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. 2018 Feb 22;8(1):3479.
doi: 10.1038/s41598-018-21100-x.

Micro-pharmacokinetics: Quantifying local drug concentration at live cell membranes

Karolina Gherbi  1   2 , Stephen J Briddon  1   3 , Steven J Charlton  4   5   6
Affiliations

Micro-pharmacokinetics: Quantifying local drug concentration at live cell membranes

Karolina Gherbi et al. Sci Rep. .

Abstract

Fundamental equations for determining pharmacological parameters, such as the binding affinity of a ligand for its target receptor, assume a homogeneous distribution of ligand, with concentrations in the immediate vicinity of the receptor being the same as those in the bulk aqueous phase. It is, however, known that drugs are able to interact directly with the plasma membrane, potentially increasing local ligand concentrations around the receptor. We have previously reported an influence of ligand-phospholipid interactions on ligand binding kinetics at the β2-adrenoceptor, which resulted in distinct "micro-pharmacokinetic" ligand profiles. Here, we directly quantified the local concentration of BODIPY630/650-PEG8-S-propranolol (BY-propranolol), a fluorescent derivative of the classical β-blocker propranolol, at various distances above membranes of single living cells using fluorescence correlation spectroscopy. We show for the first time a significantly increased ligand concentration immediately adjacent to the cell membrane compared to the bulk aqueous phase. We further show a clear role of both the cell membrane and the β2-adrenoceptor in determining high local BY-propranolol concentrations at the cell surface. These data suggest that the true binding affinity of BY-propranolol for the β2-adrenoceptor is likely far lower than previously reported and highlights the critical importance of understanding the "micro-pharmacokinetic" profiles of ligands for membrane-associated proteins.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
FCS experimental set-up used in this study. (a) Confocal image of receptor expressing (cell 1) and non-receptor expressing (cell 2) CHO-β2GFP cells, and control areas of no cell (area 3) used for FCS measurements. (b) Crosshair placement over the nucleus of a single cell was used to define the positioning of the FCS confocal volume in the x-y plane. (c) Detection of BY-propranolol fluorescence intensities in the z dimension allowed localisation of the upper cell membrane. (d) Schematic representation of confocal volume positions covering a range of distances from 2–200 µm above the upper membrane of a single cell in 1, 2, 10 and 50 μm steps. (e) Determination of particle number (N) and dwell time (τD1) to quantify concentration and diffusion coefficient of BY-propranolol from its FCS autocorrelation curve.
Figure 2
Figure 2
Role of the presence of the target receptor and the cell membrane on local BY-propranolol concentrations and diffusion coefficients. (a,b) Local concentrations (a) and diffusion coefficients (b) of BY-propranolol measured 2–200 µm above membranes of receptor expressing (high) CHO-β2GFP cells in the absence (n = 13) and presence of 550 nM ICI 118,551 (ICI; n = 7) and non-receptor expressing (none) CHO-β2GFP cells (n = 10) following 2 hours BY-propranolol incubation. The same experiments were carried out in areas of no cell (3–207 µm above the coverslip; absence of antagonist only; n = 8). Data shown are mean ± s.e.m. of n individual cells investigated on the same number of separate experimental days, and #denotes statistical significance (P < 0.05) of the value determined in receptor-expressing cells (CHO-β2GFP high) compared to the value determined in no cells, non-receptor expressing (CHO-β2GFP none) cells and receptor-expressing cells in the presence of ICI 118,551 at an equivalent distance from the coverslip (2-way ANOVA, Tukey’s post hoc test), whilst * Indicates statistically significant differences (P < 0.05) in ligand concentrations at various distances above the coverslip compared to the concentration determined at the furthest distance measured for each individual condition (2-way ANOVA, Tukey’s post hoc test). BY-propranolol diffusion coefficients were not statistically different across the range of distances tested (P > 0.05, 2-way ANOVA, Tukey’s post hoc test).
Figure 3
Figure 3
Effect of incubation time on BY-propranolol concentrations in the immediate vicinity of cell membranes. Local concentrations of BY-propranolol 2 µm above membranes of receptor expressing (high) CHO-β2GFP cells in the absence (n = 13) and presence of 550 nM ICI 118,551 (ICI; n = 7) and non-receptor expressing (none) CHO-β2GFP cells (n = 10) following a 15, 30, 60, 90 and 120 minutes BY-propranolol incubation. The same experiments were carried out in areas of no cell (data from measurements 3 µm above the coverslip; absence of antagonist only; n = 8). Data shown are mean ± s.e.m. of n individual cells investigated on the same number of separate experimental days, and #denotes statistical significance (P < 0.05) of the value determined in receptor-expressing cells (CHO-β2GFP high) compared to the value determined in no cells at an equivalent time point (2-way ANOVA, Tukey’s post hoc test). *Indicates statistically significant differences (P < 0.05) in ligand concentrations compared to the concentration determined at the 15 minute time point (2-way ANOVA, Tukey’s post hoc test).
Figure 4
Figure 4
Schematic representation of increased local ligand concentrations in the immediate vicinity of the cell membrane and target receptors compared to the bulk aqueous phase. A ligand concentration gradient may potentially be caused by ligand interactions with both cell membrane components and target receptors (R). To account for heterogeneous ligand distribution in the determination of pharmacological parameters, higher local ligand concentrations (Lmicro) may be used, as shown here for affinity (Kd) calculations.
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