Monod-Wyman-Changeux allosteric mechanisms of action and the pharmacology of etomidate

Abstract

Purpose of review: Formal Monod-Wyman-Changeux allosteric mechanisms have proven valuable in framing research on the mechanism of etomidate action on its major molecular targets, γ-aminobutyric acid type A (GABAA) receptors. However, the mathematical formalism of these mechanisms makes them difficult to comprehend.

Recent findings: We illustrate how allosteric models represent shifting equilibria between various functional receptor states (closed versus open) and how co-agonism can be readily understood as simply addition of gating energy associated with occupation of distinct agonist sites. We use these models to illustrate how the functional effects of a point mutation, α1M236W, in GABAA receptors can be translated into an allosteric model phenotype.

Summary: Allosteric co-agonism provides a robust framework for design and interpretation of structure-function experiments aimed at understanding where and how etomidate affects its GABAA receptor target molecules.

Figure 1. Two-state MWC allosteric gating models for GABA_A receptors with zero, one, and two GABA sites

Each panel depicts the free energy balance between opening and closing forces as a see-saw with closing forces on the left and opening (agonist) forces on the right. One scale shows the difference between basal gating energy (ΔG⁰) and that induced by addition of agonists (ΔΔG). Two other scales indicate the balance of closed:open (C:O) receptors and the corresponding open probability (P_open). Note that when opening vs. closing energy is equal (horizontal dashed line), C:O = 1 and open probability is 0.5. Insets show different states and equilibria, with dominant states identified with larger font size. Panel A depicts the basic two-state model, characterized by a single C:O equilibrium constant L₀ = 20,000. The ΔΔG scale is set at zero for this C:O ratio. This low level of spontaneous activity cannot be detected using macrocurrent electrophysiology methods. Panel B depicts a MWC allosteric model with a single GABA (G) binding site. Using our estimated efficacy value for each GABA, corresponding to 16 kJ/mol of gating energy, binding of a single GABA molecule is expected to increase P_open to approximately 0.05. This prediction is remarkably consistent with results of experiments where one of the two GABA sites is altered with a βY205S mutation, dramatically reducing GABA affinity for that site [20]. Panel C depicts the MWC allosteric model of Chang & Weiss [19] with two equivalent GABA sites. At high GABA concentrations, occupation of both sites contributes 32 kJ/mol of gating energy, increasing P_open to about 0.85.

Figure 2. Two-state MWC allosteric co-agonist model for α1β2γ2L GABA_A receptor gating by etomidate and GABA

Panel A: In comparison to Figure 1, two etomidate agonist sites have been added and ΔG⁰ is the same. The inset shows the model from Rusch et al [15] with the highlighted states involved in direct etomidate activation. Note that these states represent a model similar to that in Figure 1C. The low efficacy of etomidate (corresponding to 12 kJ/mol per site) results in P_open ≈ 0.35 with full etomidate occupancy. Panel B: In the presence of a clinical concentration of etomidate (3.2 μM) and no GABA, gating energy is just below the detection threshold for macrocurrent techniques (P_open ≈ 0.005). Panel C: In the presence of 3.2 μM etomidate, less GABA agonist energy is required to result in detectable current. As a result, receptors appear more sensitive to GABA and GABA also appears more efficacious, resulting in a maximal P_open indistinguishable from 1.0. Panel D depicts the co-agonist model open probability as a function of varying GABA and etomidate (ETO). Lines were generated using Equation 6 and the following parameters: L₀ = 20,000; K_G = 80 μM, K_E = 20 μM, c = 0.002, d = 0.008. The solid line represents the GABA concentration response (Fig. 1C). The dashed line represents direct etomidate concentration-response (Fig. 2A). The dotted line represents GABA concentration-response in the presence of 3.2 μM etomidate (Fig. 2C). GABA EC₅₀ is indicated by a “+” sign in each GABA response curve. Note the large leftward shift and the increase in maximal P_open in the presence of 3.2 μM etomidate.

Figure 3. Two-state MWC allosteric co-agonist model for α1M236Wβ2γ2L GABA_A receptor gating by etomidate and GABA

Panel A depicts the effect of the α1M236W mutations on basal gating activity. These receptors display about 15% spontaneous activity, corresponding to about 22 kJ/mol of gating energy in comparison to wild-type receptors. The ΔΔG scale has been zeroed to this open probability. Panel B depicts the high efficacy of GABA in α1M236Wβ2γ2L receptors. Assuming that the efficacy of GABA is unchanged from wild-type, maximal Popen is indistinguishable from 1.0. Panel C depicts why, despite etomidate’s low efficacy in α1M236Wβ2γ2L receptors, it appears to be a potent and efficacious agonist. Note that the gating energy associated with full etomidate occupancy of both mutated etomidate sites is only about 10 kJ/mol (compared with 24 kJ/mol in wild-type receptors; Fig. 2A). However, when added to the basal gating energy, this is sufficient to achieve a P_open near 0.9. Panel D depicts the α1M236Wβ2γ2L co-agonist model open probability as a function of varying GABA and etomidate (ETO). Data were generated using Equation 6 and the following parameters: L₀ = 6.2; K_G = 50 μM, K_E = 24 μM, c = 0.02, d = 0.18. The solid line represents the GABA concentration response (Fig. 3B). The dashed line represents direct etomidate concentration-response (Fig. 3C). The dotted line represents GABA concentration-response in the presence of 3.2 μM etomidate. GABA EC₅₀ is indicated by a “+” sign in each GABA response curve. Note the small leftward shift and the lack of increased maximal P_open in the presence of 3.2 μM etomidate.