Studies of macromolecular heterogeneous associations involving cross-linking: a re-examination of the ovalbumin-lysozyme system

A system is considered in which a multivalent acceptor interacts with a bivalent ligand in solution to form an array of complexes via multiple binding and cross-linking reactions. With the use of reacted site probability functions expressions are derived in terms of a site binding constant which are of potential use in the interpretation of sedimentation equilibrium and binding results obtained with such systems. Their potential use is explored in relation to results obtained on the interacting ovalbumin-lysozyme system at pH 6.80, ionic strength 0.02. A comparison is made of this interpretation with that based on an interaction pattern involving only multiple binding of ligand in the absence of cross-linking effects. While both interpretations quantitatively describe certain results, it is shown, by invoking further experimental observations on apparent weight-average molecular weight and precipitation behavior, that the more favored interpretation is that involving the operation of a spectrum of forces leading to a large array of ovalbumin-lysozyme complexes, including those of the cross-linked type. It is stressed that the particular ovalbumin-lysozyme system is but one example of interaction between oppositely charged macromolecules and therefore that the derived equations may find wider application to such systems and those known to involve more specific cross-linking interactions.     

Design and synthesis of a multivalent homing device for targeting to murine CD22

CD22 is a cell-surface glycoprotein uniquely located on mature B-cells and B-cell derived tumour cells. Current evidence suggests that binding of endogenous ligands to CD22 leads to modulation of B-cell activation by antigen. Incidentally, however, B-cell activation may derail. and lead to an undesired immune response, for example in cases of allergy, rheumatoid arthritis and Crohn's disease. In this situation, synthetic high-affinity ligands for CD22 may be of therapeutic value as inhibitors of B-cell activation. Recent studies have revealed that natural ligands for CD22 contain the trisaccharide NeuAc alpha-2,6-Lac as the basic binding motif. In addition, it has been demonstrated that binding to CD22 is strongly enhanced by multivalent presentation of the basic binding motif (cluster effect). In this paper. the stepwise development of a novel multivalent high-affinity ligand for CD22 is described. In the first stage, a series of monovalent NeuAc alpha-2,6-Glc(Y)X type binding motifs was prepared, and their affinity for murine CD22 was monitored, to obtain more insight into the effect of separate structure elements on ligand recognition. In the second stage, we prepared a trivalent cluster, based on the monovalent motif that displayed the highest affinity for CD22, NeuAc alpha-2,6-GlcNBzNO2OMe (7). This cluster, TRIS(NeuAc alpha-2,6-GlcNBzNO2)3 (52), displayed a more than 58-fold higher affinity for CD22 than the reference structure NeuAc alpha-2,6-LacOMe (10). To our knowledge, the cluster 52 is one of the most potent antagonists for CD22 yet synthesised.     

Selective immobilization of multivalent ligands for surface plasmon resonance and fluorescence microscopy

Cell surface multivalent ligands, such as proteoglycans and mucins, are often tethered by a single attachment point. In vitro, however, it is difficult to immobilize multivalent ligands at single sites due to their heterogeneity. Moreover, multivalent ligands often lack a single group with reactivity orthogonal to other functionality in the ligand. Biophysical analyses of multivalent ligand-receptor interactions would benefit from the availability of strategies for uniform immobilization of multivalent ligands. To this end, we report the design and synthesis of a multivalent ligand that has a single terminal orthogonal functional group and we demonstrate that this material can be selectively immobilized onto a surface suitable for surface plasmon resonance (SPR) experiments. The polymeric ligand we generated displays multiple copies of 3,6-disulfogalactose, and it can bind to the cell adhesion molecules P- and L-selectin. Using SPR measurements, we found that surfaces displaying our multivalent ligands bind specifically to P- and L-selectin. The affinities of P- and L-selectin for surfaces displaying the multivalent ligand are five- to sixfold better than the affinities for a surface modified with the corresponding monovalent ligand. In addition to binding soluble proteins, surfaces bearing immobilized polymers bound to cells displaying L-selectin. Cell binding was confirmed by visualizing adherent cells by fluorescence microscopy. Together, our results indicate that synthetic surfaces can be created by selective immobilization of multivalent ligands and that these surfaces are capable of binding soluble and cell-surface-associated receptors with high affinity.     

Statistical fluctuations in processes of gene expression regulation: consideration of the problem from point of view of statistical mechanics

The regulation of gene expression is a basic problem of biology. In some cases, the gene activity is regulated by specific binding of regulatory proteins to DNA. In terms of statistical mechanics, this binding is described as the process of adsorption of ligands on the one-dimensional lattice and has a probability nature. As a random physical process, the adsorption of regulatory proteins on DNA introduces a noise to the regulation of gene activity. We derived equations, which make it possible to estimate this noise in the case of the binding of the lac repressor to the operator and showed that these estimates correspond to experimental data. Many ligands are able to bind nonspecifically to DNA. Nonspecific binding is characterized by a lesser equilibrium constant but a greater number of binding sites on the DNA, as compared with specific binding. Relations are presented, which enable one to estimate the probability of the binding of a ligand on a specific site and on nonspecific sites on DNA. The competition between specific and nonspecific binding of regulatory proteins plays a great role in the regulation of gene activity. Similar to the one-dimensional "lattice gas" of particles, ligands adsorbed on DNA produce "one-dimensional" pressure on proteins located at the termini of free regions of DNA. This pressure, an analog of osmotic pressure, may be of importance in processes leading to changes in chromatin structure and activation of gene expression.     

Pleomorphic Ensembles: Formation of Large Clusters Composed of Weakly Interacting Multivalent Molecules

Molecular interactions of importance to cell biology are subject to sol-gel transitions: large clusters of weakly interacting multivalent molecules (gel phase) are produced at a critical concentration of monomers. Examples include cell-cell and cell-matrix adhesions, nucleoprotein bodies, and cell signaling platforms. We use the term pleomorphic ensembles (PEs) to describe these clusters, because they have dynamic compositions and sizes and have rapid turnover of their molecular constituents; this plasticity can be highly responsive to cellular signals. The classical polymer physical chemistry theory developed by Flory and Stockmayer provides a brilliant framework for treating multivalent interactions for simple idealized systems. But the complexity and variability of PEs challenges existing modeling approaches. Here we describe and validate a computational algorithm that extends the Flory-Stockmayer formalism to overcome the limitations of analytic theories. We divide the problem by deterministically calculating the fraction of bound sites for each type of binding site, followed by the stochastic assignment of the bonds to a finite number of molecules. The method allows for high valency within many different kinds of interacting molecules and site types, permits simulation of steady-state distributions, as well as assembly kinetics, and can treat cooperative binding within one of the interacting molecules. We then apply our method to the analysis of interactions in the nephrin-Nck-N-Wasp signaling system, demonstrating how multivalent layered scaffolds produce PEs at low monomer concentrations despite weak binding interactions. We show how the experimental data for this system are most consistent with synergistic cooperative interactions between Nck and N-Wasp.     

Pleomorphic Ensembles: Formation of Large Clusters Composed of Weakly Interacting Multivalent Molecules

Molecular interactions of importance to cell biology are subject to sol-gel transitions: large clusters of weakly interacting multivalent molecules (gel phase) are produced at a critical concentration of monomers. Examples include cell-cell and cell-matrix adhesions, nucleoprotein bodies, and cell signaling platforms. We use the term pleomorphic ensembles (PEs) to describe these clusters, because they have dynamic compositions and sizes and have rapid turnover of their molecular constituents; this plasticity can be highly responsive to cellular signals. The classical polymer physical chemistry theory developed by Flory and Stockmayer provides a brilliant framework for treating multivalent interactions for simple idealized systems. But the complexity and variability of PEs challenges existing modeling approaches. Here we describe and validate a computational algorithm that extends the Flory-Stockmayer formalism to overcome the limitations of analytic theories. We divide the problem by deterministically calculating the fraction of bound sites for each type of binding site, followed by the stochastic assignment of the bonds to a finite number of molecules. The method allows for high valency within many different kinds of interacting molecules and site types, permits simulation of steady-state distributions, as well as assembly kinetics, and can treat cooperative binding within one of the interacting molecules. We then apply our method to the analysis of interactions in the nephrin-Nck-N-Wasp signaling system, demonstrating how multivalent layered scaffolds produce PEs at low monomer concentrations despite weak binding interactions. We show how the experimental data for this system are most consistent with synergistic cooperative interactions between Nck and N-Wasp.     

Studies on the binding sites of IgG2 monoclonal antibodies recognized by terpyridine‐based affinity ligands

This investigation has examined the origin of the molecular recognition associated with the interaction of monoclonal IgG2's with terpyridine‐based ligands immobilized onto agarose‐derived chromatographic adsorbents. Isothermal titration calorimetric (ITC) methods have been employed to acquire thermodynamic data associated with the IgG2‐ligand binding. These ITC investigations have documented that different enthalpic and entropic processes are involved depending on the nature of the chemical substituents in the core structure of the terpyridinyl moiety. In addition, molecular docking studies have been carried out with IgG2 structures with the objective to identify possible ligand binding sites and key interacting amino acid residues. These molecular docking experiments with the different terpyridine‐based ligands have shown that all of the examined ligands can potentially undergo favorable interactions with a site located within the Fab region of the IgG2. However, another favorable binding site was also identified from the docking poses to exist within the Fc region of the IgG2 for some, but not all, of the ligands studied. These investigations have provided a basis to elucidate the unique binding properties and chromatographic behaviors shown by several substituted terpyridine ligands in their interaction with IgGs of different isotype. Copyright © 2016 John Wiley & Sons, Ltd.     

Database of protein complexes with multivalent binding ability: Bival‐bind

Phenomena of multivalent binding of ligands with receptors are ubiquitous in biology and of growing interest in material sciences. Multivalency can enhance binding affinity dramatically. To understand the mechanism of multivalent binding in more detail model systems of bi‐ and multivalent receptors are needed, but are difficult to find. Furthermore it is useful to know about multivalent receptors, which can serve as targets to design multivalent drugs. The present contribution tries to close this gap. The Bival‐Bind database ( http://agknapp.chemie.fu‐berlin.de/bivalbind ) provides a relatively complete list – 2073 protein complexes with less than 90% sequence identity – out of the protein database, which can serve as bi‐ or multivalent receptors. Steric clashes of molecular spacers – necessary to connect the monomeric ligand units – with the receptor surface can diminish binding affinity dramatically and, thus, abolish the expected enhancement of binding affinity due to the multivalency. The potential multivalent receptors in the Bival‐Bind database are characterized with respect to the receptor surface topography. A height profile between the receptor binding pockets is provided, which is an important information to estimate the influence of unfavorable spacer receptor interaction. Proteins 2014; 82:744–751. © 2013 Wiley Periodicals, Inc.     

Graphical analysis of binding data reflecting competition between two ligands for the same acceptor sites

A theoretical expression is derived for the analysis of results from competitive binding studies in which two multivalent ligands compete for acceptor sites, and a linear transform is suggested for simple graphical representation and assessment of experimental results. The protocol is illustrated by application to competitive binding data, obtained by ultrafiltration, on the interactions of bovine serum albumin with two structurally similar organic anions, methyl orange and methyl red. In a second experimental study the present approach is then used to establish that lactate dehydrogenase and aldolase compete for the same myofibrillar sites of bovine cardiac muscle. Finally, numerically simulated behavior of systems with additional binding sites for either ligand is used to emphasize that the criterion for classical (complete) competition is agreement between an experimentally determined equilibrium constant for ligand binding and the apparent value deduced from competitive binding studies. Nevertheless, the present analysis of competitive binding data should still offer considerable scope for screening quantitatively the cross-reactivities of drug and antigen analogs for their respective specific protein-acceptor sites.     

Use of binding site neighbor-effect parameters to evaluate the interactions between adjacent ligands on a linear lattice. Effects on ligand-lattice association.

A method using binding site "neighbor-effect" parameters (NEPs) is introduced to evaluate the effects of interaction between adjacent ligands on their binding to an infinite linear lattice. Binding site overlap is also taken into account. This enables the conditional probability approach of McGhee & von Hippel to be extended to more complex situations. The general equation for the isotherm is v/LF = SFKF, where v is the ratio of bound ligands to lattice residues, LF is the free ligand concentration, SF is the fraction of binding sites that are free, and KF is the average association constant of a free site. Solutions are derived for three cases: symmetric ligands, and asymmetric ligands on isotropic or anisotropic lattices. For symmetric ligands there is one NEP, E, which is the ratio of the average binding affinity of a free site if the status of the lattice residue neighboring one end of the site is unspecified (left to chance) to the affinity when this residue is free (holding the other neighbor constant). Thus KF is KE2, where K is the affinity of an isolated site. If a site is n residues long, SF is f ffn-1, where f = 1 - nv is the fraction of residues that are free and ff is the conditional probability that a free residue is bordered on a given side by another free residue. The expression for ff is 1/(1 + x/E), where x is v/f, E is (1 - x + [(1 - x)2 + 4x omega]1/2)/2, and omega is the co-operativity parameter. The binding of asymmetric ligands to an isotropic lattice is described by two NEPs; the last case involves four NEPs and a bound ligand orientation parameter. For each case, the expected length distribution of clusters of bound ligands can be calculated as a function of v. When Scatchard plots with the same intercepts and initial slope are compared, it is found that ligand asymmetry lowers the isotherm (relative to the corresponding symmetric ligand isotherm), whereas lattice anisotrophy raises it.     

Sequence-defined glycopolymer segments presenting mannose: synthesis and lectin binding affinity

We present for the first time the synthesis of sequence-defined monodisperse glycopolymer segments via solid-phase polymer synthesis. Functional building blocks displaying alkyne moieties and hydrophilic ethylenedioxy units were assembled stepwise on solid phase. The resulting polymer segments were conjugated with mannose sugars via 1,3-dipolar cycloaddition. The obtained mono-, di-, and trivalent mannose structures were then subject to Con A lectin binding. Surface plasmon resonance studies showed a nonlinear increase in binding regarding the number and spacing of sugar ligands. The results of Con A lectin binding assays indicate that the chemical composition of the polymeric scaffold strongly contributes to the binding activities as well as the spacing between the ligands and the number of presented mannose units. Our approach now allows for the synthesis of highly defined glycooligomers and glycopolymers with a diversity of properties to investigate systematically multivalent effects of polymeric ligands.     

Prediction of IgE(Lb4)–ligand complex structures by automated docking

A mouse monoclonal anti-2,4,6-trinitrophenyl IgE (clone Lb4) was screened with a random set of over 2000 compounds, and several ligands were found to bind with affinities comparable to that of the immunizing hapten (K_D in the μM range). An automated docking algorithm was used for the prediction of complex structures formed by 2,4-dinitrophenyl (DNP) and non-DNP ligands in the fragment variable region of IgE(Lb4). All ligands were found to dock in an L-shaped cavity of 15 × 16 × 10 Å, surrounded by complementary-determining regions L1, L3, H2 and H3. The ligands were found to occupy the same binding site in different orientations. For rigid ligands the most stable orientation could be predicted with high probability, based on the calculated energy of binding and the occurrence frequencies of identical complexes obtained by repeated simulations. The localization of a flexible ligand (cycrimine-R) was more ambiguous, but it still docked in the same site. The results support a model for heteroligating antibody (Ab) binding sites, where different ligands utilize the total set of available contacts in different combinations. It is suggested that although pseudoenergies calculated by the docking algorithm do not correlate with experimentally measured binding energies, the screening-and-docking procedure can be useful for the mapping of Ab and other receptor binding sites ligating small molecules.     

Identification of Novel Contributions to High-affinity Glycoprotein-Receptor Interactions using Engineered Ligands

Engineered receptor fragments and glycoprotein ligands employed in different assay formats have been used to dissect the basis for the dramatic enhancement of binding of two model membrane receptors, dendritic cell-specific intercellular adhesion molecule 3-grabbing nonintegrin (DC-SIGN) and the macrophage galactose lectin, to glycoprotein ligands compared to simple sugars. These approaches make it possible to quantify the importance of two major factors that combine to enhance the affinity of single carbohydrate-recognition domains (CRDs) for glycoprotein ligands by 100-to 300-fold. First, the presence of extended binding sites within a single CRD can enhance interaction with branched glycans, resulting in increases of fivefold to 20-fold in affinity. Second, presentation of glycans on a glycoprotein surface increases affinity by 15-to 20-fold, possibly due to low-specificity interactions with the surface of the protein or restriction in the conformation of the glycans. In contrast, when solution-phase networking is avoided, enhancement due to binding of multiple branches of a glycan to multiple CRDs in the oligomeric forms of these receptors is minimal and binding of a receptor oligomer to multiple glycans on a single glycoprotein makes only a twofold contribution to overall affinity. Thus, in these cases, multivalent interactions of individual glycoproteins with individual receptor oligomers have a limited role in achieving high affinity. These findings, combined with considerations of membrane receptor geometry, are consistent with the idea that further enhancement of the binding to multivalent glycoprotein ligands requires interaction of multiple receptor oligomers with the ligands.     

Comparison of approaches to combine species distribution models based on different sets of predictors

Distribution models should take into account the different limiting factors that simultaneously influence species ranges. Species distribution models built with different explanatory variables can be combined into more comprehensive ones, but the resulting models should maximize complementarity and avoid redundancy. Our aim was to compare the different methods available for combining species distribution models. We modelled 19 threatened vertebrate species in mainland Spain, producing models according to three individual explanatory factors: spatial constraints, topography and climate, and human influence. We used five approaches for model combination: Bayesian inference, Akaike weight averaging, stepwise variable selection, updating, and fuzzy logic. We compared the performance of these approaches by assessing different aspects of their classification and discrimination capacity. We demonstrated that different approaches to model combination give rise to disparities in the model outputs. Bayesian integration was systematically affected by an error in the equations that are habitually used in distribution modelling. Akaike weights produced models that were driven by the best single factor and therefore failed at combining the models effectively. The updating and the stepwise approaches shared recalibration as the basic concept for model combination, were very similar in their performance, and showed the highest sensitivity and discrimination capacity. The fuzzy‐logic approach yielded models with the highest classification capacity according to Cohen's kappa. In conclusion: 1) Bayesian integration, employing the currently used equation, and the Akaike weight procedure should be avoided; 2) the updating and stepwise approaches can be considered minor variants of the same recalibrating approach; and 3) there is a trade‐off between this recalibrating approach, which has the highest sensitivity, and fuzzy logic, which has the highest overall classification capacity. Recalibration is better if unfavourable conditions in one environmental factor may be counterbalanced with favourable conditions in a different factor, otherwise fuzzy logic is better.     

Switches of hydrogen bonds during ligand–protein association processes determine binding kinetics

Revealing the processes of ligand–protein associations deepens our understanding of molecular recognition and binding kinetics. Hydrogen bonds (H‐bonds) play a crucial role in optimizing ligand–protein interactions and ligand specificity. In addition to the formation of stable H‐bonds in the final bound state, the formation of transient H‐bonds during binding processes contributes binding kinetics that define a ligand as a fast or slow binder, which also affects drug action. However, the effect of forming the transient H‐bonds on the kinetic properties is little understood. Guided by results from coarse‐grained Brownian dynamics simulations, we used classical molecular dynamics simulations in an implicit solvent model and accelerated molecular dynamics simulations in explicit waters to show that the position and distribution of the H‐bond donor or acceptor of a drug result in switching intermolecular and intramolecular H‐bond pairs during ligand recognition processes. We studied two major types of HIV‐1 protease ligands: a fast binder, xk263, and a slow binder, ritonavir. The slow association rate in ritonavir can be attributed to increased flexibility of ritonavir, which yields multistep transitions and stepwise entering patterns and the formation and breaking of complex H‐bond pairs during the binding process. This model suggests the importance of conversions of spatiotemporal H‐bonds during the association of ligands and proteins, which helps in designing inhibitors with preferred binding kinetics. Copyright © 2014 John Wiley & Sons, Ltd.     

Membrane IgM-mediated signaling of human B cells. Effect of increased ligand binding site valency on the affinity and concentration requirements for inducing diverse stages of activation.

The potential for ligand-initiated signal transduction through B cell membrane IgM is assessed in terms of ligand concentration, binding site valency, and binding site affinity for membrane Ig. Estimates of the physicochemical requirements for achieving G0* enhancement of class II MHC expression, G1 entry, and S phase entry in human B cells were made by comparing the stimulatory effects of three affinity-diverse anti-Cmu2 mAb when in bivalent (unconjugated) form, or as mAb-dextran conjugates with low binding site valency (oligovalent ligands) or high binding site valency (multivalent ligands). An increase in binding site number (and concomitant molecular mass) caused a profound reduction in both the minimal concentration and affinity requisites for B cell activation. The enhancing effect of increased binding site valency was most evident for the signaling of those most distal stages in B cell activation, i.e., G1 and S phase, which were difficult to induce with bivalent ligands. The results suggest that highly multimeric TI-2 Ag may be good immunogens because they are able to elicit a full activation response not only from infrequent high affinity B cells, but also from a substantial proportion of the many lower affinity Ag-specific B cells in virgin B cell populations. Interestingly, the activation of B cells by ligands with binding sites of high intrinsic affinity (Ka = 5 x 10(8) M-1) was less influenced by increases in binding site valency than was B cell activation by ligands with intermediate binding site affinity (Ka = 2 x 10(7) M-1). This suggests that the minimal epitope valency requirement for T cell-independent B cell activation by mIg cross-linking Ag may be dependent on the intrinsic affinity with which membrane Ig molecules on a given B cell interact with the redundantly expressed epitopes.     

An application of CIFAP for predicting the binding affinity of Chk1 inhibitors derived from 2‐aminothiazole‐4‐carboxamide

Investigation of protein‐ligand interactions obtained from experiments has a crucial part in the design of newly discovered and effective drugs. Analyzing the data extracted from known interactions could help scientists to predict the binding affinities of promising ligands before conducting experiments. The objective of this study is to advance the CIFAP (compressed images for affinity prediction) method, which is relevant to a protein‐ligand model, identifying 2D electrostatic potential images by separating the binding site of protein‐ligand complexes and using the images for predicting the computational affinity information represented by pIC₅₀ values. The CIFAP method has 2 phases, namely, data modeling and prediction. In data modeling phase, the separated 3D structure of the binding pocket with the ligand inside is fitted into an electrostatic potential grid box, which is then compressed through 3 orthogonal directions into three 2D images for each protein‐ligand complex. Sequential floating forward selection technique is performed for acquiring prediction patterns from the images. In the prediction phase, support vector regression (SVR) and partial least squares regression are used for testing the quality of the CIFAP method for predicting the binding affinity of 45 CHK1 inhibitors derived from 2‐aminothiazole‐4‐carboxamide. The results show that the CIFAP method using both support vector regression and partial least squares regression is very effective for predicting the binding affinities of CHK1‐ligand complexes with low‐error values and high correlation. As a future work, the results could be improved by working on the pose of the ligands inside the grid.     

Cooperative effects during the binding of large ligands with DNA. Non-contact interaction between adsorbed ligands

Equations are derived to describe the cooperative binding of large ligands to DNA. A mathematical approach is developed which enables one to give a simple probabilistic interpretation of binding equations and to solve them in the general case when long-range interactions are allowed between bound ligands. These interactions can be mediated by conformation changes induced in the DNA in the course of binding process and transformed over some distances beyond the DNA region immediately covered by a bound ligand molecule (allosteric effect of DNA). Interactions between ligand molecules can be formally described in terms of model potential characterizing pairwise interactions between bound ligands. A procedure is developed which allows one to determined the form of such potential from experimentally measured binding isotherms. It is based on a comparison of experimental binding isotherms with the appropriate curves calculated for the case of non-interacting ligands.