Antidepressants are modifiers of lipid bilayer properties

Abstract

The two major classes of antidepressants, tricyclic antidepressants (TCAs) and selective serotonin reuptake inhibitors (SSRIs), inhibit neurotransmitter reuptake at synapses. They also have off-target effects on proteins other than neurotransmitter transporters, which may contribute to both desired changes in brain function and the development of side effects. Many proteins modulated by antidepressants are bilayer spanning and coupled to the bilayer through hydrophobic interactions such that the conformational changes underlying their function will perturb the surrounding lipid bilayer, with an energetic cost (ΔG _def) that varies with changes in bilayer properties. Here, we test whether changes in ΔG _def caused by amphiphilic antidepressants partitioning into the bilayer are sufficient to alter membrane protein function. Using gramicidin A (gA) channels to probe whether TCAs and SSRIs alter the bilayer contribution to the free energy difference for the gramicidin monomer⇔dimer equilibrium (representing a well-defined conformational transition), we find that antidepressants alter gA channel activity with varying potency and no stereospecificity but with different effects on bilayer elasticity and intrinsic curvature. Measuring the antidepressant partition coefficients using isothermal titration calorimetry (ITC) or cLogP shows that the bilayer-modifying potency is predicted quite well by the ITC-determined partition coefficients, and channel activity is doubled at an antidepressant/lipid mole ratio of 0.02-0.07. These results suggest a mechanism by which antidepressants could alter the function of diverse membrane proteins by partitioning into cell membranes and thereby altering the bilayer contribution to the energetics of membrane protein conformational changes.

Figure 1.

Membrane proteins are energetically coupled to the lipid bilayer. (A) Schematic depiction of an ion channel that can exist in an inactive (closed) state and an active (open) state. The hydrophobic length of the two conformers differ, with the open state having the shorter hydrophobic length, leading to a hydrophobic mismatch between the protein’s hydrophobic domain and the bilayer hydrophobic core. In response, the bilayer adjusts by compressing and bending the surrounding lipids, which incurs an energetic cost. This bilayer deformation energy, as well as any residual mismatch energy (Mondal et al., 2011), will contribute to the equilibrium between the two conformational states and varies with changes in bilayer material properties, which can be altered by adsorption of small amphiphilic molecules. (B) Schematic depiction of gA channel formation. gA is a pentadecapeptide with β^6.3-helical structure that dimerizes to form a transmembrane channel. The association/dissociation of the channel can be observed as changes in the single-channel current. The length of the conducting channel is less than the thickness of the bilayer, causing gramicidin channel activity (lifetime and frequency of appearance) to be dependent on the bilayer deformation energy. Changes in bilayer properties are observed as changes in lifetime and frequency.

Figure 2.

Effect of fluoxetine (R−/S+) on the time course of ANTS fluorescence quenching. The gray dots represent individual experiments, with the data normalized to the maximum fluorescence in the absence of the quencher. (A) The red dots denote the average of the repeats for a given experimental condition. (B) The red line denotes a stretched exponential fit to each experiment. The blue stippled line demarcates 2 ms, where fluorescence quench rate was determined.

Figure 3.

Summary of the antidepressants' effects on ANTS fluorescence quench rates. (A) Results for the TCAs. (B) Results for the SSRIs. Quench rates were quantified at 2 ms and the rates in the presence of the ADs were normalized to the control rate (no drug, only DMSO) determined in experiments nearest in time to the experiment with the AD. Only a subset of drugs, depending on their potency, were tested at the lowest (10 µM) and the highest (250 µM) concentrations.

Figure 4.

Partition coefficients and molar enthalpies of partitioning determined by ITC as compared with cLogP. (A) Heats of reaction observed when 100 µM fluoxetine (S+) was titrated with 2-µl injections of 15 mM DC_22:1PC LUVs (final lipid concentration in the cell was 2.4 mM). (B) The heats of binding from A were integrated to determine the cumulative reaction enthalpy (circles) for each injection. The results were fit by Eqs. 7 and 8 (solid line) to determine K₂ (= 6.5 ⋅ 10⁻⁴ cm) and $H_{\mathrm{AD}}^{\mathrm{W}\to \mathrm{L}}$ (= –2.5 kcal/mole), R₂ = 0.97. (C) $K_1\mathrm{ }(=2\cdot K_2/d_0)$ determined by ITC (left black or colored columns; colored columns denote compounds that were studied also using the electrophysiology assay) and estimated by cLogP (right gray columns; the consensus cLogP from the ACD/Percepta PhysChem Suite (2012). Values represent mean ± SE; n ≥ 3.

Figure 5.

Comparing the bilayer-modifying potency of ADs with different measures of hydrophobicity (logK₁ in A, cLogP in B, and cLogD₇ in C). The subset of drugs that were tested using ITC are highlighted in red. (A) The slope of the straight line fit to logK₁ versus log(D_AD): −1.28 ± 0.35 (R² = 0.60). (B) The slope of the straight line fit to cLogP versus log(D_AD): −1.46 ± 0.58 (R² = 0.25). Without lofepramine, the slope is −1.24 ± 0.50 (R² = 0.25). (C) Slope of the straight line fit to cLogD₇ versus log(D_AD): −0.68 ± 0.92 (R² = 0.02). Without lofepramine, the slope is −0.016 ± 0.55 (R² = 0.06). The values for cLogP and cLogD₇ are from the ACD/Percepta PhysChem Suite (2012).

Figure 6.

Effect of amitriptyline on gA activity in the single-channel assay. (A) Single-channel current traces recorded with increasing concentrations of amitriptyline added to both sides of a DC_18:1PC/n-decane bilayer doped with gA⁻(13) and AgA(15). The lines denote the current transition amplitudes for gA⁻(13) (red) and AgA(15) (blue). (B) Current transition amplitude histograms of gA⁻(13) and AgA(15). The darker the shading, the greater the amitriptyline concentration. In the absence of the drug, the characteristic current transition peaks were 3.2 ± 0.1 pA and 2.0 ± 0.1 pA for AgA(15) and gA⁻(13), respectively. 100 µM amitriptyline shifted the two peaks to 2.8 ± 0.1 and 1.8 ± 0.1 pA. (C and D) Normalized single-channel survivor histograms (black, solid lines) of AgA(15) (C) and gA⁻(13) (D). The histograms were fit with single exponential distributions (Eq. 7; red dotted lines), with lifetimes (τ).

Figure 7.

Summary of effects of ADs on gA channel activity in the single-channel assay. (A and B) Normalized (A) AgA(15) and (B) gA⁻(13) lifetimes, τ_AD,15/τ_cntrl,15 and τ_AD,13/τ_cntrl,13, respectively, with increasing concentration of the given AD. The colors represent different ADs: amitriptyline (purple), imipramine (pink), fluoxetine (S+; red), fluoxetine (R−; orange), citalopram (S+; blue), citalopram (R−; green).. (C) The ratio of normalized gA⁻(13) versus the normalized AgA(15) single-channel lifetimes at different drug concentrations. A ratio >1 (denoted by the dashed line) indicates a greater effect on channels formed by the shorter gA analogue by the given drug at that concentration. Values represent mean ± SE; n = 3–4.

Figure 8.

Comparing changes in gA⁻(13) lifetimes with AgA(15) lifetimes for a library of compounds. (A) Changes in gA⁻(13) channel lifetimes versus the corresponding changes in AgA(15) channel lifetimes. Gray dots represent previously published data (Lundbæk et al., 2010a; Rusinova et al., 2011, 2015); colored symbols represent different concentrations of the ADs amitriptyline (purple), imipramine (pink), fluoxetine (S+; red), fluoxetine (R−; orange), citalopram (S+; blue), citalopram (R−; green). Values are mean ± SE of ln(normalized τ); n ≥ 3. DC_18:1PC/n-decane. Slope of the straight line fit is 1.17 ± 0.02, with residuals shown in Fig. S3. (B) Histogram of slopes from straight line fits to individual compounds where the maximum lifetime change is at least 150% of the control lifetimes for both gA^–(13) and AgA(15) at maximum concentration. The width of the distribution suggests that some compounds alter bilayer properties other than elasticity. If fitted with a Gaussian distribution, the mean is 1.12, with a SD of 0.06.