Primary and Secondary Binding of Exenatide to Liposomes

Article

Primary and Secondary Binding of Exenatide to Liposomes Anja Stulz,1 Michaela Breitsamer,2 Gerhard Winter,2 and Heiko Heerklotz1,3,4,* 1 € t, Freiburg, Germany; 2Pharmaceutical Technology and Biopharmaceutics, Institute of Pharmaceutical Sciences, Albert-Ludwigs-Universita €t Mu € nchen, Munich, Germany; 3Signalling Research Centres BIOSS and CIBSS, Department of Pharmacy, Ludwig-Maximilians-Universita Freiburg, Germany; and 4Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario, Canada

ABSTRACT The interactions of exenatide, a Trp-containing peptide used as a drug to treat diabetes, with liposomes were studied by isothermal titration calorimetry (ITC), tryptophan (Trp) fluorescence, and microscale thermophoresis measurements. The results are not only important for better understanding the release of this specific drug from vesicular phospholipid gel formulations but describe a general scenario as described before for various systems. This study introduces a model to fit these data on the basis of primary and secondary peptide-lipid interactions. Finally, resolving apparent inconsistencies between different methods aids the design and critical interpretation of binding experiments in general. Our results show that the net cationic exenatide adsorbs electrostatically to liposomes containing anionic diacyl phosphatidylglycerol lipids (PG); however, the ITC data could not properly be fitted by any established model. The combination of electrostatic adsorption of exenatide to the membrane surface and its self-association (Kd ¼ 46 mM) suggested the possibility of secondary binding of peptide to the first, primarily (i.e., lipid-) bound peptide layer. A global fit of the ITC data validated this model and suggested one peptide to bind primarily per five PG molecules with a Kd z 0.2 mM for PC/PG 1:1 and 0.6 mM for PC/PG 7:3 liposomes. Secondary binding shows a weaker affinity and a less exothermic or even endothermic enthalpy change. Depending on the concentration of liposomes, secondary binding may also lead to liposomal aggregation as detected by dynamic light-scattering measurements. ITC quantifies primary and secondary binding separately, whereas microscale thermophoresis and Trp fluorescence represent a summary or average of both effects, possibly with the fluorescence data showing somewhat greater weighting of primary binding. Systems with secondary peptide-peptide association within the membrane are mathematically analogous to the adsorption discussed here.

SIGNIFICANCE Isothermal titration calorimetry (ITC) is a versatile method to study peptide interactions with lipid membranes. However, for complex binding behaviors, analysis of ITC data can be challenging because the usage of established binding models might be inappropriate. The peptide exenatide binds primarily to lipid membranes and secondarily to prebound peptide, resulting in ITC curves of complex shape. We established a binding model that allowed a quantitative characterization of primary and secondary binding and resolved apparent inconsistencies between ITC data, tryptophan fluorescence, and microscale thermophoresis measurements. This approach may also be appropriate for the analysis of similar ITC data previously reported in the literature.

INTRODUCTION Isothermal titration calorimetry (ITC), tryptophan (Trp) fluorescence, microscale thermophoresis (MST) and other methods have been used to quantify the binding of ligands to receptor molecules or to the lipid matrix of biomembranes. Although the quantitative models used to Submitted August 21, 2019, and accepted for publication December 23, 2019. *Correspondence: [email protected] Editor: Kalina Hristova. https://doi.org/10.1016/j.bpj.2019.12.028 Ó 2020 Biophysical Society.

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analyze the binding data describe many experimental systems, other systems cannot be analyzed satisfactorily with the existing binding models. The peptide exenatide is one such ligand. The ITC data for the interaction of this ligand are biphasic and satisfactorily described only by a model that includes two independent binding sites. This is the first, to our knowledge, description of such a binding model; it is the main aim of this study. A quantitative understanding of the binding of peptides and peptide mimics to liposomes is important for a variety of reasons. First, in studies of membrane-active drugs, liposomes are used as models of cell membranes (1–6). Second,

Primary and Secondary Peptide Binding

liposomes and other lipid-based drug delivery systems are used to formulate drugs and diagnostics for parenteral, oral, transdermal, and other delivery routes (7–9). Third, peptide-drug conjugates and peptide-modified drug delivery systems enhance the bioavailability of drugs by enhancing the penetration of biological barriers and entry to the cytoplasm of cells (10). In the pharmaceutical context, interactions with peptides and other membrane-binding compounds with liposomes are involved in loading, retaining, and releasing drugs to achieving controlled or targeted release, enhancing cell uptake, or endosomal release. For these applications, knowledge of the membrane-bound fraction of the peptide and this fraction’s changes as a function of lipid composition, lipid concentration, and other conditions is essential. To this end, a wide variety of analytical methods are available, including ITC (11–13), surface plasmon resonance (SPR) (14), MST (15), fluorescence techniques using intrinsic fluorophores or fluorescent labels (16), and the equipotency analyses based on whatever peptide-dependent membrane parameter (17). The results obtained using any of these methods should, of course, agree with each other in the ideal case (18), but their applicability and their experimental errors may differ a great deal because of effects related to immobilization (19), turbidity, aggregation (20), heats of dilution, et cetera. Furthermore, the use of inappropriate or oversimplified binding models may not affect the evaluation of the data in the same manner. The details of the interaction between ligands and membranes give rise to alternative, thermodynamic models describing the binding. Small hydrophobic or amphiphilic molecules typically exhibit unspecific, nonsaturating partitioning into lipid membranes that is described adequately by Nernst’s (21) partition coefficient or similar models based on mole ratios or fractions that take into account the insertion of the amphiphile into a two-dimensional membrane (22). These models can be extended with the Gouy-Chapman theory to account for electrostatic interactions, which result in a continuously decreasing apparent partition coefficient as the electrostatic surface potential of the membrane is more and more affected by the ligand (23–25). Ligand binding to defined binding sites on the membrane surface may be treated as a Langmuir adsorption isotherm (26). The limitation of binding to ‘‘sites’’ may have several origins. For example, a binding site might be defined by the interaction of a molecule or group. Alternatively, it may be characterized by excluded volume effects of, for example, a peptide forming a more or less dense monolayer on the surface of the membrane. All these models share the commonality of the corresponding ITC curves showing monotonically decreasing heats per mole of injected titrant. This decrease may be sigmoidal (Langmuir), quasiexponential (constant partition coefficient), or a combination of the two (Gouy-Chapman), but none of these models can explain a local maximum or minimum of the curve. Titrations

crossing a phase boundary, for example, between membranes and micelles (27,28) or between membranes and lipid-cyclodextrin complexes in solution (29) typically exhibit sharp breakpoints as a new phase appears. A qualitatively different, nonmonotonic behavior involving a broad local maximum of the absolute titration heat at intermediate titrant concentration has been obtained here for exenatide. Exenatide is a synthetic form of a peptide found in the saliva of the Gila monster and used as a drug to treat type 2 diabetes mellitus (30,31). It has been considered for sustained release formulations using vesicular phospholipid gels (32); thus, much attention has been focused on its interactions with liposomes of different compositions. In ITC measurements, exenatide yielded data that are qualitatively similar to those found for gomesin (33) and antimicrobial b-17 peptide (34) interacting with liposomes and lauryl-FF1 binding to LPS (35). Membrane interactions of aurein (36) and fengycin ((37) data not shown) gave rise to similar ITC curves. All these ITC curves resembled what had been termed two-sets-of-sites behavior in ligand-receptor binding studies. Examples for such curves fitted quantitatively are those of mitoxantrone binding to different sites on human serum albumin (38), C2 domains of protein kinases binding one Ca2þ exothermally with high affinity and two more endothermally with lower affinity (39), and ZnO binding to ZnO-binding peptides (40). Hinderliter and co-workers (41) used a partition-function approach to evaluate biphasic ITC curves arising from binding of calcium ions to annexin V in the solution and membrane-associated states. As gomesin and b-17 peptide, exenatide does not only seem to bind to two different sites on the membrane (in the absence of another protein), it also self-associates in solution and at high concentration, and it induces the aggregation of liposomes containing anionic lipids. This raised the hypothesis that the two sites might correspond to 1) the direct, primary binding or adsorption of the peptide at the lipid membrane surface and 2) the secondary binding of one or more additional exenatide molecules to primarily bound exenatide. In other words, self-associated exenatide does not only exist in solution but also, at even lower concentration, on the membrane surface. It should be noted that although involving two types of sites, this case cannot be treated with the script for independent binding to two sets of sites that is enclosed in the MicroCal data evaluation software (Malvern Panalytical, Worcestershire, United Kingdom). Instead, this concept is largely analogous to allosteric binding with a second site becoming available only after occupation of the primary one. Physically, it is closely related to a Brunauer-Emmett-Teller (BET) isotherm (42). This applies to molecules that 1) adsorb to a surface and 2) show a tendency to selfassociate in the bulk, either by condensation from the gas phase or, analogously, by precipitation from solution. Then, further deposition on top of the preformed Langmuir monolayer on the surface will start already at concentrations

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below saturation in the bulk because ‘‘the large free surface energy of small clusters makes their formation improbable. On the other hand, in adsorption the ‘liquid surface’ is practically complete after the first layer has been adsorbed, so that during the formation of successive layers hardly any surface tension has to be overcome’’ (42). This approach resembles to some extent what has been described for the loading of doxorubicin to polymeric nanoparticles (43). The aim of this work is of methodical and conceptual nature. It adds an approach to the toolbox of handling and modeling membrane binding that is needed for a variety of other cases as well. Whereas lipid bilayer interactions of exenatide are of ‘‘merely’’ pharmaceutical interest, the same behavior has also been found for numerous systems of major interest for the biomembrane biophysics community. Finally, the new, to our knowledge, concept may help resolving apparent inconsistencies between different binding assays that result from their different responses to different modes or sites of binding.

ITC ITC measurements were done using a MicroCal VP-ITC instrument (Malvern Panalytical). Typically, repeating injections of 8 mL were made every 5–10 min at 25 C and a stirring speed of 394 rpm. As usual, a first 1 mL injection was discarded from the analysis because it is prone to artifacts. In lipid-into-exenatide titrations, aliquots from the syringe containing a dispersion of vesicles (0.2–2 mM lipid) were injected to the calorimeter cell (Vcell ¼ 1.4288 mL), which contained an exenatide solution of various concentrations (1–10 mM). In the reverse experiment titrating exenatide into lipid, the cell was filled with a dispersion of vesicles (typically 80 mM), and the syringe was loaded with an exenatide solution (typically 100 mM). Samples were prepared in 50 mM sodium acetate buffer (pH 4.5) or 10 mM Tris buffer (pH 7.4; containing 110 mM NaCl and 0.5 mM EDTA). Before loading into the calorimeter, the samples were degassed at reduced pressure to avoid air bubbles. In parallel to some runs, DLS measurements were conducted to check vesicle size and size distribution during the ITC experiment. To imitate the exenatide-into-lipid ITC run, 8 mL aliquots of an exenatide solution (100 mM) were titrated into a cuvette containing 1.4 mL POPC/POPG 1:1 vesicles (80 mM lipid) every 5 min. Vice versa, 8 mL aliquots of POPC/POPG 1:1 vesicles (0.8 mM lipid) were titrated into 1.4 mL exenatide solution (3 mM) imitating the lipid-into-exenatide ITC. Five minutes after each injection, Zaverage size and PDI were measured with a Zetasizer Nano ZS.

MATERIALS AND METHODS Materials

Isothermal steady-state fluorescence

Exenatide acetate was purchased from Chemos (Regenstauf, Germany). As described in (9), exenatide acetate was purified by dialysis (MWCO 5 kDa) into highly purified water (Purelab Plus; Elga LabWater, High Wycombe, United Kingdom) and freeze dried for storage. Exenatide stock solutions with a concentration of 200 mM were freshly prepared in buffer, and dilutions thereof were used for interaction measurements. All measurements at pH 4.5 were done with a 50 mM sodium acetate buffer (pH 4.5). Furthermore, a 10 mM Tris buffer (pH 7.4; containing 110 mM NaCl and 0.5 mM EDTA) was prepared for ITC measurements and a 20 mM phosphate-buffered saline (PBS) (pH 7.4) for Trp fluorescence measurements at pH 7.4. The phospholipids 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-(1’-rac-glycerol) (POPG) were a gift from Lipoid (Ludwigshafen am Rhein, Germany).

Steady-state fluorescence was measured using a Cary Eclipse fluorescence spectrophotometer (Agilent Technologies, Santa Clara, CA) and an Optim 1000 instrument (Avacta Life Sciences, Wetherby, United Kingdom). Dilution series were prepared with a constant amount of exenatide in the solution (typically 5 mM) and increasing amount of liposomes. The two components were incubated for 10 min before measurement. Samples were prepared either in 50 mM sodium acetate buffer (pH 4.5) or in 20 mM PBS (pH 7.4). Interactions were assessed by steady-state fluorescence using a Cary Eclipse spectrophotometer with an excitation wavelength of 280 nm while emission was measured from 300 to 450 nm. Fluorescence was measured at 20 C; the spectra were corrected for background intensities and scattering of liposomes by background subtraction (16). Excitation and emission slits with 5 nm bandpass were used for all measurements. For the Optim 1000 instrument, intrinsic fluorescence mode was used with all measurements (lexc ¼ 266 nm, lem ¼ 250–720 nm). Experiments were performed in isothermal mode at 20 C. Micro-cuvette arrays (MCAs) with a capillary volume of 9 mL were used for the measurements. Each MCA was measured five times. Background subtraction of the respective blanks was performed for spectra correction.

Liposome preparation To compare our results to those in (9), liposomes were prepared as described there. Large unilamellar vesicles were prepared by thin-film hydration and extrusion. The phospholipids were dissolved in chloroform (25 mg/mL) and the accurate amount of phospholipid stock solutions was mixed as needed. Chloroform was removed at 40 C using a SpeedVac system (rotational vacuum concentrator 2-18; Martin Christ Gefrier trocknungs anlagen, Osterode am Harz, Germany) or under a constant stream of nitrogen while the glass vial was turned. The resulting thin phospholipid film was hydrated with 50 mM sodium acetate buffer (pH 4.5), 10 mM Tris buffer (pH 7.4; containing 110 mM NaCl and 0.5 mM EDTA), or 20 mM PBS (pH 7.4). Extrusion was done with a Lipex (Transferra Nanosciences, Burnaby, British Columbia, Canada) or LiposoFast (Avestin, Ottawa, Ontario, Canada) extruder. To achieve a homogenous dispersion, the liposomes were extruded five times through a 200-nm polycarbonate membrane and several times through a 100-nm polycarbonate membrane. Z-average hydrodynamic diameter and polydispersity index (PDI) were determined by dynamic light scattering (DLS) using a Zetasizer Nano ZS (Malvern Panalytical). The final phospholipid concentration was either determined using a Bartlett assay or by gravimetric determination (44,45).

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RESULTS Self-association studied by ITC Fig. 1 shows the heats produced by the dilution of aliquots of 100 mM exenatide at pH 4.5 injected into the cell filled with matching buffer. The data show small but significant heats that decrease quasiexponentially with increasing concentration of titrant in the cell. This behavior is typical if the molecules of the titrant interact strongly in the syringe (43,46–48). Such interactions may range from short-lived dimers to stable oligomers. After an injection of an aliquot, the associated species dissociate because of dilution. For subsequent interactions, the concentration of monomers in the cell is higher and the degree of dissociation of the

Primary and Secondary Peptide Binding 8

the stretch EEAVRLFIEWLK, suggesting an amphipathic section of the helix with alternating charges.

ITC: 100 µM exenatide into matching buffer

7

NDH (kJ/mol)

6 5

ITC binding experiments to POPC/POPG 1:1

4

Fig. 2 shows membrane-binding experiments. A dispersion containing POPC/POPG 1:1 liposomes was titrated into the cell filled with exenatide at different concentrations up to 5 mM. The curves obtained with R2 mM exenatide show exothermic heats of titration with a local minimum (i.e., maximally exothermic). As detailed in the introduction, such curve shapes are typical for two-sets-of-sites systems and cannot be described by standard partitioning, Langmuir (‘‘one set of sites’’), or electrostatically modulated partitioning (Gouy-Chapman) models, all of which exhibit monotonically decreasing heats. What are the two types of exenatide binding sites on the liposomes used here? One possibility is that the two membrane constituents, PC and PG, bind exenatide differently. This possibility is ruled out by two observations. PC alone shows no exenatide binding at all (see Fig. S4) and PG alone shows the two-sets-of-sites behavior (data not shown). Another hypothesis to explain the two types of sites is suggested by the fact that exenatide self-associates in solution with a Kd of 46 mM (Fig. 1). The interaction responsible for self-association may lead to one exenatide molecule binding with another that is already bound to the membrane. The positive net charge could be partially compensated by the PG, and there would be no entropy penalty for immobilization of the prebound partner and no substantial increase in interfacial energy. To test the applicability of such a model of primary and secondary binding, we have carried out a global fit of several ITC curves recorded at different concentrations (Fig. 2, A– D). To this end, we modeled changes in the occupation of the different possible states of exenatide after each injection by an approach with some resemblance of Gauer et al.’s (41) partition-function model. Because the model outlined below does not explicitly consider exenatide self-association in solution and heat effects from liposome aggregation, we have only fitted data sets to exenatide concentrations up to 3 mM with full weight. At this concentration, the monomeric fraction of exenatide in the cell has decreased to 89%, and a minor increase in Z-average hydrodynamic diameter and polydispersity (up to PDI z 0.2) is detected by DLS (Fig. 2 E). To test increased errors at 5 mM exenatide (monomeric fraction 85%), we have included this data set in the fit with a small weight of its square deviations of 6.2% only. The data set obtained with 10 mM exenatide was not fitted (Fig. S2 B). We consider an equilibrium of sites on the membrane, S, binding a peptide, P. The first binding event is given by

3 2 1 0

0

2

4

6

8

10

12

14

16

18

Exenatide concentration (µM) FIGURE 1 A dilution experiment. Aliquots of exenatide (100 mM) were injected into matching acetate buffer at pH 4.5. The data indicate that exenatide self-assembles at high concentrations. The solid curve is a fit to the data of a model that assumes dimerization (Eq. 2) with Kddim ¼ 46 mM and an enthalpy change of 16.7 kJ/mol per dimerizing monomer.

injectant decreases. Such ITC signals have been used to describe the oligomerization behavior of doxorubicin (43). An ITC fit of dimer dissociation, P þ P% PP; K dim d

(1)

with a dissociation constant of K dim ¼ d

C2P ; CPP

(2)

yielded Kddim ¼ 46 mM, with a DHdim ¼ 16.7 kJ per mole of peptide monomers (P) dimerizing, following the fit routine described in (43). It should be noted that the data can also be explained by a stepwise aggregation process (49): Pj þ P%Pjþ1 ; K SA d

(3)

with KdSA ¼ 92 mM and DHSA ¼ 16.7 kJ/mol for adding another exenatide monomer to an existing dimer or oligomer. However, these values imply that even if stepwise aggregation is possible, there would be very limited formation of complexes larger than dimers under the conditions used in these measurements (see Figs. 2 and 5). Therefore, we will refer to complexes in aqueous solution as dimers, while acknowledging that the solution may also contain a small fraction of larger species. Exenatide is largely helical in solution with a primary structure HGEGTFTSBLSKQMEEEAVRLFIEWLKNGGP SSGAPPPS-NH2. It has an isoelectric point of 4.86 (50); at pH 4.5, it will contain four cationic and less than four anionic side chains. Plausible interaction sites for salt bridges and/or hydrophobic interactions are in the middle of the molecule, in

S þ P#SP; K 1d

(4)

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A

B

C

D

E

F

FIGURE 2 (A–D) ITC data obtained by titrating POPC/POPG 1:1 liposomes into exenatide solutions of different concentrations as indicated, at pH 4.5. The blue lines show global fit curves for a model including primary and secondary binding as outlined in the text. (E) Dynamic light-scattering (DLS) data of samples resembling the conditions during the ITC experiment with 3 mM exenatide revealed a slight loss of homogeneity but no strong aggregation of the liposomes. (F) A landscape plot of normalized sum of squared deviations (NSSD) is shown as a function of n and Kd1, indicating best-fit parameters with Kd1 ¼ (0.12–0.35) mM and n ¼ (9.7–12) for NSSD %1.1 at Kd2 ¼ 10 mM. The corresponding DH1 is strongly exothermic, 35 kJ/mol.

and the binding of the subsequent peptides is given by SPi þ P# SPiþ1 : i Kd

(5)

In the fitting routine, we allowed for up to five peptides per site. However, in the low-concentration range addressed here, the only species present at non-negligible concentrations are S, SP, and SP2. From our data, we cannot determine whether or not the species SP3, SP4, etc. might form at higher concentrations. According to the procedure detailed in the Supporting Materials and Methods, we performed a support-plane analysis (SPA) selecting dissociation constants for primary and secondary binding, Kd1 and Kd2, and the number of lipid molecules per primary binding site, nprim: cL nprim ¼ : (6) 5 P cS þ cSPi i¼1

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For each set of these parameters, we fitted the corresponding enthalpy changes of primary and secondary binding, DH1 and DH2, globally along with individual values of Qoffset for each curve using the Excel Solver tool (51) (Microsoft, Redmon, WA); the global fit is represented by bold blue curves in Fig. 2, A–D. Qoffset accounts for a small, constant offset that results from heats of dilution and micro-Kelvin-temperature mismatches that should largely (but not necessarily precisely) agree with the heats of a lipid-into-buffer titration. We found that Kd2 correlated strongly with DH2; hence, any value of Kd2 R 10 mM had little effect on the quality of the final fit. This is illustrated by the relative change in overall NSSD (normalized sum of squared deviations) as a function of Kd2 shown in Fig. S1 C. Following the principles of BET adsorption, it is likely that secondary adsorption is favored compared to dimerization in solution. Thus, we can only determine that Kd2 lies within the range of 10 to 46 mM and DH2 in the range of 6.7 to 57 kJ/mol. The fit yields only a lower bound of Kd2; however, this reduces the parameter space to be covered by simulations to two dimensions, Kd1 and n. Fig. 2 F shows a landscape

Primary and Secondary Peptide Binding

plot of NSSD as a function of these input values, indicating some correlation but still a fairly good resolution with Kd1 ¼ 0.12–0.35 mM and n ¼ 9.7–12 for NSSD %1.1 at Kd2 ¼ 10 mM. The corresponding DH1 is strongly exothermic, 35 kJ/mol. We note that the reliability of uncertainties provided from an SPA of a global fit is much better than the deviation of fits of identical replicates because it challenges the validity of the model and reveals correlations between fit parameters, which is a serious problem in our case. To assess the influence of dimerization or oligomerization of exenatide in solution, liposome aggregation, and other possible complications that might affect the data, we also performed a lipid-into-exenatide titration at 10 mM exenatide and one titrating 100 mM exenatide into 80 mM lipid as presented in Fig. S2. We did not attempt to fit these data given that we know our model does not apply to these cases. Instead, we have simulated corresponding model curves based on the parameters in Table 1 to illustrate the deviations. ITC binding experiments to other lipid compositions ITC data of injecting 100 mM exenatide into a liposomal dispersion of 80 mM POPC are indistinguishable from those obtained in the absence of lipid as shown in Figs. 1 and S4 A. The reverse experiment, titrating POPC liposomes into exenatide, yielded virtually no heats (see Fig. S4 B for data). These results are most likely explained by an absence of binding in the concentration range studied, that is, a Kd >> 80 mM. It should however be mentioned that we cannot TABLE 1 Results of Association and Binding Experiments of Exenatide to Liposomes as Indicated Kd (mM)

n

n/PG

DH (kJ/mol)

46

ND

ND

17

No Lipid ITC (dimerization/ oligomerization) POPC/POPG 1:1 ITC (secondary binding) 10–46 ND ND (6.7)–57a ITC (primary binding) 0.2 [0.12–0.35] 11 [9.7–12] 5.5 35 Trp-intensity 0.6 [0.2–1.3] 4.3 [3.5–4.9] 2.2 ND MST 2.4 3.1 1.6 ND POPC/POPG 7:3 ITC (secondary binding) ITC (primary binding) Trp-intensity MST

10–46 0.6 [0.3–1.2] 2.3 [1.6–3.5] 2.3

ND 17 [14–20] 7.5 [6.1–8.7] 2.9

ND 5.1 2.3 0.9

33240a 40 ND ND

The ranges given are based on the assumption that Kd of secondary binding should, typically, be lower than that of dimerization in solution. Uncertainties are given as ranges with the NSSD % 1.1 in the SPA (see, e.g., Fig. 2 F). ND, no data. a The data showed a strong correlation of Kd2 with DH2, which rendered determination of an upper limit for Kd2 impossible.

strictly exclude an enthalpically silent binding process (DH z 0) governed by entropy exclusively, which would not be detected by ITC. Mixed liposomes with POPC/POPG 7:3 were studied analogously to the experiments in Fig. 2 (see Fig. S3). The fit parameters are compiled in Table 1.

Binding characterized by tryptophan fluorescence The sensitivity of the initial tryptophan fluorescence of exenatide to exenatide-liposome interactions seen in the MST system (see (9)) motivated a more detailed inspection of the interaction with fluorescence spectroscopy (52). Contact of tryptophan with water causes fluorescence quenching and dipolar relaxation resulting in a red shift of the fluorescence spectrum. Hence, binding processes screening previously water-exposed tryptophan residues from water and rendering their environment less polar can be detected by an increase in intensity and a spectral shift to shorter wavelengths (52–56). A significant shift of the fluorescence spectral maximum of exenatide to shorter wavelengths (blue shift) was observed at pH 4.5 in the presence of liposomes composed of POPC/POPG mixtures or POPG (see Fig. 3 A). The fluorescence maximum shifts from 347 to 334 nm after the addition of POPG liposomes to a 5 mM exenatide solution at pH 4.5. Similar shifts were observed for the liposomes composed of the POPC/POPG mixtures. No changes in fluorescence maximum were observed for the addition of liposomes composed only of POPC (see Fig. 3 B) and for all formulations at pH 7.4. For a standard fit of membrane binding or partitioning, Ladokhin et al. (16) emphasized that the intensity change at any fixed wavelength should be a linear response function, that is, it changes its value proportionally to the change in the membrane-bound fraction of the peptide. They point out that the wavelength or intensity at the maximum and other parameters quantifying the spectral shift are not linear response functions. They also emphasize the need to correct for turbidity effects, particularly using liposomes in the millimolar lipid range. Given that the effective lipid concentrations in our experiments are orders of magnitude below those needed for typical peptide partitioning studies, we did not need to explicitly correct for turbidity effects here. Given that turbidity effects in a standard cuvette cause both a loss in intensity and a red shift (16), significant turbidity effects can be excluded based on the good global fit of F350 and F330. Because Trp fluorescence does not display two binding events, we analyzed these data with a simplified set of equations by modifying Eqs. 4 and 5: S þ P%SP: Kd

(7)

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Fl(0) and Fl(1) equal the intensity expected if all peptide is free or all peptide is bound, respectively. These values should not depend on xb and should be conserved in a binding experiment if the peptide concentration is constant. To compute xb for a given parameter set, we calculate the concentration of bound peptide, cSP, by solving Eq. 9 and taking into account mass balances for the peptide and lipid:

Normalized Fluorescence Intensity

A 1.0

0.8

0.6

0.4

Kd cSP ¼ 2 2 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi3   tot tot tot tot 2 tot tot c þ c c  c c þ c P P S P 4 S þ1 þ2 S þ 1 5: Kd Kd Kd

0.2

0.0 300

320

340

360

380

400

420

440

Wavelength (nm)

(12)

Normalized Fluorescence Intensity

B 1.0

0.8

0.6

0.4

0.2

0.0 300

320

340

360

380

400

420

440

Wavelength (nm)

FIGURE 3 Normalized fluorescence spectra of the titration of exenatide (5 mM) with (A) POPG liposomes (0.5–1.5  105 mM) and (B) POPC liposomes (0.5–1.5  105 mM).

In this model, the binding of each ligand, P, is considered to occupy a site, S, without consideration of whether the ligand is primarily or secondarily bound. Thus, in contrast to Eq. 6, we obtain an apparent number of lipids per site, napp: napp ¼ cS þ

cLip 5 P i¼1

;

(8)

i cSPi

so that napp % nprim, and Kd ¼

cS  cP : cSP

(9)

These equations describe a two-state system in which tryptophan is either free in solution or bound. The fluorescence intensity at a given wavelength, Fl, as a function of the membrane-bound fraction of exenatide, xb, is given by Fl ðxb Þ ¼ xb Fl ð1Þ þ ð1  xb ÞFl ð0Þ;

(10)

with xb defined as cSP xb h tot : cP

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(11)

Equations 10 through 12 were used to fit Kd and n along with F330(0), F330(1), F350(0), and F350(1) to the intensity changes at both 330 and 350 nm simultaneously as a function of lipid concentration (Fig. 4 A, fit parameters in Table 1). For the fit, each data point represented the average of the intensities of three samples and was weighted with their standard deviation. Alternatively, we have derived a nonlinear response function to fit the spectral shift independently. To this end, the position of the spectrum was specified in terms of intensity ratio I350/I330. However, the resulting fit showed a strong correlation between n and Kd so that it should only be used if the number of sites per lipid, n, is known. Because this is not the case here, we will not discuss it further. In line with the ITC data, tryptophan fluorescence spectra of exenatide were unaffected by the addition of POPC liposomes at pH 4.5 as well as any lipid tested at pH 7.4. MST data The binding measurements of the systems and conditions addressed here were carried out using MST, using the built-in evaluation routine that does not treat the size of a binding site, n, as an adjustable parameter (9). The data from these measurements showed that exenatide binds to PG-containing liposomes at pH 4.5 with a low micromolar Kd, whereas no binding was detected for POPC or at pH 7.4 for all tested lipid mixtures. To render the results of these measurements directly comparable to the more detailed model used here, we have refitted these data using Eq. 9. The results are included in Table 1. DISCUSSION Primary and secondary binding of exenatide to lipid membranes A nonmonotonic ITC curve is consistent with ligand binding to two types of sites (or states) with different enthalpy values. What seems natural for drug insertion into different

Primary and Secondary Peptide Binding

A

B

FIGURE 4 Fluorescence intensity at 330 nm (down triangles) and 350 nm (up triangles) as a function of lipid concentration at 5 mM exenatide (average of three samples, each). (A) Data for liposomes of PC/PG 1:1 and (B) data for liposomes of PG/PC 7:3 are shown. (C) Results of the SPA for Kd are shown. Optimal fits and confidence intervals for Kd and n are compiled in Table 1; fit results for Il(0, 1) are not listed. Error bars reflect standard deviations of 3 samples, each.

binding pockets of an albumin is much less obvious for lipid membrane binding. One might think of specific binding to different membrane domains or constituents or a distinction between isolated peptides and such establishing strong, specific peptide-peptide interactions. We have studied exenatide-liposome interactions under conditions in which strong electrostatic interactions were either present or not present. The observation of strong binding only for cationic peptide (pH 4.5) to anionic, POPG-containing membranes supports the idea of a largely electrostatic, superficial adsorption with little or no intrusion of hydrophobic side chains into the membrane. This is in line with the lack of any extended hydrophobic structure of the peptide that could insert into the membrane. These considerations motivated the choice of a mass action or Langmuir-based adsorption model. The additional finding of peptide-peptide association in solution and of the aggre-

gation of peptide-covered liposomes suggests that the second class of binding site arises from peptide-peptide binding on the membrane surface. We have devised a model that assumes a saturating, primary binding of peptide to defined membrane sites and a secondary binding of one or more peptides on each primarily bound peptide. Secondary binding proceeds with lower affinity; thus, it does not occur between primarily bound peptides, which would lead to clustering on the membrane. Depending on whether the interaction sites of the peptides lead to a face-to-face or stacking arrangement of the molecules, secondary binding might be limited to a second peptide (SP2) or proceed to additional ‘‘layers’’ SP3, SP4, etc., as more peptide becomes available. In principle, our model allows for an unlimited extent of secondary binding. In this context, we should have a closer look into the distribution of species during the experiments as illustrated by Fig. 5. The ITC titration into 1 mM exenatide shown in Fig. 2 A gave rise to a quasisigmoidal curve without significant deviation because of secondary binding; this agrees with the fact that SP2 is not populated more than 2% (Fig. 5 A). In the first few injections in this measurement, the available lipid is too dilute (< Kd1, not more than 2% of the sites bind a second exenatide molecule. The amounts of SP3 and higher occupancies are negligible. Continued titration of lipid adds more sites that withdraw secondarily bound exenatide to become primarily bound. At 3 mM exenatide (Fig. 5 B), SP2 reaches a maximum concentration of 0.16 mM and SP3 is predicted to reach a concentration of 0.01 mM at the maximum. The corresponding contribution of forming or dissociating SP3 to the ITC curve is weak, and our data do not allow us to distinguish between secondary binding being limited to SP2 and higher levels of ligand interactions. The average number of lipids per primary binding site, n, equals 11 and 17 lipids per site for membranes with 50%, and 30% PG, respectively. Expressed per POPG only, which would be responsible for electrostatic binding, we obtain an average of 5 POPG molecules per site in all cases we investigated. Given that ITC detects binding within a few minutes after injection only, it is reasonable to assume that little or no binding to the inner membrane surface occurs during these measurements. Thus, half of the lipid is inaccessible and the contact site would involve patches of 2.5 POPG, along with three or six POPC molecules, respectively (see (57)). Taking into account that a compact, spherical protein of 5 kDa would have a cross-sectional area of about the lateral area of six lipid molecules and an a-helix that of two to three lipids, it seems that the 1:1 POPC/POPG membrane is completely covered by peptide upon primary saturation.

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A

B

FIGURE 5 The concentrations of all species during the ITC experiments are shown as a function of the concentration of sites. The titration at 1 mM exenatide (A) shows very little secondary binding, whereas at 3 mM exenatide (B), SP2 reaches a maximum concentration of 0.16 mM. Continued addition of liposomes during the experiment adds more sites, and secondarily bound exenatide is withdrawn to become primarily bound.

At higher peptide and lipid concentration as in Fig. S2, we observed strong aggregation of the liposomes, apparently resulting from binding between peptides being secondarily bound to different liposomes. The binding of exenatide to zwitterionic POPC is at least two orders of magnitude weaker. Such a weak interaction may still suffice for binding all peptide in a lipid gel with its far higher concentration, but the weaker binding energy would likely exhibit a faster off rate and, hence, release kinetics from the surface to the bulk solution.

General importance of peptide-peptide binding on or in membranes The behavior observed and quantitatively described here shows parallels to that observed for the binding of gomesin to liposomes presented by Domingues et al. (33). Gomesin differs from exenatide by a hydrophobic contribution to binding, which results in membrane leakage and which ne-

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cessitates the use of the Gouy-Chapman model for fitting primary binding. However, it shows small deviations from the model for both lipid-into-peptide and peptide-into-lipid ITC measurements; this behavior mimics the data shown in Figs. 2 and S2 quite well. Interestingly, gomesin also causes liposome aggregation (33) and shows an effective stoichiometry of 1 site per 15 lipids (POPC or POPG), corresponding to 1 site per 5 PG molecules. Andr€a et al. (35) showed similar biphasic ITC curves obtained for the binding of lauryl-FF11, an alkylated lactoferricin-derived peptide, to LPS. Interestingly, the cationic peptide self-associates in solution, binds primarily electrostatically to the anionic LPS, and binds secondarily as suggested by positive z potentials at high peptide concentration. Then, it reaches very high binding stoichiometries of the order of two peptides per LPS. Although the situation is probably not identical with the one described here given the significant hydrophobic contribution to binding, the parallels in the overall behavior are interesting. Epand et al. (34) presented a similar ITC curve for the antimicrobial b-17 peptide interacting with liposomes, again implying two modes of binding and involving liposome aggregation. It should be emphasized that the general concept and model of fitting peptide-lipid and peptide-peptide interactions as presented here applies not only to BET-type, secondary adsorption onto primarily bound peptide layers. Another important, conceptually related case is the oligomerization of the peptide within the membrane. Examples of this phenomenon were observed for aurein (36) and fengycin (37), which must oligomerize to activate their membrane permeabilizing activity. As mentioned above, this mechanism is unlikely to apply to exenatide given the low affinity of secondary binding. Clustering or, more generally, strong nonideal interactions within the membrane, might be governed by a model analogous to the one presented here but might also involve additional features. Nonideal interactions in a well-mixed membrane may result in a composition-dependent enthalpy of binding (58). The sequestering of the membrane to form peptide-rich and peptide-depleted domains or phases would probably give rise to rather sharp break points as seen for solubilization (27,58) or additiveinduced domain formation (59) rather than following the typical pattern of two-sets-of-sites binding. Overall, there is a wealth of complex ITC data for peptide-lipid interactions in the literature. Some of these data may have been underused but suitable to provide detailed, quantitative insight into primary and secondary binding effects. The study presented here provides an approach to make full use of such data. Comparing methods and models Our findings have implications for the design of studies of ligand binding to membranes. Semiquantitative techniques can detect interactions and compare affinities of different

Primary and Secondary Peptide Binding

ligands under the specific conditions of the measurement. For example, a routine test using MST at 5 mM exenatide and micromolar lipid implied, correctly, that under these conditions, exenatide binds significantly to PG-containing liposomes at pH 4.5 but not at pH 7.4 or to exclusively zwitterionic membranes (9). Fluorescence and MST data yielded good and largely consistent, empirical fits to a mass action or Langmuir model with one set of binding sites represented by two to three POPG molecules, and virtually all corresponding, effective Kd values were in good agreement with each other, with values on the order of a few mM. The true complexity of the binding behavior was not obvious from these fits directly but indirectly evident from the fact that a binding capacity of one peptide per as little as three to four lipids must be considered unrealistic for direct adsorption to the lipid bilayer surface. ITC revealed more detail and indicated a more complex behavior, but no routinely available model allowed for quantification of the binding processes. We have presented a quantitative model to fit certain, suitable ITC curves (i.e., lipid-into-peptide titrations at low peptide concentration) and permit quantitative analysis of the ITC data. The strength of ITC measurements in this context is that different binding scenarios can be distinguished in terms of their different binding enthalpies rather than relying exclusively on quantifying the amount of bound peptide as a function of concentration. At first glance, the results from the different methods compiled in Table 1 might appear inconsistent in several respects. However, a closer look resolves these issues. ITC revealed initial binding of one peptide per 5 POPG molecules with a high-affinity binding constant of 0.2 mM. Additional secondary peptide binding occurs with a lower affinity of 10 mM or higher. Let us discuss the result expected for a method that does not tell primary from secondary binding. If five POPGs represent a primary site, secondary binding to form SP2 would, for example, give an effective stoichiometry of five PGs per two peptides, that is, 2.5 PGs per peptide. This is in line with what is seen by MST, which detects the changes in mass of the liposome and should, therefore, not tell primary from secondary binding. MST also yields an intermediate Kd of 2 mM, which can be interpreted as an effective average between the 0.2 and >10 mM values for primary and secondary binding. Tryptophan fluorescence is sensitive to changes in the polarity of the molecular environment surrounding the tryptophan residue in the peptide. In this case, it is not clear a priori whether primary binding, where the Trp residue might become localized close to the lipids, and secondary binding farther away from the membrane should have a similar effect on Trp fluorescence intensity and wavelength. The binding experiments yielded confidence intervals for Kd and n that were largely spanning the range from the ITC re-

sults for primary binding and the MST parameters for total binding (see Table 1). Summarizing, quick, simple, and thrifty methods such as SPR, MST or tryptophan fluorescence provided a good empirical description of the binding behavior in the concentration range studied with more or less routine data evaluation. This may serve the purpose of a certain research project fairly well (33). However, these methods do not explain apparently unrealistic parameters (such as the high binding capacity) and should not be used to predict binding or release under different conditions. Let us, for example, consider a membrane-active peptide such as gomesin and assume, for the sake of the argument, it had the same binding parameters as exenatide studied here. Tryptophan fluorescence performed at concentrations of the order of 10– 100 mM lipid yielded an effective Kd in the micromolar range. In a biological system or microbiological activity assay, the effective lipid concentration may be below 1 mM. For this case, the effective Kd would predict little of the peptide to be bound, but this would be wrong because the primarily bound fraction has a lower Kd and may still be present to a large extent. For exenatide in a vesicular phospholipid gel formulation with its lipid concentration above 100 mM, the amount of exenatide bound might be much higher than predicted from the Trp assay if secondary binding is not limited to SP2. However, the ITC data suggest that there might be two off rates of releasing this bound drug upon dilution, with a fraction (the primarily bound one) lagging behind. Such behavior would not be comprehensible on the basis of the tryptophan fluorescence data. ITC gives more detailed, mechanistic information and allows for a more realistic, quantitative modeling but only after the sometimes tedious process of setting up and validating a proper model. For this reason, it is common practice to screen samples with MST, SPR, or fluorescence methods first and perform ITC on selected lead compounds of particular interest later. CONCLUSIONS There is a considerable body of literature on peptide-lipid interactions possibly involving some kind of primary and secondary binding effects that have not been modeled quantitatively and could benefit from the method of analysis presented here. In our case, the net cationic exenatide adsorbs to anionic liposomes in a primary and one or more secondary steps, reminiscent of a BET isotherm. A model to globally fit sets of ITC curves based on such a behavior has been successfully introduced here. Analysis of our data revealed that primary binding to the membrane surface shows high affinity (0.2–0.6 mM) and highly exothermic enthalpy. One primary binding site required a membrane patch of at least five POPG molecules along with 5–14 POPC molecules in total; half of these lipids are likely inaccessible in

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Stulz et al. 5. Nguyen, L. T., E. F. Haney, and H. J. Vogel. 2011. The expanding scope of antimicrobial peptide structures and their modes of action. Trends Biotechnol. 29:464–472.

the liposome interior and do not truly contribute to adsorption. Potentially sequential, secondary binding of additional peptide with a lower affinity on the range of probably 10–46 mM, involves a much less exothermic or even endothermic binding. The secondary binding is hypothesized to occur by interactions between a ligand and another ligand already interacting with the membrane. Self-association of exenatide in solution, that is, without the assistance of a previously immobilized layer, is exothermic with an affinity of 46 mM. Aggregation is observed at high concentrations of exenatide-covered liposomes. Peptide binding to lipid membranes can involve many different interactions and structural outcomes, possibly several in parallel or sequence. Typical experimental approaches reveal only part of this complexity and may therefore produce incomplete, apparently inconsistent results. Only with the full complexity becoming understood, the apparently contradictory results of MST, tryptophan fluorescence, and ITC turned out to be mutually consistent in focusing on different aspects of the binding behavior. This emphasizes the particular power of combining less demanding methods such as MST, fluorescence, or SPR with ITC performed for selected samples.

14. Besenicar, M., P. Macek, ., G. Anderluh. 2006. Surface plasmon resonance in protein-membrane interactions. Chem. Phys. Lipids. 141:169– 178.

SUPPORTING MATERIAL

15. Jerabek-Willemsen, M., C. J. Wienken, ., S. Duhr. 2011. Molecular interaction studies using microscale thermophoresis. Assay Drug Dev. Technol. 9:342–353.

Supporting Material can be found online at https://doi.org/10.1016/j.bpj. 2019.12.028.

16. Ladokhin, A. S., S. Jayasinghe, and S. H. White. 2000. How to measure and analyze tryptophan fluorescence in membranes properly, and why bother? Anal. Biochem. 285:235–245.

AUTHOR CONTRIBUTIONS

17. Saliba, A. E., I. Vonkova, and A. C. Gavin. 2015. The systematic analysis of protein-lipid interactions comes of age. Nat. Rev. Mol. Cell Biol. 16:753–761.

A.S. and M.B. performed the experiments. H.H.H., A.S., and M.B. established fit models and analyzed the data. H.H.H. and G.W. supervised and designed the research. All authors discussed the results and contributed to writing the manuscript.

ACKNOWLEDGMENTS We thank Annika Vogt for carrying out some of the ITC experiments. We are indebted to Rob Macgregor (Toronto) for thoroughly editing this manuscript. Nicole Specht is acknowledged for support with lipid analytics. A.S. was funded by the Deutsche Forschungsgemeinschaft (German Research Foundation), 27800225/RTG 2202.

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