Receptor theory

Last updated

Receptor theory is the application of receptor models to explain drug behavior. [1] Pharmacological receptor models preceded accurate knowledge of receptors by many years. [2] John Newport Langley and Paul Ehrlich introduced the concept that receptors can mediate drug action at the beginning of the 20th century. Alfred Joseph Clark was the first to quantify drug-induced biological responses (specifically, f-mediated receptor activation). So far, nearly all of the quantitative theoretical modelling of receptor function has centred on ligand-gated ion channels and G protein-coupled receptors. [3]

Contents

History

The receptor concept

In 1901, Langley challenged the dominant hypothesis that drugs act at nerve endings by demonstrating that nicotine acted at sympathetic ganglia even after the degeneration of the severed preganglionic nerve endings. [4] In 1905 he introduced the concept of a receptive substance on the surface of skeletal muscle that mediated the action of a drug. Langley postulated that these receptive substances were different in different species (citing the fact that nicotine-induced muscle paralysis in mammals was absent in crayfish). [5] Around the same time, Ehrlich was trying to understand the basis of selectivity of agents. [6] He theorized that selectivity was the basis of a preferential distribution of lead and dyes in different body tissues. However, he later modified the theory in order to explain immune reactions and the selectivity of the immune response. [6] Thinking that selectivity was derived from interaction with the tissues themselves, Ehrlich envisaged molecules extending from cells that the body could use to distinguish and mount an immune response to foreign objects. However, it was only after Ahlquist demonstrated the differential effects of adrenaline on two distinct receptor populations, that the theory of receptor-mediated drug interactions gained acceptance. [7] [8]

Nature of receptor–drug interactions

Receptor occupancy model

The receptor occupancy model, which describes agonist and competitive antagonists, was built on the work of Langley, Hill, and Clark. The occupancy model was the first model put forward by Clark to explain the activity of drugs at receptors and quantified the relationship between drug concentration and observed effect. It is based on mass-action kinetics and attempts to link the action of a drug to the proportion of receptors occupied by that drug at equilibrium. [9] [10] In particular, the magnitude of the response is directly proportional to the amount of drug bound, and the maximum response would be elicited once all receptors were occupied at equilibrium. He applied mathematical approaches used in enzyme kinetics systematically to the effects of chemicals on tissues. [2] He showed that for many drugs, the relationship between drug concentration and biological effect corresponded to a hyperbolic curve, similar to that representing the adsorption of a gas onto a metal surface [11] and fitted the Hill–Langmuir equation. [3] Clark, together with Gaddum, was the first to introduce the log concentration–effect curve and described the now-familiar 'parallel shift' of the log concentration–effect curve produced by a competitive antagonist. [3] Attempts to separate the binding phenomenon and activation phenomenon were made by Ariëns in 1954 and by Stephenson in 1956 to account for the intrinsic activity (efficacy) of a drug (that is, its ability to induce an effect after binding). [9] [12] [13] Classic occupational models of receptor activation failed to provide evidence to directly support the idea that receptor occupancy follows a Langmuir curve as the model assumed leading to the development of alternative models to explain drug behaviour. [12]

Competitive inhibition models

The development of the classic theory of drug antagonism by Gaddum, Schild and Arunlakshana built on the work of Langley, Hill and Clark. [12] Gaddum described a model for the competitive binding of two ligands to the same receptor in short communication to The Physiological Society in 1937. The description referred only to binding, it was not immediately useful for the analysis of experimental measurements of the effects of antagonists on the response to agonists. [14] It was Heinz Otto Schild who made measurement of the equilibrium constant for the binding of an antagonist possible. He developed the Schild equation to determine a dose ratio, a measure of the potency of a drug. In Schild regression, the change in the dose ratio, the ratio of the EC50 of an agonist alone compared to the EC50 in the presence of a competitive antagonist as determined on a dose response curve used to determine the affinity of an antagonist for its receptor.

Agonist models

The flaw in Clark's receptor-occupancy model was that it was insufficient to explain the concept of a partial agonist. This led to the development of agonist models of drug action by Ariens in 1954 and by Stephenson in 1956 to account for the intrinsic activity (efficacy) of a drug (that is, its ability to induce an effect after binding). [12] [13]

Two-state receptor theory

The two-state model is a simple linear model to describe the interaction between a ligand and its receptor, but also the active receptor (R*). [15] The model uses an equilibrium dissociation constant to describe the interaction between ligand and receptor. It proposes that ligand binding results in a change in receptor state from an inactive to an active state based on the receptor's conformation. A receptor in its active state will ultimately elicit its biological response. It was first described by Black and Leff in 1983 as an alternative model of receptor activation. [16] Similar to the receptor occupancy model, the theory originated from earlier work by del Castillo & Katz on observations relating to ligand-gated ion channels. [3] In this model, agonists and inverse agonists are thought to have selective binding affinity for the pre-existing resting and active states [3] [17] or can induce a conformational change to a different receptor state. Whereas antagonists have no preference in their affinity for a receptor state. [18] [19] The fact that receptor conformation (state) would affect binding affinity of a ligand was used to explain a mechanism of partial agonism of receptors by del Castillo & Katz in 1957 was based on their work on the action of acetylcholine at the motor endplate [3] build on similar work by Wyman & Allen in 1951 on conformational-induced changes in hemoglobin's oxygen binding affinity occurring as a result of oxygen binding. [20] The del Castillo-Katz mechanism divorces the binding step (that can be made by agonists as well as antagonists) from the receptor activation step (that can be only exerted by agonists), describing them as two independent events. [20]

Ternary complex model

The original Ternary complex model was used to describe ligand, receptor, and G-protein interactions. It uses equilibrium dissociation constants for the interactions between the receptor and each ligand (Ka for ligand A; Kb for ligand B), as well as a cooperativity factor (α) that denotes the mutual effect of the two ligands on each other's affinity for the receptor. An α > 1.0 refers to positive allosteric modulation, an α < 1.0 refers to negative allosteric modulation, and an α = 1.0 means that binding of either ligand to the receptor does not alter the affinity of the other ligand for the receptor (i.e., a neutral modulator). [15] Further, the α parameter can be added as a subtle but highly useful extension to the ATCM in order to include effects of an allosteric modulator on the efficacy (as distinct from the affinity) of another ligand that binds the receptor, such as the orthosteric agonist. Some ligands can reduce the efficacy but increase the affinity of the orthosteric agonist for the receptor. [15]

Although it is a simple assumption that the proportional amount of an active receptor state should correlate with the biological response, the experimental evidence for receptor overexpression and spare receptors suggests that the calculation of the net change in the active receptor state is a much better measure for response than is the fractional or proportional change. This is demonstrated by the effects of agonist/ antagonist combinations on the desensitization of receptors. This is also demonstrated by receptors that are activated by overexpression, since this requires a change between R and R* that is difficult to understand in terms of a proportional rather than a net change, and for the molecular model that fits with the mathematical model. [21] [22] [23]

Postulates of receptor theory

Related Research Articles

<span class="mw-page-title-main">Allosteric regulation</span> Regulation of enzyme activity

In biochemistry, allosteric regulation is the regulation of an enzyme by binding an effector molecule at a site other than the enzyme's active site.

<span class="mw-page-title-main">Agonist</span> Chemical which binds to and activates a biochemical receptor

An agonist is a chemical that activates a receptor to produce a biological response. Receptors are cellular proteins whose activation causes the cell to modify what it is currently doing. In contrast, an antagonist blocks the action of the agonist, while an inverse agonist causes an action opposite to that of the agonist.

<span class="mw-page-title-main">Receptor (biochemistry)</span> Protein molecule receiving signals for a cell

In biochemistry and pharmacology, receptors are chemical structures, composed of protein, that receive and transduce signals that may be integrated into biological systems. These signals are typically chemical messengers which bind to a receptor and produce physiological responses such as change in the electrical activity of a cell. For example, GABA, an inhibitory neurotransmitter inhibits electrical activity of neurons by binding to GABAA receptors. There are three main ways the action of the receptor can be classified: relay of signal, amplification, or integration. Relaying sends the signal onward, amplification increases the effect of a single ligand, and integration allows the signal to be incorporated into another biochemical pathway.

<span class="mw-page-title-main">Receptor antagonist</span> Type of receptor ligand or drug that blocks a biological response

A receptor antagonist is a type of receptor ligand or drug that blocks or dampens a biological response by binding to and blocking a receptor rather than activating it like an agonist. Antagonist drugs interfere in the natural operation of receptor proteins. They are sometimes called blockers; examples include alpha blockers, beta blockers, and calcium channel blockers. In pharmacology, antagonists have affinity but no efficacy for their cognate receptors, and binding will disrupt the interaction and inhibit the function of an agonist or inverse agonist at receptors. Antagonists mediate their effects by binding to the active site or to the allosteric site on a receptor, or they may interact at unique binding sites not normally involved in the biological regulation of the receptor's activity. Antagonist activity may be reversible or irreversible depending on the longevity of the antagonist–receptor complex, which, in turn, depends on the nature of antagonist–receptor binding. The majority of drug antagonists achieve their potency by competing with endogenous ligands or substrates at structurally defined binding sites on receptors.

<span class="mw-page-title-main">Pharmacodynamics</span> Area of Academic Study

Pharmacodynamics (PD) is the study of the biochemical and physiologic effects of drugs. The effects can include those manifested within animals, microorganisms, or combinations of organisms.

Efficacy is the ability to perform a task to a satisfactory or expected degree. The word comes from the same roots as effectiveness, and it has often been used synonymously, although in pharmacology a distinction is now often made between efficacy and effectiveness.

<span class="mw-page-title-main">Inverse agonist</span> Agent in biochemistry

In pharmacology, an inverse agonist is a drug that binds to the same receptor as an agonist but induces a pharmacological response opposite to that of the agonist.

IC<sub>50</sub> Half maximal inhibitory concentration

Half maximal inhibitory concentration (IC50) is a measure of the potency of a substance in inhibiting a specific biological or biochemical function. IC50 is a quantitative measure that indicates how much of a particular inhibitory substance (e.g. drug) is needed to inhibit, in vitro, a given biological process or biological component by 50%. The biological component could be an enzyme, cell, cell receptor or microorganism. IC50 values are typically expressed as molar concentration.

Functional selectivity is the ligand-dependent selectivity for certain signal transduction pathways relative to a reference ligand at the same receptor. Functional selectivity can be present when a receptor has several possible signal transduction pathways. To which degree each pathway is activated thus depends on which ligand binds to the receptor. Functional selectivity, or biased signaling, is most extensively characterized at G protein coupled receptors (GPCRs). A number of biased agonists, such as those at muscarinic M2 receptors tested as analgesics or antiproliferative drugs, or those at opioid receptors that mediate pain, show potential at various receptor families to increase beneficial properties while reducing side effects. For example, pre-clinical studies with G protein biased agonists at the μ-opioid receptor show equivalent efficacy for treating pain with reduced risk for addictive potential and respiratory depression. Studies within the chemokine receptor system also suggest that GPCR biased agonism is physiologically relevant. For example, a beta-arrestin biased agonist of the chemokine receptor CXCR3 induced greater chemotaxis of T cells relative to a G protein biased agonist.

<span class="mw-page-title-main">Hill equation (biochemistry)</span> Diagram showing the proportion of a receptor bound to a ligand

In biochemistry and pharmacology, the Hill equation refers to two closely related equations that reflect the binding of ligands to macromolecules, as a function of the ligand concentration. A ligand is "a substance that forms a complex with a biomolecule to serve a biological purpose", and a macromolecule is a very large molecule, such as a protein, with a complex structure of components. Protein-ligand binding typically changes the structure of the target protein, thereby changing its function in a cell.

<span class="mw-page-title-main">Ligand (biochemistry)</span> Substance that forms a complex with a biomolecule

In biochemistry and pharmacology, a ligand is a substance that forms a complex with a biomolecule to serve a biological purpose. The etymology stems from Latin ligare, which means 'to bind'. In protein-ligand binding, the ligand is usually a molecule which produces a signal by binding to a site on a target protein. The binding typically results in a change of conformational isomerism (conformation) of the target protein. In DNA-ligand binding studies, the ligand can be a small molecule, ion, or protein which binds to the DNA double helix. The relationship between ligand and binding partner is a function of charge, hydrophobicity, and molecular structure.

<span class="mw-page-title-main">Monod–Wyman–Changeux model</span> Biochemical model of protein transitions

In biochemistry, the Monod–Wyman–Changeux model describes allosteric transitions of proteins made up of identical subunits. It was proposed by Jean-Pierre Changeux in his PhD thesis, and described by Jacques Monod, Jeffries Wyman, and Jean-Pierre Changeux. It contrasts with the sequential model.

<span class="mw-page-title-main">Schild equation</span>

In pharmacology, Schild regression analysis, based upon the Schild equation, both named for Heinz Otto Schild, are tools for studying the effects of agonists and antagonists on the response caused by the receptor or on ligand-receptor binding.

<span class="mw-page-title-main">Adrenergic antagonist</span>

An adrenergic antagonist is a drug that inhibits the function of adrenergic receptors. There are five adrenergic receptors, which are divided into two groups. The first group of receptors are the beta (β) adrenergic receptors. There are β1, β2, and β3 receptors. The second group contains the alpha (α) adrenoreceptors. There are only α1 and α2 receptors. Adrenergic receptors are located near the heart, kidneys, lungs, and gastrointestinal tract. There are also α-adreno receptors that are located on vascular smooth muscle.

Dopamine receptor D<sub>2</sub> Main receptor for most antipsychotic drugs

Dopamine receptor D2, also known as D2R, is a protein that, in humans, is encoded by the DRD2 gene. After work from Paul Greengard's lab had suggested that dopamine receptors were the site of action of antipsychotic drugs, several groups, including those of Solomon Snyder and Philip Seeman used a radiolabeled antipsychotic drug to identify what is now known as the dopamine D2 receptor. The dopamine D2 receptor is the main receptor for most antipsychotic drugs. The structure of DRD2 in complex with the atypical antipsychotic risperidone has been determined.

<span class="mw-page-title-main">Intrinsic activity</span>

Intrinsic activity (IA) and efficacy refer to the relative ability of a drug-receptor complex to produce a maximum functional response. This must be distinguished from the affinity, which is a measure of the ability of the drug to bind to its molecular target, and the EC50, which is a measure of the potency of the drug and which is proportional to both efficacy and affinity. This use of the word "efficacy" was introduced by Stephenson (1956) to describe the way in which agonists vary in the response they produce, even when they occupy the same number of receptors. High efficacy agonists can produce the maximal response of the receptor system while occupying a relatively low proportion of the receptors in that system. There is a distinction between efficacy and intrinsic activity.

In pharmacology and biochemistry, allosteric modulators are a group of substances that bind to a receptor to change that receptor's response to stimuli. Some of them, like benzodiazepines or alcoholic beverages, function as psychoactive drugs. The site that an allosteric modulator binds to is not the same one to which an endogenous agonist of the receptor would bind. Modulators and agonists can both be called receptor ligands.

<span class="mw-page-title-main">Org 27569</span> Chemical compound

Org 27569 is a drug which acts as a potent and selective negative allosteric modulator of the cannabinoid CB1 receptor. Studies in vitro suggest that it binds to a regulatory site on the CB1 receptor target, causing a conformational change that increases the binding affinity of CB1 agonists such as CP 55,940, while decreasing the binding affinity of CB1 antagonists or inverse agonists such as rimonabant. However while Org 27569 increases the ability of CB1 agonists to bind to the receptor, it decreases their efficacy at stimulating second messenger signalling once bound, and so in practice behaves as an insurmountable antagonist of CB1 receptor function.

<span class="mw-page-title-main">Buprenorphine/samidorphan</span> Combination drug formulation

Buprenorphine/samidorphan is a combination formulation of buprenorphine and samidorphan which is under development as an add on to antidepressants in treatment-resistant depression (TRD).

A receptor modulator, or receptor ligand, is a general term for a substance, endogenous or exogenous, that binds to and regulates the activity of chemical receptors. They are ligands that can act on different parts of receptors and regulate activity in a positive, negative, or neutral direction with varying degrees of efficacy. Categories of these modulators include receptor agonists and receptor antagonists, as well as receptor partial agonists, inverse agonists, orthosteric modulators, and allosteric modulators, Examples of receptor modulators in modern medicine include CFTR modulators, selective androgen receptor modulators (SARMs), and muscarinic ACh receptor modulators.

References

  1. ↑ Kenakin T (2008). "What systems can and can't do". Br. J. Pharmacol. 153 (5): 841–3. doi:10.1038/sj.bjp.0707677. PMC   2267279 . PMID   18204481.
  2. 1 2 Kenakin, T. (2004). "Principles: Receptor theory in pharmacology". Trends Pharmacol Sci. 25 (4): 186–192. doi:10.1016/j.tips.2004.02.012. PMID   15063082.
  3. 1 2 3 4 5 6 Rang HP (2006). "The receptor concept: pharmacology's big idea". Br. J. Pharmacol. 147 (S1): S9–16. doi:10.1038/sj.bjp.0706457. PMC   1760743 . PMID   16402126.
  4. ↑ Langley J. On the stimulation and paralysis of nerve cells and of nerve-endings. Part 1. J Physiol 1901 October 16; 27(3): 224–236.
  5. ↑ J. N. Langley. On the reaction of cells and of nerve-endings to certain poisons, chiefly as regards the reaction of striated muscle to nicotine and to curare. J Physiol 1905; 33: 374–413.
  6. 1 2 Limbird LE (2004). "The receptor concept: a continuing evolution". Mol. Interv. 4 (6): 326–36. doi:10.1124/mi.4.6.6. PMID   15616162.
  7. ↑ Ahlquist, R.P. (1948). "A study of the adrenotrophic receptors". Am J Physiol. 155 (3): 586–600. doi:10.1152/ajplegacy.1948.153.3.586. PMID   18882199. S2CID   1518772.
  8. ↑ L.E. Limbird (2005) Cell Surface Receptors: A Short Course on Theory and Methods. 3rd Edition Springer ISBN   0-387-23069-6
  9. 1 2 Christopoulos A, El-Fakahany EE (1999). "Qualitative and quantitative assessment of relative agonist efficacy". Biochem. Pharmacol. 58 (5): 735–48. doi:10.1016/S0006-2952(99)00087-8. PMID   10449182.
  10. ↑ E.M Ross, and T.P. Kenakin. (2001) Pharmacodynamics. Mechanisms of drug action and the relationship between drug concentration and effect. In Goodman & Gilman’s The Pharmacological Basis of Therapeutics, Vol. Tenth. J.G. Hardman & L.E. Limbird, Eds. McGraw-Hill. New York.
  11. ↑ Quirke V (2006). "Putting theory into practice: James Black, receptor theory and the development of the beta-blockers at ICI, 1958-1978". Med Hist. 50 (1): 69–92. doi:10.1017/s0025727300009455. PMC   1369014 . PMID   16502872.
  12. 1 2 3 4 D. Colquhoun, The relation between classical and cooperative models for drug action. In: H.P. Rang, Editor, Drug Receptors, Macmillan Press (1973), pp. 149–182. http://www.ucl.ac.uk/Pharmacology/dc-bits/colquhoun-1973.pdf
  13. 1 2 Maehle AH, Prüll CR, Halliwell RF (2002). "The emergence of the drug receptor theory". Nature Reviews. Drug Discovery. 1 (8): 637–41. doi:10.1038/nrd875. PMID   12402503. S2CID   205479063.
  14. ↑ Colquhoun D (2006). "The quantitative analysis of drug-receptor interactions: a short history". Trends Pharmacol. Sci. 27 (3): 149–57. doi:10.1016/j.tips.2006.01.008. PMID   16483674.
  15. 1 2 3 Bridges TM, Lindsley CW (July 2008). "G-Protein-Coupled Receptors: From Classical Modes of Modulation to Allosteric Mechanisms". ACS Chem. Biol. 3 (9): 530–41. doi:10.1021/cb800116f. PMID   18652471.
  16. ↑ J.W. Black and P. Leff. (1983) Operational Models of Pharmacological Agonism. In: Proc. R. Soc. London Ser. B 220, pp. 141–162.
  17. ↑ Leff P (1995). "The two-state model of receptor activation". Trends Pharmacol. Sci. 16 (3): 89–97. doi:10.1016/S0165-6147(00)88989-0. PMID   7540781.
  18. ↑ Giraldo J (2004). "Agonist induction, conformational selection, and mutant receptors". FEBS Lett. 556 (1–3): 13–8. doi:10.1016/S0014-5793(03)01404-2. PMID   14706818. S2CID   2580606.
  19. ↑ Vauquelin G, Van Liefde I (2005). "G protein-coupled receptors: a count of 1001 conformations". Fundamental and Clinical Pharmacology. 19 (1): 45–56. doi: 10.1111/j.1472-8206.2005.00319.x . PMID   15660959.
  20. 1 2 Colquhoun D (1998). "Binding, gating, affinity and efficacy: the interpretation of structure-activity relationships for agonists and of the effects of mutating receptors". Br. J. Pharmacol. 125 (5): 924–47. doi:10.1038/sj.bjp.0702164. PMC   1565672 . PMID   9846630.
  21. ↑ Optimal Agonist/Antagonist Combinations Maintain Receptor Response by Preventing Rapid β-adrenergic Receptor Desensitization | BIO BALANCE
  22. ↑ Molecular dynamics of a biophysical model for b2-adrenergic and G protein-coupled receptor activation | BIO BALANCE
  23. ↑ The Biophysical Basis for the Graphical Representations | BIO BALANCE
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.