; Laub, Michael T
Two-component signal transduction systems typically involve a sensor histidine kinase that specifically phosphorylates a single, cognate response regulator. This protein-protein interaction relies on molecular recognition via a small set of residues in each protein. To better understand how these residues determine the specificity of kinase-substrate interactions, we rationally rewired the interaction interface of a Thermotoga maritima two-component system, HK853-RR468, to match that found in a different two-component system, Escherichia coli PhoR-PhoB. The rewired proteins interacted robustly with each other, but no longer interacted with the parent proteins. Analysis of the crystal structures of the wild-type and mutant protein complexes and a systematic mutagenesis study reveal how individual mutations contribute to the rewiring of interaction specificity. Our approach and conclusions have implications for studies of other protein-protein interactions and protein evolution and for the design of novel protein interfaces. PMID:23954504
Sternberg, M J; Aloy, P; Gabb, H A; Jackson, R M; Moont, G; Querol, E; Aviles, F X
A computational system is described that predicts the structure of protein/protein and protein/DNA complexes starting from unbound coordinate sets. The approach is (i) a global search with rigid-body docking for complexes with shape complementarity and favourable electrostatics; (ii) use of distance constraints from experimental (or predicted) knowledge of critical residues; (iii) use of pair potential to screen docked complexes and (iv) refinement and further screening by protein-side chain optimisation and interfacial energy minimisation. The system has been applied to model ten protein/protein and eight protein-repressor/DNA (steps i to iii only) complexes. In general a few complexes, one of which is close to the true structure, can be generated. PMID:9783224
Hoggard, Logan R; Zhang, Yongqiang; Zhang, Min; Panic, Vanja; Wisniewski, John A; Ji, Haitao
Selective inhibition of α-helix-mediated protein-protein interactions (PPIs) with small organic molecules provides great potential for the discovery of chemical probes and therapeutic agents. Protein Data Bank data mining using the HippDB database indicated that (1) the side chains of hydrophobic projecting hot spots at positions i, i + 3, and i + 7 of an α-helix had few orientations when interacting with the second protein and (2) the hot spot pockets of PPI complexes had different sizes, shapes, and chemical groups when interacting with the same hydrophobic projecting hot spots of α-helix. On the basis of these observations, a small organic molecule, 4'-fluoro-N-phenyl-[1,1'-biphenyl]-3-carboxamide, was designed as a generic scaffold that itself directly mimics the binding mode of the side chains of hydrophobic projecting hot spots at positions i, i + 3, and i + 7 of an α-helix. Convenient decoration of this generic scaffold led to the selective disruption of α-helix-mediated PPIs. A series of small-molecule inhibitors selective for β-catenin/B-cell lymphoma 9 (BCL9) over β-catenin/cadherin PPIs was designed and synthesized. The binding mode of new inhibitors was characterized by site-directed mutagenesis and structure-activity relationship studies. This new class of inhibitors can selectively disrupt β-catenin/BCL9 over β-catenin/cadherin PPIs, suppress the transactivation of canonical Wnt signaling, downregulate the expression of Wnt target genes, and inhibit the growth of Wnt/β-catenin-dependent cancer cells. PMID:26352795
Thomas, T; Shah, N; Klinge, C M; Faaland, C A; Adihkarakunnathu, S; Gallo, M A; Thomas, T J
We investigated the effects of polyamine biosynthesis inhibition on the estrogenic signaling pathway of MCF-7 breast cancer cells using a protein-protein interaction system. Estrogen receptor (ER) linked to glutathione-S-transferase (GST) was used to examine the effects of two polyamine biosynthesis inhibitors, difluoromethylornithine (DFMO) and CGP 48664. ER was specifically associated with a 45 kDa protein in control cells. In cells treated with estradiol, nine proteins were associated with ER. Cells treated with polyamine biosynthesis inhibitors in the absence of estradiol retained the binding of their ER with a 45 kDa protein and the ER also showed low-affinity interactions with a number of cellular proteins; however, these associations were decreased by the presence of estradiol and the inhibitors. When samples from the estradiol+DFMO treatment group were incubated with spermidine prior to GST-ER pull down assay, an increased association of several proteins with ER was detected. The intensity of the ER-associated 45 kDa protein increased by 10-fold in the presence of 1000 microM spermidine. These results indicate a specific role for spermidine in ER association of proteins. Western blot analysis of samples eluted from GST-ER showed the presence of chicken ovalbumin upstream promoter-transcription factor, an orphan nuclear receptor, and the endogenous full-length ER. These results show that multiple proteins associate with ER and that the binding of some of these proteins is highly sensitive to intracellular polyamine concentrations. Overall, our results indicate the importance of the polyamine pathway in the gene regulatory function of estradiol in breast cancer cells. PMID:10194516
Cedano Juan; Querol Enrique; Bonàs Sílvia; Gómez Antonio; Delicado Pedro; Amela Isaac
Abstract Background Is it possible to identify what the best solution of a docking program is? The usual answer to this question is the highest score solution, but interactions between proteins are dynamic processes, and many times the interaction regions are wide enough to permit protein-protein interactions with different orientations and/or interaction energies. In some cases, as in a multimeric protein complex, several interaction regions are possible among the monomers. These dynamic pro...
Ding Don; Tong Weida; Fang Hong; Ye Yanbin; Su Zhenqiang; Guo Li; Liu Zhichao; Martha Venkata-Swamy; Xu Xiaowei
Abstract Background Protein-protein interactions (PPIs) are a critical component for many underlying biological processes. A PPI network can provide insight into the mechanisms of these processes, as well as the relationships among different proteins and toxicants that are potentially involved in the processes. There are many PPI databases publicly available, each with a specific focus. The challenge is how to effectively combine their contents to generate a robust and biologically relevant P...
Jianhua eYang; Kim eOsman; Mudassar eIqbal; Stekel, Dov J; Zewei eLuo; Armstrong, Susan J; Franklin, F. Chris H.
Following successful completion of the Brassica rapa sequencing project, the next step is to investigate functions of individual genes/proteins. For Arabidopsis thaliana, large amounts of protein-protein interaction (PPI) data are available from the major PPI databases. It is known that Brassica crop species are closely related to A. thaliana. This provides an opportunity to infer the B. rapa interactome using PPI data available from A. thaliana. In this paper, we present an inferred B. rapa ...
Lei Yang; Xianglong Tang
Cliques (maximal complete subnets) in protein-protein interaction (PPI) network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based m...
Gillis, Jesse; Ballouz, Sara; Pavlidis, Paul
Networks constructed from aggregated protein-protein interaction data are commonplace in biology. But the studies these data are derived from were conducted with their own hypotheses and foci. Focusing on data from budding yeast present in BioGRID, we determine that many of the downstream signals present in network data are significantly impacted by biases in the original data. We determine the degree to which selection bias in favor of biologically interesting bait proteins goes down with st...
Jiang Jonathan Q; Wu Maoying
Abstract Background Proteins that interact in vivo tend to reside within the same or "adjacent" subcellular compartments. This observation provides opportunities to reveal protein subcellular localization in the context of the protein-protein interaction (PPI) network. However, so far, only a few efforts based on heuristic rules have been made in this regard. Results We systematically and quantitatively validate the hypothesis that proteins physically interacting with each other probably shar...
Sun, Xiaoyun; Hong, Pengyu; Kulkarni, Meghana; Kwon, Young; Perrimon, Norbert
Background: Tandem affinity purification coupled with mass-spectrometry (TAP/MS) analysis is a popular method for the identification of novel endogenous protein-protein interactions (PPIs) in large-scale. Computational analysis of TAP/MS data is a critical step, particularly for high-throughput datasets, yet it remains challenging due to the noisy nature of TAP/MS data. Results: We investigated several major TAP/MS data analysis methods for identifying PPIs, and developed an advanced method, ...
Xu Feng; Zhao Chen; Li Yuhua; Li Jiang; Deng Youping; Shi Tieliu
Abstract Background Currently, several systems have been proposed to classify viruses and indicate the relationships between different ones, though each system has its limitations because of the complexity of viral origins and their rapid evolution rate. We hereby propose a new method to explore the relationships between different viruses. Method A new method, which is based on the virus-host protein-protein interaction network, is proposed in this paper to categorize viruses. The distances b...
Kaleeckal Mathew, Oommen; Sowdhamini, Ramanathan
Protein-protein interactions are essential for the basic biological machinery of the cell. This is important for processes like protein synthesis, enzyme kinetics, molecular assembly and signal transduction. A high number of macromolecular structural complexes are known due to recent advances in structure determination techniques. Therefore, it is of interest to develop an interactive tool to objectively analyze large protein complexes. Hence, we describe the development and utility of a web ...
Claudio Peri; Giulia Morra; Giorgio Colombo
Understanding protein-protein interactions (PPI) at the molecular level is a fundamental task in the design of new drugs, the prediction of protein function and the clarification of the mechanisms of (dis)regulation of biochemical pathways. In this study, we use a novel computational approach to investigate the energetics of aminoacid networks located on the surface of proteins, isolated and in complex with their respective partners. Interestingly, the analysis of individual proteins identifi...
Panstruga Ralph; Lahaye Thomas; Bhat Riyaz A
Abstract Non-invasive fluorophore-based protein interaction assays like fluorescence resonance energy transfer (FRET) and bimolecular fluorescence complementation (BiFC, also referred to as "split YFP") have been proven invaluable tools to study protein-protein interactions in living cells. Both methods are now frequently used in the plant sciences and are likely to develop into standard techniques for the identification, verification and in-depth analysis of polypeptide interactions. In this...
Bosque, Gabriel; Folch-Fortuny, Abel; Picó, Jesús; Ferrer, Alberto; Santiago, F Elena
Background One of the central interests of Virology is the identification of host factors that contribute to virus infection. Despite tremendous efforts, the list of factors identified remains limited. With omics techniques, the focus has changed from identifying and thoroughly characterizing individual host factors to the simultaneous analysis of thousands of interactions, framing them on the context of protein-protein interaction networks and of transcriptional regulatory networks. This new...
G Jack Peterson; Steve Pressé; Peterson, Kristin S.; Dill, Ken A.
We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the t...
Zhao Yiqiang; Mooney Sean D
Abstract Background Based on the distinguishing properties of protein-protein interaction networks such as power-law degree distribution and modularity structure, several stochastic models for the evolution of these networks have been purposed, motivated by the idea that a validated model should reproduce similar topological properties of the empirical network. However, being able to capture topological properties does not necessarily mean it correctly reproduces how networks emerge and evolv...
Jillian L Blatti; Joris Beld; Behnke, Craig A; Michael Mendez; Mayfield, Stephen P; Burkart, Michael D.
Microalgae are a promising feedstock for renewable fuels, and algal metabolic engineering can lead to crop improvement, thus accelerating the development of commercially viable biodiesel production from algae biomass. We demonstrate that protein-protein interactions between the fatty acid acyl carrier protein (ACP) and thioesterase (TE) govern fatty acid hydrolysis within the algal chloroplast. Using green microalga Chlamydomonas reinhardtii (Cr) as a model, a structural simulation of docking...
Guangyu Cui; Yu Chen; De-Shuang Huang; Kyungsook Han
Biological processes are often performed by a group of proteins rather than by individual proteins, and proteins in a same biological group form a densely connected subgraph in a protein-protein interaction network. Therefore, finding a densely connected subgraph provides useful information to predict the function or protein complex of uncharacterized proteins in the highly connected subgraph. We have developed an efficient algorithm and program for finding cliques and near-cliques in a prote...
Tan Kai; Kim Jongkwang
Abstract Background Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in multiple species and in both normal and diseased cells. As the size of the interaction dataset increases, powerful computational methods are required in order to effectively distil network models from large-scale interactome data. Results We present an algorithm, miPALM (Module Inference by Parametric Local Modularity), to infer protein complexes in a protein-pr...
Ru Shen; Xiaosheng Wang; Chittibabu Guda
Background. The molecular profiles exhibited in different cancer types are very different; hence, discovering distinct functional modules associated with specific cancer types is very important to understand the distinct functions associated with them. Protein-protein interaction networks carry vital information about molecular interactions in cellular systems, and identification of functional modules (subgraphs) in these networks is one of the most important applications of biological networ...
Xiaomin Wang; Zhengzhi Wang; Jun Ye
With the availability of more and more genome-scale protein-protein interaction (PPI) networks, research interests gradually shift to Systematic Analysis on these large data sets. A key topic is to predict protein complexes in PPI networks by identifying clusters that are densely connected within themselves but sparsely connected with the rest of the network. In this paper, we present a new topology-based algorithm, HKC, to detect protein complexes in genome-scale PPI networks. HKC mainly use...
Best, Christoph; Zimmer, Ralf; Apostolakis, Joannis
We discuss probabilistic methods for predicting protein functions from protein-protein interaction networks. Previous work based on Markov Randon Fields is extended and compared to a general machine-learning theoretic approach. Using actual protein interaction networks for yeast from the MIPS database and GO-SLIM function assignments, we compare the predictions of the different probabilistic methods and of a standard support vector machine. It turns out that, with the currently available netw...
The docking problem is to start with unbound conformations for the components of a complex, and computationally model a near-native structure for the complex. This thesis describes work in developing computer programs to tackle both protein/protein and protein/DNA docking. Empirical pair potential functions are generated from datasets of residue/residue interactions. A scoring function was parameterised and then used to screen possible complexes, generated by the global search computer algori...
Bourquard, Thomas; Bernauer, Julie; Azé, Jérôme; Poupon, Anne
A protein-protein docking procedure traditionally consists in two successive tasks: a search algorithm generates a large number of candidate conformations mimicking the complex existing in vivo between two proteins, and a scoring function is used to rank them in order to extract a native-like one. We have already shown that using Voronoi constructions and a well chosen set of parameters, an accurate scoring function could be designed and optimized. However to be able to perform large-scale in...
Protein-domains play an important role in mediating protein-protein interactions. Furthermore, the same domain-pairs mediate different interactions in different contexts and in various organisms, and therefore domain-pairs are considered as the building blocks of interactome networks. Here we extend these principles to the host-virus interface and find the domain-pairs that potentially mediate human-herpesvirus interactions. Notably, we find that the same domain-pairs used by other organisms ...
Lim, Dajeong; Kim, Nam-Kuk; Park, Hye-Sun; Lee, Seung-Hwan; Cho, Yong-Min; Oh, Sung Jong; Kim, Tae-Hun; Kim, Heebal
Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The present study systemically analyzed genes associated with bovine marbling score and identified their relationships. The candidate nodes were obtained using MedScan text-mining tools and linked by protein-protein intera...
Ahmed, Mostafa H; Habtemariam, Mesay; Safo, Martin K; Scarsdale, J Neel; Spyrakis, Francesca; Cozzini, Pietro; Mozzarelli, Andrea; Kellogg, Glen E
The importance of protein-protein interactions (PPIs) is becoming increasingly appreciated, as these interactions lie at the core of virtually every biological process. Small molecule modulators that target PPIs are under exploration as new therapies. One of the greatest obstacles faced in crystallographically determining the 3D structures of proteins is coaxing the proteins to form "artificial" PPIs that lead to uniform crystals suitable for X-ray diffraction. This work compares interactions formed naturally, i.e., "biological", with those artificially formed under crystallization conditions or "non-biological". In particular, a detailed analysis of water molecules at the interfaces of high-resolution (≤2.30 Å) X-ray crystal structures of protein-protein complexes, where 140 are biological protein-protein complex structures and 112 include non-biological protein-protein interfaces, was carried out using modeling tools based on the HINT forcefield. Surprisingly few and relatively subtle differences were observed between the two types of interfaces: (i) non-biological interfaces are more polar than biological interfaces, yet there is better organized hydrogen bonding at the latter; (ii) biological associations rely more on water-mediated interactions with backbone atoms compared to non-biological associations; (iii) aromatic/planar residues play a larger role in biological associations with respect to water, and (iv) Lys has a particularly large role at non-biological interfaces. A support vector machines (SVMs) classifier using descriptors from this study was devised that was able to correctly classify 84% of the two interface types. PMID:24076743
Full Text Available Abstract Background Protein-protein interaction data used in the creation or prediction of molecular networks is usually obtained from large scale or high-throughput experiments. This experimental data is liable to contain a large number of spurious interactions. Hence, there is a need to validate the interactions and filter out the incorrect data before using them in prediction studies. Results In this study, we use a combination of 3 genomic features – structurally known interacting Pfam domains, Gene Ontology annotations and sequence homology – as a means to assign reliability to the protein-protein interactions in Saccharomyces cerevisiae determined by high-throughput experiments. Using Bayesian network approaches, we show that protein-protein interactions from high-throughput data supported by one or more genomic features have a higher likelihood ratio and hence are more likely to be real interactions. Our method has a high sensitivity (90% and good specificity (63%. We show that 56% of the interactions from high-throughput experiments in Saccharomyces cerevisiae have high reliability. We use the method to estimate the number of true interactions in the high-throughput protein-protein interaction data sets in Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens to be 27%, 18% and 68% respectively. Our results are available for searching and downloading at http://helix.protein.osaka-u.ac.jp/htp/. Conclusion A combination of genomic features that include sequence, structure and annotation information is a good predictor of true interactions in large and noisy high-throughput data sets. The method has a very high sensitivity and good specificity and can be used to assign a likelihood ratio, corresponding to the reliability, to each interaction.
Nahálková, Jarmila; Tomkinson, Birgitta
Tripeptidyl-peptidase II (TPPII) is an aminopeptidase with suggested regulatory effects on cell cycle, apoptosis and senescence. A protein-protein interaction study revealed that TPPII physically interacts with the tumor suppressor MYBBP1A and the cell cycle regulator protein CDK2. Mutual protein-protein interaction was detected between MYBBP1A and CDK2 as well. In situ Proximity Ligation Assay (PLA) using HEK293 cells overexpressing TPPII forming highly enzymatically active oligomeric complexes showed that the cytoplasmic interaction frequency of TPPII with MYBBP1A increased with the protein expression of TPPII and using serum-free cell growth conditions. A specific reversible inhibitor of TPPII, butabindide, suppressed the cytoplasmic interactions of TPPII and MYBBP1A both in control HEK293 and the cells overexpressing murine TPPII. The interaction of MYBBP1A with CDK2 was confirmed by in situ PLA in two different mammalian cell lines. Functional link between TPPII and MYBBP1A has been verified by gene expression study during anoikis, where overexpression of TPP II decreased mRNA expression level of MYBBP1A at the cell detachment conditions. All three interacting proteins TPPII, MYBBP1A and CDK2 have been previously implicated in the research for development of tumor-suppressing agents. This is the first report presenting mutual protein-protein interaction network of these proteins. PMID:25303791
Full Text Available Viroporins are members of a rapidly growing family of channel-forming small polypeptides found in viruses. The present review will be focused on recent structural and protein-protein interaction information involving two viroporins found in enveloped viruses that target the respiratory tract; (i the envelope protein in coronaviruses and (ii the small hydrophobic protein in paramyxoviruses. Deletion of these two viroporins leads to viral attenuation in vivo, whereas data from cell culture shows involvement in the regulation of stress and inflammation. The channel activity and structure of some representative members of these viroporins have been recently characterized in some detail. In addition, searches for protein-protein interactions using yeast-two hybrid techniques have shed light on possible functional roles for their exposed cytoplasmic domains. A deeper analysis of these interactions should not only provide a more complete overview of the multiple functions of these viroporins, but also suggest novel strategies that target protein-protein interactions as much needed antivirals. These should complement current efforts to block viroporin channel activity.
Full Text Available Abstract Background With the development of genome-sequencing technologies, protein sequences are readily obtained by translating the measured mRNAs. Therefore predicting protein-protein interactions from the sequences is of great demand. The reason lies in the fact that identifying protein-protein interactions is becoming a bottleneck for eventually understanding the functions of proteins, especially for those organisms barely characterized. Although a few methods have been proposed, the converse problem, if the features used extract sufficient and unbiased information from protein sequences, is almost untouched. Results In this study, we interrogate this problem theoretically by an optimization scheme. Motivated by the theoretical investigation, we find novel encoding methods for both protein sequences and protein pairs. Our new methods exploit sufficiently the information of protein sequences and reduce artificial bias and computational cost. Thus, it significantly outperforms the available methods regarding sensitivity, specificity, precision, and recall with cross-validation evaluation and reaches ~80% and ~90% accuracy in Escherichia coli and Saccharomyces cerevisiae respectively. Our findings here hold important implication for other sequence-based prediction tasks because representation of biological sequence is always the first step in computational biology. Conclusions By considering the converse problem, we propose new representation methods for both protein sequences and protein pairs. The results show that our method significantly improves the accuracy of protein-protein interaction predictions.
Full Text Available Protein-protein interactions are important layers of regulation in all kingdoms of life. Identification and characterization of these interactions is one challenging task of the post-genomic era and crucial for understanding of molecular processes within a cell. Several methods have been successfully employed during the past decades to identify protein-protein interactions in bacteria, but most of them include tedious and time-consuming manipulations of DNA. In contrast, the MultiSite Gateway system is a fast tool for transfer of multiple DNA fragments between plasmids enabling simultaneous and site directed cloning of up to four fragments into one construct. Here we developed a new set of Gateway vectors including custom made entry vectors and modular Destination vectors for studying protein-protein interactions via Fluorescence Resonance Energy Transfer (FRET, Bacterial two Hybrid (B2H and split Gaussia luciferase (Gluc, as well as for fusions with SNAP-tag and HaloTag for dual-color super-resolution microscopy. As proof of principle, we characterized the interaction between the Salmonella effector SipA and its chaperone InvB via split Gluc and B2H approach. The suitability for FRET analysis as well as functionality of fusions with SNAP- and HaloTag could be demonstrated by studying the transient interaction between chemotaxis response regulator CheY and its phosphatase CheZ.
Thanigaimani Rajarathinam; Yen-Han Lin
The underlying principle governing the natural phenomena of life is one of the critical issues receiving due importance in recent years. A key feature of the scale-free architecture is the vitality of the most connected nodes (hubs). The major objective of this article was to analyze the protein-protein and metabolic interaction networks of Drosophila melanogaster by considering the architectural patterns and the consequence of removal of hubs on the topological parameter of the two interaction systems. Analysis showed that both interaction networks follow a scale-free model, establishing the fact that most real world networks,from varied situations, conform to the small world pattern. The average path length showed a two-fold and a three-fold increase (changing from 9.42 to 20.93 and from 5.29 to 17.75, respectively) for the protein-protein and metabolic interaction networks, respectively, due to the deletion of hubs. On the contrary, the arbitrary elimination of nodes did not show any remarkable disparity in the topological parameter of the protein-protein and metabolic interaction networks (average path length: 9.42±0.02 and 5.27±0.01, respectively). This aberrant behavior for the two cases underscores the significance of the most linked nodes to the natural topology of the networks.
Full Text Available Abstract Background Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in multiple species and in both normal and diseased cells. As the size of the interaction dataset increases, powerful computational methods are required in order to effectively distil network models from large-scale interactome data. Results We present an algorithm, miPALM (Module Inference by Parametric Local Modularity, to infer protein complexes in a protein-protein interaction network. The algorithm uses a novel graph theoretic measure, parametric local modularity, to identify highly connected sub-networks as candidate protein complexes. Using gold standard sets of protein complexes and protein function and localization annotations, we show our algorithm achieved an overall improvement over previous algorithms in terms of precision, recall, and biological relevance of the predicted complexes. We applied our algorithm to predict and characterize a set of 138 novel protein complexes in S. cerevisiae. Conclusions miPALM is a novel algorithm for detecting protein complexes from large protein-protein interaction networks with improved accuracy than previous methods. The software is implemented in Matlab and is freely available at http://www.medicine.uiowa.edu/Labs/tan/software.html.
Estruch, Sara B.; Fisher, Simon E.
Assays based on Bioluminescence Resonance Energy Transfer (BRET) provide a sensitive and reliable means to monitor protein-protein interactions in live cells. BRET is the non-radiative transfer of energy from a 'donor' luciferase enzyme to an 'acceptor' fluorescent protein. In the most common configuration of this assay, the donor is Renilla reniformis luciferase and the acceptor is Yellow Fluorescent Protein (YFP). Because the efficiency of energy transfer is strongly distance-dependent, observation of the BRET phenomenon requires that the donor and acceptor be in close proximity. To test for an interaction between two proteins of interest in cultured mammalian cells, one protein is expressed as a fusion with luciferase and the second as a fusion with YFP. An interaction between the two proteins of interest may bring the donor and acceptor sufficiently close for energy transfer to occur. Compared to other techniques for investigating protein-protein interactions, the BRET assay is sensitive, requires little hands-on time and few reagents, and is able to detect interactions which are weak, transient, or dependent on the biochemical environment found within a live cell. It is therefore an ideal approach for confirming putative interactions suggested by yeast two-hybrid or mass spectrometry proteomics studies, and in addition it is well-suited for mapping interacting regions, assessing the effect of post-translational modifications on protein-protein interactions, and evaluating the impact of mutations identified in patient DNA. PMID:24893771
Dhole, Kaustubh; Singh, Gurdeep; Pai, Priyadarshini P; Mondal, Sukanta
Protein-protein interactions are of central importance for virtually every process in a living cell. Information about the interaction sites in proteins improves our understanding of disease mechanisms and can provide the basis for new therapeutic approaches. Since a multitude of unique residue-residue contacts facilitate the interactions, protein-protein interaction sites prediction has become one of the most important and challenging problems of computational biology. Although much progress in this field has been reported, this problem is yet to be satisfactorily solved. Here, a novel method (LORIS: L1-regularized LOgistic Regression based protein-protein Interaction Sites predictor) is proposed, that identifies interaction residues, using sequence features and is implemented via the L1-logreg classifier. Results show that LORIS is not only quite effective, but also, performs better than existing state-of-the art methods. LORIS, available as standalone package, can be useful for facilitating drug-design and targeted mutation related studies, which require a deeper knowledge of protein interactions sites. PMID:24486250
M Teplova; L Malinina; J Darnell; J Song; M Lu; R Abagyan; K Musunuru; A Teplov; S Burley; et al.
Nova onconeural antigens are neuron-specific RNA-binding proteins implicated in paraneoplastic opsoclonus-myoclonus-ataxia (POMA) syndrome. Nova harbors three K-homology (KH) motifs implicated in alternate splicing regulation of genes involved in inhibitory synaptic transmission. We report the crystal structure of the first two KH domains (KH1/2) of Nova-1 bound to an in vitro selected RNA hairpin, containing a UCAG-UCAC high-affinity binding site. Sequence-specific intermolecular contacts in the complex involve KH1 and the second UCAC repeat, with the RNA scaffold buttressed by interactions between repeats. Whereas the canonical RNA-binding surface of KH2 in the above complex engages in protein-protein interactions in the crystalline state, the individual KH2 domain can sequence-specifically target the UCAC RNA element in solution. The observed antiparallel alignment of KH1 and KH2 domains in the crystal structure of the complex generates a scaffold that could facilitate target pre-mRNA looping on Nova binding, thereby potentially explaining Nova's functional role in splicing regulation.
Prsa, Andrej; Matijevic, Gal; Latkovic, Olivera; Vilardell, Francesc; Wils, Patrick
PHOEBE (PHysics Of Eclipsing BinariEs) is a modeling package for eclipsing binary stars, built on top of the widely used WD program (Wilson & Devinney 1971). This introductory paper overviews most important scientific extensions (incorporating observational spectra of eclipsing binaries into the solution-seeking process, extracting individual temperatures from observed color indices, main-sequence constraining and proper treatment of the reddening), numerical innovations (suggested improvements to WD's Differential Corrections method, the new Nelder & Mead's downhill Simplex method) and technical aspects (back-end scripter structure, graphical user interface). While PHOEBE retains 100% WD compatibility, its add-ons are a powerful way to enhance WD by encompassing even more physics and solution reliability.
Kaur, Kawaljit; Chatterjee, Srirupa; De Guzman, Roberto N
Many Gram-negative pathogens, such as Shigella and Salmonella, assemble the type III secretion system (T3SS) to inject virulence proteins directly into eukaryotic cells to initiate infectious diseases. The needle apparatus of the T3SS consists of a base, an extracellular needle, a tip protein complex, and a translocon. The atomic structure of the assembled tip complex and the translocon is unknown. Here, we show by NMR paramagnetic relaxation enhancement (PRE) that the mixed α-β domain at the distal region of the Shigella and Salmonella tip proteins interacts with the N-terminal ectodomain of their major translocon proteins. Our results reveal the binding surfaces involved in the tip-translocon protein-protein interaction and provide insights about the assembly of the needle apparatus of the T3SS. PMID:26749041
Full Text Available Phosphate-binding protein(s was found in the inner mitochondrial membrane of calf heart by Sephadex G-200 and G-25 gel filtration. The binding activity was inhibited by N-ethylmaleimide and competed by a large amount of cold phosphate. The amount of phosphate bound to the fraction was 29 nmoles per mg of protein. Affinity chromatography with phosphate-bound Sepharose 4B confirmed the presence of phosphate-binding protein(s in the active fraction of mitochondrial membrane fractionated by gel filtration.
Nandy, Subir Kumar; Jouhten, Paula; Nielsen, Jens
BACKGROUND: Several protein-protein interaction studies have been performed for the yeast Saccharomyces cerevisiae using different high-throughput experimental techniques. All these results are collected in the BioGRID database and the SGD database provide detailed annotation of the different...... proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. RESULTS: Here we describe an annotated reconstruction of the protein-protein interactions around four key nutrient-sensing and...... metabolic regulatory signal transduction pathways (STP) operating in Saccharomyces cerevisiae. The reconstructed STP network includes a full protein-protein interaction network including the key nodes Snf1, Tor1, Hog1 and Pka1. The network includes a total of 623 structural open reading frames (ORFs) and...
路雅静; 宫夏霓; 孟斐; 杨予涛; 徐志卿
Objective To get insight into the molecular mechanisms of signaling and trafficking of galanin receptor 2 ( GalR2) , and to investigate the interaction between human galanin receptor 2 (hCalR2) and cytoplasmic adapter proteins. Methods Yeast two-hybrid method was used to find which proteins interact with the C terminal of hGalR2. Then yeast co-transformation system and co-immunoprecipitation were applied to confirm the protein-protein interaction. Results Cyste-ine-rich PDZ-binding protein ( CRIFT) was found interact with the C terminal of hGalR2. The protein-protein interaction was confirmed by yeast co-transformation system and co-immunoprecipitation. Conclusion CRIFT interacts with GalR2 and this protein-protein interaction may be involved in trafficking and signaling of GalR2.%目的 通过寻找与人甘丙肽2型受体(hGalR2)C端相互作用的蛋白,以进一步探讨hGalR2转运和信号传导机制.方法 利用酵母双杂交实验寻找可以与hGalR2 C端相互作用的蛋白,并通过酵母双转验证和免疫共沉淀实验验证受体和目标蛋白之间的相互作用.结果 酵母双杂交方法结合免疫共沉淀实验发现和证实hGalR2与蛋白Cysteine-rich PDZ-binding protein(CRIPT)之间存在相互作用.结论 CRIPT可以与hGalR2结合而发生相互作用并可能因此参与hGalR2的转运或信号传导.
Dong, Aiping; Zhou, Lan; Zhang, Xing; Stickel, Shawn; Roberts, Richard J.; Cheng, Xiaodong
We have determined the structure of a mutant (Q237W) of HhaI DNA methyltransferase, complexed with the methyl-donor product AdoHcy. The Q237W mutant proteins were crystallized in the monoclinic space group C2 with two molecules in the crystallographic asymmetric unit. Protein-protein interface calculations in the crystal lattices suggest that the dimer interface has the specific characteristics for homodimer protein-protein interactions, while the two active sites are spatially...
Nielsen Jens; Jouhten Paula; Nandy Subir K
Abstract Background Several protein-protein interaction studies have been performed for the yeast Saccharomyces cerevisiae using different high-throughput experimental techniques. All these results are collected in the BioGRID database and the SGD database provide detailed annotation of the different proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. Results Here we des...