A simple method for calculating the dissociation constant of a receptor (or enzyme).unlabeled ligand complex from radioligand displacement measurements

A general procedure is described for determining the dissociation constant of a receptor (or enzyme).unlabeled ligand complex (EI) by analyzing the I-dependent displacement of bound radioligand (A*) from EA*. The procedure (which involves measuring free A* in the presence of I) requires a knowledge of the total concentrations of receptor ([E]t), unlabeled ligand ([I]t) and radioligand ([A*]t), and the dissociation constant of the EA* complex. The unknown Kd is obtained from five simple, sequential calculations which are valid for either high or low affinity competitive unlabeled ligands and are independent of total receptor concentration or initial degree of saturation with A*. The procedure also provides the information needed to construct a distribution curve of all enzyme and ligand species (E, EA*, EI, A*, I) as [I]t is varied.     

Probing a model of a GPCR/ligand complex in an explicit membrane environment: the human cholecystokinin-1 receptor

A three-dimensional model structure of a complex formed by a G-protein-coupled receptor (GPCR) and an agonist ligand is probed and refined using molecular-dynamics simulations and free energy calculations in a realistic environment. The model of the human receptor of cholecystokinin associated to agonist ligand CCK9 was obtained from a synergistic procedure combining site-directed mutagenesis experiments and in silico modeling. The 31-ns molecular-dynamics simulation in an explicit membrane environment indicates that both the structure of the receptor and its interactions with the ligand are robust. Whereas the secondary structure of the alpha-helix bundle is well preserved, the region of the intracellular loops exhibits a significant flexibility likely to be ascribed to the absence of G-protein subunits in the model. New insight into the structural features of the binding pocket is gained, in particular, the interplay of the ligand with both the receptor and internal water molecules. Water-mediated interactions are shown to participate in the binding, hence, suggesting additional site-directed mutagenesis experiments. Accurate free energy calculations on mutated ligands provide differences in the receptor-ligand binding affinity, thus offering a direct, quantitative comparison to experiment. We propose that this detailed consistency-checking procedure be used as a routine refinement step of in vacuo GPCR models, before further investigation and application to structure-based drug design.     

A simple and rapid orientation procedure for the estimation of affinities (1/Kd) and maximum binding capacities (Bmax) of ligand binding to two receptor subpopulations

This paper describes a simple and rapid procedure for the estimation of specific parameters (dissociation constants, Kd and maximum binding capacities, Bmax) of ligand binding to two receptor subpopulations. This procedure provides, in a few minutes, the investigator, performing the actual binding studies, the necessary information about receptor heterogeneity, enabling the investigator to plan further experiments. The procedure is based on the graphical comparison of experimental binding data (ligand binding to one or two receptor subpopulations) with the theoretical values of ligand binding to one receptor population at four levels). The values of Kd and Bmax for high- and low-affinity receptors are derived from 4 horizontal deviations of experimental data from a theoretical data plot at these levels by their comparison with tabulated deviations. The correctness of the estimated parameters can be confirmed by the comparison of experimental data with those simulated on the basis of applying the values of Kd and Bmax found in the formula for ligand binding to two receptor subpopulations. The practical applicability of this procedure was demonstrated both on simulated and experimental data, and confirmed by the well known computer programs for evaluating receptor heterogeneity, namely "LIGAND" and "Affinity spectra".     

Study of a structurally similar kappa opioid receptor agonist and antagonist pair by molecular dynamics simulations

Among the structurally similar guanidinonaltrindole (GNTI) compounds, 5′-GNTI is an antagonist while 6′-GNTI is an agonist of the κOR opioid receptor. To explore how a subtle alteration of the ligand structure influences the receptor activity, we investigated two concurrent processes: the final steps of ligand binding at the receptor binding site and the initial steps of receptor activation. To trace these early activation steps, the membranous part of the receptor was built on an inactive receptor template while the extracellular loops were built using the ab initio CABS method. We used the simulated annealing procedure for ligand docking and all-atom molecular dynamics simulations to determine the immediate changes in the structure of the ligand–receptor complex. The binding of an agonist, in contrast to an antagonist, induced the breakage of the “3–7 lock” between helices TM3 and TM7. We also observed an action of the extended rotamer toggle switch which suggests that those two switches are interdependent.     

Kinetic aspects of l-quinuclidinyl benzilate interaction with muscarinic receptor

l-Quinuclidinyl benzilate is undoubtedly the most widely used radioactive reporter ligand for studies on muscarinic receptor. In the present Commentary the kinetic aspects of the interaction of this ligand with muscarinic receptor are summarized. On the basis of these results a kinetic mechanism has been proposed involving consequential isomerization of the receptor-ligand complex and cooperative regulation of this process by the excess of the ligand. In addition, the data give evidence of at least two different types of binding sites on the receptor. Owing to the solubilization of the receptor protein there occur remarkable changes in its kinetic properties. The kinetic analysis points to inadequacy of the simple one-step equilibrium binding scheme for l-quinuclidinyl benzilate interaction with muscarinic receptor, which may explain the apparently contradictory data in the literature, such as the large scattering of the K_d values and the different regularities described in the case of the receptor-ligand complex dissociation reaction. That points to the conclusion that l-quinuclidinyl benzilate is an “inconvenient” ligand for receptor studies, which call for true equilibrium conditions of the system.     

Cytochrome P-450-dependent 14 alpha-demethylation of lanosterol in Candida albicans.

Analysis of receptor-ligand binding characteristics can be greatly hampered by the presence of non-specific binding, defined as low-affinity binding to non-receptor domains which is not saturable within the range of ligand concentrations used. Conventional binding analyses, e.g. according to the methods described by Scatchard or Klotz, relate the amount of specific receptor-ligand binding to the concentration of free ligand, and therefore require assumptions on the amount of non-specific binding. In this paper a method is described for determining the parameters of specific receptor-ligand interaction which does not require any assumption or separate determination of the amount of non-specific binding. If the concentration of labelled free ligand is constant, a plot of Fu/(B0*-B*) versus Fu yields a linear relationship, in the case of a single receptor class, in which Fu is the concentration of unlabelled free ligand, B0* is the total amount of labelled bound ligand in the absence of unlabelled ligand and B* is the total amount of labelled bound ligand in the presence of an unlabelled ligand concentration Fu; all of these data are readily obtained from binding studies. This linear relationship holds irrespective of the amount of non-specific binding, and the values for receptor density, ligand dissociation constant and a constant for non-specific binding can be readily obtained from it. If the concentration of labelled free ligand is not a constant for all data points, data are first converted according to a straightforward normalization procedure to permit the use of this relationship. The presence of multiple receptor classes with dissociation constants in the range of the ligand concentrations used results in a negative deviation from this linearity, and therefore the presence of multiple receptor classes can be discriminated unequivocally from non-specific binding. Both theoretical and practical advantages of the present method are described. The method, which will be referred to as the linear subtraction method, is illustrated using the binding of tumour promoters and polypeptide growth factors to their specific cellular receptors.     

Structure of the complement factor 5a receptor-ligand complex studied by disulfide trapping and molecular modeling

Complement factor 5a (C5a) is an anaphylatoxin that acts by binding to a G protein-coupled receptor, the C5aR. The relative orientation of this ligand-receptor pair is investigated here using the novel technique of disulfide trapping by random mutagenesis (DTRM) and molecular modeling. In the DTRM technique, an unpaired cysteine is introduced in the ligand, and a library of randomly mutagenized receptors is screened to identify mutants that introduce a cysteine at a position in the receptor that allows functional interactions with the ligand. By repeating this analysis at six positions of C5a, we identify six unique sets of intermolecular interactions for the C5a-C5aR complex, which are then compared with an independently developed computational three-dimensional model of the complex. This analysis reveals that the interface of the receptor N terminus with the cysteine-containing ligand molecules is selected from a variety of possible receptor conformations that exist in dynamic equilibrium. In contrast, DTRM identifies a single position in the second extracellular loop of the receptor that interacts specifically with a cysteine probe placed in the C-terminal tail of the C5a ligand.     

The isolation of human beta-interferon receptor by wheat germ lectin affinity and immunosorbent column chromatographies

Radioiodinated human beta-interferon-Ser 17 (Betaseron) was reversibly cross-linked to Daudi cells by dithiobis(succinimidylpropionate). The radioactive ligand was cross-linked to three macromolecules forming labeled complexes of apparent Mr values of 130,000, 220,000, and 320,000. Betaseron, human alpha-interferon, human interleukin 2 but not recombinant human gamma-interferon competed with the labeled ligand for binding to these putative receptor(s). Human leukocyte-produced gamma-interferon competed weakly with 125I-Betaseron for binding to Daudi cells. The Betaseron-receptor complex(es) was purified by passage through a wheat germ lectin column followed by chromatography on an anti-interferon immunosorbent column and semipreparative gel electrophoresis. The cross-linked ligand-receptor complex was shown to be highly purified by sodium dodecyl sulfate and acetic acid:urea:Triton X-100 polyacrylamide gel electrophoresis. It can be dissociated into the labeled Betaseron (Mr = 17,000) ligand and a receptor moiety which has an apparent molecular weight of 110,000. The chromatographic behavior of the ligand-receptor complex on wheat germ lectin column suggests that the receptor is a glycoprotein. The described procedure yielded about 1 microgram of Betaseron receptor from 10(10) Daudi cells, estimated to contain a maximum of about 15 micrograms of the receptor.     

Modeling G protein‐coupled receptors for structure‐based drug discovery using low‐frequency normal modes for refinement of homology models: Application to H3 antagonists

G Protein‐Coupled Receptors (GPCRs) are integral membrane proteins that play important role in regulating key physiological functions, and are targets of about 50% of all recently launched drugs. High‐resolution experimental structures are available only for very few GPCRs. As a result, structure‐based drug design efforts for GPCRs continue to rely on in silico modeling, which is considered to be an extremely difficult task especially for these receptors. Here, we describe Gmodel, a novel approach for building 3D atomic models of GPCRs using a normal mode‐based refinement of homology models. Gmodel uses a small set of relevant low‐frequency vibrational modes derived from Random Elastic Network model to efficiently sample the large‐scale receptor conformation changes and generate an ensemble of alternative models. These are used to assemble receptor–ligand complexes by docking a known active into each of the alternative models. Each of these is next filtered using restraints derived from known mutation and binding affinity data and is refined in the presence of the active ligand. In this study, Gmodel was applied to generate models of the antagonist form of histamine 3 (H3) receptor. The validity of this novel modeling approach is demonstrated by performing virtual screening (using the refined models) that consistently produces highly enriched hit lists. The models are further validated by analyzing the available SAR related to classical H3 antagonists, and are found to be in good agreement with the available experimental data, thus providing novel insights into the receptor–ligand interactions. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

A molecular model for singlet/singlet energy transfer of monovalent ligand/receptor interactions

A stochastic model is described that predicts the degree of singlet/singlet energy transfer in complexes formed between monovalent ligands and monovalent receptors. The modeling approach is intended to serve as an analytical tool for approximating the level of fluorescence quenching that can be expected to occur in fluorescently labeled monovalent ligands and receptors that are bound together in complexes. This approach has utility in areas such as modeling protein/protein interactions and designing fluorescence energy transfer assays.Using the crystallographic data for papain (monovalent ligand ) and concanavalin A (monovalent receptor ) along with a molecular graphics computational package the ligand and receptor were docked together to form a ligand/receptor complex. The intermolecular distances between the lysine resides of the ligand and receptor were then estimated, receptor complex was calculated assuming a value for the characteristic length R(0) of the donor/acceptor pair. Results from the stochastic model were used to calculate the level of fluorescence quenching one would expect for a resonance energy transfer competition assay based on the monovalent ligand/pair.Three key assumptions were made during the model development. First, all lysine resides for the ligand and receptor were equally reactive with the dye molecules so the stoichiometry of the donor and acceptor chromophores was governed by a binomial distribution. Second, the dye molecules were located at the alpha-carbon position for each reactive lysine residue. Finally, in the energy transfer competition assay, it was assumed that equilibrium existed between the ligand, receptor, and competing hapten at all times. Based on these assumptions, results are presented that indicate the maximum energy transfer for the monovalent papain/concanavalin. A complex is strongly dependent on the number of acceptor chromophores and on the value of R(0). Results are also presented on the approximate level of fluorescence quenching that may occur in a competition assay based on the papin/pConA complex. Lastly, a strategy is discussed for maximizing the dynamic range and linearity of energy transfer assays by optimizing several key design variables.     

Modeling molecular mechanisms of binding of the anaphylatoxin C5a to the C5a receptor

This study presents the 3D model of the complex between the anaphylatoxin C5a and its specific receptor, C5aR. This is the first 3D model of a G-protein-coupled receptor (GPCR) complex with a peptide ligand deduced by a molecular modeling procedure analyzing various conformational possibilities of the extracellular loops and the N-terminal segment of the GPCR. The modeling results indicated two very different ways of interacting between C5a and C5aR at the two interaction sites suggested earlier based on the data of site-directed mutagenesis. Specifically, C5a and C5aR can be involved in "mutual-induced fit", where the interface between the molecules is determined by both the receptor and the ligand. The rigid core of the C5a ligand selects the proper conformations of the highly flexible N-terminal segment of C5aR (the first interaction site). At the same time, the binding conformation of the flexible C-terminal fragment of C5a is selected by well-defined interactions with the TM region of the C5aR receptor (the second interaction site). The proposed 3D model of C5a/C5aR complex was built without direct use of structural constraints derived from site-directed mutagenesis reserving those data for validation of the model. The available data of site-directed mutagenesis of C5a and C5aR were successfully rationalized with the help of the model. Also, the modeling results predicted that the full-length C5a and C5a-des74 metabolite would have different binding modes with C5aR. Modeling approaches employed in this study are readily applicable for studies of molecular mechanisms of binding of other polypeptide ligands to their specific GPCRs.     

Optimization of time-resolved fluorescence assay for detection of europium-tetraazacyclododecyltetraacetic acid-labeled ligand-receptor interactions

Lanthanide-based luminescent ligand binding assays are superior to traditional radiolabel assays due to improving sensitivity and affordability in high-throughput screening while eliminating the use of radioactivity. Despite significant progress using lanthanide(III)-coordinated chelators such as diethylenetriaminepentaacetic acid (DTPA) derivatives, dissociation-enhanced lanthanide fluoroimmunoassays (DELFIAs) have not yet been successfully used with more stable chelators (e.g., tetraazacyclododecyltetraacetic acid [DOTA] derivatives) due to the incomplete release of lanthanide(III) ions from the complex. Here a modified and optimized DELFIA procedure incorporating an acid treatment protocol is introduced for use with Eu(III)-DOTA-labeled peptides. Complete release of Eu(III) ions from DOTA-labeled ligands was observed using hydrochloric acid (2.0 M) prior to the luminescent enhancement step. [Nle⁴,d-Phe⁷]-α-melanocyte-stimulating hormone (NDP-α-MSH) labeled with Eu(III)-DOTA was synthesized, and the binding affinity to cells overexpressing the human melanocortin-4 (hMC4) receptor was evaluated using the modified protocol. Binding data indicate that the Eu(III)-DOTA-linked peptide bound to these cells with an affinity similar to its DTPA analogue. The modified DELFIA procedure was further used to monitor the binding of an Eu(III)-DOTA-labeled heterobivalent peptide to the cells expressing both hMC4 and cholecystokinin-2 (CCK-2) receptors. The modified assay provides superior results and is appropriate for high-throughput screening of ligand libraries.     

A two-step selection approach for the identification of ligand-binding determinants in cytokine receptors

We have developed a novel cell-based method for the isolation and selection of mutant cytokine receptors with defects in ligand binding and applied it to the human interleukin-4 receptor. The experimental procedure is based upon the functional heterologous expression of receptor mutants in eukaryotic cells followed by a two-step selection procedure. Positive selection for cells that express receptor variants is achieved by means of an agonistic antibody that mediates cell survival through receptor dimerization. An IL-4-coupled toxin is subsequently used to select against cells expressing wild-type receptors. Cells expressing mutant receptors that are unable to bind the cytotoxic ligand survive and can be amplified. The procedure allows the isolation of rare receptor variants from cell pools containing predominantly wild-type cells. This method, which should be equally applicable to similar receptor systems, was used to demonstrate the importance of a critical charged amino acid residue in the human IL-4 receptor alpha-subunit for IL-4-induced receptor activation.     

Molecular docking of balanol to dynamics snapshots of protein kinase A

Even if the structure of a receptor has been determined experimentally, it may not be a conformation to which a ligand would bind when induced fit effects are significant. Molecular docking using such a receptor structure may thus fail to recognize a ligand to which the receptor can bind with reasonable affinity. Here, we examine one way to alleviate this problem by using an ensemble of receptor conformations generated from a molecular dynamics simulation for molecular docking. Two molecular dynamics simulations were conducted to generate snapshots for protein kinase A: one with the ligand bound, the other without. The ligand, balanol, was then docked to conformations of the receptors presented by these trajectories. The Lamarckian genetic algorithm in Autodock [Goodsell et al. J Mol Recognit 1996;9(1):1-5; Morris et al. J Comput Chem 1998;19(14):1639-1662] was used in the docking. Three ligand models were used: rigid, flexible, and flexible with torsional potentials. When the snapshots were taken from the molecular dynamics simulation of the protein-ligand complex, the correct docking structure could be recovered easily by the docking algorithm in all cases. This was an easier case for challenging the docking algorithm because, by using the structure of the protein in a protein-ligand complex, one essentially assumed that the protein already had a pocket to which the ligand can fit well. However, when the snapshots were taken from the ligand-free protein simulation, which is more useful for a practical application when the structure of the protein-ligand complex is not known, several clusters of structures were found. Of the 10 docking runs for each snapshot, at least one structure was close to the correctly docked structure when the flexible-ligand models were used. We found that a useful way to identify the correctly docked structure was to locate the structure that appeared most frequently as the lowest energy structure in the docking experiments to different snapshots.     

Immunosensor with a controlled orientation of antibodies by using NeutrAvidin-protein A complex at immunoaffinity layer

The orientation of antibody was controlled by using NeutrAvidin-protein A complex on the gold surface of SPR biosensor. The surface density of receptor antibody (anti-hIgG) was compared by treatment of receptor antibody to the layer of avidin, NeutrAvidin, protein A, NeutrAvidin-protein A complex and bare gold surface of SPR biosensor. The ligand antibody (hIgG) was injected to each IA layer and the binding ratio of ligand antibody per unit receptor was estimated as a parameter of orientation control. The NeutrAvidin-protein A complex on gold surface of SPR biosensor showed the highest surface density of receptor antibody as well as the binding ratio of ligand antibody per receptor antibody. The NeutrAvidin-protein A complex was also prepared on biotin-labelled SAM, and the binding ratio of ligand per receptor was found to be significantly improved in comparison to the IA layer prepared by chemical coupling of receptor antibody to the SAM layer. The NeutrAvidin-protein A complex which showed the highest efficiency for the binding of ligand antibodies, was applied for the detection of a cancer marker called CEA. By using NeutrAvidin-protein A complex and sandwich assay for signal amplification, sensitivity was improved to be 1.5-fold higher than bare gold surface and the detection of CEA with the detection limit of 30 ng/ml was achieved.     

A Monte Carlo study of the dynamics of G-protein activation.

To link quantitatively the cell surface binding of ligand to receptor with the production of cellular responses, it may be necessary to explore early events in signal transduction such as G-protein activation. Two different model frameworks relating receptor/ligand binding to G-protein activation are examined. In the first framework, a simple ordinary differential equation model is used to describe receptor/ligand binding and G-protein activation. In the second framework, the events leading to G-protein activation are simulated using a dynamic Monte Carlo model. In both models, reactions between ligand-bound receptors and G-proteins are assumed to be diffusion-limited. The Monte Carlo model predicts two regimes of G-protein activation, depending upon whether the lifetime of a receptor/ligand complex is long or short compared with the time needed for diffusional encounters of complexes and G-proteins. When the lifetime of a complex is relatively short compared with the diffusion time, the movement of ligand among free receptors by binding and unbinding ("switching") significantly enhances G-protein activation. Receptor antagonists dramatically reduce G-protein activation and, thus, signal transduction in this case, and significant clustering of active G-proteins near receptor/ligand complexes results. The simple ordinary differential equation model poorly predicts G-protein activation for this situation. In the alternative case, when diffusion is relatively fast, ligand movement among receptors is less important and the simple ordinary differential equation model and Monte Carlo model results are similar. In this case, there is little clustering of active G-proteins near receptor/ligand complexes. Results also indicate that as the GTPase activity of the alpha-subunit decreases, the steady-state level of alpha-GTP increases, although temporal sensitivity is compromised.     

Formation of a uniquely stable type I interferon receptor complex by interferon beta is dependent upon particular interactions between interferon beta and its receptor and independent of tyrosine phosphorylation

Human type I interferons (IFN) require two receptor chains, IFNAR1 and IFNAR2c for high affinity (pM) binding and biological activity. Our previous studies have shown that the ligand dependent assembly of the type I IFN receptor chains is not identical for all type I IFNs. IFNbeta appears unique in its ability to assemble a stable complex of receptor chains, as demonstrated by the observation that IFNAR2c co-immunoprecipitates with IFNAR1 when cells are stimulated with IFNbeta but not with IFNalpha. The characteristics of such a receptor complex are not well defined nor is it understood if differential signaling events can be mediated by variations in receptor assembly. To further characterize the factors required for formation of such a stable receptor complex we demonstrate using IFN stimulated Daudi cells that (1) IFNAR2c co-immunoprecipitates with IFNAR1 even when tyrosine phosphorylation of receptor chains is blocked with staurosporine, and (2) IFNbeta1b but not IFNalpha2, is present in the immunoprecipitated receptor complex. These results demonstrate that the unique IFNbeta induced assembly of type I IFN receptor chains is independent of receptor tyrosine phosphorylation and the recruitment of additional proteins to the receptor by such events. Furthermore, the presence of IFNbeta1b in the immunoprecipitated IFN receptor complex suggests that IFNbeta interacts and binds differently to the receptor than IFNalpha2. These results suggest that the specific assembly of type I IFN receptor chains is ligand dependent and may represent an early event which leads to the differential biological responses observed among type I IFNs.     

Assignment of transforming growth factor beta1 and beta3 and a third new ligand to the type I receptor ALK-1

Germ line mutations in one of two distinct genes, endoglin or ALK-1, cause hereditary hemorrhagic telangiectasia (HHT), an autosomal dominant disorder of localized angiodysplasia. Both genes encode endothelial cell receptors for the transforming growth factor beta (TGF-beta) ligand superfamily. Endoglin has homology to the type III receptor, betaglycan, although its exact role in TGF-beta signaling is unclear. Activin receptor-like kinase 1 (ALK-1) has homology to the type I receptor family, but its ligand and corresponding type II receptor are unknown. In order to identify the ligand and type II receptor for ALK-1 and to investigate the role of endoglin in ALK-1 signaling, we devised a chimeric receptor signaling assay by exchanging the kinase domain of ALK-1 with either the TGF-beta type I receptor or the activin type IB receptor, both of which can activate an inducible PAI-1 promoter. We show that TGF-beta1 and TGF-beta3, as well as a third unknown ligand present in serum, can activate chimeric ALK-1. HHT-associated missense mutations in the ALK-1 extracellular domain abrogate signaling. The ALK-1/ligand interaction is mediated by the type II TGF-beta receptor for TGF-beta and most likely through the activin type II or type IIB receptors for the serum ligand. Endoglin is a bifunctional receptor partner since it can bind to ALK-1 as well as to type I TGF-beta receptor. These data suggest that HHT pathogenesis involves disruption of a complex network of positive and negative angiogenic factors, involving TGF-beta, a new unknown ligand, and their corresponding receptors.