Measuring protein-protein interactions

Multiplex measurement of protein-peptide dissociation constants using dialysis and mass spectrometry

We propose a high-throughput method for quantitively measuring hundreds of protein-peptide binding affinities in parallel. In this assay a solution of protein is dialyzed into a buffer containing a pool of potential binding peptides, such that upon equilibration the relative abundance of a peptide species is mathematically related to that peptide's dissociation constant, K_d . We use isobaric multiplexed quantitative proteomics to simultaneously determine the relative abundance, and hence the K_d and its associated error, for an entire peptide library. We apply this technique, which we call PEDAL (Parallel Equilibrium Dialysis for Affinity Learning), to determine accurate K_d 's between a PDZ domain and hundreds of peptides, spanning an affinity range of multiple orders of magnitude in a single experiment. PEDAL is a convenient, fast, and low-cost method for measuring large numbers of protein-peptide affinities in parallel, providing a rare combination of true in-solution binding equilibria with the ability to multiplex. This article is protected by copyright. All rights reserved.

Proximity labeling for investigating protein-protein interactions

The study of protein complexes and protein-protein interactions is of great importance due to their fundamental roles in cellular function. Proximity labeling, often coupled with mass spectrometry, has become a powerful and versatile tool for studying protein-protein interactions by enriching and identifying proteins in the vicinity of a specified protein-of-interest. Here, we describe and compare traditional approaches to investigate protein-protein interactions to current day state-of-the-art proximity labeling methods. We focus on the wide array of proximity labeling strategies and underscore studies using diverse model systems to address numerous biological questions. In addition, we highlight current advances in mass spectrometry-based technology that exhibit promise in improving the depth and breadth of the data acquired in proximity labeling experiments. In all, we show the diversity of proximity labeling strategies and emphasize the broad range of applications and biological inquiries that can be addressed using this technology.

The concept of protein folding/unfolding and its impacts on human health

Proteins have evolved in specific 3D structures and play different functions in cells and determine various reactions and pathways. The newly synthesized amino acid chains once depart ribosome must crumple into three-dimensional structures so can be biologically active. This process of protein that makes a functional molecule is called protein folding. The protein folding is both a biological and a physicochemical process that depends on the sequence of it. In fact, this process occurs more complicated and in some cases and in exposure to some molecules like glucose (glycation), mistaken folding leads to amyloid structures and fatal disorders called conformational diseases. Such conditions are detected by the quality control system of the cell and these abnormal proteins undergo renovation or degradation. This scenario takes place by the chaperones, chaperonins, and Ubiquitin-proteasome complex. Understanding of protein folding mechanisms from different views including experimental and computational approaches has revealed some intermediate ensembles such as molten globule and has been subjected to biophysical and molecular biology attempts to know more about prevalent conformational diseases.

A novel index of protein-protein interface propensity improves interface residue recognition

Background

Protein-protein interface holds important information of protein-protein interactions which play key roles in most biological processes. In the past few years, a lot of efforts have been made to improve interface residue recognition by characterizing protein-protein interfaces and extracting relevant features. However, most previous studies were carried out in a qualitative level, and there are also some inconsistencies between them.

Results

In the present work, to improve interface residue recognition, we built a novel quantitative residue protein-protein interface propensity index (QIPI) and gained a comprehensive picture of protein-protein interface through analyzing protein-protein interfaces on our comprehensive protein-protein interfaces dataset (Astral2.05-40-4506). Furthermore, in order to assess the effect of QIPI in improving the protein-protein interface prediction, we developed an interface residue recognition method SPR (Single domain based Patch Recognition) based on the QIPI. The evaluation results proved that our novel QIPI is able to improve the interface residue recognition.

Conclusions

Through a comprehensive quantitative analysis of protein-protein interface, we constructed a novel quantitative protein-protein interface propensity index (QIPI), which could be easily applied to improve the interface residue recognition and helpful in understanding the protein-protein interface.

Availability

QIPI and SPR are available to non-commercial users at our website: http://www.scbit.org/QIPI/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0351-7) contains supplementary material, which is available to authorized users.

C-terminal unfolding of an amyloidogenic β2-microglobulin fragment: ΔN6β2-microglobulin

OBJECTIVES

A β2-microglobulin (β2m) fragment that lacks the first six amino acids, i.e., ΔN6β2-microglobulin (ΔN6β2m), is an endogenous, proteolytically derived, amyloidogenic fragment of β2m, the precursor protein in Aβ2M amyloidosis (dialysis-related amyloidosis). As reports suggest the importance of C-terminal unfolding for the amyloidogenicity of β2m, in this study we aimed to investigate conformational characteristics of ΔN6β2m related to amyloidogenicity. We also measured the concentration of an amyloidogenic intermediate of β2m with C-terminal unfolding (β2m92-99) in serum samples from 10 patients undergoing hemodialysis (HD).

METHODS

We utilized capillary electrophoretic analysis, surface plasmon resonance and enzyme-linked immunosorbent assay.

RESULTS AND CONCLUSIONS

We confirmed the normal core structure of ΔN6β2m with a commercial monoclonal anti-β2m antibody. In addition, using the specific monoclonal antibody for the C-terminal peptide, i.e. mAb 92-99, we confirmed unfolding in the C-terminal region of ΔN6β2m. On the basis of these findings, we established an ELISA to measure β2m92-99 using ΔN6β2m as a standard molecule in circulation. However, we did not detect β2m92-99 in serum from 10 HD patients, despite the absence of uremic inhibitors in the serum.

in silico identification of protein-protein interactions in Silkworm, Bombyx mori

The Domesticated silkworm, Bombyx mori, an economically important insect has been used as a lepidopteran molecular model next only to Drosophila. Compared to the genomic information in silkworm, the protein-protein interaction data are limited. Therefore experimentally identified PPI maps from five model organisms such as E.coli, C.elegans, D.melanogaster, H. sapiens, S. cerevisiae were used to infer the PPI network of silkworm using the well-recognized Interlog based method. Among the 14623 silkworm proteins, 7736 protein-protein interaction pairs were predicted which include 2700 unique proteins of the silkworms. Using the iPfam interaction domains and the gene expression data, these predictions were validated. In that 625 PPI pairs of predicted network were associated with the iPfam domain-domain interactions and the random network has average of 9. In the gene expression method, the average PCC value of the predicted network and random network was 0.29 and 0.23100±0.00042 respectively. It reveals that the predicted PPI networks of silkworm are highly significant and reliable. This is the first PPI network for the silkworm which will provide a framework for deciphering the cellular processes governing key metabolic pathways in the silkworm, Bombyx mori and available at SilkPPI (http://210.212.197.30/SilkPPI/).

Fluorescence Observables and Enzyme Kinetics in the Investigation of PPI Modulation by Small Molecules: Detection, Mechanistic Insight, and Functional Consequences

The potential of fluorescence-based methods and kinetic analysis in the screening and molecular-scale mechanistic investigation of PPI modulation by small molecules is discussed through several representative examples collected and commented. These experimental approaches take advantage of a variety of observables. Changes in the protein aggregation pattern have been monitored through fluorescence properties such as spectra, intensities (related to quantum yields), time-decays, and anisotropies of intrinsic protein fluorophores, of extrinsic fluorescent tags and, even, of the same small molecules added to modulate PPIs, as well as through bimolecular excited-state processes such as static and collisional quenching, including electron and excitation-energy transfer, or exciton interaction, whose efficiencies are crucially structure dependent. Besides allowing for qualitative and quantitative information on the small-molecule induced PPI modulation, these approaches can take advantage from the sensitivity of fluorescence observables on fine structural details to shed light on the molecular-scale mechanisms of action and their functional consequences. Direct investigation of the latter by kinetic inhibition analysis represents a useful change in perspective whenever PPI are relevant for enzyme activity. Dissociative inhibition, that is, the ability of some small molecules to inhibit enzymes by disrupting their active oligomeric assembly is shortly reviewed.

The origins of the evolutionary signal used to predict protein-protein interactions

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.

Comparison of tertiary structures of proteins in protein-protein complexes with unbound forms suggests prevalence of allostery in signalling proteins

BACKGROUND

Most signalling and regulatory proteins participate in transient protein-protein interactions during biological processes. They usually serve as key regulators of various cellular processes and are often stable in both protein-bound and unbound forms. Availability of high-resolution structures of their unbound and bound forms provides an opportunity to understand the molecular mechanisms involved. In this work, we have addressed the question "What is the nature, extent, location and functional significance of structural changes which are associated with formation of protein-protein complexes?"

RESULTS

A database of 76 non-redundant sets of high resolution 3-D structures of protein-protein complexes, representing diverse functions, and corresponding unbound forms, has been used in this analysis. Structural changes associated with protein-protein complexation have been investigated using structural measures and Protein Blocks description. Our study highlights that significant structural rearrangement occurs on binding at the interface as well as at regions away from the interface to form a highly specific, stable and functional complex. Notably, predominantly unaltered interfaces interact mainly with interfaces undergoing substantial structural alterations, revealing the presence of at least one structural regulatory component in every complex.Interestingly, about one-half of the number of complexes, comprising largely of signalling proteins, show substantial localized structural change at surfaces away from the interface. Normal mode analysis and available information on functions on some of these complexes suggests that many of these changes are allosteric. This change is largely manifest in the proteins whose interfaces are altered upon binding, implicating structural change as the possible trigger of allosteric effect. Although large-scale studies of allostery induced by small-molecule effectors are available in literature, this is, to our knowledge, the first study indicating the prevalence of allostery induced by protein effectors.

CONCLUSIONS

The enrichment of allosteric sites in signalling proteins, whose mutations commonly lead to diseases such as cancer, provides support for the usage of allosteric modulators in combating these diseases.

Roles of residues in the interface of transient protein-protein complexes before complexation

Transient protein-protein interactions play crucial roles in all facets of cellular physiology. Here, using an analysis on known 3-D structures of transient protein-protein complexes, their corresponding uncomplexed forms and energy calculations we seek to understand the roles of protein-protein interfacial residues in the unbound forms. We show that there are conformationally near invariant and evolutionarily conserved interfacial residues which are rigid and they account for ∼65% of the core interface. Interestingly, some of these residues contribute significantly to the stabilization of the interface structure in the uncomplexed form. Such residues have strong energetic basis to perform dual roles of stabilizing the structure of the uncomplexed form as well as the complex once formed while they maintain their rigid nature throughout. This feature is evolutionarily well conserved at both the structural and sequence levels. We believe this analysis has general bearing in the prediction of interfaces and understanding molecular recognition.

An adaptable luminescence resonance energy transfer assay for measuring and screening protein-protein interactions and their inhibition

Protein-protein interactions (PPIs) are central to biological processes and represent an important class of therapeutic targets. Here we show that the interaction between FK506-binding protein 12 fused to green fluorescent protein (GFP-FKBP) and the rapamycin-binding domain of mTor fused to Escherichia coli dihydrofolate reductase (FRB-eDHFR) can be sensitively detected (signal-to-background ratio (S/B)>100) and accurately quantified within an impure cell lysate matrix using a luminescence resonance energy transfer (LRET) assay. Ascomycin-mediated inhibition of GFP-FKBP-rapamycin-FRB-eDHFR complex formation was also detected at high S/B ratio (>80) and Z'-factor (0.89). The method leverages the selective, stable binding of trimethoprim (TMP)-terbium complex conjugates to eDHFR, and time-resolved, background-free detection of the long-lifetime (∼ms) terbium-to-GFP LRET signal that indicates target binding. TMP-eDHFR labeling can be adapted to develop high-throughput screening assays and complementary, quantitative counter-screens for a wide variety of PPI targets with a broad range of affinities that may not be amenable to purification.

Improving accuracy of protein-protein interaction prediction by considering the converse problem for sequence representation

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.

Effect of ionic strength on PNA-DNA hybridization on surfaces and in solution

Peptide nucleic acids (PNAs) are mimics of oligonucleotides containing a neutral peptidelike backbone and are able to bind complementary DNA targets with high affinity and selectivity. In order to investigate the effect of the ionic strength of the buffer solution, hybridization experiments with PNAs as (catcher) probes and DNAs as target oligonucleotides were performed in different salt solutions. Surface plasmon field-enhanced fluorescence spectroscopy was employed for real-time monitoring of DNA hybridizations to surface bound PNA. Probes with three different strand lengths were immobilized by self-assembly on the sensor surface. By introducing Cy5-labeled DNA targets the affinity constants, K(A)=k(on) (association)/k(off) (dissociation), were determined for fully complementary (MM0) as well as for single base mismatched (MM1) duplexes. Furthermore, the thermal stability of each duplex was determined by measuring melting curves in solution which was then compared to the kinetic and affinity parameters determined for the surface hybridization reactions. The results indicate that ions do not play a significant role for the PNA/DNA hybridization kinetics at surfaces. However, changes in the configuration of the PNA/DNA duplex due to the ionic strength variations influence the fluorescence yield drastically.

Molecular and cellular approaches for the detection of protein-protein interactions: latest techniques and current limitations

Homotypic and heterotypic protein interactions are crucial for all levels of cellular function, including architecture, regulation, metabolism, and signaling. Therefore, protein interaction maps represent essential components of post-genomic toolkits needed for understanding biological processes at a systems level. Over the past decade, a wide variety of methods have been developed to detect, analyze, and quantify protein interactions, including surface plasmon resonance spectroscopy, NMR, yeast two-hybrid screens, peptide tagging combined with mass spectrometry and fluorescence-based technologies. Fluorescence techniques range from co-localization of tags, which may be limited by the optical resolution of the microscope, to fluorescence resonance energy transfer-based methods that have molecular resolution and can also report on the dynamics and localization of the interactions within a cell. Proteins interact via highly evolved complementary surfaces with affinities that can vary over many orders of magnitude. Some of the techniques described in this review, such as surface plasmon resonance, provide detailed information on physical properties of these interactions, while others, such as two-hybrid techniques and mass spectrometry, are amenable to high-throughput analysis using robotics. In addition to providing an overview of these methods, this review emphasizes techniques that can be applied to determine interactions involving membrane proteins, including the split ubiquitin system and fluorescence-based technologies for characterizing hits obtained with high-throughput approaches. Mass spectrometry-based methods are covered by a review by Miernyk and Thelen (2008; this issue, pp. 597-609). In addition, we discuss the use of interaction data to construct interaction networks and as the basis for the exciting possibility of using to predict interaction surfaces.

Integrating diverse data for structure determination of macromolecular assemblies

To understand the cell, we need to determine the macromolecular assembly structures, which may consist of tens to hundreds of components. First, we review the varied experimental data that characterize the assemblies at several levels of resolution. We then describe computational methods for generating the structures using these data. To maximize completeness, resolution, accuracy, precision, and efficiency of the structure determination, a computational approach is required that uses spatial information from a variety of experimental methods. We propose such an approach, defined by its three main components: a hierarchical representation of the assembly, a scoring function consisting of spatial restraints derived from experimental data, and an optimization method that generates structures consistent with the data. This approach is illustrated by determining the configuration of the 456 proteins in the nuclear pore complex (NPC) from baker's yeast. With these tools, we are poised to integrate structural information gathered at multiple levels of the biological hierarchy--from atoms to cells--into a common framework.

Kinetics of cholesterol extraction from lipid membranes by methyl-beta-cyclodextrin--a surface plasmon resonance approach

The kinetics of cholesterol extraction from cellular membranes is complex and not yet completely understood. In this paper we have developed an experimental approach to directly monitor the extraction of cholesterol from lipid membranes by using surface plasmon resonance and model lipid systems. Methyl-beta-cyclodextrin was used to selectively remove cholesterol from large unilamellar vesicles of various compositions. The amount of extracted cholesterol is highly dependent on the composition of lipid membrane, i.e. the presence of sphingomyelin drastically reduced and slowed down cholesterol extraction by methyl-beta-cyclodextrin. This was confirmed also in the erythrocyte ghosts system, where more cholesterol was extracted after erythrocytes were treated with sphingomyelinase. We further show that the kinetics of the extraction is mono-exponential for mixtures of 1,2-dioleoyl-sn-glycero-3-phosphocholine and cholesterol. The kinetics is complex for ternary lipid mixtures composed of 1,2-dioleoyl-sn-glycero-3-phosphocholine, bovine brain sphingomyelin and cholesterol. Our results indicate that the complex kinetics observed in experiments with cells may be the consequence of lateral segregation of lipids in cell plasma membrane.

A functional single-molecule binding assay via force spectroscopy

Protein-ligand interactions, including protein-protein interactions, are ubiquitously essential in biological processes and also have important applications in biotechnology. A wide range of methodologies have been developed for quantitative analysis of protein-ligand interactions. However, most of them do not report direct functional/structural consequence of ligand binding. Instead they only detect the change of physical properties, such as fluorescence and refractive index, because of the colocalization of protein and ligand, and are susceptible to false positives. Thus, important information about the functional state of protein-ligand complexes cannot be obtained directly. Here we report a functional single-molecule binding assay that uses force spectroscopy to directly probe the functional consequence of ligand binding and report the functional state of protein-ligand complexes. As a proof of principle, we used protein G and the Fc fragment of IgG as a model system in this study. Binding of Fc to protein G does not induce major structural changes in protein G but results in significant enhancement of its mechanical stability. Using mechanical stability of protein G as an intrinsic functional reporter, we directly distinguished and quantified Fc-bound and Fc-free forms of protein G on a single-molecule basis and accurately determined their dissociation constant. This single-molecule functional binding assay is label-free, nearly background-free, and can detect functional heterogeneity, if any, among protein-ligand interactions. This methodology opens up avenues for studying protein-ligand interactions in a functional context, and we anticipate that it will find broad application in diverse protein-ligand systems.

SPR biosensor for the detection of L. monocytogenes using phage-displayed antibody

Whole cells of Listeria monocytogenes were detected with a compact, surface plasmon resonance (SPR) sensor using a phage-displayed scFv antibody to the virulence factor actin polymerization protein (ActA) for biorecognition. Phage Lm P4:A8, expressing the scFv antibody fused to the pIII surface protein was immobilized to the sensor surface through physical adsorption. A locally constructed fluidics system was used to deliver solutions to the compact, two-channel SPREETA sensor. Specificity of the sensor was tested using common food-borne bacteria and a control phage, M13K07 lacking the scFv fusion on its coat protein. The detection limit for L. monocytogenes whole cells was estimated to be 2 x 10(6)cfu/ml. The sensor was also used to determine the dissociation constant (Kd) for the interaction of phage-displayed scFv and soluble ActA in solution as 4.5 nM.

Protein-protein interaction site mapping using NMR-detected mutational scanning

We demonstrate a novel NMR method for the mapping of protein-protein interaction sites. In our approach protein-protein binding sites are mapped by competition binding experiments using indirect NMR reporter technology and Ala positional scanning. The methodology provides high sensitivity, ease of implementation and high-throughput capabilities. The feasibility of the technique is demonstrated with an application to the beta-Catenin/Tcf4 complex.

Generic method for quantification of FLAG-tagged fusion proteins by a real time biosensor

Availability of rapid quantitative protein-expression analysis is often the bottleneck in high throughput screening applications. A real time biosensor was employed to establish a quantitative assay for FLAG fusion proteins using FLAG-tagged bacterial alkaline phosphatase as standard. A range of FLAG-tagged bacterial alkaline phosphatase concentrations were injected over the anti-FLAG M2 antibody surface of the biosensor and used as standards to determine the concentration of different FLAG-tagged proteins with a molecular mass of 18.1 kDa respectively 49.3 kDa from yeast culture supernatants. The M2 immobilized chip was found to retain binding capacity following regeneration for at least 120 cycles. This real time biosensor method allows the quantitation of proteins from culture supernatants using a calibration curve obtained with a different protein. Further benefits include the short assay time of approximately 5 min, the small amount of sample required (35 microl per injection) and the ability to monitor the binding event in real time.

Predicting protein-protein interactions based only on sequences information

Protein-protein interactions (PPIs) are central to most biological processes. Although efforts have been devoted to the development of methodology for predicting PPIs and protein interaction networks, the application of most existing methods is limited because they need information about protein homology or the interaction marks of the protein partners. In the present work, we propose a method for PPI prediction using only the information of protein sequences. This method was developed based on a learning algorithm-support vector machine combined with a kernel function and a conjoint triad feature for describing amino acids. More than 16,000 diverse PPI pairs were used to construct the universal model. The prediction ability of our approach is better than that of other sequence-based PPI prediction methods because it is able to predict PPI networks. Different types of PPI networks have been effectively mapped with our method, suggesting that, even with only sequence information, this method could be applied to the exploration of networks for any newly discovered protein with unknown biological relativity. In addition, such supplementary experimental information can enhance the prediction ability of the method.

From protein-protein complexes to interactomics

Protein-protein interactions (or PPIs) are key elements for the normal functioning of a living cell. A large description of the protein interactomics field is given in this review where different aspects will be discussed. We first give an introduction of the different large scale experimental approaches from yeast two-hybrid to mass spectrometry used to discover PPIs and build protein interaction maps. Single PPI validation techniques such as co-immunoprecipitation or fluorescence methods are then presented as they are more and more integrated in global PPI discovery strategy. Data from different experimental sets are compared and an assessment of the different large scale technologies is presented. Bioinformatics tools can also predict with a good accuracy PPIs in silico, PPIs databases are now numerous and topological analysis has led to interesting insights into the nature of network connection. Finally, PPI, as an association of two proteins, has been structurally characterized for many protein complexes and is largely discussed throughout existing examples. The results obtained so far already provide the biologist with a large set of structured data from which knowledge on pathways and associated protein function can be extracted.

Helicobacter pylori acyl carrier protein: expression, purification, and its interaction with beta-hydroxyacyl-ACP dehydratase

Acyl carrier protein (ACP) is an essential component in the type II fatty acid biosynthesis (FAS II) process and is responsible for the acyl group transfer within a series of related enzymes. In this work, the ACP from Helicobacter pylori strain SS1 was cloned and the gene sequence of Hpacp was deposited in the GenBank database (Accession No.: AY904356). Two forms of HpACP (apo, holo) were successfully purified and characterized. The thermal stability of these two forms was quantitatively investigated by CD spectral analyses. The results revealed that the holo-HpACP was more stable than apo-HpACP according to the transition midpoint temperature(Tm). Moreover, the interaction of HpACP with the related enzyme (beta-hydroxyacyl-ACP dehydratase, HpFabZ) was determined by GST-pull down assay and surface plasmon resonance (SPR) technique in vitro, the results showed that HpACP displays a strong binding affinity to HpFabZ (KD=1.2 x 10(-8)M). This current work is hoped to supply useful information for better understanding the ACP features of Helicobacter pylori SS1 strain.

Applications of ESI-MS in drug discovery: interrogation of noncovalent complexes

For many years, analytical mass spectrometry has had numerous supporting roles in the drug development process, including the assessment of compound purity; quantitation of absorption, distribution, metabolism and excretion; and compound-specific pharmacokinetic analyses. More recently, mass spectrometry has emerged as an effective technique for identifying lead compounds on the basis of the characterization of noncovalent ligand-macromolecular target interactions. This approach offers several attractive properties for screening applications in drug discovery compared with other strategies, including the small quantities of target and ligands required, and the capacity to study ligands or targets without having to label them. Here, we review the application of electrospray ionization mass spectrometry to the interrogation of noncovalent complexes, highlighting examples from drug discovery efforts aimed at a range of target classes.

Surface plasmon resonance in protein-membrane interactions

Surface plasmon resonance (SPR) has become one of the most important techniques for studying macromolecular interactions. The most obvious advantages of SPR over other techniques are: direct and rapid determination of association and dissociation rates of binding process, no need for labelling of protein or lipids, and small amounts of sample used in the assay (often nM concentrations of proteins). In biochemistry, SPR is used mainly to study protein-protein interactions. On the other hand, protein-membrane interactions, although crucial for many cell processes, are less well studied. Recent advances in the preparation of stable membrane-like surfaces and the commercialisation of sensor chips has enabled widespread use of SPR in protein-membrane interactions. One of the most popular is Biacore's L1 sensor chip that allows capture of intact liposomes or even subcellular preparations. Lipid specificity of protein-membrane interactions can, therefore, be easily studied by manipulating the lipid composition of the immobilised membrane. The number of published papers has increased steadily in the last few years and the examples include domains or proteins that participate in cell signalling, pore-forming proteins, membrane-interacting peptides, coagulation factors, enzymes, amyloidogenic proteins, prions, etc. This paper gives a brief overview of different membrane-mimetic surfaces that can be prepared on the surface of SPR chips, properties of liposomes on the surface of L1 chips and some selected examples of protein-membrane interactions studied with such system.

Probabilistic prediction of protein-protein interactions from the protein sequences

Prediction of protein-protein interactions is very important for several bioinformatics tasks though it is not a straightforward problem. In this paper, employing only protein sequence information, a framework is presented to predict protein-protein interactions using a probabilistic-based tree augmented nai ve (TAN) Bayesian network. Our framework also provides a confidence level for every predicted interaction, which is useful for further analysis by the biologists. The framework is applied to the yeast interaction datasets for predicting interactions and it is shown that our framework gives better performance than support vector machine (SVM). The framework is implemented as a webserver and is available for prediction.

Exploring biology with small organic molecules

Small organic molecules have proven to be invaluable tools for investigating biological systems, but there is still much to learn from their use. To discover and to use more effectively new chemical tools to understand biology, strategies are needed that allow us to systematically explore 'biological-activity space'. Such strategies involve analysing both protein binding of, and phenotypic responses to, small organic molecules. The mapping of biological-activity space using small molecules is akin to mapping the stars--uncharted territory is explored using a system of coordinates that describes where each new feature lies.

Gold nanoparticle-based competitive colorimetric assay for detection of protein–protein interactions

A gold nanoparticle-based competitive colorimetric assay uses the ensemble of Concanavalin (ConA) and mannopyranoside-encapsulated gold nanoparticles (Man-GNPs) to identify the binding partners for ConA and the binding constants are determined based on the wavelength shifts.

Physical evidence for the induced release of the Bacillus subtilis transcription factor, sigma(F), from its inhibitory complex

The release of the transcription factor sigma(F) from its inhibitory complex with SpoIIAB is a key regulatory step in the control of sporulation in Bacillus subtilis as it initiates a pattern of differential gene expression in the mother cell and prespore compartments. The sigma(F).SpoIIAB complex is dissociated by the unphosphorylated form of the protein SpoIIAA, the alternative binding partner of SpoIIAB. Here, we employ fluorescence spectroscopy to examine the mechanism by which SpoIIAA acts on the sigma(F).SpoIIAB complex. We constructed a mutant of sigma(F), sigma(F)-W46L, which displayed a reproducible fluorescence response on binding to SpoIIAB. Using this mutant we were able to quantify the amount of sigma(F) bound to SpoIIAB in real time. The results provide physical evidence for the "induced release" mechanism of sigma(F) activation. We demonstrate that SpoIIAA interacts directly with the sigma(F).SpoIIAB complex, greatly decreasing the affinity of SpoIIAB for sigma(F) and thus causing the release of the latter. We also demonstrate that sigma(F) is released before SpoIIAA is phosphorylated and that release occurs on a similar time scale to the binding of SpoIIAA to SpoIIAB.

Molecular imaging of homodimeric protein-protein interactions in living subjects

Homodimeric protein interactions are potent regulators of cellular functions, but are particularly challenging to study in vivo. We used a split synthetic renilla luciferase (hRLUC) complementation-based bioluminescence assay to study homodimerization of herpes simplex virus type 1 thymidine kinase (TK) in mammalian cells and in living mice. We quantified and imaged homodimerization of TK chimeras containing N-terminal (N-hRLUC) or C-terminal (C-hRLUC) fragments of hRLUC in the upstream and downstream positions, respectively (tail-to-head homodimer). This was monitored using luminometry (68-fold increase, and was significantly [P<0.01] above background light emission) and by CCD camera imaging of living mice implanted with ex vivo transfected 293T cells (2.7-fold increase, and is significantly [P<0.01] above background light emission). We also made a mutant-TK to generate N-hRLUC mutant TK and mutant TK-C-hRLUC by changing a single amino acid at position 318 from arginine to cysteine, a key site that has previously been reported to be essential for TK homo-dimerization, to support the specificity of the hRLUC complementation signal from TK homodimerization. Ex vivo substrate (8-3H Penciclovir) accumulation assays in 293T cells expressing the TK protein chimeras showed active TK enzyme. We also devised an experimental strategy by constructing variant TK chimeras (possessing extra N-hRLUC or C-hRLUC 'spacers') to monitor incremental lack of association of the tail-to-head TK homodimer. Application of this potentially generalizable assay to screen for molecules that promote or disrupt ubiquitous homodimeric protein-protein interactions could serve not only as an invaluable tool to understand biological networks but could also be applied to drug discovery and validation in living subjects.

Molecular imaging of drug-modulated protein-protein interactions in living subjects

Networks of protein interactions mediate cellular responses to environmental stimuli and direct the execution of many different cellular functional pathways. Small molecules synthesized within cells or recruited from the external environment mediate many protein interactions. The study of small molecule-mediated interactions of proteins is important to understand abnormal signal transduction pathways in cancer and in drug development and validation. In this study, we used split synthetic renilla luciferase (hRLUC) protein fragment-assisted complementation to evaluate heterodimerization of the human proteins FRB and FKBP12 mediated by the small molecule rapamycin. The concentration of rapamycin required for efficient dimerization and that of its competitive binder ascomycin required for dimerization inhibition were studied in cell lines. The system was dually modulated in cell culture at the transcription level, by controlling nuclear factor kappaB promoter/enhancer elements using tumor necrosis factor alpha, and at the interaction level, by controlling the concentration of the dimerizer rapamycin. The rapamycin-mediated dimerization of FRB and FKBP12 also was studied in living mice by locating, quantifying, and timing the hRLUC complementation-based bioluminescence imaging signal using a cooled charged coupled device camera. This split reporter system can be used to efficiently screen small molecule drugs that modulate protein-protein interactions and also to assess drugs in living animals. Both are essential steps in the preclinical evaluation of candidate pharmaceutical agents targeting protein-protein interactions, including signaling pathways in cancer cells.

Peeking into a secret world of pore-forming toxins: membrane binding processes studied by surface plasmon resonance

Pore-formation in cell membranes is used by many toxins to kill cells. It is usually a process involving multiple steps that are difficult to analyse at the molecular level. The use of surface plasmon resonance (SPR) has only recently been introduced into the study of pore-forming toxins (PFT). It can give useful data mostly on the first steps of the pore-forming process; the binding to the lipid membranes. In particular, it can make unique contributions to our knowledge of ligand specificity and the kinetics of binding. This mini-review summarizes some recent SPR studies of PFT.

The organization of the microbial biodegradation network from a systems-biology perspective

Microbial biodegradation of environmental pollutants is a field of growing importance because of its potential use in bioremediation and biocatalysis. We have studied the characteristics of the global biodegradation network that is brought about by all the known chemical reactions that are implicated in this process, regardless of their microbial hosts. This combination produces an efficient and integrated suprametabolism, with properties similar to those that define metabolic networks in single organisms. The characteristics of this network support an evolutionary scenario in which the reactions evolved outwards from the central metabolism. The properties of the global biodegradation network have implications for predicting the fate of current and future environmental pollutants.

Combined affinity and rate constant distributions of ligand populations from experimental surface binding kinetics and equilibria

The present article considers the influence of heterogeneity in a mobile analyte or in an immobilized ligand population on the surface binding kinetics and equilibrium isotherms. We describe strategies for solving the inverse problem of calculating two-dimensional distributions of rate and affinity constants from experimental data on surface binding kinetics, such as obtained from optical biosensors. Although the characterization of a heterogeneous population of analytes binding to uniform surface sites may be possible under suitable experimental conditions, computational difficulties currently limit this approach. In contrast, the case of uniform analytes binding to heterogeneous populations of surface sites is computationally feasible, and can be combined with Tikhonov-Phillips and maximum entropy regularization techniques that provide the simplest distribution that is consistent with the data. The properties of this ligand distribution analysis are explored with several experimental and simulated data sets. The resulting two-dimensional rate and affinity constant distributions can describe well experimental kinetic traces measured with optical biosensors. The use of kinetic surface binding data can give significantly higher resolution than affinity distributions from the binding isotherms alone. The shape and the level of detail of the calculated distributions depend on the experimental conditions, such as contact times and the concentration range of the analyte. Despite the flexibility introduced by considering surface site distributions, the impostor application of this model to surface binding data from transport limited binding processes or from analyte distributions can be identified by large residuals, if a sufficient range of analyte concentrations and contact times are used. The distribution analysis can provide a rational interpretation of complex experimental surface binding kinetics, and provides an analytical tool for probing the homogeneity of the populations of immobilized protein.

Proteomics methods for probing molecular mechanisms in signal transduction1

mRNA splicing and various posttranslational modifications to proteins result in a larger number of proteins than genes. Assessing the dynamic nature of this proteome is the challenge of modern proteomics. Recent advances in high throughput methods greatly facilitate the analysis of proteins involved in signal transduction, their production, posttranslational modifications and interactions. Highly reproducible two dimensional polyacrylamide gel electrophoresis (2D-PAGE) methods, coupled with matrix assisted laser desorption-time of flight-mass spectrometry (MALDI-TOF-MS) allow rapid separation and identification of proteins. These methods, alone or in conjunction with other techniques such as immunoprecipitation, allow identification of various critical posttranslational modifications, such as phosphorylation. High throughput identification of important protein-protein interactions is accomplished by yeast two hybrid approaches. In vitro and in vivo pulldown assays, coupled with MALDI-TOF-MS, provide an important alternative to two hybrid approaches. Emerging advances in production of protein-based arrays promise to further increase throughput of proteomics-based approaches to signal transduction.

MULTIPROSPECTOR: an algorithm for the prediction of protein-protein interactions by multimeric threading

In this postgenomic era, the ability to identify protein-protein interactions on a genomic scale is very important to assist in the assignment of physiological function. Because of the increasing number of solved structures involving protein complexes, the time is ripe to extend threading to the prediction of quaternary structure. In this spirit, a multimeric threading approach has been developed. The approach is comprised of two phases. In the first phase, traditional threading on a single chain is applied to generate a set of potential structures for the query sequences. In particular, we use our recently developed threading algorithm, PROSPECTOR. Then, for those proteins whose template structures are part of a known complex, we rethread on both partners in the complex and now include a protein-protein interfacial energy. To perform this analysis, a database of multimeric protein structures has been constructed, the necessary interfacial pairwise potentials have been derived, and a set of empirical indicators to identify true multimers based on the threading Z-score and the magnitude of the interfacial energy have been established. The algorithm has been tested on a benchmark set comprised of 40 homodimers, 15 heterodimers, and 69 monomers that were scanned against a protein library of 2478 structures that comprise a representative set of structures in the Protein Data Bank. Of these, the method correctly recognized and assigned 36 homodimers, 15 heterodimers, and 65 monomers. This protocol was applied to identify partners and assign quaternary structures of proteins found in the yeast database of interacting proteins. Our multimeric threading algorithm correctly predicts 144 interacting proteins, compared to the 56 (26) cases assigned by PSI-BLAST using a (less) permissive E-value of 1 (0.01). Next, all possible pairs of yeast proteins have been examined. Predictions (n = 2865) of protein-protein interactions are made; 1138 of these 2865 interactions have counterparts in the Database of Interacting Proteins. In contrast, PSI-BLAST made 1781 predictions, and 1215 have counterparts in DIP. An estimation of the false-negative rate for yeast-predicted interactions has also been provided. Thus, a promising approach to help assist in the assignment of protein-protein interactions on a genomic scale has been developed.

Structural and thermodynamic correlates of T cell signaling

The first crystal structures of intact T cell receptors (TCRs) bound to class I peptide-MHC (pMHCs) antigens were determined in 1996. Since then, further structures of class I TCR/pMHC complexes have explored the degree of structural variability in the TCR-pMHC system and the structural basis for positive and negative selection. The recent determination of class II and allogeneic class I TCR/pMHC structures, as well as those of accessory molecules (e.g., CD3), has pushed our knowledge of TCR/pMHC interactions into new realms, shedding light on clinical pathologies, such as graft rejection and graft-versus-host disease. Furthermore, the determination of coreceptor structures lays the foundation for a more comprehensive structural description of the supramolecular TCR signaling events and those assemblies that arise in the immunological synapse. While these telling photodocumentaries of the TCR/pMHC interaction are composed mainly from static crystal structures, a full description of the biological snapshots in T cell signaling requires additional analytical methods that record the dynamics of the process. To this end, surface plasmon resonance (SPR), isothermal titration calorimetry (ITC), and ultracentrifugation (UC) have furnished both affinities and kinetics of the TCR/pMHC association. In the past year, structural, biochemical, and molecular biological data describing TCR/pMHC interactions have sublimely coalesced into a burgeoning well of understanding that promises to deliver further insights into T cell recognition. The coming years will, through a more intimate union of structural and kinetic data, allow many pressing questions to be addressed, such as how TCR/pMHC ligation is affected by coreceptor binding and what is the mechanism of TCR signaling in both early and late stages of T cell engagement with antigen-presenting cells.

Biophysical characterization of proteins in the post-genomic era of proteomics

Proteomics focuses on the high throughput study of the expression, structure, interactions, and, to some extent, function of large numbers of proteins. A true understanding of the functioning of a living cell also requires a quantitative description of the stoichiometry, kinetics, and energetics of each protein complex in a cellular pathway. Classical molecular biophysical studies contribute to understanding of these detailed properties of proteins on a smaller scale than does proteomics in that individual proteins are usually studied. This perspective article deals with the role of biophysical methods in the study of proteins in the proteomic era. Several important physical biochemical methods are discussed briefly and critiqued from the standpoint of information content and data acquisition. The focus is on conformational changes and macromolecular assembly, the utility of dynamic and static structural data, and the necessity to combine experimental approaches to obtain a full functional description. The conclusions are that biophysical information on proteins is a useful adjunct to "standard" proteomic methods, that data can be obtained by high throughput technology in some instances, but that hypothesis-driven experimentation may frequently be required.