The role of weak protein-protein interactions in multivalent lectin-carbohydrate binding: crystal structure of cross-linked FRIL

Binding of multivalent glycoconjugates by lectins often leads to the formation of cross-linked complexes. Type I cross-links, which are one-dimensional, are formed by a divalent lectin and a divalent glycoconjugate. Type II cross-links, which are two or three-dimensional, occur when a lectin or glycoconjugate has a valence greater than two. Type II complexes are a source of additional specificity, since homogeneous type II complexes are formed in the presence of mixtures of lectins and glycoconjugates. This additional specificity is thought to become important when a lectin interacts with clusters of glycoconjugates, e.g. as is present on the cell surface. The cryst1al structure of the Glc/Man binding legume lectin FRIL in complex with a trisaccharide provides a molecular snapshot of how weak protein-protein interactions, which are not observed in solution, can become important when a cross-linked complex is formed. In solution, FRIL is a divalent dimer, but in the crystal FRIL forms a tetramer, which allows for the formation of an intricate type II cross-linked complex with the divalent trisaccharide. The dependence on weak protein-protein interactions can ensure that a specific type II cross-linked complex and its associated specificity can occur only under stringent conditions, which explains why lectins are often found forming higher-order oligomers.     

Kinetic studies of protein-protein interactions

The structure of a protein-protein interaction, its affinity and thermodynamic characteristics depict a 'frozen' state of a complex. This picture ignores the kinetic nature of complex formation and dissociation, which are of major biological and biophysical interest. This review highlights recent advances in deciphering the kinetic pathway of protein-protein complexation, the nature of the encounter complex, transition state and intermediate along the reaction, and the effects of mutation, viscosity, pH and salt on association.     

Solid phase proteomics: dramatic reinforcement of very weak protein-protein interactions

Very weak protein-protein interactions may play a critical role in cell physiology but they are not easily detectable in "in vitro" experiments. To detect these weak interactions, we have developed a strategy that included: (a) design of a rapid and very effective crosslinking of protein-protein complexes with poly-functional reagents; (b) selective adsorption of very large proteins on lowly activated ionic exchangers, based on the need of a multipoint physical adsorption to incorporate the proteins into the matrix; (c) purification by selective adsorption of protein-protein complexes formed by strong protein-protein interactions, via selective adsorption of the complexes on lowly activated ionic exchangers via multi-protein physical adsorption and leaving the non-associated proteins in the solution; (d) reinforcement of very weak protein-protein interactions by selective adsorption of the complex on lowly activated ionic exchange supports via a synergetic cooperation of the weak protein-protein interaction plus the interactions of both proteins with the support enabling the almost full shifting of the equilibrium towards the association position; (e) control of the aggregation state of proteins like BSA, formed by weak protein-protein interactions. In this last case, it seems that the interaction of the protein molecules placed on the borders of the aggregate with the groups on the support partially stabilizes the whole aggregate, although, some molecules of the aggregate cannot interact with the support. The size of the aggregates may be defined by controlling the concentration of ionised groups on the support: the less activated the supports are, the bigger the complexes. In this way, solid-phase proteomics could be a very interesting tool to detect weak protein-protein interactions.     

On the role of electrostatics in protein-protein interactions

The role of electrostatics in protein-protein interactions and binding is reviewed in this paper. A brief outline of the computational modeling, in the framework of continuum electrostatics, is presented and the basic electrostatic effects occurring upon the formation of the complex are discussed. The effect of the salt concentration and pH of the water phase on protein-protein binding free energy is demonstrated which indicates that the increase of the salt concentration tends to weaken the binding, an observation that is attributed to the optimization of the charge-charge interactions across the interface. It is pointed out that the pH-optimum (pH of optimal binding affinity) varies among the protein-protein complexes, and perhaps is a result of their adaptation to particular subcellular compartments. The similarities and differences between hetero- and homo-complexes are outlined and discussed with respect to the binding mode and charge complementarity.     

Isolation of protein subpopulations undergoing protein-protein interactions

A new method is described for isolating and identifying proteins participating in protein-protein interactions in a complex mixture. The method uses a cyanogen bromide-activated Sepharose matrix to isolate proteins that are non-covalently bound to other proteins. Because the proteins are accessible to chemical manipulation, mass spectrometric identification of the proteins can yield information on specific classes of interacting proteins, such as calcium-dependent or substrate-dependent protein interactions. This permits selection of a subpopulation of proteins from a complex mixture on the basis of specified interaction criteria. The new method has the advantage of screening the entire proteome simultaneously, unlike the two-hybrid system or phage display, which can only detect proteins binding to a single bait protein at a time. The method was tested by selecting rat brain extract for proteins exhibiting calcium-dependent protein interactions. Of 12 proteins identified by mass spectrometry, eight were either known calcium-binding proteins or proteins with known calcium-dependent protein interactions, indicating that the method is capable of enriching a subpopulation of proteins from a complex mixture on the basis of a specific class of protein interactions. Because only naturally occurring interactions of proteins in their native state are observed, this method will have wide applicability to studies of protein interactions in tissue samples and autopsy specimens, for screening for perturbations of protein-protein interactions by signaling molecules, pharmacological agents or toxins, and screening for differences between cancerous and untransformed cells.     

Oligomeric protein structure networks: insights into protein-protein interactions

Background  

Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues) with special emphasis to protein interfaces.     

Calculation of weak protein-protein interactions: the pH dependence of the second virial coefficient

Interactions between proteins are often sufficiently weak that their study through the use of conventional structural techniques becomes problematic. Of the few techniques capable of providing experimental measures of weak protein-protein interactions, perhaps the most useful is the second virial coefficient, B(22), which quantifies a protein solution's deviations from ideal behavior. It has long been known that B(22) can in principle be computed, but only very recently has it been demonstrated that such calculations can be performed using protein models of true atomic detail (Biophys. J. 1998, 75:2469-2477). The work reported here extends these previous efforts in an attempt to develop a transferable energetic model capable of reproducing the experimental trends obtained for two different proteins over a range of pH and ionic strengths. We describe protein-protein interaction energies by a combination of three separate terms: (i) an electrostatic interaction term based on the use of effective charges, (ii) a term describing the electrostatic desolvation that occurs when charged groups are buried by an approaching protein partner, and (iii) a solvent-accessible surface area term that is used to describe contributions from van der Waals and hydrophobic interactions. The magnitude of the third term is governed by an adjustable, empirical parameter, gamma, that is altered to optimize agreement between calculated and experimental values of B(22). The model is applied separately to the proteins lysozyme and chymotrypsinogen, yielding optimal values of gamma that are almost identical. There are, however, clear difficulties in reproducing B(22) values at the extremes of pH. Explicit calculation of the protonation states of ionizable amino acids in the 200 most energetically favorable protein-protein structures suggest that these difficulties are due to a neglect of the protonation state changes that can accompany complexation. Proper reproduction of the pH dependence of B(22) will, therefore, almost certainly require that account be taken of these protonation state changes. Despite this problem, the fact that almost identical gamma values are obtained from two different proteins suggests that the basic energetic formulation used here, which can be evaluated very rapidly, might find use in dynamical simulations of weak protein-protein interactions at intermediate pH values.     

Luxury accommodations: the expanding role of structural plasticity in protein-protein interactions

The recognition of multiple ligands at a single molecular surface is essential to many biological processes. Conformational flexibility has emerged as a compelling strategy for association at such convergent binding sites. Studies over the past few years have brought about a greater understanding of the role that protein plasticity might play in protein-protein interactions.     

Prediction of protein-protein interactions using protein signature profiling

Protein domains are conserved and functionally independent structures that play an important role in interactions among related proteins. Domain-domain interactions 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 elegans, 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 under the receiver operating characteristic (ROC) curve. When proteins containing one or two signatures were removed, the sensitivity of the predicted PPI pairs increased 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 average 4 times better than those predicted by either phylogenetic profiling or gene expression profiling.     

Novel role of pleckstrin homology domain of the Bcr-Abl protein: Analysis of protein-protein and protein-lipid interactions

The Bcr-Abl protein is a marker for malignant transformation in chronic myeloid leukemia and in acute lymphoblastic leukemia. There are three Bcr-Abl chimeras known so far, p190, p210 and p230. The only structural difference between the three Bcr-Abl proteins is the presence of DH and PH domains from the Bcr gene in p210 and p230. The Bcr-Abl DH domain is functioning as a guanine nucleotide exchange factor for Rho family of small GTPases. The PH domain confers binding to phosphoinositides but some PH domains have also been found to bind specific target proteins. Here we show that the PH domain from Bcr-Abl binds a number of proteins involved in vital cellular processes. These proteins include PLC?, Zizimin1, tubulin and SMC1. The revelation of the role of the Bcr-Abl PH domain in leukemogenesis is likely to provide clues to the molecular mechanisms underlying the phenotypes of Bcr-Abl positive leukemia and could therefore provide tools for the identification of targets for the development of therapeutic treatments.     

Fluorescence studies of possible protein-protein interactions in model lipoprotein complexes

Summary The structure of model lipoprotein complexes, extracted from an aqueous phase into isooctane, has been investigated using a fluorescence technique. The technique is based on the transfer of excitation energy from one protein (or DNS-labelled protein) to a second protein containing a fluorescence quencher, such as a haem group. The results obtained with model complexes in isooctane are consistent with a structure comprised of an inner protein core, and an outer layer of phospholipids.     

The role of weak interactions in lignin polymerization

Lignin is the most abundant natural polymer composed by aromatic moieties. Its chemical composition and its abundance have focused efforts to unlock its potential as a source of aromatic compounds for many years. The lack of a proper way for lignin de-polymerization has hampered its success as a natural solution for commodity aromatic chemicals, which is also due to the lack of understanding of the underlying mechanisms of lignin polymerization. A fuller fundamental understanding of polymerization mechanisms could lead to improvements in de-polymerization strategies, and therefore a proper methodology and a predictive theoretical framework are required for such purpose. This work presents a complete computational study on some of the key steps of lignin polymerization mechanisms. Density functional theory (DFT) calculations have been performed to evaluate the most appropriate methodology and to compute the chemical structures and reaction enthalpies for the monolignol dimerization, the simplest key step that controls the polymerization. Quantum theory of atoms in molecules (QTAIM) has been applied to understand the coupling reaction mechanisms, for which the radical species and transition states (TSs) involved have been characterized. The coupling that leads to the formation of the β–O–4 linkage has been theoretically reproduced according to proposed mechanisms, for which weak interactions have been found to play a key role in the arrangement of reactants. The hydrogen bond formed between the oxygen of the phenoxy radical, and the alcohol of the aliphatic chain, together with the interaction between aromatic rings, locates the reactants in a position that favors such β–O–4 linkage.

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Graphical Abstract QTAIM analysis of the complex between coumaryl and coniferyl alcohols. It emphasizes the importance of weak interactions during the formation of beta-O-4 linkages in the polymerization of lignin.

     

Learning to predict protein-protein interactions from protein sequences

In order to understand the molecular machinery of the cell, we need to know about the multitude of protein-protein interactions that allow the cell to function. High-throughput technologies provide some data about these interactions, but so far that data is fairly noisy. Therefore, computational techniques for predicting protein-protein interactions could be of significant value. One approach to predicting interactions in silico is to produce from first principles a detailed model of a candidate interaction. We take an alternative approach, employing a relatively simple model that learns dynamically from a large collection of data. In this work, we describe an attraction-repulsion model, in which the interaction between a pair of proteins is represented as the sum of attractive and repulsive forces associated with small, domain- or motif-sized features along the length of each protein. The model is discriminative, learning simultaneously from known interactions and from pairs of proteins that are known (or suspected) not to interact. The model is efficient to compute and scales well to very large collections of data. In a cross-validated comparison using known yeast interactions, the attraction-repulsion method performs better than several competing techniques.     

Using indirect protein-protein interactions for protein complex prediction

Protein complexes are fundamental for understanding principles of cellular organizations. As the sizes of protein-protein interaction (PPI) networks are increasing, accurate and fast protein complex prediction from these PPI networks can serve as a guide for biological experiments to discover novel protein complexes. However, it is not easy to predict protein complexes from PPI networks, especially in situations where the PPI network is noisy and still incomplete. Here, we study the use of indirect interactions between level-2 neighbors (level-2 interactions) for protein complex prediction. We know from previous work that proteins which do not interact but share interaction partners (level-2 neighbors) often share biological functions. We have proposed a method in which all direct and indirect interactions are first weighted using topological weight (FS-Weight), which estimates the strength of functional association. Interactions with low weight are removed from the network, while level-2 interactions with high weight are introduced into the interaction network. Existing clustering algorithms can then be applied to this modified network. We have also proposed a novel algorithm that searches for cliques in the modified network, and merge cliques to form clusters using a "partial clique merging" method. Experiments show that (1) the use of indirect interactions and topological weight to augment protein-protein interactions can be used to improve the precision of clusters predicted by various existing clustering algorithms; and (2) our complex-finding algorithm performs very well on interaction networks modified in this way. Since no other information except the original PPI network is used, our approach would be very useful for protein complex prediction, especially for prediction of novel protein complexes.     

Link between protein-solvent and weak protein-protein interactions gives insight into halophilic adaptation

Malate dehydrogenase (Hm MalDH) from the extreme halophile Haloarcula marismortui is a very acidic protein with extensive ion binding properties. It is a good model for the study of solvation-solubility relationships. We measured the small-angle neutron or X-ray scattering profiles of folded and stable Hm MalDH at various protein concentrations and derived the second virial coefficients A(2). In NaCl, CsCl, KF, KCl, and NaCH(3)CO(2), A(2) values are positive, indicating globally repulsive protein-protein interactions. Below 1 M MgCl(2) and MgSO(4) or above 2 M (NH(4))(2)SO(4), A(2) rapidly decreases. From structure factor modeling with DLVO (Derjaguin, Landau, Verwey, and Overbeek)-like potentials, an effective diameter of 80-82 A is found for the protein particle in solution, compatible with its structural dimensions; the effective charge of the particle is undefined because of the high salt concentration. The strong variations of the protein-protein interaction are correlated to an attractive potential whose depth evolves with the salinity but in an opposite way in Mg salts and (NH(4))(2)SO(4). A repulsive Donnan term, corresponding to counterion dissociation, and an attractive term related to previously measured preferential salt binding parameters are discussed from well-established thermodynamics considerations and qualitatively account for the behavior of the protein-protein interactions in the various solutions. Because a solvation shell with a composition different from bulk induces protein-protein attraction, molecular adaptation to high salt would be directed to allow protein-salt interactions in order to avoid water or salt enrichment at the surface of the protein and thus preserve its solubility.     

Detection of protein-protein interactions in vivo based on protein splicing

In mammalian cells, protein-protein interactions constitute essential regulatory steps that modulate the activity of signaling pathways. In recent years, several approaches towards understanding the interactions have been developed. We describe herein a new method for detecting protein-protein interactions in vivo based on protein splicing and highlight some potential applications of this technique.     

High-throughput and multiplexed protein array technology: protein-DNA and protein-protein interactions

Miniaturized protein arrays address protein interactions with various types of molecules in a high-throughput and multiplexed fashion. This review focuses on achievements in the analysis of protein-DNA and protein-protein interactions. The technological feasibility of protein arrays depends on the different factors that enable the arrayed proteins to recognize molecular partners and on the specificity of the interactions involved. Proteome-scale studies of molecular interactions require high-throughput approaches for both the production and purification of functionally active proteins. Various solutions have been proposed to avoid non-specific protein interactions on array supports and to monitor low-abundance molecules. The data accumulated indicate that this emerging technology is perfectly suited to resolve networks of protein interactions involved in complex physiological and pathological phenomena in different organisms and to develop sensitive tools for biomedical applications.     

Synchrotron protein footprinting: a technique to investigate protein-protein interactions.

Traditional approaches for macromolecular structure elucidation, including NMR, crystallography and cryo-EM have made significant progress in defining the structures of protein-protein complexes. A substantial number of macromolecular structures, however, have not been examined with atomic detail due to sample size and heterogeneity, or resolution limitations of the technique; therefore, the general applicability of each method is greatly reduced. Synchrotron footprinting attempts to bridge the gap in these methods by monitoring changes in accessible surface areas of discrete macromolecular moieties. As evidenced by our previous studies on RNA folding and DNA-protein interactions, the three-dimensional structure is probed by examining the reactions of these moieties with hydroxyl radicals generated by synchrotron X-rays. Here we report the application of synchrotron footprinting to the investigation of protein- protein interactions, as the novel technique has been utilized to successfully map the contact sites of gelsolin segment-1 in the gelsolin segment 1/actin complex. Footprinting results demonstrate that phenylalanine 104, located on the actin binding helix of gelsolin segment 1, is protected from hydroxyl radical modification in the presence of actin. This change in reactivity results from the specific protection of gelsolin segment-1, consistent with the substantial decrease in solvent accessibility of F104 upon actin binding, as calculated from the crystal structural of the gelsolin segment 1/actin complex. The results presented here establish synchrotron footprinting as a broadly applicable method to probe structural features of macromolecular complexes that are not amenable to conventional approaches.