Competitive androgen receptor antagonism as a factor determining the predictability of cumulative antiandrogenic effects of widely used pesticides

Copyright @ 2012 National Institute of Environmental Health Sciences.This article has been made available through the Brunel Open Access Publishing Fund.Background: Many pesticides in current use have recently been revealed as in vitro androgen receptor (AR) antagonists, but information about their combined effects is lacking.
Objective: We investigated the combined effects and the competitive AR antagonism of pesticide mixtures.
Methods: We used the MDA-kb2 assay to test a combination of eight AR antagonists that did not also possess AR agonist properties (“pure” antagonists; 8 mix: fludioxonil, fenhexamid, ortho-­phenylphenol, imazalil, tebuconazole, dimetho­morph, methiocarb, pirimiphos-methyl), a combina­tion of five AR antagonists that also showed agonist activity (5 mix: cyprodinil, pyrimethanil, vinclozolin, chlor­propham, linuron), and all pesticides combined (13 mix). We used concentration addition (CA) and independent action (IA) to formu­late additivity expectations, and Schild plot analyses to investigate competitive AR antagonism.
Results: A good agreement between the effects of the mixture of eight “pure” AR antagonists and the responses predicted by CA was observed. Schild plot analysis revealed that the 8 mix acted by competi­tive AR antagonism. However, the observed responses of the 5 mix and the 13 mix fell within the “prediction window” boundaries defined by the predicted regression curves of CA and IA. Schild plot analysis with these mixtures yielded anomalous responses incompatible with competitive receptor antagonism.
Conclusions: A mixture of widely used pesticides can, in a predictable manner, produce combined AR antagonist effects that exceed the responses elicited by the most potent component alone. Inasmuch as large populations are regularly exposed to mixtures of anti­androgenic pesticides, our results underline the need for considering combination effects for these substances in regulatory practice.
This article is made available through the Brunel Open Access Publishing Fund. This work was funded by the European Commission, FP7 programme (CONTAMED, grant 212502).

Biased agonism

Seven-transmembrane receptors are commonly coupled to multiple signaling pathways in cells. The simple model describing agonists for these receptors as producing a common active state to induce uniform activation of the pathways linked to the receptor has been shown to be untenable in light of a large body of data that suggest that some agonists produce activation of some but not all available pathways. These agonists are referred to as ‘biased’ in that they select which signaling pathways become activated upon binding to the receptor. The data to support this mechanism as well as ideas on the possible therapeutic application of this effect will be discussed

Allosteric Theory: Taking Therapeutic Advantage of the Malleable Nature of GPCRs

The description of the allosteric modification of receptors to affect changes in their function requires a model that considers the effects of the modulator on both agonist affinity and efficacy. A model is presented which describes changes in affinity in terms of the constant α (ratio of affinity in the presence vs the absence of modulator) and also the constant ξ (ratio of intrinsic efficacy of the agonist in the presence vs absence of modulator). This allows independent effects of both affinity and efficacy and allows the modeling of any change in the dose-response curve to an agonist after treatment with modulator. Examples are given where this type of model can predict effects of modulators that reduce efficacy but actually increase affinity of agonist (i.e. ifenprodil) and also of modulators that block the action of some agonists (the CXCR4 agonist SDF-1α by the antagonist AMD3100) but not others for the same receptor (SDF-1α peptide fragments RSVM and ASLW)

Analyzing Binding Data

Measuring the rate and extent of radioligand binding provides information on the number of binding sites, and their affinity and accessibility of these binding sites for various drugs. This unit explains how to design and analyze such experiments. Curr. Protoc. Neurosci. 52:7.5.1‐7.5.65. © 2010 by John Wiley & Sons, Inc.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143761/1/cpns0705.pd

The classification of drugs and drug receptors in isolated tissues

The major premise of this review is that isolated more effective therapeutic agents for man. In this contissues can be used efıctively to obtain information text, the bias of this paper will be pharmacological in about drugs and drug receptors which transcends species that receptors will be used to gain information about and function. This information, in turn, should be valu- drugs rather than the more physiological bias of drugs used to gain information about receptors. This bias is reflected in the still very timely statement made by Buchheim 135 years ago

New concepts in pharmacological efficacy at 7TM receptors: IUPHAR Review 2: Developing concepts for drug efficacy

The present-day concept of drug efficacy has changed completely from its original description as the property of agonists that causes tissue activation. The ability to visualize the multiple behaviours of seven transmembrane receptors has shown that drugs can have many efficacies and also that the transduction of drug stimulus to various cellular stimulus–response cascades can be biased towards some but not all pathways. This latter effect leads to agonist ‘functional selectivity’, which can be favourable for the improvement of agonist therapeutics. However, in addition, biased agonist potency becomes cell type dependent with the loss of the monotonic behaviour of stimulus–response mechanisms, leading to potential problems in agonist quantification. This has an extremely important effect on the discovery process for new agonists since it now cannot be assumed that a given screening or lead optimization assay will correctly predict therapeutic behaviour. This review discusses these ideas and how new approaches to quantifying agonist effect may be used to circumvent the cell type dependence of agonism. This article, written by a corresponding member of the International Union of Basic and Clinical Pharmacology Committee on Receptor Nomenclature and Drug Classification (NC-IUPHAR), reviews our current understanding of the interaction of ligands with seven transmembrane receptors. Further information on these pharmacological concepts is being incorporated into the IUPHAR/BPS database http://GuideToPharmacology.org

The potential for selective pharmacological therapies through biased receptor signaling

Abstract The discovery that not all agonists uniformly activate cellular signaling pathways (biased signaling) has greatly changed the drug discovery process for agonists and the strategy for treatment of disease with agonists. Technological advances have enabled complex receptor behaviors to be viewed independently and through these assays, the bias for an agonist can be quantified. It is predicted that therapeutic phenotypes will be linked, through translational studies, to quantified scales of bias to guide medicinal chemists in the drug discovery process

The mass action equation in pharmacology: Mass action applied to pharmacology

The mass action equation is the building block from which all models of drug–receptor interaction are built. In the simplest case, the equation predicts a sigmoidal relationship between the amount of drug–receptor complex and the logarithm of the concentration of drug. The form of this function is also the same as most dose–response relationships in pharmacology (such as enzyme inhibition and the protein binding of drugs) but the potency term in dose–response relationships very often differs in meaning from the similar term in the simple mass action relationship. This is because (i) most pharmacological systems are collections of mass action reactions in series and/or in parallel and (ii) the important assumptions in the mass action reaction are violated in complex pharmacological systems. In some systems, the affinity of the receptor R for some ligand A is modified by interaction of the receptor with the allosteric ligand B and concomitantly the affinity of the receptor for ligand B is modified to the same degree. When this occurs, the observed affinity of the ligand A for the receptor will depend on both the concentration of the co‐binding allosteric ligand and its nature. The relationships between drug potency in pharmacological models and the equilibrium dissociation constants defined in single mass action reactions are discussed. More detailed knowledge of efficacy has led to new models of drug action that depend on the relative probabilities of different states, and these have taken knowledge of drug–receptor interactions beyond Guldberg and Waage

A Scale of Agonism and Allosteric Modulation for Assessment of Selectivity, Bias, and Receptor Mutation

An index of agonism is described that can be used to quantify agonist receptor selectivity, bias, cell-based agonism, and the effects of receptor mutation on signaling. The parameter is derived from agonist concentration-response curves and comprises the maximal response to the agonist (max) and the EC50 in the form of Δlog(max/EC50). This parameter is derived from equations describing agonists as positive allosteric facilitators of receptor-signaling protein interaction. A similar index is also derived to quantify the potentiating effects of positive allosteric modulators, which can be used to quantify in situ positive allosteric modulator activity in vivo. These indices lend themselves to statistical analysis and are system-independent in that the effects of the system processing of agonist response and differences in assay sensitivity and receptor expression are cancelled. The various applications of the Δlog(max/EC50) scale are described for each pharmacologic application

Agonist-receptor efficacy II: agonist trafficking of receptor signals

There is evidence to suggest that receptors with seven transmembrane domains can exist in G protein-activating conformations. It is not known how many activated receptor forms exist for each receptor. Furthermore, if there are multiple forms, does the chemical structure of the agonist determine which form dominates, and therefore, which response pathway is activated? This latter scheme is referred to as agonist-receptor trafficking, and is discussed in this, the second of two articles by Terry Kenakin. One way to approach these questions is to study receptors that couple to more than one G protein and, in essence, to try to allow the G protein to indicate the receptor state