Weighted edge based clustering to identify protein complexes in protein–protein interaction networks incorporating gene expression profile

Protein complex detection from protein–protein interaction (PPI) network has received a lot of focus in recent years. A number of methods identify protein complexes as dense sub-graphs using network information while several other methods detect protein complexes based on topological information. While the methods based on identifying dense sub-graphs are more effective in identifying protein complexes, not all protein complexes have high density. Moreover, existing methods focus more on static PPI networks and usually overlook the dynamic nature of protein complexes. Here, we propose a new method, Weighted Edge based Clustering (WEC), to identify protein complexes based on the weight of the edge between two interacting proteins, where the weight is defined by the edge clustering coefficient and the gene expression correlation between the interacting proteins. Our WEC method is capable of detecting highly inter-connected and co-expressed protein complexes. The experimental results of WEC on three real life data shows that our method can detect protein complexes effectively in comparison with other highly cited existing methods.Availability: The WEC tool is available at http://agnigarh.tezu.ernet.in/~rosy8/shared.html.     

A shotgun approach for the identification of platinum–protein complexes

A shotgun approach including peptide-based OFFGEL-isoelectric focusing (IEF) fractionation has been developed with the aim of improving the identification of platinum-binding proteins in biological samples. The method is based on a filter-aided sample preparation (FASP) tryptic digestion under denaturing and reducing conditions of cisplatin–, oxaliplatin–, and carboplatin–protein complexes, followed by OFFGEL-IEF separation of the peptides. Any risk of platinum loss is minimized throughout the procedure due to the removal of the reagents used after each stage of the FASP method and the absence of thiol-based reagents in the focusing buffer employed in the IEF separation. The platinum–peptide complexes stability after the FASP digestion and the IEF separation was confirmed by size exclusion chromatography-inductively coupled plasma-mass spectrometry (SEC-ICP-MS). The suitability of peptide-based OFFGEL-IEF fractionation for reducing the sample complexity for further nano-liquid chromatography-electrospray ionization-tandem mass spectrometry (nLC-ESI-MS/MS) analysis has been demonstrated, allowing the detection of platinum-containing peptides, with significantly lower abundance and ionization efficiency than unmodified peptides. nLC-MS/MS analysis of selected OFFGEL-IEF fractions from tryptic digests with different complexity degrees: standard human serum albumin (HSA), a mixture of five proteins (albumin, transferrin, carbonic anhydrase, myoglobin, and cytochrome-c) and human blood serum allowed the identification of several platinum–peptides from cisplatin–HSA. Cisplatin-binding sites in HSA were elucidated from the MS/MS spectra and assessed considering the protein three-dimensional structure. Most of the potential superficial binding sites available on HSA were identified for all the samples, including a biologically relevant cisplatin-cross-link of two protein domains, demonstrating the capabilities of the methodology.

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Graphical Abstract Graphical abstract shows the several steps involved in the identification of platinum-protein complexes: FASP digestion of proteins, peptide fractionation by OFFGEL-IEF and identification of Pt-complexes by nLC-ESIMS/MS

     

Development of non-denaturing off-gel isoelectric focusing for the separation of uranium–protein complexes in fish

An off-gel non-denaturing isoelectric focusing (IEF) method was developed to separate uranium–biomolecule complexes from biological samples as a first step in a multidimensional metalloproteomic approach. Analysis of a synthetic uranium–bovine serum albumin complex demonstrated the focusing ability of the liquid-phase IEF method and the preservation of most of the uranium–protein interactions. The developed method was applied to gill cytosol prepared from zebrafish (Danio rerio) exposed to depleted uranium. The results were compared in terms of resolution, recovery, and protein identities with those obtained by in-gel IEF using an immobilized pH gradient gel strip.     

Forces mediating protein–protein interactions: a computational study of p53 “approaching” MDM2

The protein MDM2 forms a complex with the tumor suppressing protein p53 and targets it for proteolysis in order to down-regulate p53 in normal cells. Inhibition of this interaction is of therapeutic importance. Molecular dynamics simulations of the association between p53 and MDM2 have revealed mutual modulation of the two surfaces. Analysis of the simulations of the two species approaching each other in solution shows how long range electrostatics steers these two proteins together. The net electrostatics is controlled largely by a few cationic residues that surround the MDM2 binding site. There is an overall separation in electrostatics of MDM2 and p53 that are mutually complementary and drive association. Upon close approach, there is significant energetic strain as the charges are occluded from water (desolvated). However, the complexation is driven by packing interactions that lead to highly favorable van der Waals interactions. Although the complementarity of the electrostatics of the two surfaces is essential for the two partners to form a complex, steric collisions of Y100 and short ranged van der Waals interactions of F19, W23, L26 of p53 determine the final steps of native complex formation. The electrostatics seem to be evolutionarily conserved, including variations in both partners.     

Capillary electrophoresis methods for the determination of covalent polyphenol–protein complexes

The bioactivities and bioavailability of plant polyphenols including proanthocyanidins and other catechin derivatives may be affected by covalent reaction between polyphenol and proteins. Both processing conditions and gastrointestinal conditions may promote formation of covalent complexes for polyphenol-rich foods and beverages such as wine. Little is known about covalent reactions between proteins and tannin, because suitable methods for quantitating covalent complexes have not been developed. We established capillary electrophoresis methods that can be used to distinguish free protein from covalently bound protein-polyphenol complexes and to monitor polyphenol oxidation products. The methods are developed using the model protein bovine serum albumin and the representative polyphenol (-)epigallocatechin gallate. By pairing capillaries with different diameters with appropriate alkaline borate buffers, we are able to optimize resolution of either the protein-polyphenol complexes or the polyphenol oxidation products. This analytical method, coupled with purification of the covalent complexes by diethylaminoethyl cellulose chromatography, should facilitate characterization of covalent complexes in polyphenol-rich foods and beverages such as wine.     

Empirical estimation of the energetic contribution of individual interface residues in structures of protein–protein complexes

We report a simple algorithm to scan interfaces in protein–protein complexes for identifying binding ‘hot spots’. The change in side-chain solvent accessible area (ΔASA) of interface residues has been related to change in binding energy due to mutating interface residues to Ala (ΔΔG _X → ALA) based on two criteria—hydrogen bonding across the interface and location in the interface core—both of which are major determinants in specific, high-affinity binding. These relationships are used to predict the energetic contribution of individual interface residues. The predictions are tested against 462 experimental X → ALA mutations from 28 interfaces with an average unsigned error of 1.04 kcal/mol. More than 80% of interface hot spots (with experimental ΔΔG ≥ 2 kcal/mol) could be identified as being energetically important. From the experimental values, Asp, Lys, Tyr and Trp are found to contribute most of the binding energy, burying >45 Å² on average. The method described here would be useful to understand and interfere with protein interactions by assessing the energetic importance of individual interface residues. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Capillary electrophoresis methods for the determination of covalent polyphenol–protein complexes

The bioactivities and bioavailability of plant polyphenols including proanthocyanidins and other catechin derivatives may be affected by covalent reaction between polyphenol and proteins. Both processing conditions and gastrointestinal conditions may promote formation of covalent complexes for polyphenol-rich foods and beverages such as wine. Little is known about covalent reactions between proteins and tannin, because suitable methods for quantitating covalent complexes have not been developed. We established capillary electrophoresis methods that can be used to distinguish free protein from covalently bound protein–polyphenol complexes and to monitor polyphenol oxidation products. The methods are developed using the model protein bovine serum albumin and the representative polyphenol (−)epigallocatechin gallate. By pairing capillaries with different diameters with appropriate alkaline borate buffers, we are able to optimize resolution of either the protein–polyphenol complexes or the polyphenol oxidation products. This analytical method, coupled with purification of the covalent complexes by diethylaminoethyl cellulose chromatography, should facilitate characterization of covalent complexes in polyphenol-rich foods and beverages such as wine.     

Computer-aided design and discovery of protein–protein interaction inhibitors as agents for anti-HIV therapy

Protein–protein interactions (PPI) are involved in most of the essential processes that occur in organisms. In recent years, PPI have become the object of increasing attention in drug discovery, particularly for anti-HIV drugs. Although the use of combinations of existing drugs, termed highly active antiretroviral therapy (HAART), has revolutionized the treatment of HIV/AIDS, problems with these agents, such as the rapid emergence of drug-resistant HIV-1 mutants and serious adverse effects, have highlighted the need for further discovery of new drugs and new targets. Numerous investigations have shown that PPI play a key role in the virus’s life cycle and that blocking or modulating them has a significant therapeutic potential. Here we summarize the recent progress in computer-aided design of PPI inhibitors, mainly focusing on the selection of the drug targets (HIV enzymes and virus entry machinery) and the utilization of peptides and small molecules to prevent a variety of protein–protein interactions (viral–viral or viral–host) that play a vital role in the progression of HIV infection.     

Protein function prediction using neighbor relativity in protein–protein interaction network

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called “Neighbor Relativity Coefficient” (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network.     

Prediction of protein–protein complexes using replica exchange with repulsive scaling

The realistic prediction of protein–protein complex structures is import to ultimately model the interaction of all proteins in a cell and for the design of new protein–protein interactions. In principle, molecular dynamics (MD) simulations allow one to follow the association process under realistic conditions including full partner flexibility and surrounding solvent. However, due to the many local binding energy minima at the surface of protein partners, MD simulations are frequently trapped for long times in transient association states. We have designed a replica-exchange based scheme employing different levels of a repulsive biasing between partners in each replica simulation. The bias acts only on intermolecular interactions based on an increase in effective pairwise van der Waals radii (repulsive scaling (RS)-REMD) without affecting interactions within each protein or with the solvent. For a set of five protein test cases (out of six) the RS-REMD technique allowed the sampling of near-native complex structures even when starting from the opposide site with respect to the native binding site for one partner. Using the same start structures and same computational demand regular MD simulations sampled near native complex structures only for one case. The method showed also improved results for the refinement of docked structures in the vicinity of the native binding geometry compared to regular MD refinement.     

Activity-Directed Synthesis of Inhibitors of the p53/hDM2 Protein–Protein Interaction

Protein–protein interactions (PPIs) provide a rich source of potential targets for drug discovery and biomedical science research. However, the identification of structural-diverse starting points for discovery of PPI inhibitors remains a significant challenge. Activity-directed synthesis (ADS), a function-driven discovery approach, was harnessed in the discovery of the p53/hDM2 PPI. Over two rounds of ADS, 346 microscale reactions were performed, with prioritisation on the basis of the activity of the resulting product mixtures. Four distinct and novel series of PPI inhibitors were discovered that, through biophysical characterisation, were shown to have promising ligand efficiencies. It was thus shown that ADS can facilitate ligand discovery for a target that does not have a defined small-molecule binding site, and can provide distinctive starting points for the discovery of PPI inhibitors.     

Study of tungstate–protein interaction in human serum by LC–ICP-MS and MALDI-TOF

Oral administration of sodium tungstate is an effective treatment for type 1 and 2 diabetes in animal models; it does not incur significant side effects, and it may constitute an alternative to insulin. However, the mechanism by which tungstate exerts its observed metabolic effects in vivo is still not completely understood. In this work, serum-containing proteins which bind tungstate have been characterized. Size exclusion chromatography (SEC) coupled to inductively coupled plasma mass spectrometry (ICP-MS) with a Phenomenex Bio-Sep-S 2000 column and 20 mM HEPES and 150 mM NaCl at pH 7.4 as the mobile phase was chosen as the most appropriate methodology to screen for tungsten–protein complexes. When human serum was incubated with tungstate, three analytical peaks were observed, one related to tungstate–albumin binding, one to free tungstate, and one to an unknown protein binding (MW higher than 300 kDa). Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometric analysis of the tungsten-containing fractions collected from SEC–ICP-MS chromatograms, after desalting and preconcentration processes, confirmed the association of tungstate with albumin and the other unknown protein. Figure SEC-ICP-MS // MALDI-TOF     

MOEPGA: A novel method to detect protein complexes in yeast protein–protein interaction networks based on MultiObjective Evolutionary Programming Genetic Algorithm

The identification of protein complexes in protein–protein interaction (PPI) networks has greatly advanced our understanding of biological organisms. Existing computational methods to detect protein complexes are usually based on specific network topological properties of PPI networks. However, due to the inherent complexity of the network structures, the identification of protein complexes may not be fully addressed by using single network topological property. In this study, we propose a novel MultiObjective Evolutionary Programming Genetic Algorithm (MOEPGA) which integrates multiple network topological features to detect biologically meaningful protein complexes. Our approach first systematically analyzes the multiobjective problem in terms of identifying protein complexes from PPI networks, and then constructs the objective function of the iterative algorithm based on three common topological properties of protein complexes from the benchmark dataset, finally we describe our algorithm, which mainly consists of three steps, population initialization, subgraph mutation and subgraph selection operation. To show the utility of our method, we compared MOEPGA with several state-of-the-art algorithms on two yeast PPI datasets. The experiment results demonstrate that the proposed method can not only find more protein complexes but also achieve higher accuracy in terms of fscore. Moreover, our approach can cover a certain number of proteins in the input PPI network in terms of the normalized clustering score. Taken together, our method can serve as a powerful framework to detect protein complexes in yeast PPI networks, thereby facilitating the identification of the underlying biological functions.     

A flow-injection ultrafiltration sampling chemiluminescence system for on-line determination of drug–protein interaction

A flow-injection ultrafiltration sampling chemiluminescence system for on-line determination of cimetidine–bovine serum albumin (BSA) interaction is proposed in this paper. Cimetidine can be oxidized by N-bromosuccinimide (NBS) and sensitized by fluorescein to produce high chemiluminescence emission in basic media. The concentration of cimetidine is linear with the CL intensity in the range 3×10^–7–1×10^–4 mol L^–1 with a detection limit of 1×10^–7 mol L^–1 (3). The drug and protein were mixed in different molar ratios in 0.067 mol L^–1 phosphate buffer, pH 7.4, and incubated at 37 °C in a water bath. The ultrafiltration probe was utilized to sample the mixed solution at a flow rate of 5 µL min^–1. The data obtained by the proposed ultrafiltration flow-injection chemiluminescence method was analyzed with Scrathard analysis and a Klotz plot. The estimated association constant (K) and the number of the binding site (n) on one molecule of BSA by Scrathard analysis and Klotz plot were 3.15×10⁴ L mol^–1 and 0.95, 3.25×10⁴ L mol^–1 and 0.92, respectively. The proposed system proved that flow-injection chemiluminescence analysis coupled with on-line ultrafiltration sampling is a simple and reliable technique for the study of drug–protein interaction.     

Microarray of DNA–protein complexes on poly-3-hydroxybutyrate surface for pathogen detection

A novel strategy was developed for the specific immobilization of DNA probes on poly-3-hydroxybutyrate (PHB) surface by using the substrate-binding domain (SBD) of PHB depolymerase as an active binding motif. To demonstrate whether this method can be used for the detection of clinical pathogens, the pathogen-specific biotin-labeled DNA probes were immobilized via core streptavidin (cSA) fused to the SBD. The pathogen-specific 15-mer oligonucleotide probes were designed for four model pathogens, while the target DNAs were prepared by PCR using universal primers. The complex of pathogen-specific probes and cSA-SBD fusion protein was immobilized on the PHB-coated slide by microspotting. This DNA–protein complex microarray was able to successfully diagnose Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Furthermore, the specific pathogens could be diagnosed in the presence of other microorganisms. Thus, the DNA–protein complex microarray platform technology employing PHB and the SBD reported here can be widely used for the detection of DNA–DNA and DNA–biomolecule interactions without synthetic or chemical modification of biomolecules or solid surface.     

Assessment of high-confidence protein–protein interactome in yeast

The identification of protein–protein interactions (PPIs) and their networks is vitally important to systemically define and understand the roles of proteins in biological systems. In spite of development of numerous experimental systems to detect PPIs and diverse research on assessment of the quality of the obtained data, a consensus – highly reliable, almost complete – interactome of Saccharomyces cerevisiae is not presented yet. In this work, we proposed an unsupervised statistical approach to create a high-confidence yeast PPI network. For this, we assembled databases of interacting protein pairs for yeast and obtained an extremely large PPI dataset which comprises of 135 154 non-redundant interactions between 6191 yeast proteins. A scoring scheme considering eight heterogeneous biological features resulted with a broad score distribution and a highly reliable network consisting of 29 046 physical interactions with scores higher than the threshold value of 0.85, for which sensitivity, specificity and coverage were 86%, 68%, and 72%, respectively. We evaluated our method by comparing it with other scoring schemes and showed that reducing the noise inherent in experimental PPIs via our scoring scheme further increased the accuracy. Current study is expected to increase the efficiency of the methodologies in biological research which make use of protein interaction networks.     

Capillary HPLC–ICP MS mapping of selenocompounds in spots obtained from the 2-D gel electrophoresis of the water-soluble protein fraction of selenized yeast

A method based on ICP collision-cell MS detection in capillary HPLC was developed to gain an insight into the purity and identity of selenium-containing proteins separated by 1-D and 2-D electrophoresis. The bands and spots obtained after the separation of water-soluble proteins in selenized yeast were digested with trypsin prior to chromatography. Selenium could be detected down to the subpicogram level. The method, assisted by information obtained by MALDI TOF MS on the 5000 Da cut-off fraction, permitted the purity of bands and spots to be estimated and the efficiency of tryptic digestion and the quantity of selenium present in individual peptides to be evaluated. Owing to the high sensitivity and the lack of matrix suppression effects, the method provided chromatograms with signal-to-noise ratios of 10–1000 in conditions where the common ES Q–TOF MS detection failed.