Intrasubunit and Intersubunit Steroid Binding Sites Independently and Additively Mediate α 1 β 2 γ 2L GABAA Receptor Potentiation by the Endogenous Neurosteroid Allopregnanolone

Abstract

Prior work employing functional analysis, photolabeling, and X-ray crystallography have identified three distinct binding sites for potentiating steroids in the heteromeric GABA_A receptor. The sites are located in the membrane-spanning domains of the receptor at the β-α subunit interface (site I) and within the α (site II) and β subunits (site III). Here, we have investigated the effects of mutations to these sites on potentiation of the rat α1β2γ2L GABA_A receptor by the endogenous neurosteroid allopregnanolone (3α5αP). The mutations were introduced alone or in combination to probe the additivity of effects. We show that the effects of amino acid substitutions in sites I and II are energetically additive, indicating independence of the actions of the two steroid binding sites. In site III, none of the mutations tested reduced potentiation by 3α5αP, nor did a mutation in site III modify the effects of mutations in sites I or II. We infer that the binding sites for 3α5αP act independently. The independence of steroid action at each site is supported by photolabeling data showing that mutations in either site I or site II selectively change steroid orientation in the mutated site without affecting labeling at the unmutated site. The findings are discussed in the context of linking energetic additivity to empirical changes in receptor function and ligand binding. SIGNIFICANCE STATEMENT: Prior work has identified three distinct binding sites for potentiating steroids in the heteromeric γ-aminobutyric acid type A receptor. This study shows that the sites act independently and additively in the presence of the steroid allopregnanolone and provide estimates of energetic contributions made by steroid binding to each site.

Fig. 1.

Docking of 3α5αP in the putative binding sites. The panels show side views of the putative β-α intersubunit binding site (site I; A), the intra-α subunit site (site II; B), and the intra-β subunit site (site III; C). The α subunit is shown in tan, the β subunit in gray. 3α5αP (cyan) is docked in each site. In site I, the Q241 residue in α1TM1 is shown as a sphere. Residues homologous to Y308 (Y309) and F297 (F298) in TM3 are photolabeled by KK200 in ELIC-α1 and ELIC-α1(Q242L), respectively, and are shown as ball & stick. In site II, the V226 residue in αTM1 is shown as a sphere. The N407 and Y410 residues in αTM4 previously identified to contribute to steroid binding are shown as ball & stick. In site III, the M283 (light gray; βTM3), Y443 (light gray; βTM4), and Y447 (black; βTM4) are shown as sphere. The G287 residue in βTM3 is identified as black ribbon.

Fig. 2.

Modulation of GABA-activated wild-type and mutant α1β2γ2L receptors by 3α5αP. The panels show sample current traces (A) and steroid concentration-response curves for wild-type α1β2γ2L and mutant receptors with mutations to steroid sites I and II (B) or site III (C). In (B) and (C), the data points show mean ± SD from 5–7 cells. The curves are calculated using the mean fitted parameters provided in Table 2. The inset in (B) gives the concentration-response curves for receptors containing the α1(Q241L) and α1(Q241L+V226W) mutations at higher resolution.

Fig. 3.

Potentiation of the α1(Q241L)β2γ2L receptor by 3α5αP and alfaxalone. (A) shows the effect of 1 µM 3α5αP on steady-state current elicited by 50 µM GABA. The peak P_A of the response to GABA was 0.063. (B) shows the effect of 3 µM alfaxalone (ALF) on peak responses to 20 µM GABA. The mean peak P_A of the responses to GABA before exposure to the steroid was 0.037.

Fig. 4.

Double mutant cycle analysis. Comparison of energetic effects of mutations introduced alone or in combination to sites I and II (A), sites I and III (B), and sites II and III (C). The ΔG in parentheses indicate the stabilization energy provided by 3α5αP in each receptor. ΔΔG values showing the effects of mutations are given in blue. The ΔG in brackets (red) for the double mutants gives the expected stabilization energy, calculated based on ideal additivity of the effects of single mutations. The closeness of the measured and calculated ΔG values for the double mutants indicates that the mutations act independently and additively.

Fig. 5.

Summary of effects of modifications to one or both binding sites on receptor activation. The graphs show modeled peak open probability (P_A) versus agonist (X) concentration. Modeling was done using K_R,X of 10 arbitrary units (a.u.) and N_X of 2. The graphs compare the effects of loss-of-function modifications to one or both agonist binding sites. (A–C) describe a model with L of 1000 mimicking direct activation by X, and (D–F) describe a model with L of 19 mimicking X-mediated potentiation of receptor activity elicited by another agonist. (A, B, D, and E) show the effects of changing the value of c in one (blue lines) or both binding sites (red line) from 0.01 to 0.9. The precise maximal P_A values for each condition are given in text. (C and F) describe the reduction in maximal P_A (fold-effect) in receptors containing one (blue solid line) or both (black line) modified binding sites. The value of modified c was held at 0.9. The value of unmodified, i.e., wild-type c is given by the abscissa. The blue dashed line gives a squared fold-effect observed when one binding site is modified.

Fig. 6.

Summary of effects of modifications to one or both binding sites on receptor P_A/P_R. The graphs show calculated values of P_A/P_R for the same conditions as were used in Figure 5. (A) shows a logarithmic plot for values when L = 1000, with values for c₁ and c₂ indicated. The low concentration asymptote is 1/L (0.001) for all the curves, whereas the high-concentration asymptote is 1/(Lc₁c₂). The arrows show the multiplicative relationship between the maximal values (90-fold when the nonmutated c = 0.01 and 9-fold when the nonmutated c = 0.1). (B) shows similar calculations for L=19. Note that the curves in (B) are shifted upwards by the ratio 1000/19 but are otherwise identical. MT, mutant; WT, wild-type.

Fig. 7.

Summary of effects of modifications to one or both binding sites for allosteric agonist on binding of orthosteric agonist. The simulations show potentiation of muscimol binding by allosteric agonist X. The simulations were based on α1β2γ2L GABA_A receptor with L = 8000 and Q = 0.29 (Shin et al., 2017; Germann et al., 2019). The properties (K_R,muscimol = 0.5 µM, c_muscimol = 0.01, N_muscimol = 2 binding sites) and concentration (0.039 µM) of muscimol were selected so as to generate equilibrium occupancy of 10% of binding sites. The allosteric agonist X was assigned K_R,X = 0.5 units and N_X = 2 binding sites, with c₁ = c₂ = 0.01 (A) or c₁ = c₂ = 0.25 (B). Introduction of a loss-of-function mutation to one or both binding sites was simulated by changing the value of c in that binding site to 0.9.