Drug Receptors & Pharmacodynamics – Comprehensive Bullet-Point Notes

Receptor Concept & Pharmacodynamics

• Therapeutic AND toxic drug effects arise from interactions with specific macromolecules—receptors.
  • Definition: Receptor = cellular component that binds drug, initiates chain of events → observed effect.
• Receptors explain dose–response relationships, selectivity, agonism/antagonism, spare receptors, desensitisation, etc.
• Concept originated > 100 yrs ago; now central in pharmacology, endocrinology, immunology, molecular biology.

Practical Consequences of the Receptor Concept

• Quantitative dose–effect relations
  • Affinity (high ↔ low $K_d$) determines concentration needed for significant drug–receptor complexes.
  • Total receptor number sets upper limit (efficacy).
• Selectivity
  • Size, shape, charge dictate which receptors a drug binds.
  • Small structural tweaks → big therapeutic/toxic changes.
• Agonists vs antagonists
  • Agonists activate; antagonists bind without activation → block endogenous agonists.
  • Allosteric modulators bind distinct site; may enhance (+) or decrease (–) signalling.

Clinical Case Study (Asthma + Hypertension)

• 51-y male, acute bronchospasm ➜ IM epinephrine improves breathing.
• History: Mild HTN on propranolol (non-selective β-blocker).
• Clinician stops propranolol, starts verapamil.
  • Rationale:
  • Propranolol blocks β2-mediated bronchodilation → can worsen asthma.
  • Verapamil (Ca2+-channel blocker) lowers BP without bronchoconstriction.
  • Alternatives: β1-selective blockers (eg, metoprolol) or ACE inhibitors, ARBs, diuretics.
• Illustrates need to match receptor selectivity with comorbidities.

Macromolecular Nature of Drug Receptors

• Most are proteins; identified originally by radioligand binding, now by sequence homology.
• Discovery of orphan receptors (ligand unknown) → potential drug targets.
• Classes:
  • Regulatory proteins: mediate endogenous signals (NTs, hormones, autacoids).
  • Enzymes (eg, DHFR – methotrexate; HMG-CoA-reductase – statins; kinases).
  • Transporters (Na⁺/K⁺-ATPase – digitalis; NET/SERT – antidepressants; DAT – cocaine).
  • Structural proteins (tubulin – colchicine).

Drug Concentration–Response Relationships

• In vitro hyperbolic relation: $E = \frac{E<em>{max}\,C}{EC</em>{50}+C}$
• Receptor occupancy: $B = \frac{B<em>{max}\,C}{K</em>d + C}$
• $EC<em>{50}$ = conc. for 50 % max effect; $K</em>d$ = conc. for 50 % receptor occupancy.
• Plotting E vs log C → sigmoid curve → linear mid-portion (easier comparison).

Spare Receptors & Coupling

• Coupling: linkage between occupancy & response.
• Spare receptors exist when max response occurs without full occupancy.
  • Demonstrated using irreversible antagonist + agonist (Figure 2-2 concept).
  • Heart: max inotropy even when 90 % β-receptors blocked ➜ large receptor reserve.
• Clinical implication: tissue sensitivity depends on $K_d$ + receptor reserve; disease/drugs altering receptor number shift sensitivity.

Antagonism

Competitive (Reversible) Antagonists

• Shift curve right; Emax unchanged.
• Schild equation: $\frac{C'}{C} = 1 + \frac{[I]}{K_i}$
  • Dose-ratio relates antagonist conc. to $K_i$.
• Clinical pearls: Effect depends on antagonist and agonist concentrations (eg, propranolol vs exercise catecholamines).

Irreversible / Non-competitive Antagonists

• Bind covalently or with very high affinity → ↓Emax (cannot surmount).
• Duration tied to receptor turnover, not drug clearance (phenoxybenzamine in pheochromocytoma).
• Presence of spare receptors may mask Emax fall until high antagonist dose.

Allosteric Modulators

• Bind separate site; change receptor activity.
  • Negative: ↓ response (non-competitive).
  • Positive: ↑ response (eg, benzodiazepines on GABA_A).
• Can work on proteins lacking orthosteric ligand (ivacaftor on CFTR).

Partial Agonists

• Produce sub-maximal response even at full occupancy.
• Act as agonist–antagonists vs full agonists (competition lowers overall effect).
  • Clinical: buprenorphine safer analgesic (respiration plateau) but can precipitate withdrawal & block stronger opioids.

Non-Receptor Antagonism

• Chemical: protamine + heparin (ionic binding).
• Physiologic: drug opposes pathway via different receptor (insulin vs glucocorticoids; atropine vs vagal bradycardia).

Signalling Mechanisms & Drug Action

Five canonical transmembrane strategies (Figure 2-5):

1. Intracellular receptors for lipid-soluble ligands.
2. Receptor–enzyme (intrinsic catalytic domain, eg, receptor tyrosine kinase).
3. Receptor linked to separate kinase (eg, cytokine receptors + JAKs).
4. Ligand-gated ion channels (fast synaptic transmission).
5. GPCRs → G-protein → effector (enzyme or ion channel).

1. Intracellular (Gene-Active) Receptors

• Steroids, thyroid hormone, vitamin D cross membrane.
• Bind receptor → release hsp90, dimerize, bind DNA response elements.
• Features:
  • Lag time (≥ 30 min) for protein synthesis ➜ not for acute relief.
  • Persistent effects after drug withdrawal due to protein turnover.

2. Receptor Tyrosine Kinases (RTKs)

• Single-pass TM proteins; ligand induces dimerization → autophosphorylation on Tyr → docking sites for signalling proteins.
• Ligands: insulin, EGF, PDGF, ANP (guanylyl cyclase variant), TGF-β (Ser/Thr kinase variant).
• Down-regulation by endocytosis (EGFR fast internalisation; mutation → cancer).
• Drugs: monoclonal Abs (trastuzumab), small-molecule TKIs (gefitinib).

3. Cytokine Receptors (No intrinsic kinase)

• Associate with JAK family kinases → phosphorylate STATs → gene transcription.
• Ligands: growth hormone, erythropoietin, interferons.

4. Ion Channels

Ligand-Gated

• nAChR: pentamer; ACh binds α-subunits → Na⁺ influx → depolarisation.
• Glutamate receptors: "venus flytrap" ligand domain; target for drugs at multiple sites.
• Regulation: phosphorylation, endocytosis, synaptic plasticity.

Voltage-Gated

• Targeted by drugs at sites distinct from voltage sensor.
  • Verapamil blocks L-type Ca²⁺ channels → anti-HTN/anti-arrhythmic.
  • Local anaesthetics block Na⁺ channels.
  • CFTR (atypical): lumacaftor (trafficking), ivacaftor (conductance).

5. GPCRs & G Proteins

• 7-TM (serpentine) receptors; agonist causes outward movement of TM-helices V–VI → cavity for G protein.
• G-protein cycle (Figure 2-10):
  1. R* promotes GDP → GTP exchange on Gα.
  2. Gα-GTP + Gβγ regulate effectors.
  3. Intrinsic GTPase hydrolyses GTP → GDP (timed shut-off).
• Key G-protein families (Table 2-1): $G<em>s, G</em>i, G<em>q, G</em>{olf}, G_t$ etc.

Second Messengers

• cAMP
  • $ATP \xrightarrow[AC]{G_s} cAMP$; degraded by PDEs.
  • Activates PKA (R₂C₂ → 2 C*).
  • Pharmacology: milrinone (PDE3 inh.), caffeine (non-selective PDE inhibition).
• IP₃ / DAG / Ca²⁺
  • $PIP<em>2 \xrightarrow[PLC]{G</em>q / RTK} IP_3 + DAG$.
  • IP₃ opens ER Ca²⁺ channels → CaM-dependent kinases.
  • DAG activates PKC.
  • Lithium interferes with inositol recycling.
• cGMP
  • Generated by membrane GC (ANP) or soluble GC (NO).
  • Activates PKG → smooth-muscle relaxation.
  • Drugs: nitroglycerin (NO donor); sildenafil (PDE5 inhibitor).

Signal Integration & Localisation

• cAMP and Ca²⁺ may oppose (vascular smooth muscle) or synergise (hepatic glycogenolysis).
• Spatial confinement via PDEs, scaffolding proteins, Ca²⁺ buffers.

Receptor Regulation & Desensitisation

• Rapid loss of response despite agonist presence (tachyphylaxis).
• Mechanism (β-AR prototype, Figure 2-12):
  • GRKs phosphorylate activated GPCR → β-arrestin binds → uncouples Gs.
  • β-arrestin promotes endocytosis; receptors either recycle (resensitise) or degrade (down-regulation).
  • β-arrestin can scaffold alternative signalling pathways (biased agonism).

Receptor Classes & Drug Development

• Subtype selectivity exploits multiple receptors for same ligand (eg, β vs α ARs; H₁ vs H₂ histamine).
• Example: tamoxifen = ER antagonist in breast, agonist in bone ➜ treats cancer, prevents osteoporosis but risk endometrial stimulation.
• Drug design expanding to downstream elements (kinase inhibitors, Ras-G12C inhibitors).
• Computational docking uses GPCR & kinase crystal structures to find new leads.

Dose–Response in Clinical Practice

Graded Curves (single subject/system)

• Potency = $EC<em>{50}$; Efficacy = $E</em>{max}$.
• Steep curves (slope high) → small dose error cause big effect (risk).

Quantal (Population) Curves

• Plot % individuals achieving defined effect vs log-dose.
• $ED<em>{50}$ = median effective dose; $TD</em>{50}$ or $LD_{50}$ for toxicity/death.
• Therapeutic Index = $\frac{TD<em>{50}}{ED</em>{50}}$; clinically use Therapeutic Window (range between minimal effective & minimal toxic doses).

Variation in Drug Responsiveness

• Idiosyncratic: uncommon, often genetic or immune.
• Quantitative differences:
  1. Pharmacokinetic: absorption, distribution, metabolism (eg, MDR transporters), clearance.
  2. Endogenous agonist levels (eg, propranolol effect varies with catecholamines).
  3. Receptor number/function changes (up/down-regulation, tolerance, genetic polymorphisms).
  4. Post-receptor changes & compensatory mechanisms (disease severity, interacting systems).
• Pharmacogenetics & precision medicine: EGFR mutations predicting TKI response; tumors with KRas-G12C → targeted inhibitors.

Beneficial vs Toxic Effects (Selectivity)

• No drug absolutely specific; goal = maximise desirable/ minimise harmful via:
  • Selecting receptor-specific drugs.
  • Using lowest effective dose + monitoring.
  • Combining drugs with different mechanisms to lower individual doses (eg, antihypertensive combos).
  • Targeted delivery (inhaled steroids).
• Toxicity can be:
  • Extension of same mechanism (warfarin bleeding).
  • Different tissue with same receptor (digitalis on Na⁺/K⁺-ATPase in heart vs GI/brain).
  • Different receptor (off-target), managed by developing more selective analogues.

Ethical, Philosophical & Practical Implications

• Balancing efficacy vs toxicity involves patient values, disease severity, comorbidities.
• Need for personalised therapy informed by genetics, biomarkers.
• Over- or under-use of antagonists/agonists can cause rebound phenomena (eg, clonidine withdrawal crisis).
• Drug development must consider receptor biology, downstream pathways, and socioeconomic access to selective agents.