The peptides were synthesized manually using in situ neutralization cycles for Boc-solid

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1 SUPPLEMENTAL DATA Peptide Synthesis, Purification and Labeling The peptides were synthesized manually using in situ neutralization cycles for Boc-solid phase peptide synthesis as described. 1 The peptides were synthesized on 0.1 mmol MBHA resin (4-Methylbenzhydrylamine, Peptides International, Louisville, KY) using 1.1 mmol amino acid, 1.0 mmol HCTU ([2-(1H-6-chlorobenzotriazol-1-yl)-1,1,3,3- tetramethyluronium hexafluorophosphate], 2 ml of 0.5 M solution in DMF) and 0.5 ml DIEA (N,N-(Diisopropyl)aminomethylpolystyrene). Coupling times were typically 15 min. Following chain assembly, the peptides were cleaved from the resin with HF and 10% anisole for 1 h at 0 C. The N-terminus of the collagenase and chymotrypsin peptides were blocked with an acetyl group. Aib was activated using 0.3 mmol Boc-Aib- OH, 0.3 mmol TFFH (fluorotetramethylformamidinium hexafluorphophate) and 0.5 ml DiEA in 1.5 ml DMF for 15 min at 25 C. The peptides were purified by HPLC. Analytical reversed-phase HPLC was performed on a Rainin HPLC system equipped with a Vydac C-18 column (Hesperia, CA, 10 µm, 1.0 x 15 cm, flow rate 1 ml/min). Preparative reversed-phase HPLC was performed on a Waters 4000 HPLC system using Vydac C-18 columns (10 µm, cm) and a Gilson UV detector. Linear gradients of acetonitrile in water/0.1% tri-fluoroacetic acid (TFA) were used to elute bound peptides. Peptides were characterized using electrospray ionization MS on an API-III triple quadrupole mass spectrometer (Sciex, Thornhill, CA). Peptide masses were calculated from the experimental mass to charge (m/z) ratios from all of the observed protonation states of a peptide by using MacSpec software (Sciex). All observed peptide masses agreed with the calculated average masses within 0.5 Da. Cy3 maleimide was 1

2 obtained from Amersham Biosciences (Piscataway, NJ) and QXL-520 from Anaspec (San Jose, CA). Dye-labeled peptides were prepared and purified on LC-18 SPE columns (Supelco, Bellefonte PA) as described. 2 The Thr peptide was also labeled with QXL-520 using an alternative method. 3 mg peptide (1.5 µmol) was added to 1.1 mg dye (1.5 µmol) dissolved in 220 µl 50 mm sodium phosphate ph 6.5 and 124 µl acetonitrile and allowed to react overnight at room temperature followed by HPLC purification. Poisson Distribution The self-assembly processes used here for forming our QD bioconjugates results in a distribution of peptide to QD ratios that obeys a Poisson distribution. The equation for a Poisson distribution is: n k e n p( k, n) (S1) k! where k is the specific number of occurrences in a given interval (an index number) and n is the average number of occurrences in that interval. 3 As expected, the mean and variance are equal to n which implies that the distribution broadens as the average increases. In our system, n is the average number of dye-labeled acceptors per QD. The effect of this distribution on the FRET efficiency can be considered by calculating the efficiencies of individual subpopulations of bioconjugates where k 1, 2, 3, etc. Using equation S1, for a given molar ratio of labeled biomolecules per QD, n, mixed in solution we can determine the fraction of conjugates p that have k labels per QD and sum the contributions (efficiencies) of these subpopulations over the entire sample: E ( n) p k, n) E( k) k 1 ( (S2) 2

3 This gives us the overall FRET efficiency for a sample that is properly weighted for a Poisson distribution. If we compare this result to the naïve assumption that all bioconjugates have n dye-labeled biomolecules per QD (a single population), we find that the deviation between the two models (or the error ) depends strongly on the ratio r R 0 and n, which will change for a given QD bioconjugate system. For n 4, there is a maximum error of 5.6% in the predicted efficiency regardless of the ratio r R0. This suggests that the single population model is sufficiently accurate to describe multivalent bioconjugates. For n < 4, there can be significant errors in the single population model as r R 0 becomes small (i.e., small separation distances). For example, if r R0 1, the single population model will overpredict the FRET efficiency by 35.9% for n 1. The error decreases significantly as n and r R0 increase, but this highlights the need for a proper model of the number of dyes per QD in such systems. Essentially, there is only a significant discrepancy between the models for small n and small r R0. With respect to the QD-peptide systems considered in this paper, Figure S1 summarizes the predicted efficiency errors as a function of n. Although errors in the efficiency may be significant when assuming a single population model in these systems for small n, they quickly diminish as n increases. The distances measured in this study used several values of n to determine the donor-acceptor distance r, which will greatly improve the accuracy of these measurements. We note that these errors are only important when calculating distances from measured efficiencies at low ratios; however, they play no role in estimating the number cleaved peptides or subsequently the enzymatic activity. This is because we perform an independent 3

4 calibration for each system, which does not rely on knowledge of the donor-acceptor distance percent error Casp1 Thr Coll Chym number of dyes/qd, n Figure S1. Predicted efficiency errors for the various QD-peptide conjugates as a function of the number of labeled peptides per QD. Stern-Volmer Analysis Collisional quenching due to diffusion of QDs and acceptor dyes (manuscript Figure 2B) was analyzed using a Stern-Volmer model. 4 As predicted, the ratio F 0 /F (inverse normalized fluorescence intensity) follows a linear trend as the concentration of free Cy3 dye increases (Figure S2). The K D for this process was found to be 0.13 µm -1 (corresponding to 50% PL quenching at 7.7 µm) which is similar to our previous results for QD quenching using free protein-dye in solution. 2 This experimental condition represents a limiting case where all of the Cy3 is free to diffuse in solution. This is 4

5 different from the assay conditions where only a fraction of dye-labeled peptides become unbound after interactions with the enzyme. The effect of dynamic quenching is small compared to FRET quenching that occurs when dye-labeled peptides are bound to the QD surface and does not alter the performance of the assay. 1.5 F 0 /F n, equivalent number of Cy3/QD Figure S2. Stern-Volmer analysis of data presented in manuscript Figure 2B where n equivalent amounts of Cy3 dyes were added to 538 nm QDs in solution. Enzyme Activity Caspase-1. Calbiochem ( defines one unit of activity as the amount of enzyme that will cleave 1.0 pmol of Ac-YVAD-pNA labeled peptide substrate per minute at 30 C/pH 7.4. Thrombin. Sigma-Aldrich ( defines the activity in NIH units obtained by direct comparison to a NIH Thrombin reference standard. The NIH assay procedure uses 0.2 ml diluted plasma (1:1 with saline) as a substrate and 0.1 ml of thrombin sample (stabilized in a 1% buffered albumin solution) based on a modification 5

6 of the Biggs method. Only clotting times in the range of s are used for determining the concentration of thrombin. 5 Collagenase. Sigma-Aldrich ( defines one collagen digestion unit as the amount that liberates peptides from collagen equivalent in ninhydrin color to 1 µmol of leucine in 5 hrs at 37 C/pH 7.4 in the presence of calcium. Chymotrypsin. Sigma-Aldrich ( defines one unit of activity as the amount that will hydrolyze 1.0 µmol of N-Benzoyl-L-tyrosine ethyl ester substrate per min at 25 C/ ph 7.8. Recognition and cleavage sequences of peptides These sequences are selected based on what is available in the literature and also on what is reported or defined by the manufacturer of each enzyme (see above). Enzymatic Data Analysis To estimate the enzymatic activity, we first derived a series of standard/calibration curves that correlate the number of dye-labeled peptides immobilized on the QD in each solution (free of enzymes) to the measured PL signal (or FRET efficiency). When assaying for all four of the enzymes (caspase-1, thrombin, collagenase, and chymotrypsin) activity was determined by correlating the variation in FRET efficiency (QD PL loss) with the number of labeled peptides/qd. For the caspase-1 assay, the change in ratio of Cy3 to QD emission PL can also be used and yields similar results. These data were fitted with a polynomial formula in SigmaPlot (Statistical Solutions, Saugus, MA) to establish a oneto-one functional relationship between the measured PL signal (e.g., QD PL loss) and number of labeled-peptides assembled on the QD. The standard curves allowed us to 6

7 determine the number of intact (non-cleaved) peptide-acceptors on the QD by quantitative comparison. This provides a method for determining the final number of cleaved peptides per QD by measuring changes in the PL signal of the QD-substrate solution upon exposure to a particular enzyme. The amount of cleaved substrate per QDconjugate is deduced from the difference between the number of peptide-dye measured before (no enzyme) and after the reaction is complete. Enzymatic activity rates or velocities were measured by converting the number of peptides cleaved into concentration of cleaved peptide per minute knowing the concentration of QD bioconjugates and reaction time. For our purposes, we define proteolytic velocity as picomoles of peptide cleaved/min. Relevant kinetic parameters were determined by measuring the enzymatic activity as a function of enzyme concentration (excess enzyme) except for the caspase-1 assay which used excess substrate. For assays conducted under excess enzyme conditions, we took care to ensure that only initial rates were measured. The subsequent data analysis showed that in all cases ~ 80% of the substrate was unconsumed under these conditions confirming that we were in the initial rate regime. The data are then interpreted within the framework of the standard Michaelis-Menten kinetic model This model assumes that there is a steady-state between enzymesubstrate intermediate complexes and free compounds, and that either substrate or enzyme is in excess. Under these conditions two analogous equations corresponding to either excess substrate, [S], or excess enzyme, [E], can be obtained: V d [ P] Vmax [ S] dt K [ S] M + for excess substrate, (S3) or 7

8 V d [ P] Vmax [ E] dt K [ E] M + for excess enzyme, (S4) where P is the reaction product (cleaved peptide), V is the (initial) velocity or rate of cleaved substrate, [S] is the substrate (intact peptide) concentration, V max is the maximum velocity or enzymatic reaction rate, and K M is the Michaelis constant corresponding to the concentration at half-maximal velocity. In a plot of the enzymatic rate versus concentration, the above two parameters are extracted by non-linear least-squares fitting: V max is the asymptotic rate at high concentrations, and K M is the concentration at which V V max /2. Data were fit to the above equations to determine these parameters. For the thrombin inhibition assay, the data were analyzed using a non-competitive inhibition model, which is described using a slightly modified equation: V d app [ P] Vmax [ S] app dt K + [ S] M or V d app [ P] Vmax [ E] app dt K + [ E] M (S5) where the V max app and K M app corresponds to the Michaelis-Menten parameters in the presence of an inhibitor. If the inhibitor can bind only to the enzyme and not the ES complex, then app K M K M and only V app max is affected The following equation is then used to derive K i, the inhibitor dissociation constant: V Vmax 1 where [I] is the inhibitor concentration. app max (S6) ( + [] I K i ) 8

9 Model for Initial Rates in Excess Enzyme Conditions A simple model for the enzymatic reaction is given by: 6-10 k 1 k 2 E+S ES E+P k -1 (S7) where E is enzyme, S is substrate, ES is enzyme-substrate complex, and P is product. The rate constant k 2 specifies the rate at which ES complex is converted to product and is equivalent to the turnover number k cat. Use of the Michaelis-Menten equation requires that either the enzyme or substrate is in excess and that there is a pseudo steady-state condition on the ES complex such that its concentration is effectively constant with time. The Michaelis-Menten equation itself does not describe the concentration profiles of each species with time, but rather depicts the initial rate of the reaction (or velocity ) as a function of either the substrate or enzyme concentration (depending on which is in excess). For the excess substrate condition where the ES complex is at steady-state (and a constant value), the formation of P and depletion of S follow zero order kinetics: [ P] d dt [ S] d dt [ ES] [ P] [ P] + k [ ES] t k2 0 (S8) 2 [ ES] [ S] [ S] k [ ES] t k2 0 2 (S9) Equation S9 implies/assumes that the depletion of substrate [S] is rate-limited by the conversion of the [ES] complex into product [P] when the initial binding of enzyme is fast. A representative solution to the coupled rate equations is shown in Figure S3 for the excess substrate condition. 9

10 5 concentration (a.u.) [S] [ES] [P] [E] time (a.u.) Figure S3. Plot of concentrations versus time for the constituent species shown in equation S7 for an excess substrate condition. Dashed line depicts the duration of enzymatic digestion in a typical experiment such that the assumptions in the Michaelis- Menten equation are valid. Of note is the linear decrease and increase of [S] and [P], respectively, in accordance with equations S8 and S9, over the time period where [ES] is constant. These conditions allow us to properly extract kinetic parameters from a Michaelis-Menten model for the initial reaction rate. A representative solution for the excess enzyme case is shown in Figure S4. In this case, we see that substrate is quickly bound by enzyme to form the ES complex. This does not necessarily mean that the substrate is rapidly depleted. Rather, the reaction is proceeding at the initial rate for the concentrations and conditions in use. In either excess substrate or enzyme conditions, sufficient substrate remains intact and unreacted during the assay such that the assumptions of the Michaelis-Menten equation are valid. 10

11 concentration (a.u.) [S] [E] [ES] [P] time (a.u.) Figure S4. Plot of concentrations versus time for the constituent species shown in equation S7 for an excess enzyme condition. Dashed line depicts the duration of enzymatic digestion in a typical experiment such that the assumptions in the Michaelis- Menten equation are valid. Photoluminescence (arbitrary units) Casp1-Cy3/QD 1 Casp1-Cy3/QD 2 Casp1-Cy3/QD 4 Casp1-Cy3/QD 6 Casp1-Cy3/QD 8 Casp1-Cy3/QD 10 Casp1-Cy3/QD Wavelength (nm) Figure S5. Raw PL spectra for QD-casp-1-Cy3 conjugates from which data presented in Figure 2A were processed; 538 nm QDs were used. 11

12 Photoluminescence (arbitrary units) # of Thr-QXL peptides/qd QD PL (%) Wavelength (nm) # of Thr-QXL peptide/qd Figure S6. Titration of 538 nm QDs with an increasing Thr-QXL-to-QD ratio, n. Inset shows the QD PL loss plotted as % versus ratio n. Construction of the QD-Peptide Conjugate Model Structure. The QD PL quenching data combined with Förster analysis were used to determine separation distances between the QD center and acceptor dye. Peptide structures were modeled using a combination of Chem3D and MidasPlus. 11,12 The peptide stretch designed to be alpha helical was constrained to form a helix and the entire peptide was energy minimized using the MM2 module in Chem3D. Final adjustments to torsion angles were made in MidasPlus to achieve the desired fluorophore-qd distances determined from FRET. MidasPlus is also used for final rendering. 11,12 In manuscript Figure 1C, the QXL-520 dark quencher on the Thr-QXL peptide terminus is represented as a sphere placed 10.5 Å from the cysteinesulfur atom as the chemical structure remains proprietary. 12

13 Supplementary References: 1. Schnolzer, M., P. Alewood, et al. (1992). "In situ neutralization in Boc-chemistry solid phase peptide synthesis. Rapid, high yield assembly of difficult sequences." Int. J. Pept. Protein. Res. 40: Goldman, E., I. L. Medintz, et al. (2005). "A hybrid quantum dot-antibody fragment fluorescence resonance energy transfer-based TNT sensor." J. Am. Chem. Soc. 127: Grimmett, G. and D. Stirzaker (1992). Probability and Random Processes. Oxford, Oxford University Press. 4. Lakowicz, J. R. (1999). Principles of Fluorescence Spectroscopy, Kluwer Academic/Plenum Publishers. 5. Gaffney, P. J. and T. A. Edgell (1995). "The International and NIH Units for Thrombin - How Do They Compare." Thrombosis and Haemostasis 74(3): Dixon, M. (1953). "The Determination of Enzyme Inhibitor Constants." Biochemical Journal 55(1): Harris, D. A. (1987). Spectrophotometric Assays. Washington DC, IRL Press. 8. Segel, I. H. (1993). Enzyme Kinetics : Behavior and Analysis of Rapid Equilibrium and Steady-State Enzyme Systems. Hoboken, New Jersey, Wiley-Interscience. 9. Kim, N. and J. Suh (1994). "Artificial Metallophosphoesterases Built on Poly(Ethylenimine)." Journal of Organic Chemistry 59: Bowden, A. C. (1995). Fundamentals of Enzyme Kinetics. London, Portland Press Limited. 11. Ferrin, T.E., Huang, C.C., Jarvis, L.E. & Langridge, R. 1988). The midas display system. Journal of Molecular Graphics 6, Huang, C.C., Pettersen, E.F., Klein, T.E., Ferrin, T.E. & Langridge, R. (1991). Conic - a fast renderer for space-filling molecules with shadows. Journal of Molecular Graphics 9,