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Receptor Theory & Toxicant-Receptor Interactions

Receptor Theory & Toxicant-Receptor Interactions. Richard B. Mailman. 1 . 2 . ligand. Ion. ligand. E. R. 1. R. R. a. a. b. g. b. g. E. 2. ligand. 3 . 4 . ligand. R. R. R. R. R. R. ATP. ATP. ADP. ADP. P. P. P. P. nucleus. E. Some examples of receptors.

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Receptor Theory & Toxicant-Receptor Interactions

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  1. Receptor Theory & Toxicant-Receptor Interactions Richard B. Mailman

  2. 1 2 ligand Ion ligand E R 1 R R a a b g b g E 2 ligand 3 4 ligand R R R R R R ATP ATP ADP ADP P P P P nucleus E Some examples of receptors

  3. What is a receptor? • To a neuroscientist • A protein that binds a neurotransmitter/modulator • To a cell biologist or biochemist • A protein that binds a small molecule • A protein that binds another protein • A nucleic acid that binds a protein • To a toxicologist • A macromolecule that binds a toxicant • Etc.

  4. Definitions • Affinity: • the “tenacity” by which a ligand binds to its receptor • Intrinsic activity (= “efficacy”): • the relative maximal response caused by a drug in a tissue preparation. A full agonist causes a maximal effect equal to that of the endogenous ligand (or sometimes another reference compound if the endogenous ligand is not known); a partial agonist causes less than a maximal response. • Intrinsic efficacy (outmoded): the property of how a ligand causes biological responses via a single receptor (hence a property of a drug). • Potency: • how much of a ligand is needed to cause a measured change (usually functional).

  5. Radioactivity Principles • Specific activity depends on half-life, and is totally independent of mode or energy of decay. • When decay occurs for all of the biologically important isotopes (14C; 3H; 32P; 35S; 125I; etc.), the decay event changes the chemical identity of the decaying atom, and in the process, destroys the molecule on which the atom resided. • e.g., 3H He • Do NOT adjust the specific activity of your radiochemical based on decay – for every decay, there is a loss of the parent molecule.

  6. Drug-Receptor Interactions Lgand-Receptor Complex Ligand + Receptor Response(s)

  7. Bimolecular Interactions: Foundation of Most Studies Ligand-ReceptorComplex Ligand + Receptor Response(s) At equilibrium: Rearrange that equation to define the equilibrium dissociation constant KD.

  8. Saturation Equations Michealis-Menten form Scatchard form

  9. 1 1 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0 0 -2 -1 0 1 2 Linear & Semilog Linear Plot Bound 20 40 60 80 100 0 Free Semi-Log Plot Bound log [Free]

  10. Saturation Equations Michealis-Menten form Scatchard form

  11. Saturation Radioreceptor Assays receptor preparation radiolabeled drug TissuePreparation drug-receptorcomplex BetaCounter Filtration unbound labeled drug + unbound test drug

  12. 800 600 400 200 0 0 2 4 6 8 10 12 14 16 18 Characterizing Drug-Receptor Interactions:Saturation curves Total Binding Specific Binding! (calculated) Amount Bound Non-Specific Radioligand Added (cpm x 1000)

  13. Saturation Equations Michealis-Menten form Scatchard form

  14. Scatchard plot -1/KD B/F (Specific Binding/ Free Radioligand) Bmax B(Specific Binding)

  15. Competition Radioreceptor Assays receptor preparation radiolabeled drug test drug TissuePreparation drug-receptorcomplex BetaCounter Filtration unbound labeled drug + unbound test drug

  16. 100 90 80 70 60 50 40 30 20 10 0 0.01 0.1 1.0 10 100 Competition Curve Top Total Binding (dpm *10, e.g.) Specific Binding IC50 Bottom NSB log [ligand] (nM)

  17. 100 75 50 25 0 10-9 10-8 10-7 10-6 10-5 10-4 10-3 Calculations from Basic Theory (I) 90% Specific Binding (%) 10% 81 Fold log [competing ligand] (M)

  18. 100 75 50 25 0 10-9 10-8 10-7 10-6 10-5 10-4 10-3 Calculations from Basic Theory (II) Commit this to memory!!!!! 91% Specific Binding (%) 9% 100-fold log [competing ligand] (M)

  19. 100 90 80 70 60 50 40 30 20 10 0 0.01 0.1 1.0 10 100 1000 Competition Curves A Specific Binding (%) B Log [ligand] (nM)

  20. 100 90 80 70 60 50 40 30 20 10 0 0.01 0.1 1.0 10 100 1000 Specific Binding (%) A B C D Concentration (nM)

  21. 1.0 0.8 0.6 0.4 0.2 0 -11 -10 -9 -8 -7 -6 Functional effects & antagonists + Increasingconcentrationsof antagonist B Raw Data Control(agonist with no antagonist) Response (Fraction of maximal) Log Agonist Concentration (M)

  22. E1 E1 a a b b g g R E2 Spare receptors and “full agonists” D1 D1 D1 cAMP stimulation ???? ????

  23. Full & Partial Agonists 100 Full agonist 80 cAMP synthesis 60 (% stimulation relative to dopamine) Partial agonist 40 20 0 1 10 100 1000 10000 100000 Concentration (nM)

  24. bg a Ligand #1 Typical Agonist Ligand #2 Functionally Selective Agonist A B Normal Agonist F.S. Drug bg Functional Complex #1 D2R a G-protein C D Functional Complex #2 No activation

  25. SideEffect 1 • TherapeuticEffect 1 • SideEffect 2 Ligand action on three pathways via a single receptor: Traditional view of “full” agonist

  26. SideEffect 1 • TherapeuticEffect 1 • SideEffect 2 Ligand action on three pathways via a single receptor: Traditional view of “partial” agonist

  27. SideEffect 1 • TherapeuticEffect 1 • SideEffect 2 Ligand action on three pathways via a single receptor: Traditional view of antagonist

  28. SideEffect 1 • TherapeuticEffect 1 • SideEffect 2 Activation of three pathways via a single receptor:“Functionally selective” compound

  29. Lessons of functional selectivity • Increases complexity in understanding mechanisms of toxicity. • BUT ….provides opportunities to dissociate toxicity from therapeutic effects mediated via a single receptor. • Universal to almost all targets for small molecules.

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