Measures of cooperativity in the binding of ligands to proteins and their relation to non-additivity in protein-protein interactions

The analogy between cooperativity in the binding of ligands to proteins and non-additivity in protein-protein interactions is demonstrated and discussed in terms of the Wong and the Hill coefficients. A measure of non-additivity, the interaction constant, is rigorously derived for four thermodynamic cycles, involving the binding of small molecules to proteins and protein association. It is the reciprocal of the 'defect factor' of Laskowski et al. in Proteinase inhibitors: medical and biological aspects (ed. N. Katunuma et al.), pp. 55-68 (1983), and its logarithm is the Wong measure of cooperativity. These three measures are thus here given a common theoretical basis. The Hill coefficient for an asymmetric dimer that binds two different ligands which do not compete for the same site, at 50% saturation of each site, is derived. It is shown to be a function of the interaction constant and of the fraction of protein to which ligand is bound at both sites. These relations for protein-ligand interactions are then discussed in the context of non-additivity in protein-protein interactions.     

The use of supramolecular structures as protein ligands

Congo red dye as well as other eagerly self-assembling organic molecules which form rod-like or ribbon-like supramolecular structures in water solutions, appears to represent a new class of protein ligands with possible wide-ranging medical applications. Such molecules associate with proteins as integral clusters and preferentially penetrate into areas of low molecular stability. Abnormal, partly unfolded proteins are the main binding target for such ligands, while well packed molecules are generally inaccessible. Of particular interest is the observation that local susceptibility for binding supramolecular ligands may be promoted in some proteins as a consequence of function-derived structural changes, and that such complexation may alter the activity profile of target proteins. Examples are presented in this paper.     

Restricted mobility of side chains on concave surfaces of solenoid proteins may impart heightened potential for intermolecular interactions

Significant progress has been made in the determination of the protein structures with their number today passing over a hundred thousand structures. The next challenge is the understanding and prediction of protein–protein and protein–ligand interactions. In this work we address this problem by analyzing curved solenoid proteins. Many of these proteins are considered as “hub molecules” for their high potential to interact with many different molecules and to be a scaffold for multisubunit protein machineries. Our analysis of these structures through molecular dynamics simulations reveals that the mobility of the side‐chains on the concave surfaces of the solenoids is lower than on the convex ones. This result provides an explanation to the observed preferential binding of the ligands, including small and flexible ligands, to the concave surface of the curved solenoid proteins. The relationship between the landscapes and dynamic properties of the protein surfaces can be further generalized to the other types of protein structures and eventually used in the computer algorithms, allowing prediction of protein–ligand interactions by analysis of protein surfaces . Proteins 2015; 83:1654–1664. © 2015 Wiley Periodicals, Inc.     

High-resolution structures of retinol-binding protein in complex with retinol: pH-induced protein structural changes in the crystal state

The targeted delivery of non-polar ligands by binding proteins to membranes or membrane receptors involves the release of these ligands on or near the plasma membrane of target cells. Because these hydrophobic ligands are often bound inside a deep cavity of binding proteins, as shown previously for plasma retinol-binding protein (RBP), their release from these proteins might require the destabilization of the protein structure by partially denaturing conditions, such as those possibly present near plasma membranes. RBP is a plasma transport protein which delivers specifically retinol from its store sites to target cells. Here, we report the high-resolution (1.1-1.4A) crystal structures of bovine holo-RBP at five different pH values, ranging from 9 to 2. While unraveling details of the native protein structure and of the interactions with retinol at nearly atomic resolution at neutral pH, this study provides evidence for definite pH-induced modifications of several structural features of RBP. The structure most representative of the changes that holo-RBP undergoes at different pH values is that of its flexible state at pH 2. At this pH, most significant are the alteration of the arrangement of salt bridges and of the network of water molecules/H-bonds that participates in the retinol-RBP interaction, an appreciable increase of the volume of the beta-barrel cavity, a considerably higher degree of mobility of the RBP-bound ligand and of several protein regions and the disorder of a large number of solvent molecules that are ordered at neutral pH. These changes are likely to be accompanied by a modification of the pattern of charge distribution on the protein surface. All these changes, which reveal a substantially lowered conformational stability of RBP, presumably occur at the initial stages of the acidic denaturation of RBP and are possibly associated with a facilitated release of the retinol molecule from its carrier protein.     

Enzyme classification by ligand binding

The problem of assigning a biochemical function to newly discovered proteins has been traditionally approached by expert enzymological analysis, sequence analysis, and structural modeling. In recent years, the appearance of databases containing protein-ligand interaction data for large numbers of protein classes and chemical compounds have provided new ways of investigating proteins for which the biochemical function is not completely understood. In this work, we introduce a method that utilizes ligand-binding data for functional classification of enzymes. The method makes use of the existing Enzyme Commission (EC) classification scheme and the data on interactions of small molecules with enzymes from the BRENDA database. A set of ligands that binds to an enzyme with unknown biochemical function serves as a query to search a protein-ligand interaction database for enzyme classes that are known to interact with a similar set of ligands. These classes provide hypotheses of the query enzyme's function and complement other computational annotations that take advantage of sequence and structural information. Similarity between sets of ligands is computed using point set similarity measures based upon similarity between individual compounds. We present the statistics of classification of the enzymes in the database by a cross-validation procedure and illustrate the application of the method on several examples.     

Specific interactions for ab initio folding of protein terminal regions with secondary structures

Proteins fold into unique three-dimensional structures by specific, orientation-dependent interactions between amino acid residues. Here, we extract orientation-dependent interactions from protein structures by treating each polar atom as a dipole with a direction. The resulting statistical energy function successfully refolds 13 out of 16 fully unfolded secondary-structure terminal regions of 10-23 amino acid residues in 15 small proteins. Dissecting the orientation-dependent energy function reveals that the orientation preference between hydrogen-bonded atoms is not enough to account for the structural specificity of proteins. The result has significant implications on the theoretical and experimental searches for specific interactions involved in protein folding and molecular recognition between proteins and other biologically active molecules.     

Application of an allosteric model to describe the interactions among retinol binding protein 4, transthyretin, and small molecule retinol binding protein 4 ligands

Retinol binding protein 4 (RBP4) is a serum protein that serves as the major transport protein for retinol (vitamin A). Recent reports suggest that elevated levels of RBP4 are associated with insulin resistance and that insulin sensitivity may be improved by reducing serum RBP4 levels. This can be accomplished by administration of small molecules, such as fenretinide, that compete with retinol for binding to RBP4 and disrupt the protein-protein interaction between RBP4 and transthyretin (TTR), another serum protein that protects RBP4 from renal clearance. We developed a fluorescence resonance energy transfer (FRET) assay that measures the interaction between RBP4 and TTR and can be used to determine the binding affinities of RBP4 ligands. We present an allosteric model that describes the pharmacology of interaction among RBP4, TTR, retinol, and fenretinide, and we show data that support the model. We show that retinol increases the affinity of RBP4 for TTR by a factor of 4 and determine the affinity constants of fenretinide and retinyl acetate. The assay may be useful for characterizing small molecule ligands that bind to RBP4 and disrupt its interaction with TTR. In addition, such a model could be used to describe other protein-protein interactions that are modulated by small molecules.     

Lectin receptor kinases participate in protein-protein interactions to mediate plasma membrane-cell wall adhesions in Arabidopsis

Interactions between plant cell walls and plasma membranes are essential for cells to function properly, but the molecules that mediate the structural continuity between wall and membrane are unknown. Some of these interactions, which are visualized upon tissue plasmolysis in Arabidopsis (Arabidopsis thaliana), are disrupted by the RGD (arginine-glycine-aspartic acid) tripeptide sequence, a characteristic cell adhesion motif in mammals. In planta induced-O (IPI-O) is an RGD-containing protein from the plant pathogen Phytophthora infestans that can disrupt cell wall-plasma membrane adhesions through its RGD motif. To identify peptide sequences that specifically bind the RGD motif of the IPI-O protein and potentially play a role in receptor recognition, we screened a heptamer peptide library displayed in a filamentous phage and selected two peptides acting as inhibitors of the plasma membrane RGD-binding activity of Arabidopsis. Moreover, the two peptides also disrupted cell wall-plasma membrane adhesions. Sequence comparison of the RGD-binding peptides with the Arabidopsis proteome revealed 12 proteins containing amino acid sequences in their extracellular domains common with the two RGD-binding peptides. Eight belong to the receptor-like kinase family, four of which have a lectin-like extracellular domain. The lectin domain of one of these, At5g60300, recognized the RGD motif both in peptides and proteins. These results imply that lectin receptor kinases are involved in protein-protein interactions with RGD-containing proteins as potential ligands, and play a structural and signaling role at the plant cell surfaces.     

Reading the glyco-code: New approaches to studying protein–carbohydrate interactions

The surface of all living cells is decorated with carbohydrate molecules. Hundreds of functional proteins bind to these glycosylated ligands; such binding events subsequently modulate many aspects of protein and cell function. Identifying ligands for glycan-binding proteins (GBPs) is a defining challenge of glycoscience research. Here, we review recent advances that are allowing protein-carbohydrate interactions to be dissected with an unprecedented level of precision. We specifically highlight how cell-based glycan arrays and glyco-genomic profiling are being used to define the structural determinants of glycan-protein interactions in living cells. Going forward, these methods create exciting new opportunities for the study of glycans in physiology and disease.     

Peptides as protein binding site mimetics

The rational/structure-based design and/or combinatorial development of molecules capable of structurally and functionally mimicking the binding sites of proteins represents a promising strategy for the exploration and understanding of protein structure and function. The ultimate goal of using such molecules is the modulation of protein function through controlled interference with the underlying binding events. In addition to their basic significance, such proteinmimetics are also useful tools for a range of biomedical applications, in particular the inhibition of disease-associated protein-ligand interactions. Owing to their chemical and structural relation to proteins, as well as the relative simplicity of their chemical or recombinant synthesis, peptides have emerged as adequate molecules for the mimicry of protein binding sites, as well as the inhibition of protein-protein interactions.     

Computer-based screening of functional conformers of proteins

A long-standing goal in biology is to establish the link between function, structure, and dynamics of proteins. Considering that protein function at the molecular level is understood by the ability of proteins to bind to other molecules, the limited structural data of proteins in association with other bio-molecules represents a major hurdle to understanding protein function at the structural level. Recent reports show that protein function can be linked to protein structure and dynamics through network centrality analysis, suggesting that the structures of proteins bound to natural ligands may be inferred computationally. In the present work, a new method is described to discriminate protein conformations relevant to the specific recognition of a ligand. The method relies on a scoring system that matches critical residues with central residues in different structures of a given protein. Central residues are the most traversed residues with the same frequency in networks derived from protein structures. We tested our method in a set of 24 different proteins and more than 260,000 structures of these in the absence of a ligand or bound to it. To illustrate the usefulness of our method in the study of the structure/dynamics/function relationship of proteins, we analyzed mutants of the yeast TATA-binding protein with impaired DNA binding. Our results indicate that critical residues for an interaction are preferentially found as central residues of protein structures in complex with a ligand. Thus, our scoring system effectively distinguishes protein conformations relevant to the function of interest.     

Supramolecularity creates nonstandard protein ligands

Congo red and a group of structurally related dyes long used to stain amyloid proteins are known to associate in water solutions. The self-association of some dyes belonging to this group appears particularly strong. In water solutions their molecules are arranged in ribbon-like micellar forms with liquid crystalline properties. These compounds have recently been found to form complexes with some native proteins in a non-standard way. Gaps formed by the local distribution of beta-sheets in proteins probably represent the receptor sites for these dye ligands. They may result from higher structural instability in unfolding conditions, but also may appear as long range cooperative fluctuations generated by ligand binding. Immunoglobulins G were chosen as model binding proteins to check the mechanism of binding of these dyes. The sites of structural changes generated by antigen binding in antibodies, believed to act as a signal propagated to distant parts of the molecule, were assumed to be suitable sites for the complexation of liquid-crystalline dyes. This assumption was confirmed by proving that antibodies engaged in immune complexation really do bind these dyes; as expected, this binding affects their function by significantly enhancing antigen binding and simultaneously inhibiting C1q attachment. Binding of these supramolecular dyes by some other native proteins including serpins and their natural complexes was also shown. The strict dependence of the ligation properties on strong self-assembling and the particular arrangement of dye molecules indicate that supramolecularity is the feature that creates non-standard protein ligands, with potential uses in medicine and experimental science.     

Searching for protein signatures using a multilevel alphabet

Short motifs are known to play diverse roles in proteins, such as in mediating the interactions with other molecules, binding to membranes, or conducting a specific biological function. Standard approaches currently employed to detect short motifs in proteins search for enrichment of amino acid motifs considering mostly the sequence information. Here, we presented a new approach to search for common motifs (protein signatures) which share both physicochemical and structural properties, looking simultaneously at different features. Our method takes as an input an amino acid sequence and translates it to a new alphabet that reflects its intrinsic structural and chemical properties. Using the MEME search algorithm, we identified the proteins signatures within subsets of protein which encompass common sequence and structural information. We demonstrated that we can detect enriched structural motifs, such as the amphipathic helix, from large datasets of linear sequences, as well as predicting common structural properties (such as disorder, surface accessibility, or secondary structures) of known functional‐motifs. Finally, we applied the method to the yeast protein interactome and identified novel putative interacting motifs. We propose that our approach can be applied for de novo protein function prediction given either sequence or structural information. Proteins 2013; © 2012 Wiley Periodicals, Inc.     

Annotating nucleic acid-binding function based on protein structure

Many of the targets of structural genomics will be proteins with little or no structural similarity to those currently in the database. Therefore, novel function prediction methods that do not rely on sequence or fold similarity to other known proteins are needed. We present an automated approach to predict nucleic-acid-binding (NA-binding) proteins, specifically DNA-binding proteins. The method is based on characterizing the structural and sequence properties of large, positively charged electrostatic patches on DNA-binding protein surfaces, which typically coincide with the DNA-binding-sites. Using an ensemble of features extracted from these electrostatic patches, we predict DNA-binding proteins with high accuracy. We show that our method does not rely on sequence or structure homology and is capable of predicting proteins of novel-binding motifs and protein structures solved in an unbound state. Our method can also distinguish NA-binding proteins from other proteins that have similar, large positive electrostatic patches on their surfaces, but that do not bind nucleic acids.     

How an epidermal growth factor (EGF)-like domain binds calcium. High resolution NMR structure of the calcium form of the NH2-terminal EGF-like domain in coagulation factor X.

Domains homologous to the epidermal growth factor (EGF) are important building blocks for extracellular proteins. Proteins containing these domains have been shown to function in such diverse biological processes as blood coagulation, complement activation, and the developmental determination of embryonic cell fates. Many of these proteins require calcium for their biological function. In the case of coagulation factors IX and X and anticoagulants proteins C and S, calcium has been found to bind to the EGF-like domains. We have now determined the three-dimensional structure of the calcium-bound form of the NH2-terminal EGF-like domain in coagulation factor X by two-dimensional NMR and simulated folding. Ligands to the calcium ion are the two backbone carbonyls in Gly-47 and Gly-64, as well as the side chains in Gln-49, erythro-beta-hydroxyaspartic acid (Hya) 63, and possibly Asp-46. The conserved Asp-48 is not a ligand in our present structures. The remaining ligands are assumed to be solvent molecules or, in the intact protein, ligands from neighboring domains. Other proteins interacting in a calcium-dependent manner may also contribute ligands. A comparison with the calcium-free form shows that calcium binding induces strictly local structural changes in the domain. Residues corresponding to the side chain ligands in factor X are conserved in many other proteins, such as the integral membrane protein TAN-1 of human lymphocytes and its developmentally important homolog, Notch, in Drosophila. Calcium binding to EGF-like domains may be crucial for numerous protein-protein interactions involving EGF-like domains in coagulation factors, plasma proteins, and membrane proteins. Therefore, there is reason to believe that this novel calcium site plays an important role in the biochemistry of extracellular proteins.     

Interaction-site prediction for protein complexes: a critical assessment

MOTIVATION: Proteins function through interactions with other proteins and biomolecules. Protein-protein interfaces hold key information toward molecular understanding of protein function. In the past few years, there have been intensive efforts in developing methods for predicting protein interface residues. A review that presents the current status of interface prediction and an overview of its applications and project future developments is in order. SUMMARY: Interface prediction methods rely on a wide range of sequence, structural and physical attributes that distinguish interface residues from non-interface surface residues. The input data are manipulated into either a numerical value or a probability representing the potential for a residue to be inside a protein interface. Predictions are now satisfactory for complex-forming proteins that are well represented in the Protein Data Bank, but less so for under-represented ones. Future developments will be directed at tackling problems such as building structural models for multi-component structural complexes.     

Structural stability of binding sites: Consequences for binding affinity and allosteric effects

During the course of biological function, proteins interact with other proteins, ligands, substrates, inhibitors, etc. These interactions occur at precisely defined locations within the protein but their effects are sometimes propagated to distal regions, triggering highly specific responses. These effects can be used as signals directed to activate or inhibit other sites, modulate interactions with other molecules, and/or establish inter‐molecular communication networks. During the past decade, it has become evident that the energy of stabilization of the protein structure is not evenly distributed throughout the molecule and that, under native conditions, proteins lack global cooperativity and are characterized by the occurrence of multiple independent local unfolding events. From a biological point of view, it is important to assess if this uneven distribution reflects specific functional requirements. For example, are binding sites more likely to be found in well structured regions, unstable regions, or mixed regions? In this article, we have addressed these questions by performing a structure‐based thermodynamic stability analysis of non‐structurally homologous proteins for which high resolution structures of their complexes with specific ligands are available. The results of these studies indicate that for all 16 proteins considered, the binding sites have a dual character and are characterized by the presence of regions with very low structural stability and regions with high stability. In many cases the low stability regions are loops that become stable and cover a significant portion of low molecular weight ligands upon binding. For enzymes, catalytic residues are usually, but not always, located in regions with high structural stability. It is shown that this arrangement provides significant advantages for the optimization of binding affinity of small ligands. In allosteric enzymes, low stability regions in the regulatory site are shown to play a crucial role in the transmission of information to the catalytic site. Proteins 2000;41:63–71. © 2000 Wiley‐Liss, Inc.     

A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction

Background  

Predicting which molecules can bind to a given binding site of a protein with known 3D structure is important to decipher the protein function, and useful in drug design. A classical assumption in structural biology is that proteins with similar 3D structures have related molecular functions, and therefore may bind similar ligands. However, proteins that do not display any overall sequence or structure similarity may also bind similar ligands if they contain similar binding sites. Quantitatively assessing the similarity between binding sites may therefore be useful to propose new ligands for a given pocket, based on those known for similar pockets.     

BiGGER: a new (soft) docking algorithm for predicting protein interactions

A new computationally efficient and automated "soft docking" algorithm is described to assist the prediction of the mode of binding between two proteins, using the three-dimensional structures of the unbound molecules. The method is implemented in a software package called BiGGER (Bimolecular Complex Generation with Global Evaluation and Ranking) and works in two sequential steps: first, the complete 6-dimensional binding spaces of both molecules is systematically searched. A population of candidate protein-protein docked geometries is thus generated and selected on the basis of the geometric complementarity and amino acid pairwise affinities between the two molecular surfaces. Most of the conformational changes observed during protein association are treated in an implicit way and test results are equally satisfactory, regardless of starting from the bound or the unbound forms of known structures of the interacting proteins. In contrast to other methods, the entire molecular surfaces are searched during the simulation, using absolutely no additional information regarding the binding sites. In a second step, an interaction scoring function is used to rank the putative docked structures. The function incorporates interaction terms that are thought to be relevant to the stabilization of protein complexes. These include: geometric complementarity of the surfaces, explicit electrostatic interactions, desolvation energy, and pairwise propensities of the amino acid side chains to contact across the molecular interface. The relative functional contribution of each of these interaction terms to the global scoring function has been empirically adjusted through a neural network optimizer using a learning set of 25 protein-protein complexes of known crystallographic structures. In 22 out of 25 protein-protein complexes tested, near-native docked geometries were found with C(alpha) RMS deviations < or =4.0 A from the experimental structures, of which 14 were found within the 20 top ranking solutions. The program works on widely available personal computers and takes 2 to 8 hours of CPU time to run any of the docking tests herein presented. Finally, the value and limitations of the method for the study of macromolecular interactions, not yet revealed by experimental techniques, are discussed.