Single-Molecule Fluorescence Imaging of Peptide Binding to

May 29, 2009 - (15) Bechinger, B. Biochim. Biophys. Acta 1999, 1462, 157–183. (16) Williams, R. W.; Starman, R.; Taylor, K. M.; Gable, K.; Beeler, T...
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Single-Molecule Fluorescence Imaging of Peptide Binding to Supported Lipid Bilayers Christopher B. Fox,† Joshua R. Wayment,‡ Grant A. Myers,‡ Scott K. Endicott,§ and Joel M. Harris*,†,‡ Department of Bioengineering, University of Utah, 50 South Central Campus Drive, Salt Lake City, Utah 84112-9202, Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112-0850, and HSC Core Research Facilities, University of Utah, 50 North Medical Drive, Salt Lake City, Utah 84132 Single-molecule fluorescence imaging techniques have been adapted to the quantitative characterization of peptide-binding to lipid bilayers. Peptide-membrane interactions are important in therapeutics, diagnostics, and membrane permeation and for understanding of the structure and function of membrane-bound proteins. Total-internal reflection fluorescence (TIRF) imaging is capable of determining membrane-binding equilibrium constants through the reliable counting of individual peptide molecules in order to report their surface density in the membrane. The residence times of the individual molecules in the membrane can also be determined and the rates of unbinding determined from a histogram of residence times. A combination of the unbinding kinetics and the equilibrium constant allows the binding rate of a peptide to the membrane also to be reported. We apply this method to characterize the lipid membrane affinity of glucagon-like peptide-1 (GLP-1), a 30-residue membrane-active peptide that is involved in glycemic control. Using single-molecule TIRF imaging, we have measured the affiliation of GLP-1 with a supported, phospholipid bilayer and determined its binding equilibrium constant. Two rates of dissociation were observed, suggesting strongly and weakly bound states of the peptide. The rate of membrane association was much slower than diffusioncontrolled, indicating a significant kinetic barrier to membrane binding. The data were interpreted using a heterogeneous, surface-reaction model analogous to electron-transfer kinetics at an electrode. To our knowledge, these results are the first example of using single-molecule counting to quantify peptide-lipid bilayer binding equilibria and kinetics. Peptide-membrane interactions are an active research topic due to the wide implications that this field has for other research areas such as therapeutics, diagnostics, membrane permeation and the basic need for understanding the structure and function of membrane proteins.1,2 Many analytical tech* Corresponding author. E-mail: [email protected]. † Department of Bioengineering. ‡ Department of Chemistry. § HSC Core Research Facilities. (1) Sanderson, J. M. Org. Biomol. Chem. 2005, 3, 201–212. (2) Matsuzaki, K. Biochem. Soc. Trans. 2001, 29, 598–601.

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niques have been used to elucidate peptide-membrane interactions, including surface-plasmon resonance,3-5 calorimetry,6-11 X-ray diffraction,10,12 fluorescence spectroscopy,3,8 circular dichroism,3,7-9,12-14 NMR,7,9,13,15 AFM,6,14 vibrational spectroscopy,3,14,16 Langmuir-Blodgett pressure-area isotherms,11,14 and chromatographic retention.3 These methods generally consist of ensemble measurements made at very high peptide and lipid concentrations. While valuable information about peptide-membrane interactions has been gained by the above methods, it would be advantageous to detect peptide-membrane interactions at the single-molecule level. For example, observing the kinetics of interactions can differentiate inhomogeneous kinetics associated with individual molecules, which cannot be discerned from the ensemble behavior of a large population.17 Furthermore, single-molecule counting of membrane-bound populations provides a definitive measure of their surface concentrations. Single-molecule fluorescence microscopy is an exciting field that allows investigation of binding and diffusion events of individual molecules.17-21 Single-molecule detection is made possible with high efficiency optical collection and cameras, low (3) Blondelle, S. E.; Lohner, K.; Aguilar, M. Biochim. Biophys. Acta 1999, 1462, 89–108. (4) Mozsolits, H.; Wirth, H. J.; Werkmeister, J.; Aguilar, M. I. Biochim. Biophys. Acta 2001, 1512, 64–76. (5) Papo, N.; Shai, Y. Biochemistry 2003, 42, 458–466. (6) Pedersen, T. B.; Kaasgaard, T.; Jensen, M. O.; Frokjaer, S.; Mouritsen, O. G.; Jorgensen, K. Biophys. J. 2005, 89, 2494–2503. (7) Dave, P. C.; Billington, E.; Pan, Y. L.; Straus, S. K. Biophys. J. 2005, 89, 2434–2442. (8) Poklar, N.; Fritz, J.; Macek, P.; Vesnaver, G.; Chalikian, T. V. Biochemistry 1999, 38, 14999–15008. (9) Hunter, H. N.; Jing, W.; Schibli, D. J.; Trinh, T.; Park, I. Y.; Kim, S. C.; Vogel, H. J. Biochim. Biophys. Acta 2005, 1668, 175–189. (10) Lohner, K.; Prenner, E. J. Biochim. Biophys. Acta 1999, 1462, 141–156. (11) Castillo, J. A.; Pinazo, A.; Carilla, J.; Infante, M. R.; Alsina, M. A.; Haro, I.; Clapes, P. Langmuir 2004, 20, 3379–3387. (12) Hristova, K.; Dempsey, C. E.; White, S. H. Biophys. J. 2001, 80, 801–811. (13) Beschiaschvili, G.; Seelig, J. Biochemistry 1990, 29, 52–58. (14) Deshayes, S.; Plenat, T.; Aldrian-Herrada, G.; Divita, G.; Le Grimellec, C.; Heitz, F. Biochemistry 2004, 43, 7698–7706. (15) Bechinger, B. Biochim. Biophys. Acta 1999, 1462, 157–183. (16) Williams, R. W.; Starman, R.; Taylor, K. M.; Gable, K.; Beeler, T.; Zasloff, M.; Covell, D. Biochemistry 1990, 29, 4490–4496. (17) Gell, C.; Brockwell, D.; Smith, A. Handbook of Single Molecule Fluorescence Spectroscopy; Oxford University Press: New York, 2006. (18) Michalet, X.; Kapanidis, A. N.; Laurence, T.; Pinaud, F.; Doose, S.; Pflughoefft, M.; Weiss, S. Annu. Rev. Biophys. Biomol. Struct. 2003, 32, 161–182. (19) Kapanidis, A. N.; Weiss, S. J. Chem. Phys. 2002, 117, 10953–10964. (20) Weiss, S. Science 1999, 283, 1676–1683. 10.1021/ac9007682 CCC: $40.75  2009 American Chemical Society Published on Web 05/29/2009

analyte concentrations, and background noise rejection.17 For imaging single molecules at surfaces, these conditions are optimized in a total-internal-reflection fluorescence (TIRF) microscope. In TIRF microscopy, the excitation laser is impinged on the sample coverslip through the objective at an angle greater than the critical angle. Thus, the laser is totally reflected from the glass coverslip-solution interface, creating an exponentially decaying evanescent field that selectively excites fluorophores near the coverslip surface. The fluorescence emission is then collected through the same objective and imaged onto a CCD camera. The main advantage of TIRF microscopy is that background signal from molecules in bulk solution is not collected, since the evanescent field penetration into solution limits the excitation of molecules to within 100 nm from the coverslip surface.17 TIRF microscopy has been used to image proteins and peptides in live cells, supported lipid bilayers, or immobilized on surfaces at the single-molecule level or in ensemble measurements.21-26 In the present work, we adapted single-molecule fluorescence imaging techniques to the quantitative characterization of peptidebinding to supported lipid bilayers. This method is capable of determining the binding equilibrium constants through the reliable counting of single molecules to report the number density of bound peptides versus their solution concentration. The residence times of the individual peptides in the membrane can also be used to determine the rates of unbinding. Combining the unbinding kinetics with the equilibrium constant allows the binding rate of a peptide to the membrane to be determined. We apply this method to characterize the lipid membrane affinity of glucagon-like peptide-1 (GLP-1), a 30-residue membrane-active peptide of molecular weight 3.3 kDa. GLP-1 has several important metabolic functions;27-29 it is primarily involved with glycemic control, stimulating insulin secretion in response to increasing glucose concentration, mediating glucose trafficking, suppressing secretion of glucagons in plasma, augmenting β-cell mass, inhibiting appetite, and decreasing gastric emptying.27-29 As a consequence, it has potential as a treatment for metabolic disorders such as diabetes type 2 and obesity.27,28,30 However, its therapeutic capacity is diminished by a short in vivo half-life.28,29 For this reason, various GLP-1 analogues, both natural and synthetic, are being researched for their efficacy.27-29,31,32 The closely related peptide known as exendin-4, for example, is being studied as a promising alternative with a longer half-life.29,33-36 (21) (22) (23) (24) (25) (26) (27) (28) (29) (30) (31) (32) (33)

Wayment, J. R.; Harris, J. M. Anal. Chem. 2009, 81, 336–342. Kalb, E.; Engel, J.; Tamm, L. K. Biochemistry 1990, 29, 1607–1613. Mashanov, G. I.; Molloy, J. E. Biophys. J. 2007, 92, 2199–2211. Mashanov, G. I.; Tacon, D.; Peckham, M.; Molloy, J. E. J. Biol. Chem. 2004, 279, 15274–15280. Tokimoto, T.; Bethea, T. R. C.; Zhou, M.; Ghosh, I.; Wirth, M. J. Appl. Spectrosc. 2007, 61, 130–137. Kim, K.; Kim, D.; Cho, E.; Huh, Y. SPIE, San Jose, CA, 2007; 64490K64497. Kieffer, T. J.; Habener, J. F. Endocr. Rev. 1999, 20, 876–913. Meier, J. J.; Nauck, M. A. Diabetes Metab. Res. Rev. 2005, 21, 91–117. Nielsen, L. L.; Young, A. A.; Parkes, D. G. Regul. Pept. 2004, 117, 77–88. Choi, S.; Baudys, M.; Kim, S. W. Pharm. Res. 2004, 21, 827–831. O’Harte, F. P.; Abdel-Wahab, Y. H.; Conlon, J. M.; Flatt, P. R. Diabetologia 1998, 41, 1187–1193. Youn, Y. S.; Chae, S. Y.; Lee, S.; Kwon, M. J.; Shin, H. J.; Lee, K. C. Eur. J. Pharm. Biopharm. 2008, 68, 667–675. Andersen, N. H.; Brodsky, Y.; Neidigh, J. W.; Prickett, K. S. Bioorg. Med. Chem. 2002, 10, 79–85.

The lipid membrane interactions of GLP-1 are important for its function. For instance, GLP-1 activity is mediated by its binding to the membrane-bound GLP-1 receptor.27,29,36 It has been speculated that GLP-1 first binds to the membrane and then diffuses to the membrane receptor.37 NMR and circular dichroism (CD) experiments have shown that in solution GLP-1 appears to be a random coil, but when bound to membranes, it forms an R-helix.33-35,38 To our knowledge, the lipid membrane binding equilibrium constant of GLP-1 has not been measured nor have the kinetics of its membrane association been reported. In the present work, the affiliation of GLP-1 with a supported phospholipid bilayer is measured by TIRF imaging, and its rates of membrane binding and unbinding are reported. Two unbinding rates are observed in the kinetic data, suggesting distinct populations of loosely and strongly bound peptides. The results are interpreted using a heterogeneous, surface-reaction model, where the rate of peptide binding is much slower than the diffusioncontrolled limit. EXPERIMENTAL SECTION Reagents and Materials. 1,2-Dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) >99% purity was purchased from Avanti Polar Lipids (Alabaster, AL). GLP-1 was synthesized at the Health Sciences Core Facilities at the University of Utah (see below). The fluorescent dye Cy3 maleimide was obtained from GE Healthcare (Piscataway, NJ). The polyethylene glycol (PEG) linker Fmoc-NH-(PEG)2-COOH (20 atoms) was purchased from Novabiochem (San Diego, CA). Water was quartz-distilled and then filtered with a Barnstead NANOpure II (Boston, MA) and had a minimum resistivity of 18.0 MΩ cm. Buffer components were supplied by Mallinckrodt (Paris, KY). Peptide Synthesis, Labeling, and Mass Spectrometry. The GLP-1 peptide with the PEG linker and terminal Cys was prepared by solid-phase synthesis on an Fmoc amide resin purchased from Applied Biosystems (Foster City, CA). In the case of the Cterminus-labeled peptide, the cysteine was first coupled to the resin, followed by the manual coupling of the PEG linker using the HOBt/DIC method. Finally, GLP-1 was synthesized from the C- to N-terminus on the solid-phase synthesis column. In the case of the N-terminus-labeled peptide, the GLP-1 peptide was first synthesized on the solid-phase column and the PEG linker was then manually coupled using the HOBt/DIC method. For both cases, the synthesis products were then purified using reverse phase chromatography with 0.01% TFA and an acetonitrile gradient. The best fractions, amounting to 50 µmol of peptide, were used to proceed with the dye labeling protocol. The peptide was dissolved in 2 mL of 50:50 v/v isopropyl alcohol/water, although it was not completely soluble. The dye (1 mg of Cy3 maleimide dissolved in 50 µL of DMF) was then added to the peptide solution and incubated overnight. The labeled peptide was purified from (34) Neidigh, J. W.; Fesinmeyer, R. M.; Prickett, K. S.; Andersen, N. H. Biochemistry 2001, 40, 13188–13200. (35) Thornton, K.; Gorenstein, D. G. Biochemistry 1994, 33, 3532–3539. (36) Runge, S.; Schimmer, S.; Oschmann, J.; Schiodt, C. B.; Knudsen, S. M.; Jeppesen, C. B.; Madsen, K.; Lau, J.; Thogersen, H.; Rudolph, R. Biochemistry 2007, 46, 5830–5840. (37) Braun, W.; Wider, G.; Lee, K. H.; Wuthrich, K. J. Mol. Biol. 1983, 169, 921–948. (38) Chang, X.; Keller, D.; Bjørn, S.; Led, J. J. Magn. Reson. Chem. 2001, 39, 477–483.

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unreacted dye and peptide by reverse phase chromatography using a preparative-C4 column and subsequently an analyticalC18 column. For the C-terminus-labeled peptide, unreacted dye eluted at 35 min, unreacted peptide at 60.3 min, and labeled peptide at 59.3 min. The collected fractions of the labeled peptides were analyzed using MALDI-TOF mass spectrometry. For MALDITOF analysis (PerSeptive Biosystems Voyager-DE STR Biospectrometry Workstation), 1 µL of the peptide sample at a concentration of 20-50 µM was spotted with 1 µL of saturated R-cyano4-hydroxycinnamic acid matrix solution (made up in 50:50 v:v acetonitrile/water with 0.1% TFA) and analyzed in the reflector mode with an accelerator voltage of 20 kV and 175 ns delayed extraction; 100 laser shots were acquired. Sample Preparation. Supported lipid bilayers were prepared on glass coverslips using the Langmuir-Schaefer method as described previously.39-42 The glass coverslips were first rinsed in alcohol, dried, and placed in a UV-ozone cleaner (Jelight Co. model 342) for 25 min. The Langmuir trough (KSV Minitrough, KSV Instruments, Ltd.) was cleaned by rinsing with 2-propanol, ethanol, and ultrapure water. After filling the trough with ultrapure water, a clean coverslip was immersed in the water subphase and 47 µL of 1 mg/mL DPPC in chloroform was deposited on the air-water interface by touching drops to the water surface. The chloroform was allowed to evaporate for ∼10 min before compressing the barriers at a rate of 5 mm/min until the Wilhelmy plate measured a surface pressure of 35 mN/m (∼53 Å2/ molecule); this surface pressure was held steady for ∼20 min before transferring the lipid film to the glass. The coverslip, positioned orthogonally to the trough surface, was then raised through the subphase surface at a rate of 4 or 5 mm/min to deposit a lipid monolayer. The coverslip was then positioned parallel to the subphase surface, after which it was pushed down quickly through the lipid (∼40 mm/min) to make a bilayer. The transfer ratios for the upward and downward depositions were ∼1 and ∼1.2, respectively. The slightly larger transfer ratio for the second layer may be due to some lipid sticking to the backside of the coverslip dipping apparatus.41 The flow cell with the coverslip-supported bilayer was assembled under ultrapure water so that the bilayer was never exposed to air. The flow cell was then positioned on the TIRF microscope and flushed with several milliliters of 50 mM phosphate buffer (pH 7.2). Bilayer depositions and TIRF experiments were carried out at room temperature. After a control image sequence was taken to test for background fluorescence, ∼0.8 mL of the dye-labeled GLP-1 solution (50 mM phosphate, pH 7.2) at peptide concentrations of 4, 10, 20, 50, 100, or 200 pM was injected into the flow cell. Concentrations of the labeled peptide were determined from the absorbance of stock solutions at 549 nm, ε ) 1.5 × 105 M-1 cm-1.43 TIRF Microscope. GLP-1 binding to supported lipid bilayers was imaged using an Olympus IX71 inverted microscope, operated in TIRF mode. Excitation of the sample was achieved using an (39) Charitat, T.; Bellet-Amalric, E.; Fragneto, G.; Graner, F. Eur. Phys. J. B 1999, 8, 583–593. (40) Starr, T. E.; Thompson, N. L. Langmuir 2000, 16, 10301–10308. (41) Tamm, L. K.; McConnell, H. M. Biophys. J. 1985, 47, 105–113. (42) Wright, L. L.; Palmer, A. G., 3rd; Thompson, N. L. Biophys. J. 1988, 54, 463–470. (43) Mujumdar, R. B.; Ernst, L. A.; Mujumdar, S. R.; Lewis, C. J.; Waggoner, A. S. Bioconjugate Chem. 1993, 4, 105–111.

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argon ion laser (Coherent, model Innova 300) operated at 528.7 nm and coupled into the microscope using a single-mode optical fiber. Total internal reflection was achieved by translating the fiber vertically, which in turn moved the position of the incoming laser beam to the edge of the objective (Olympus plan apo 60×, 1.45 NA, oil immersion) until internal reflection was observed at the interface between the coverslip surface and the buffer solution. TIRF microscopy image sequences were acquired using excitation laser powers ranging from ∼2 to 10 mW to test for photobleaching (see below). Light emitted by the sample was collected through the objective and passed through a dichroic beam splitter and bandpass emission filter (Chroma Z514RDC and HQ560/50, respectively), and imaged on a Photometrics Cascade II 512 CCD camera or an Andor iXONEM DU-897 CCD camera. MetaMorph (Universal Imaging) software or Andor iQ software was used to control the camera and collect images. Movies of singlemolecule events were collected for 100 s with 100 ms integration times. Pairs of 100 ms frames were coadded to improve the signal-to-noise ratio prior to data analysis, providing 200 ms time resolution for kinetic analysis. Data Analysis. The total number of observed molecules in an image was determined using ImageJ (NIH, Bethesda, MD) by counting pixels above the threshold; adjacent pixels above the threshold were counted as one spot. The threshold was set at the average background count plus 5.7 times the standard deviation of the background counts to avoid false positive events (see below). For binding time analysis, collected images were first converted into raw data format using ImageJ and then imported into GMimPro (MRC National Institute for Medical Research, London, U.K.). The GMimPro software was designed for singlemolecule surface binding analysis and has been described and demonstrated elsewhere.23,24 With the use of the GMimPro single fluorophore detection algorithm with a 3 × 3 pixel diffractionlimited spot size, the total number of fluorescent spots that both arrived at the bilayer and left the bilayer within the duration of the video were counted along with their corresponding residence times. This eliminated the effects of peptides that were already bound to the bilayer at the beginning of the video or did not unbind from the bilayer by the end of the video. A cumulative histogram of these spots was then computed from this information and plotted versus bilayer residence times. This histogram curve was fit to a Poisson-weighted biexponential decay to determine the dissociation time constants and an average (populationweighted) peptide membrane dissociation rate. RESULTS AND DISCUSSION Peptide Synthesis and Labeling. GLP-1 has a 30-residue sequence: HAEGTFTSDVSSYLEGQAAKEFIAWLVKGR-NH2.27-29 The synthesis of a fluorescently labeled GLP-1 molecule presents two major challenges for protein labeling: first, achieving homogeneous labeling to a specific site and second, assuring that the label does not perturb the structure or membrane binding interactions of the protein. Conventional amine-reactive dye labels are inappropriate in this case because of the presence of two lysine residues in the sequence, in addition to the N-terminus, any or all of which could be targeted. Furthermore, a dye molecule bound to any of these residues would likely perturb the structure of the peptide, as well as its affinity for the lipid membrane. Thus, it is desirable to bind the fluorescent dye label at a controlled site while

Figure 1. Structure of labeled GLP-1 analogues showing the peptide sequence (black), PEG spacer (blue), Cys residue (green), and Cy3 dye (red). (a) The C-terminus labeled peptide and (b) the N-terminus labeled peptide.

minimizing interference with the native structure of the peptide or its membrane association. We addressed this problem by directing the labeling chemistry to either the C- or N-terminus using a highly water-soluble dye attached by a long, flexible hydrophilic tether.25 This separates the label from the rest of the peptide and allows the charged dye molecule to reside in solution. A common and effective method of selective labeling of an amino acid other than lysine is to target cysteine residues with a maleimide derivative, forming a thioether bond.18-20,44 Because the GLP-1 sequence has no cysteine residues, this approach can be used to add a cysteine target for dye labeling to the end of the PEG tether (see Figure 1). The sequence of the C-terminally labeled GLP-1 analogue is HAEGTFTSDVSSYLEGQAAKEFIAWLVKGR-PEG2-cysteine(amide)-Cy3(maleimide); see Figure 1a. This HPLC-purified product was analyzed by MALDI-TOF mass spectrometry. The complete labeled peptide has a total molecular weight of 4471.03. At neutral pH, the 30 amino acids of the peptide fragment have zero net charge and a molecular weight of 3281.61; the 20-atom PEG linker has a zero net charge and adds 318.37 to the molecular weight; the cysteine amide fragment has zero net charge, a molecular weight of 118.16; and the Cy3 maleimide fragment has a net charge of -1 with a molecular weight of 752.90. In positive ion mode mass spectrometry, the singly charged ion is doubly protonated, which brings the molecular weight to 4473.04, (and the net charge to +1), with a calculated most abundant mass of 4472.12 for the +1 ion. The corresponding doubly charged (triply protonated) ion has a mass-to-charge ratio of 2237.03. The singly charged molecular ion is the most abundant species in the MALDI mass spectrum of the C-terminally labeled peptide, as shown in Figure 2a; the doubly charged (triply protonated) molecular ion is also detected. For the N-terminally labeled GLP-1 analogue, the sequence is Cy3(maleimide)-cysteine-PEG2-HAEGTFTSDVSSYLEGQAAKEFIAWLVKGR(amide) as shown in Figure 1b. The molecular weights of the individual component parts differ from the C-terminally labeled peptide only for the cysteine, which is no longer an amide, and the peptide, where the C-terminus is now an amide. Thus, the molecular weight of the N-terminally labeled peptide is identical to the C-terminally labeled peptide, and the most abundant ion in the MALDI mass spectrum is again (44) Hermanson, G. T. Bioconjugate Techniques; Academic Press: New York, 1996.

Figure 2. MALDI-TOF mass spectra of dye-labeled GLP-1 analogues: (a) C-terminus labeled peptide and (b) N-terminus labeled peptide.

the singly charged molecular ion, as shown in Figure 2b, where the doubly charged (triply protonated) molecular ion is also observed. Quantifying Labeled Peptides in a Supported Lipid Bilayer. To investigate the interactions between GLP-1 and lipid membranes, a DPPC lipid bilayer was deposited on a glass coverslip, illuminated in a TIRF microscope, and exposed to varying concentrations of labeled peptide in pH 7.2 phosphate buffer. Fluorescence images were acquired with 200 ms time resolution over a period of 100 s; examples of images from an acquired video are shown in Figure 3, where the binding and unbinding of a labeled peptide to the supported bilayer at a Analytical Chemistry, Vol. 81, No. 13, July 1, 2009

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Figure 5. Observed surface density of fluorescent spots, NS, molecules fit to a Poisson statistical model (solid line) that takes into account spot overlap and predicts the number density of molecules, Γ (dashed line).

Figure 3. An image sequence shows the binding and unbinding of an individual GLP-1 peptide to a supported DPPC lipid bilayer.

Figure 4. Histogram of intensities of background counts (red) and single GLP-1 molecules events on a DPPC bilayer (black), fit to Gaussian and exponentially modified Gaussian functions, respectively.

particular location is highlighted in selected frames and the time course of the intensity at that location is also plotted. To determine the peptide concentration in the membrane, the images were subjected to threshold analysis to determine the number of fluorescent spots per unit area. The background intensity and noise level were determined from data acquired for peptide-free buffer solutions. The no-fluorescence background level, µB, was ∼99 photoelectrons. The pixel-to-pixel variation in background counts exhibited a standard deviation, σB, of 11 photoelectrons, which is very close to the photoelectron shot noise limit (see Figure 4). The critical level45 or threshold for counting molecules (Lc) was set conservatively at ∼162 photoelectrons, which is 5.7 times σB above µB. This leads to a small probability (∼6 × 10-9) (45) Currie, L. A. Anal. Chem. 1968, 40, 586–593.

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of any pixel being above the threshold; multiplying by the number of pixels per frame leads to a false positive rate R ∼ 0.0004 events per frame or ∼0.2 false-positive events in a 500 frame observation. The fluorescent spots, imaged from samples containing labeled peptide, produced a distribution of detected intensities that are well above the background fluorescence, with average peak intensity µP ∼ 262 photoelectrons. The asymmetric distribution, which likely arises from a distribution of label orientations,46 is skewed toward higher intensities and well approximated by a Gaussian distribution convoluted with a single-sided exponential;21,47 see Figure 4. The width of the distribution and the highintensity tail is dominated by the exponential, where τ ) 74 photoelectrons, while the standard deviation of the Gaussian, σG ) 16, controls the shape of the histogram at low intensities. The probability of false negative events, that is failing to detect a bound GLP, was determined by dividing the area of the fitted distribution to the left of the threshold, I < Lc ) 162 photoelectrons, by the total area under the curve; the resulting false negative probability is quite small, β ∼ 0.023. As a check of this prediction, for the data in Figure 4, there were no molecule counts observed between the threshold for detection at 162 photoelectrons and the upper range of the first bin at 170 photoelectrons. Setting the threshold or critical-level, Lc )162 photoelectrons, one can count the number of the fluorescence spots from Cy3labeled GLP-1 on the membrane. The density of measured spots from GLP-1 peptide in the DPPC lipid bilayer was measured versus solution concentration and the results are plotted in Figure 5. To check the validity of these results, two control experiments were performed. First to test the affinity of the dye label for the lipid membrane, a solution of the Cy3 dye molecule without any peptide was tested and produced a surface density of only ∼0.5% of the number of fluorescent spots in the membrane for the equivalent concentration of labeled peptide in solution. This result shows that the fluorescent label itself has negligible affinity for the DPPC (46) Plakhotnik, T.; Moerner, W. E.; Palm, V.; Wild, U. P. Opt. Commun. 1995, 114, 83–88. (47) Dyson, N. A.; Smith, R. M. Chromatographic Integration Methods, 2nd ed.; Royal Society of Chemistry: London, 1998.

membrane and contributes insignificantly to the labeled peptidemembrane interactions. A second control was performed to test for adsorption of the labeled peptide onto bare glass having no supported lipid bilayer. The labeled peptide found on a clean glass surface was 16% of the population observed on a supported lipid bilayer. This result shows that any defects in the bilayer, which might expose the glass substrate, will not contribute a significant number of peptide spots to the data. The density of measured spots from GLP-1 peptide in the DPPC lipid bilayer has an apparent roll-over analogous to an isotherm (see Figure 5). This response is, however, not due to saturation of the bilayer with peptide because it begins to deviate from linearity at a surface density that is ∼10-6 of a full monolayer of peptide. This roll-over is instead due to the optical resolution of the microscope which limits the ability to count individual spots when the distance between them becomes smaller than the point spread function. The data in Figure 5 can be fit to to a Poisson statistical model,48 which accounts for the probability of spot overlap versus surface coverage: Nm ) Nc[1 - exp(-Γ/Nc)]

(1)

where Nm is the measured number density of fluorescent spots, Nc is the spot capacity of the image, and Γ is the actual surface density of GLP-1 molecules in the bilayer. The spot capacity, Nc, from the Poisson fit is 6.6 × 107 cm-2, the inverse of which is the area per resolved spot, 1.5 × 10-8 cm2 or 1.5 µm2, which corresponds to a radius of 690 nm, about twice the diffraction limit of the objective. This is a reasonable result because the algorithm counted any adjacent pixels above threshold as a single spot. From the slope of the linear region of the plot (or from the values of NS extracted from the Poisson fit), the ratio of the surface density of GLP-1 molecules in the bilayer to the concentration of molecules in solution is Γ/C ) 2.2 × 1017 cm-2 M-1. Dividing this slope by Avogadro’s number and multiplying by 1000 cm3 L-1 gives the association equilibrium constant: Ko ) Γ(1000 cm3 L-1) /CNAv

(2)

where Ko ) 3.7 × 10-4 cm or 3.7 µm. This constant is the ratio of the molecular surface concentration to the solution concentration and represents the distance into solution that contains the same number of molecules as reside in the lipid bilayer area below it.49,50 Equilibrium constants for protein binding to a membrane are generally determined by plotting the surface coverage of bound peptides at high surface concentrations versus the peptide solution concentration, fitting the resulting curve to a Langmuir isotherm,51,52 where the fraction of available sites occupied, Γ/Γmax ) θ ) KLC/ (1 + KLC). This approach is utilized because the signal from the bound molecules is not calibrated, and observing a rollover in the signal can indicate saturation of the available Hanley, D. C.; Harris, J. M. Anal. Chem. 2001, 73, 5030–5037. Hansen, R. L. Anal. Chem. 1998, 70, 4247–4256. Starr, T. E.; Thompson, N. L. Biophys. J. 2001, 80, 1575–1584. Shalev, D.; Rotem, S.; Fish, A.; Mor, A. J. Biol. Chem. 2006, 281, 9432– 9438. (52) Bong, D. T.; Janshoff, A.; Steinem, C.; Ghadiri, M. R. Biophys. J. 2000, 78, 839–845. (48) (49) (50) (51)

surface. The “full monolayer” signal extrapolated from the isotherm roll-over is equated to Γmax, so that the measured signals can be interpreted as surface concentrations, Γ, by estimating the density of available adsorption sites from the area, Am, of the adsorbing molecule, Γmax ) 1/Am. An adsorption isotherm roll-over at high coverages, however, may reflect the concentration at which the adsorbed peptide disrupts the membrane structure instead of the surface concentration that would represent a full monolayer, Γmax. Furthermore, the use of a site-occupancy model for peptide-membrane association is a misleading representation of the adsorption mechanism, because the peptide does not bind to adsorption “sites” but instead can bind anywhere on a uniform lipid membrane. Single-molecule counting avoids these problems by providing absolute quantitative information on the surface concentration of peptides, Γ (number per area), without needing to observe a saturation response or estimate its corresponding molecular density based on molecular area. The coverages used to make single-molecule counting measurements are very small fractions of a monolayer, thus avoiding issues of membrane disruption and changes in the binding response at high coverages. To compare the present result to previous studies that have employed a Langmuir isotherm analysis, we are required to estimate the area of an adsorbed peptide (the area of an adsorption “site”) in order to predict the fraction of a monolayer corresponding to the molecular surface concentrations determined in Figure 5. On the basis of measured and modeled values of hydrodynamic radii of peptides of similar molecular weight as GLP-1,53-57 the hydrodynamic radius of GLP-1 is estimated here to be ∼1.3 nm. This corresponds to a peptide area in the membrane, Am ) 5.3 × 10-14 cm2 ) 1/Γmax. Multiplying this area by the molecular surface concentration, Γ, gives the fractional surface coverage, θ; at the highest peptide concentration used in this study, θ ) ΓAm ) 2.4 × 10-6, which is indeed a small fraction of a full monolayer. The Langmuir binding equilibrium constant, KL, is the inverse of the solution concentration that leads to “halfcoverage” of the surface or θ ) 0.5. This can be determined by multiplying the slope of the linear region of the data in Figure 5 by the adsorbed peptide area: KL ) ΓAm/C ) 1.2 × 104 M-1. This result is within the range of reported values for membrane-active peptides, where KL is in the 1 × 103 to 1 × 106 M-1 range depending on the nature of the peptide and lipid.4,5,13,15,58-61 Membrane Association and Dissociation Kinetics. The observation of single-molecule binding events in the time-resolved TIRF images provides not only a direct count of the membrane(53) Ball, V. Colloids Surf., B 2004, 33, 129–142. (54) Kataoka, M.; Head, J. F.; Seaton, B. A.; Engelman, D. M. Proc. Natl. Acad. Sci. U.S.A. 1989, 86, 6944–6948. (55) Strom, R.; Podo, F.; Crifo, C.; Berthet, C.; Zulauf, M.; Zaccai, G. Biopolymers 1983, 22, 391–396. (56) Sun, S.; Luo, N.; Ornstein, R. L.; Rein, R. Biophys. J. 1992, 62, 104–106. (57) Zagrovic, B.; Jayachandran, G.; Millett, I. S.; Doniach, S.; Pande, V. S. J. Mol. Biol. 2005, 353, 232–241. (58) Wenk, M. R.; Seelig, J. Biochemistry 1998, 37, 3909–3916. (59) Kriech, M. A.; Conboy, J. C. J. Am. Chem. Soc. 2003, 125, 1148–1149. (60) Wieprecht, T.; Apostolov, O.; Beyermann, M.; Seelig, J. Biochemistry 2000, 39, 442–452. (61) Christ, K.; Wiedemann, I.; Bakowsky, U.; Sahl, H. G.; Bendas, G. Biochim. Biophys. Acta 2007, 1768, 694–704.

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Figure 6. Histogram of GLP-1 residence times on a supported DPPC bilayer. Data are fit to a biexponential decay (solid line). The solution concentration of labeled-GLP-1 is 50 pM.

associated peptide population but also the kinetics of binding. The dissociation kinetics of the peptide were determined by monitoring the residence times of individual peptides that bind and then unbind to the DPPC membrane during the course of the image sequence (see Figure 4). These residence times were collected for individual molecules and then plotted as a histogram, an example of which is shown in Figure 6. Dissociation from the membrane was expected to be a simple, first-order process, with an exponential decay of the probability of the peptide remaining in the membrane versus time. The histograms of residence times did not fit a single exponential but were well described by a biexponential decay model (see Figure 6). Including a second exponential reduced the squared deviations between the data and the model by more than a factor 12, passing a Fisher’s F-test at >99.9999% confidence. Photobleaching can interfere with determining single-molecule residence times, where the disappearance of fluorescence emission may arise from photobleaching of the dye label (with the peptide remaining bound to the membrane) rather than actual peptide dissociation from the membrane. Thus, it is critical to know whether photobleaching contributes to the apparent rate of dissociation. This can be tested by collecting dissociation data at different laser powers.24 If photobleaching is negligible, then there should be no dependence of the dissociation rates on laser power. In Figure 7, the fast and slow dissociation rates for both C-terminus- and N-terminus-labeled peptides are plotted for laser powers of ∼2, 5, and 10 mW. The fast dissociation rate, 1/τ1, is not affected by laser power, as expected. The average slower dissociation rate, 1/τ2, exhibits a slight (∼20%) increase at the highest laser power (10 mW), although this increase is not statistically significant at 95% confidence. To avoid any possible influence of photobleaching, dissociation rates are reported from the data collected at 5 mW laser power. Membrane binding studies of other amphipathic peptides5,62 have reported evidence of two dissociation rates. These two rates may correspond, respectively, to a peptide superficially associated with the membrane surface versus a peptide that is inserted and/ or folded within the membrane. In the present study, fast (62) Constantinescu, I.; Lafleur, M. Biochim. Biophys. Acta 2004, 1667, 26–37.

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Figure 7. Measured dissociation rates versus laser intensity: (a) fast dissociation rate (1/τ1) and (b) slow dissociation rate (1/τ2). Results for the C-terminus- and N-terminus-labeled GLP-1 are both plotted. Error bars indicate the standard deviation of the average of three measurements. The differences between the unbinding rates of the C- and N-terminus labeled peptides are not statistically significant at 95% confidence.

dissociation (residence time, τ1 ) 1.3 ± 0.1 s) was exhibited by ∼4.5 times more molecular visits to the membrane than slow dissociation (residence time, τ2 ∼ 13.2 ± 0.5 s). Thus, the majority of peptide adsorption events lead to superficial binding; however, because of the 10-fold greater residence time of the more tightly bound population, the inserted molecules actually dominate the membrane-affiliated population. The C-terminuslabeled peptide and N-terminus-labeled peptide exhibited statistically indistinguishable fast and slow dissociation rates and membrane-affiliated populations. This result indicates that neither terminus is buried deeply within the membrane, where dragging the attached hydrophilic tether and charged dye label into the membrane would alter the free energy of association of the labeled peptide (see discussion below). Further evidence of the dye label remaining in solution, even for the long-lived, inserted-peptide events, is found in the lack of a correlation between the peptide residence-time and fluorescence intensity. A Cy3 dye label exhibits a higher fluorescence quantum yield

in more constrained environments,63 thus confining the dye label in the membrane would be accompanied by an increase in the fluorescence intensity. A regression analysis for 1356 membrane-binding events for both the N-and C-labeled peptides showed no correlation between the label intensity and the event duration (R2 < 0.003 and the slopes are indistinguishable from zero); these results support the claim that the dye label remains in solution, when either the N- or C- labeled peptide is folded and inserted in the membrane. The membrane association equilibrium constant is the ratio of the association and dissociation rate constants, K ) kon/koff. Therefore, one can determine the membrane association rate constant by taking the product of the association equilibrium constant and the dissociation rate. The characteristic dissociation rate for GLP-1, koff, is determined from a populationweighted average of the fast and slow rates determined above, where koff ) 0.82 (±0.05) s-1. On the basis of this result, the membrane association rate constant (using the Langmuir L isotherm convention) is given by kon ) KL koff ∼ 1.0 × 104 M-1 -1 s . This on-rate has units of a conventional bimolecular rate constant because it is based on binding to a population of adsorption sites on the membrane. While this adsorption sitebinding model can be used to interpret membrane association results in cases where surface coverages are not known quantitatively (see above), the rate constant and its units are not appropriate for a reaction with a surface. A heterogeneous, surface-reaction kinetic model is more appropriate for peptide association with a membrane because the association does not occur at specific sites, rather adsorption and binding can occur anywhere on the membrane surface. Heterogeneous reaction kinetics at liquid/solid interfaces are modeled extensively in electrochemistry, where redox reaction kinetics at electrode surfaces are measured by the flow of current.64,65 In such systems, the surface (i.e., bilayer or electrode) ideally provides a uniform area for reaction (or binding). In monitoring reaction rates in electrochemistry, a heterogeneous rate constant, having units of velocity (cm/s), is used to describe the reaction of redox molecules at the electrode surface and to determine the fraction of molecule-electrode surface collisions that result in electron transfer. This formalism is applicable to peptide binding to a membrane bilayer and can also provide information about the probability of peptide-membrane encounters leading to membrane association. The membrane association equilibrium constant within a heterogeneous reaction model is also the ratio of the o association and dissociation rate constants, Ko ) kon /koff. Thus, one can determine the membrane association rate constant by taking the product of the association equilibrium constant and the population-weighted average dissociation rate to yield the heterogeneous rate constant for membrane association: o kon ) Kokoff ) (3.7 × 10-4 cm)(0.82 s-1) ) 3.0 × 10-4 cm/s

(3) (63) Sanborn, M. E.; Connolly, B. K.; Gurunathan, K.; Levitus, M. J. Phys. Chem. B 2007, 111, 11064–11074. (64) Bard, A. J.; Faulkner, L. R. Electrochemical Methods: Fundamentals and Applications, 2nd ed.; Wiley: New York, 2001. (65) White, R. J.; White, H. S. Anal. Chem. 2005, 77, 214A–220A. (66) Frieden, C.; Chattopadhyay, K.; Elson, E. L. In Advances in Protein Chemistry: Unfolded Proteins; Rose, G. D., Ed.; Academic Press: New York, 2002; Vol. 62.

This is the rate constant at which the peptide molecules associate with the bilayer. As is often done in electrochemistry, the heterogeneous rate constant can be compared with the rate of collisions between molecules and the surface to determine what fraction of the collisions lead to binding. To estimate the surface collision frequency, the diffusion coefficient of the labeled peptide in solution is needed; this can be accurately measured by fluorescence correlation spectroscopy66 or estimated by the Stokes-Einstein equation. To estimate the diffusion coefficient of GLP-1 in solution, the peptide is assumed to be a random coil33-35 with a hydrodynamic radius, r ≈ 1.3 nm.53-57 From the Stokes-Einstein equation and the viscosity of water, η ) 8.9 × 10-4 Pa s, the diffusion coefficient of the peptide is D ) kB T/6πηr ≈ 1.6 × 10-6 cm2 s-1. From Fick’s first law,64,65 the diffusion limited heterogeneous rate constant or reaction velocity can be estimated by the flux through a unit area for a given solution concentration, v ) J/C = D(dC/dx)/C. For a diffusion controlled reaction with the surface, the concentration gradient would be equal to the bulk concentration divided by the encounter distance for reaction,67 in this case about twice the hydrodynamic radius of the peptide. Thus, the solution concentration cancels and the diffusion-limited reaction velocity is given by v ) J/dx ∼ o D/2r ∼ 7 cm/s. Comparing this velocity to kon provides an estimate of the fraction of collisions between the peptide and o membrane that result in binding, kon /v ∼ 4 × 10-5. Therefore, only 1 in ∼25 000 collisions results in the peptide binding to the membrane. Peptide binding to the membrane is not a diffusion limited process but is limited by a significant free energy barrier to membrane association. The free energy barrier to membrane association can be estimated from its lowering of the reaction rate compared to the diffusion limited velocity, where ∆Gq ) -RT ln(koon/v) ∼ 25 kJ/mol. Therefore, the free energy barrier for the peptide to associate with the membrane is comparable to the energy of a strong hydrogen bond and likely represents the energy costs of creating free volume within the lipid bilayer and changes in the hydration and conformation of the peptide as it transfers from aqueous solution. GLP-1 Association with Lipid Membranes. From NMR studies, it is known that the GLP-1 structure changes from random coil in solution to an R-helix upon membrane binding.33-35 This is a common pattern observed in peptide-membrane binding studies15,68-71 that is considered to be driven by an enthalpy lowering in order to overcome the entropic cost of helix formation.72 The octanol/buffer partition coefficient of GLP-1 has been determined to be 0.002 38,73 indicating that it is only slightly hydrophobic. Octanol-water partition coefficients are, however, not equivalent to lipid-water partition coefficients.74 This is (67) Rice, S. A. In Comprehensive Chemical Kinetics; Bramford, C. H., Tipper, C. F. H., Compton, R. G., Eds.; Elsevier: Amsterdam, The Netherlands, 1985; Vol. 25. (68) Frey, S.; Tamm, L. K. Biophys. J. 1991, 60, 922–930. (69) Epand, R. M.; Vogel, H. J. Biochim. Biophys. Acta 1999, 1462, 11–28. (70) Matsuzaki, K.; Murase, O.; Tokuda, H.; Funakoshi, S.; Fujii, N.; Miyajima, K. Biochemistry 1994, 33, 3342–3349. (71) Dathe, M.; Wieprecht, T. Biochim. Biophys. Acta 1999, 1462, 71–87. (72) Wieprecht, T.; Apostolov, O.; Beyermann, M.; Seelig, J. J. Mol. Biol. 1999, 294, 785–794. (73) Kastin, A. J.; Akerstrom, V.; Pan, W. J. Mol. Neurosci. 2002, 18, 7–14. (74) Austin, R. P.; Davis, A. M.; Manners, C. N. J. Pharm. Sci. 1995, 84, 1180– 1183.

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especially true in the case of amphiphilic molecules, which may preferentially bind to the interfacial region of lipid membranes where both polar and nonpolar parts of the molecule can be accommodated. In the case of GLP-1, for example, the peptide sequence contains multiple polar or charged residues as well as many hydrophobic residues along the entire peptide sequence. The hydrophobic residues presumably interact with the nonpolar acyl chains of the lipids while the polar residues would preferentially bind nearer the lipid headgroup region. Thus, the interfacial lipid region would be most favorable for peptide insertion. This conformation maximizes the amphiphilic interactions of the peptide with the lipid and is similar to that of several other membrane-active peptides.12,15,68,75 The location of GLP-1 in the membrane has not been determined. In NMR studies using TFE or dodecylphosphocholine micelles, the C-terminal end of GLP-1 was found to be more conformationally constrained than the N-terminus and was thus thought to be buried.33-35,38 Similar findings were reported for glucagon (which has about 50% sequence homology with GLP-1) in micelles as well as vesicles, where differences in degree of peptide immersion were reported for these two structures.37,76 It should be noted that micelles have greater curvature than lipid membranes which allows looser lipid packing, greater hydration, and more room for peptide insertion. Indeed, studies comparing micelle to membrane environments have found deeper peptide insertion in the more dynamically flexible micellar chains compared to lipid membranes.77,78 In addition, the model amphiphile most often employed in the micelle studies, dodecylphosphocholine, lacks the interfacial carboxyl and glycerol group found in phosphatidylcholines. These differences limit the extrapolation of the NMR results of GLP-1 structure in micelles to its behavior in planar membrane environments. In the present work, it was surprising to find that the C-terminus- and N-terminus-labeled peptides displayed very similar membrane binding behavior (see Figure 7). Because no measurable differences in the unbinding kinetics were apparent for these two structures, then it is likely that neither terminus of the peptide is deeply buried within the membrane, where there would be an energy penalty for immersing the terminal, hydrophilic PEG tether and charged dye label in the acyl-chain environment of the lipid bilayer. The present work also uncovered two bound states of the peptide, which are thought to be loosely membrane-affiliated and more strongly bound/folded, respectively. These two forms may not be independent but rather may be related through reversible kinetics, where a surface-adsorbed peptide can enter the membrane as a folded structure, and a folded peptide leaving the membrane interior can return to the membrane-solution interface and be weakly adsorbed. This model suggests a sequential twostep mechanism, with adsorption followed by a second step for peptide insertion into the membrane. If this model indeed represents the mechanism for peptide insertion in the membrane, (75) (76) (77) (78)

Dempsey, C. E.; Butler, G. S. Biochemistry 1992, 31, 11973–11977. Maurer, T.; Lucke, C.; Ruterjans, H. Eur. J. Biochem. 1991, 196, 135–141. Bond, P. J.; Sansom, M. S. P. J. Mol. Biol. 2003, 329, 1035–1053. Souto, A. L. C. F.; Poletti, E. F.; Nakaie, C. R.; Schreier, S. Prog. Colloid Polym. Sci. 2004, 128, 203–206.

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then, at equilibrium, the ratio of the populations of the adsorbed and inserted forms would be given by the ratio of the forward and reverse rates of the second step.79,80 On the basis of the time constants and pre-exponential factors from the fitted singlemolecule dissociation kinetics, the population of the membrane inserted form is greater than the adsorbed population (see above). Therefore, at equilibrium, the rate of GLP-1 folding and insertion from the adsorbed state is faster than the rate of the peptide leaving the membrane interior, suggesting a stabilized, folded form within the membrane. The biological insight from these results may be improved by using different types of lipids or membrane compositions. For example, fluid or ripple phase lipids may behave more like natural membranes than the gel-phase DPPC,81,82 and the effects of the lipid phase on the rates of peptide insertion or emergence would be interesting to study. Lipids with different phase transition temperatures can be selected for these studies, or sample temperature control can be introduced to control the phase of the lipid. Moreover, while peptide diffusion in gel-phase DPPC is minimal, diffusion in a fluid membrane is significant. Thus, peptide diffusion in a membrane can be quantified, providing another tool to characterize peptide-membrane interactions. In addition, charged lipids or mixed lipids could be used to further approximate natural membranes, and differences in headgroup interactions with adsorbed or inserted peptides could be tested. Research along these lines could improve our understanding of peptide-membrane interactions and kinetics. Finally, these experiments have demonstrated several advantages of using single-molecule counting to measure peptidemembrane binding and kinetics. With reliable detection, absolute surface populations can be determined at very low solution and surface concentrations, thus avoiding peptide aggregation and membrane disruption and increasing the physiological relevance of the results. Surface populations are known without resorting to assumptions about molecular areas or interpreting isotherms at coverages approaching a full monolayer. Heterogeneous rate constants for membrane-surface binding are reported, which are appropriate to the mechanism of lipid-membrane binding. These rates can be compared with estimates of the diffusion limited collision rate of peptides with a planar surface to estimate energy barriers for membrane association. ACKNOWLEDGMENT This research was supported in part by the National Science Foundation under Grant CHE-0654229 and by Eli Lilly and Co. Additional support to Chris Fox from a University of Utah Graduate Research Fellowship and the assistance of the HSC MS and Proteomics Facility are gratefully acknowledged. Received for review April 9, 2009. Accepted May 19, 2009. AC9007682 (79) (80) (81) (82)

Lowry, T. M.; John, W. T. J. Chem. Soc., Trans. 1919, 97, 2634–2645. Vriens, G. N. Ind. Eng. Chem. 1954, 46, 669–671. Pott, T.; Dufourcq, J.; Dufourc, E. J. Eur. Biophys. J. 1996, 25, 55–59. Sekharam, K. M.; Bradrick, T. D.; Georghiou, S. Biochim. Biophys. Acta 1991, 1063, 171–174.