Nanopore Investigation of the Stereoselective Interactions between

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Nanopore Investigation of the Stereoselective Interactions between Cu2+ and D,L‑Histidine Amino Acids Engineered into an Amyloidic Fragment Analogue Irina Schiopu,†,§ Sorana Iftemi,‡,§ and Tudor Luchian*,‡ †

Department of Interdisciplinary Research, Alexandru Ioan Cuza University, Blvd. Carol I, No. 11, Iasi 700506, Romania Department of Physics, Laboratory of Molecular Biophysics and Medical Physics, Alexandru Ioan Cuza University, Blvd. Carol I, No. 11, Iasi 700506, Romania

‡

S Supporting Information *

ABSTRACT: Stereochemistry is an essential theme for a number of industries and applications, constructed around discriminating various chiral enantiomers, including amino acids, chiral metal complexes, and drugs. In this work, we designed a set of peptide mutants of the human amyloidic Aβ1−16 sequence, known to display an effective Cu2+ coordinating pocket provided mainly by the intramolecular His-6, His-13, and His-14 residues, that were engineered to contain L- and DHis enantiomers in positions 6 and 13 and provide a local coordination environment with distinct Cu2+ binding geometries and affinities. We examined the mechanism of selective chiral recognition of Cu2+ by such mutant peptides, by quantifying their stochastic sensing in real time with a single α-hemolysin (α-HL) protein immobilized in a planar lipid membrane, while incubated in various concentrations of Cu2+. Our data reveal that the Cu2+-binding affinity lies within the micromolar range, and decreases by orders of magnitude as L-His is replaced with its D-enantiomer, with the effect being prevalent when such changes were inflicted on the His-6 residue. The presented results demonstrate the feasibility of tuning the metal selectivity in a relatively simple peptide substrate by enantiomeric replacement of key metal binding residues and illustrates the potential of the protein nanopores as a promising approach to quantify the chiral recognition of L/D amino acids by metals.

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INTRODUCTION A prevailing paradigm in contemporary biochemistry states that selectivity of substrate recognition in protein and peptide scaffolds is accomplished by relatively few amino acids which form the selectivity site, with augmented specificity for the target. Protein-bound metal cations such as Fe3+/Fe2+, Zn2+, Cu2+/Cu+, Ca2+, and Mg2+ were found to be crucial in modulating protein energetics, aggregation, folding, and structure, by engaging in interactions with a limited set of amino acid combinations (e.g., His, Cys, Met, Glu, Asp, Tyr) to ensure an optimal metal ion coordination geometry,1 and stereochemical selectivity is widely used to control and regulate subtle biochemical events related to peptides and protein dynamics.2 In particular, it has been established that copper-bound proteins and amino acid complexes are of considerable interest in biological systems3 and transition metals in general are very useful for selecting a given stereochemistry4,5 through enhancing the stability of one of the stereoisomers. Very recently, authors used cysteine enantiomer modified graphene oxide as a model to show that surface chirality strongly influences the adsorption, nucleation, and fiber elongation processes of Aβ(1−40).6 Understanding stereoselectivity in biological molecular recognition © 2014 American Chemical Society

processes is extremely important for rational drug design, and for designing proteins and biomimetic receptors,7,8 and in a very recent study employing the Aβ1−40 peptide as well as the Aβ25−35 and Aβ12−28 fragments, authors demonstrated that triplehelical dinuclear metallosupramolecular complexes can act as a novel class of chiral amyloid-β inhibitors, through targeting α/β-discordant stretches at the early steps of aggregation.9 Quantitative investigation of distinct diastereomeric complexes represents the fundamental step toward understanding the basis for chiral distinction, and powerful experimental techniques such as NMR,10 fast atom bombardment mass spectrometry,11 and Fourier transform ion cyclotron resonance mass spectrometry12 were devised for this purpose. However, to reach the promised potential of such techniques for enantiomeric quantitative analysis, several experimental conditions must be met simultaneously, including a large chiral selectivity and no requirement for isotopically labeled reagents.13 Received: October 27, 2014 Revised: December 3, 2014 Published: December 5, 2014 387

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Table 1. Primary Sequence and Essential Characteristics of the Peptides Used Herein designation

sequence

MW (g/mol)

Q (pH 7)

pI

H (Eisenberg scale)

Aβ1 Aβ4H13dH Aβ5H6dH

DAEWRHDSGYEVHHQK DAEWRHDSGYEV(dH)HQK DAEWR(dH)DSGYEVHHQK

1994.1 1994.1 1994.1

−1.7 −1.8 −1.8

8.7 8.7 8.7

−0.39 −0.39 −0.39

with hAb1−16 analogues whose His-6 and His-13 amino acids were altered from L to D were fingerprinted by analyzing the transient blockades of the electrical current through the α-HL induced by Cu2+-free and Cu2+-bound peptides, in terms of blockade duration and rate, to assess the Cu2+ affinity to distinct chiral environments provided by the D,L-His amino acids.

As a novel approach to identify the stereoselective binding of Cu2+ ions to His amino acids belonging to an amyloidic peptide analogue, we harnessed herein the potential of the resistivepulse sensing technique through a single α-HL protein,14−20 to provide the proof-of-principle of the usefulness of the nanopore sensing method for studying the stereoselective interactions between Cu2+ and D,L-histidine amino acids. Previously, this technique was used successfully to study various chemistries at the single-molecule level,21−26 unravel microscopic details about modulatory effects induced by certain metals on peptide folding,27−31 detect amino acid enantiomers,32 demonstrate chiral discrimination of ibuprofen and thalidomide,33 and examine a reaction network that allowed the determination of the stereochemistry of thiol substitution at arsenic(III).34 In this report, we investigated the influence of the chiral environment on Cu2+ binding specificity, by employing several mutants of an intrinsically disordered amyloid fragment known for its ability to coordinate metals with specificity. Our strategy was to design a series of synthetic peptides based on the human amyloidic (hAβ) 1−16 fragment (hAβ1−16) that contain metal binding sites with identical chemical composition but different metal binding geometries, endowed by the D-histidine enantiomer which would change the metal−ligand bond lengths and angles. Our choice of the hAb1−16 substrate as a potential lucrative scaffold for a metal binding, and the particular strategy based upon D,L-histidines replacement in the hAb1−16 fragment to yield peptides with binding sites possessing distinct stereoselective affinitities to Cu2+ binding, was based on a meaningful series of aspects, including (i) His-6, His-13, and His-14 residues are major determinants of metal ions chelation by amyloid (Aβ) peptides,35−38 through their basic nitrogen atom in the imidazole moiety that has a lone electron pair, allowing it to effectively coordinate metal cations; (ii) rat Aβ, which contains three amino acid substitutions, i.e., R5G, Y10F, and H13R, binds Zn2+ and Cu2+ much less avidly than human Aβ;29,39,40 (iii) the metal-Aβ peptide structure is rather rigid and stable. Structural models inferred from X-ray absorption spectroscopy and Fourier transform infrared spectroscopy experiments proposed that two of the three imidazole rings from the Aβ’s His residues lie almost in the same plane with their normals forming an angle of about 20°, while the normal to the imidazole plane of the third His residue involved in metal coordination lies almost perpendicular to the common plane of the imidazole rings of the previously mentioned His residues;37,41 (iv) the mutation of His-6, His-13, and His-14 has effects on binding constants and enthalpies which characterize the Cu2+−hAb1−16 interactions.38 Altogether, these observations strongly suggest that peptide modifications involving the conservative His-6; His-13; His-14 motif could lead to changes in the Cu2+ coordination sphere, and promted us to conjecture that subtle sequence differences obtained by replacement of L-His amino acids with their D-enantiomers would create model substrates containing identical metal binding sites from a chemical viewpoint that would display in turn distinct Cu2+ binding affinities, through the alteration in the structural topology of the metal binding pocket. The microscopic kinetic details of the α-HL interaction

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MATERIALS AND METHODS

Peptide Synthesis. The peptides used were synthesized by the Schafer-N company (Denmark), purity >95%, based on the truncated human amyloid peptide sequence hAβ1−16 and are shown in Table 1 along with the set of parameters which characterize them comparatively. The overall charge around neutral pH was calculated using a peptide property calculator developed by Innovagen, and the mean hydrophobicity was calculated using the Eisenberg scale.42 The N-terminus and C-terminus for all the mutant peptides were left unprotected. The rationale for employing truncated amyloid sequences containing the minimal metal-binding domain such as hAβ1−16, as models to study the stereoselective Cu2+ binding to His residues, was owed to their good solubility and stability in the monomeric form, as opposed to full-length amyloids. The particular choice of L(D) mutating His-13 and His-6 amino acids lies in the fact that they were found dominant for Cu2+ coordination by amyloidic sequences.36,38,43 To ensure experimental conditions consistent with those used in electrophysiology experiments, the titration of amyloid fragments during fluorescence spectroscopy with copper was carried out in the absence of glycine as a competing ligand, as reported previously,44−47 and no buffer correction was implemented. Thus, instead of conditional dissociation constants which are usually corrected for the interaction with buffer, we employed herein apparent dissociation constants in order to assess the binding affinities of Cu2+ to distinct peptides. To facilitate the determination of such apparent dissociation constants through intrinsic fluorescence titration, a Trp residue was introduced in position 4, replacing the Phe present in the wild-type Aβ1−16 fragment. Although the intrinsic Tyr residue at position 10 has been previously used for fluorescence measurements of the Cu2+ binding constants of Aβ peptides,46,48 both detection sensitivity and specificity are affected by the relatively weak emission intensity of Tyr. We chose to preserve Tyr-10 in our peptide constructs, since it was proposed that this residue may also be implicated in the formation of the Cu2+ binding site in amyloidic peptides.49,50 Electrophysiology Experiments. Single-channel insertion of an α-HL protein into a planar lipid membrane made from L-αphosphatidylcholine was attained by adding on the cis (grounded) side aliquots of protein solution, from a stock made in 0.5 M KCl, as described previously.51 The two compartments of the bilayer cell were filled with 2 M KCl solution buffered at a pH of 7.3 with 10 mM HEPES. Once the successful insertion of a single α-HL nanopore was achieved, the peptides were pipetted in the trans side, at a 50 μM concentration. They were taken from a prestock solution (1 mM) made in water at the moment of use, from a stock solution (10 mM) made in dimethyl sulfoxide. Anhydrous copper(II) chloride was added in the same side as the peptides (i.e., the trans compartment) at a concentration ranging between 25 and 200 μM. In several control experiments, EDTA was added at a concentration of 400 μM to chelate the copper ions from the reaction mixture. Previous experiments27 with copper present in the peptide-free buffer from both sides of the membrane showed that the copper does not induce significant ion current blockades through the α-HL protein pore, and on the buffer used, it does not change the pH at the concentrations used in 388

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Figure 1. Representative electrophysiology data showing the unimolecular reversible interactions between the tested peptides and the α-HL pore, in the absence (panels a, e, and i) and presence of increasing concentrations of trans-added Cu2+. The experiments were performed with the α-HL protein added on the cis side of the membrane clamped at ΔV = −70 mV, in a buffer containing 2 M KCl and 10 mM HEPES (pH 7.3). of trans-added metals at various concentrations, was done as previously reported.27,29,53 The number of individual events taken into consideration during the analysis ranged between 150 and 250. Fluorescence Spectroscopy Experiments. The intrinsic fluorescence of the engineered Trp-4 amino acid present in all three peptide structures was used to monitor the conformational changes of the peptides induced by the Cu2+ binding, and all measurements were carried out with a FluoroMax-4 (Horiba Jobin Yvon, U.S.) spectrofluorimeter. Throughout such experiments, the concentration of the initially added peptide was 6 μM, and it was prepared similarly to the protocol described for the electrophysiology experiments. The buffer solution contained 2 M KCl and 10 mM HEPES, at a pH of 7.3. Upon Cu2+ addition at concentrations ranging from 0 to 3 μM, steady state changes in the maximum fluorescence emission of the peptides were recorded between 300 and 450 nm with a 2 nm resolution step, following the sample excitation at a wavelength of 280 nm. The apparent dissociation constants (Kd) characterizing the reversible interaction between peptides and Cu2+ were estimated via a nonlinear fit of the fluorescence titration data using the following equation (see also text):

our study, and leaves the lipid bilayer stable. All the chemicals used in this study were purchased from Sigma-Aldrich, Germany, unless stated otherwise. Throughout all the experiments, the potential applied was of −70 mV from the trans chamber by the Ag/AgCl electrode. Measurements were carried out at room temperature (∼23 °C), and the bilayer chamber was housed in a Faraday cage (Warner Instruments, U.S.A), mechanically isolated with a vibration-free platform (BenchMate 2210, Warner Instruments, U.S.A). The electric signals were recorded and amplified in the voltage-clamp mode, with an Axopatch 200B patch-clamp amplifier (Molecular Devices, U.S.A) and low-pass-filtered at a corner frequency ( fc) of 10 kHz.52 Data acquisition was performed using a NI PCI 6221 acquisition board (National Instruments, U.S.A) at a sampling frequency of 80 kHz within the LabVIEW 8.20 (National Instruments, U.S.A) graphical programming environment. Analysis of single-molecule traces and data representation were done with the help of pClamp 6.03 software (Axon Instruments, U.S.A) and Origin 6 software (OriginLab, U.S.A). The statistical analysis of average time intervals in between peptide-induced blockade events (τON) and events corresponding to a single α-HL pore temporarily blocked by a peptide (τOFF), in the absence and presence

ΔF = ΔFmax

[P0] + [Cu 0 2 +] + Kd −

([P0] + [Cu 0 2 +] + Kd)2 − 4[P0][Cu 0 2 +] 2[P0]

where ΔF is the observed change in fluorescence intensity, ΔFmax is the maximum observed change in fluorescence intensity, [P0] is the initial peptide concentration, and [Cu02+] is the added copper concentration.

(1)

lipid membrane. As shown in Figure 1, aqueous addition of either peptide leads to vigorous, transient blockades of the otherwise “silent” ion current through the α-HL protein clamped at a ΔV = −70 mV, and amplitude analysis reveals very narrow and well-defined populations of events located around the current values of I = −111.56 ± 0.04 pA for the free pore and I (Aβ1) = −15.68 ± 0.13 pA, I (Aβ4H13dH) = −9.98 ± 0.16 pA, and I (Aβ5H6dH) = −9.02 ± 0.18 pA for the pore blocked by the corresponding peptide.

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RESULTS AND DISCUSSION In a first set of experiments, we studied the reversible interaction between the trans-added Aβ1, Aβ4H13dH, and Aβ5H6dH peptides and a single α-HL protein immobilized in a planar 389

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Figure 2. Plots of the concentration dependence of the first-order association reaction rates (rateON; panels a, b, and c) and first-order dissociation rates (rateOFF; panels d, e, and f) describing the interaction of Aβ1, Aβ4H13dH, and Aβ5H6dH peptides with a single α-HL protein. Association rate plots were fitted to the equation y = k1x, where the slope k1 gave the value for the biomolecular association rate constant, and dissociation rate plots were fitted to the equation y = k2, where the intercept, k2, gave the value for the dissociation rate constant (see also Table 2). Dotted lines indicate the 95% confidence interval for the particular estimations of the association and dissociation rates at various concentrations of the bulk peptides at a holding potential of ΔV = −70 mV.

Figure 3. All-events distribution plot of current drop (ΔIblock) through a single α-HL protein versus blockade times of the studied peptides before (panels a, e, and i) and after the trans-side addition of various concentrations of Cu2+ at a holding potential of ΔV = −70 mV. 390

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As described previously,54 this behavior reflects the reversible electrophoretic capture of a single peptide at the lumen entrance of the α-HL protein by the electric field lines which extend on both cis and trans chambers, during nonequilibrium conditions maintained by an ion current across the α-HL clamped at a given transmembrane potential. The statistical analysis of average values of interevents corresponding to blocking events (τON) and times corresponding to the peptide temporarily lodged within the protein pore (τOFF), at increasing concentrations of the trans-added peptide, resulted in the evaluation of kinetic constants which characterize the reversible, noncovalent peptide−α-HL interactions, and were found consistent with a simple bimolecular interaction between the peptide and the pore (Figure 2). The Cu2+-induced changes of peptide-induced blockade events are fully reversible, since addition of excess EDTA on the trans side of the membrane fully recovers the activity seen in the absence of Cu2+ (Figure S1, Supporting Information). To more conveniently visualize the changes entailed by increasing the concentration of trans-side-added Cu2+ in the characteristics of blockade events associated with the interaction between the Aβ1, Aβ4H13dH, and Aβ5H6dH peptides with a single α-HL protein, in Figure 3, we represent the collective behavior of blockade events by scatter plots of dwell time vs relative blockade amplitude. From the scatter plots in Figure 3, one clearly sees a correlation between the peptide-induced blockade time and the concentration of the trans-added Cu2+, which alters the peptide conformation. While the characteristic dwell times of peptides blocking the α-HL pore in the absence of Cu2+ lie within a 0.1−10 ms range (Figure 3, panels a, e, and i), as the Cu2+ concentration increases, the distribution of the current blockade amplitudes broadens and a new population with larger dwell times of ∼100−1000 ms emerges (see also Figure S2, Supporting Information). This is indicative of a phenomenon through which Cu2+ binding triggers a more structured conformation in the peptide structure whose net electric charge may also become less negative, and the transport of such distorted molecules along the α-HL pore is hindered. This is in agreement with previous results regarding the interaction of metal-complexed Aβ peptides with the α-HL pore,29,30 and may be useful as a complementary approach to discriminate conformational changes on short peptides based on differences in transport dynamics (vide inf ra). The detailed kinetic analysis of current blocking events recorded in the presence of various metals added at incrementally higher concentrations in the trans chamber showed that the average time of blockade events (τOFF) (Figure 4, panels b, d, and e) and values of times in between consecutive peptide-induced blockade events (τON) (Figure 4, panels a, c, and e) increase monotonically with the concentration of added Cu2+ to an apparent plateau, in accord with previous observations made for similar systems.29 An intriguing effect is the sudden increase of τOFF related to the dissociation of the Aβ5H6dH peptide from the α-HL pore when the Cu2+ concentration changes from 75 to 100 μM (Figure 4, panel f), as opposed to Aβ1 (Figure 4, panel b) or Aβ4H13dH (Figure 4, panel d) peptides. In follow-up studies, we will seek to decipher the particular molecular events characterizing the Aβ5H6dH−Cu2+ interactions, prone to sustain such an apparent abrupt augmentation of “Cu2+-complexed” peptide−α-HL affinity beyond a threshold value of free Cu2+. These data demonstrate that, in qualitative terms, Cu2+ interaction with the studied peptides triggers conformational

Figure 4. Statistical analysis of the association (τON) and dissociation (τOFF) average dwell time intervals of a single peptide (Aβ1, panels a and b; Aβ4H13dH, panels c and d; Aβ5H6dH, panels e and f) interacting reversibly with a membrane-immobilized α-HL pore, measured at various concentrations of the trans-added Cu2+. The τON and τOFF average values were constructed by considering the lumped contributions stemming from the reversible association of the α-HL pore with either a “Cu2+-free” or “Cu2+-complexed” peptide (see text). Throughout experiments, the trans-added peptides were present at a bulk concentration of 50 μM.

changes on the peptide structure and thus alters the dynamics of reversible peptide−α-HL pore interactions, in a concentration-dependent manner. Structural changes induced by metal binding to amyloid fragments were reported before, as metal coordination was found to induce a higher degree of ordering in the conformation of various fragments of Aβ40,55 and various metals were found to alter distinctly the propensity of the interaction of related amyloid peptides with a free α-HL protein.30 With particular relevance to our data, the quantitative exploration of the peptide−α-HL interactions taking place in the presence of trans-added Cu2+ must take into consideration that, especially at low concentrations of metal, “metal-free” peptides are present in the sample so that the obtained dwell-time distributions reflect the reversible interactions between the α-HL pore and either the “metal-free” or “metal-complexed” peptides (Figure 5). Consequently, the current signature associated with the “Cu2+-free” or “Cu2+-complexed” peptide−α-HL interactions must be completely discernible in order to ascertain the fraction of time spent by either peptide on the nanopore, or capture time by the nanopore, and ensure a reliable kinetic analysis using the nanopore data. Herein and in previously related investigations,29,30 we noted that, although present as multiple Gaussians in amplitude histograms, the slight differences in relative current 391

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Figure 5. Putative kinetic model for the observed current blockades induced by the studied peptides on the ion transport through the α-HL protein in the presence of Cu2+. The (α-HL·peptide) state corresponds to the blocked pore by a “Cu2+-free” peptide entering at the trans mouth of the α-HL, whereas the (α-HL·[peptide-Cu2+]) state corresponds to the blocked pore by a “Cu2+-complexed” peptide entering at the trans mouth of the α-HL.

where [P] and [P−Cu2+] refer to the available concentrations of the “Cu2+-free” peptide and “Cu2+-complexed” peptide, respectively, k1 and k3 represent the association rate constants of the “Cu2+-free” peptide and “Cu2+-complexed” peptide with an “open” (“O”) protein pore, and k2 and k4 represent the corresponding dissociation rate constants. Within this scheme, we next referred to the theoretical values of the lumped τOFF and τON time intervals, as they were calculated on the basis of the general theory of single-channel kinetics analysis of a three-state Markov model:27,56

blockades associated with the interaction of the pore with either “Cu2+-free” or “Cu2+-complexed” peptides are not sufficiently reliable to distinguish differences in translocation patterns between two peptide species. As a result, blockade amplitude events were seen to sometimes overlap, thus giving rise to populations mixed in a way that cannot reliably allow one to pinpoint an exact occupancy state (i.e., by either “Cu2+-free” or “Cu2+-complexed” peptides) of the peptide-blocked α-HL pore. Thus, in order to undertake a meaningful analysis of our nanopore data with the goal of extracting quantitative information regarding the ability of the studied peptides to bind Cu2+, we performed statistics on τON and τOFF dwell times measured in the presence and absence of Cu2+, by taking into account the distinct kinetic routes which produce α-HL transient blockades (see Figure 5). Within the framework of a previously developed model,27 and as depicted in Figure 5, we posit that, in the presence of Cu2+, the protein can associate reversibly with either a “Cu2+-free” peptide or a “Cu2+complexed” peptide, and the kinetic scheme described above is written as k 3[P−Cu 2 +]

k1[P]

k4

k2

C2 ←⎯⎯⎯⎯⎯⎯⎯⎯→ O ←→ ⎯ C1

[P−Cu 2 +]eq =

τOFF =

k4k1·([P0] − [P−Cu 2 +]eq ) + k 2k 3[P−Cu 2 +]eq k 2k4·(k1([P0] − [P−Cu 2 +]eq ) + k 3[P−Cu 2 +]eq ) (3)

τON = =

1 k 3[P−Cu 2 +]eq + k1([P]eq ) 2+

k 3[P−Cu ]eq

1 + k1([P0] − [P−Cu 2 +]eq )

(4)

In the expressions above, the equilibrium value of the binary complex (P−Cu2+) concentration ([P−Cu2+]) is written as27

(2)

([P0] + [Cu 0 2 +] + K d) −

2

([P0] + [Cu 0 2 +] + K d) − 4[P0][Cu 0 2 +] 2

where Kd denotes the apparent dissociation constant characterizing the peptide−Cu2+ interactions and [P0] and [Cu02+] represent the initial concentrations of the free peptide (P0) and added Cu2+, respectively. As we stressed above, the “ON” and “OFF” dwell times depend on the structural features of the peptides (e.g., the net charge, cross-sectional area, and topology of the peptides). For the case of “Cu2+-complexed” species, the “ON” and “OFF” dwell times may also be correlated with the metal affinity toward the peptides, and therefore directly influence the reversible kinetics of peptide association to the pore and volumetric parameters of the peptide−α-HL complexes. As a result, quantitative evaluations of the “ON” and “OFF” dwell times vs [Cu02+] not only can serve as a molecular recognition signature to differentiate among the specific peptide species in the presence of Cu2+ but also can be used as titration curves to estimate the apparent binding affinity of Cu2+ to each peptide. The latter result can report on the effect of His enantiomers and their position in a peptide chain on the stability of the peptide−metal

(5)

complexes. To a first approximation, we disregarded in our subsequent analysis the buffer influence of the metal binding affinity to peptides45,57 or the diversity of metal-binding conformations of the peptides, and the presence of other higher order (i.e., metal-bridged peptide monomers) complexes. To estimate the apparent Kd values for the peptide species studied herein for Cu2+, our approach was comprised of two essential steps. First, we investigated the reversible interactions between the peptides and the pore in the absence of transadded Cu2+ within a simple bimolecular interaction model (Figure 5). For each of the studied peptides, the “ON” rate constant (k1 in the model above) was extracted from the slope of the linear fit of rateON vs peptide concentration (Figure 2, panels a, b, and c), while the “OFF” rate constants (k2 in the model above) were independent of peptide concentration (Figure 2, panels d, e, and f), and by virtue of the simple bimolecular model taken into account, equal rateOFF (Table 2). In the second step, we used these values to perform a nonlinear fit of expression 4 to data shown in Figure 4a, c, and e 392

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fluorescence titration data (Figure S4, Supporting Information). As demonstrated previously,27,58,59 a strong intensity change of the intrinsic fluorescence emission spectra of Trp-4 in the presence of variable amounts of Cu2+ serves as a proof of a conformational change undergone by the peptides which, in complexation with Cu2+, change the microenvironment polarity around Trp-4, making it less exposed to the hydrophilic environment. We considered a bimolecular binding case between free peptides (P) and copper ions (Cu2+), in which the two components bind reversibly to form the (P−Cu2+) complex, described by the association (kON) and dissociation (kOFF) rate constants, and took into consideration the fact that Cu2+ binding to peptides leads to a depletion of the free, available concentration of both peptide and Cu2+ (see the Supporting Information). The concentration of the metal−peptide complex calculated at equilibrium ([P−Cu2+]eq ) vs the intermediary concentration value of the added Cu2+ is written as

Table 2. Numeric Evaluations of the Rate Constants of Association (k1) and Dissociation (k2) between “Cu2+-Free” Aβ1, Aβ4H13dH, and Aβ5H6dH Peptides in the α-HL Protein −1

−1

k1 × 10 (M s ) k2 × 103 (s−1) 3

Aβ1

Aβ4H13dH

Aβ5H6dH

68.7 ± 5.9 2.08 ± 0.5

37.03 ± 2.9 1.14 ± 0.02

34.28 ± 1.19 1.69 ± 0.04

(Figure S3, Supporting Information), and arrived at estimations of dissociation constant values for Cu2+ binding to all studied peptides (Kd,Cu2+ (Aβ1) = 9.99 ± 4.51 μM, Kd,Cu2+ (Aβ4H13dH) = 22.6 ± 11.1 μM, Kd,Cu2+ (Aβ5H6dH) = 27.02 ± 10.9 μM), and k3 values assigned to the association rate constants between the “Cu2+-complexed” peptides and the α-HL pore (see model above) (k3 (Aβ1) = 26.9 × 103 M−1 s−1, k3 (Aβ4H13dH) = 15.3 × 103 M−1 s−1, k3 (Aβ5H6dH) = 12.7 × 103 M−1 s−1). To qualitatively assess the values derived above for the apparent dissociation constants of Cu2+ binding to peptides, we determined them by using an alternative route, from intrinsic

2+

[P−Cu ]eq =

([P0] + [Cu 0 2 +] + K d) −

2

([P0] + [Cu 0 2 +] + K d) − 4[P0][Cu 0 2 +]

and the difference ΔF between intermediary lumped fluorescence emission intensity (F) and the fluorescence emission intensity measured during control experiments (F0) ΔF = [Fmax − F0]

as a function of the concentration of Cu2+ added initially ([Cu02+]) becomes (see the Supporting Information)

[P−Cu 2 +] [P−Cu 2 +] = ΔFmax [P0] [P0]

2+ ΔFmax ([P0] + [Cu 0 ] + K d) − = · [P0]

2

([P0] + [Cu 0 2 +] + K d) − 4[P0][Cu 0 2 +] 2

By replacing in eq 7 the value of the initially added peptide concentration ([P0]), the apparent dissociation constant Kd was extracted from a nonlinear hyperbolic fit (Figure S4, Supporting Information) according to eq 7 (Table 3). It is instructive to note the apparent dissociation constants of Cu2+ for the peptides tested (Kd) derived from the nanopore titration data follow a similar trend with those calculated from experiments using the otherwise commonly used, intrinsic fluorescence titration approach (Table 3).

Kd

P + Cu 2 + ⇄ P−Cu 2 + Kd (μM) Kd(fluorescence) (μM)

Aβ1

Aβ4H13dH

Aβ5H6dH

9.99 0.011

22.6 0.037

27.02 0.292

(7)

the fact that the association reaction rates of the “metal-free” and “metal-complexed” peptide are voltage-dependent.53 Nevertheless, a noteworthy finding is that both singlemolecule electrophysiology and intrinsic fluorescence titration reveal a decrease in the Cu2+-binding affinity of the peptides tested as L-His is replaced with its D-enantiomer, with the effect being more prevalent when such changes were inflicted on the His-6 residue. To our knowledge, this is the first report which demonstrates the proof-of-concept of a protein nanoporebased, single-molecule sensing platform potential to assess the metal affinity to distinct chiral environments provided by the amino acid enantiomers. In addition, by replacing in expression 3 the corresponding values for k1, k2, and k3 derived as described above, a nonlinear fit with the resulting function of data shown in Figure 4 allowed the estimation of the dissociation constants of “Cu2+-complexed” peptide from the α-HL pore (k4 (Aβ1) = 168.1 ± 9.8 s−1, k4 (Aβ4H13dH) = 156.4 ± 7.3 s−1, k4 (Aβ5H6dH) = 49.8 ± 6.8 s−1) (Figure S3, Supporting Information). These values were then used to calculate the dissociation constants which describe the reversible interaction between the “Cu2+-free” (Kd = k2/k1) and “Cu2+-complexed” (Kd = k4/k3) peptides and the α-HL pore (Kd (α-HL−Aβ1) = 30.2 mM, Kd (α-HL−Aβ4H13dH) = 30.7 mM, Kd (α-HL−Aβ5H6dH) = 49.2 mM and Kd (α-HL− Cu2+·Aβ1) = 6.24 mM, Kd (α-HL−Cu2+·Aβ4H13dH) = 10.22 mM, and Kd (α-HL−Cu2+·Aβ5H6dH) = 3.92 mM), suggesting a larger affinity of “Cu2+-complexed” peptides to the pore. We plan to

Table 3. Apparent Dissociation Constants (Kd) Characterizing the Tested Peptide−Cu2+ Reversible Interactions Obtained from Electrophysiology and Fluorescence Titration Experiments

(electrophysiology)

(6)

2

We conjecture that partly the differences seen lie in the fact that, when the nanopore titration method is employed, the peptide−protein interactions are studied actually at nonequilibrium. A consequence is that the perturbing effects of the electroosmotic flow of water through the protein and electric interaction between the peptide and the electric field across the pore have the potential to bias the Kd values through 393

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study these kinetic and thermodynamic aspects in forthcoming work, but at this point, we posit at least two main contributors to this effect: (i) the overall charge of the “Cu2+-complexed” peptides is expected to be slightly less negative than that of the “Cu2+-free” peptides, meaning that the derived values of the dissociation constants between the “Cu2+-free” and “Cu2+complexed” peptides and the pore may reflect the distinct interactions of the peptides with the electric field across the αHL; (ii) Cu2+-dependent conformational changes of the peptides might render them more prone to docking with the α-HL hydrophilic pore, via an augmentation in the overall hydrophilicity of the “Cu2+-complexed” peptide, that allows for a larger enthalpy contribution to the free energy difference of the “Cu2+complexed” peptides−α-HL reaction equilibrium as compared to “Cu2+-free” peptides. In the absence of high-resolution structure of such an Aβderived peptide complexed with metal ions, and the supposition that metal ions might induce in fact an ensemble of structures,54 we concede that investigations employing EPR/ NMR and molecular modeling could further illuminate these findings. Although the role of His enantiomers and the mechanism of interactions responsible for molecular recognition of Cu2+ are yet to be revealed through complementary approaches, our data suggest that the three-dimensional molecular environment around the coordinated Cu2+ ion changes with the position-specific incorporation of His enantiomers. The presented data underline the potential of the α-HL nanopore to discriminate between peptides with identical chemical composition, whose analyte-binding sites contain amino acid enantiomers on various positions on the primary structure, based on the kinetic analysis of the peptide-induced blockade events on the open-pore current.

Article

ASSOCIATED CONTENT

S Supporting Information *

Figures showing original traces displaying the current fluctuations, selected zoomed-in data of original traces shown in Figure 1 (main text), nonlinear fitting of the τON and τOFF data, and fluorescence spectra of Trp-4 and the mathematical model for determining KD from intrinsic fluorescence data titration. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Author Contributions §

I.S., S.I.: These authors contributed equally.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS T.L. acknowledges the financial support offered by grants PN-II-ID-PCCE-2011-2-0027, PN-II-PT-PCCA-2011-3.10595. I.S. acknowledges the financial support provided by UAIC (GI - 2014 - 08).

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REFERENCES

(1) Leal, S. S.; Botelho, H. M.; Gomes, C. M. Metal Ions as Modulators of Protein Conformation and Misfolding in Neurodegeneration. Coord. Chem. Rev. 2012, 256, 2253−2270. (2) Ly, H. D.; Withers, S. G. Mutagenesis of Glycosidases. Annu. Rev. Biochem. 1999, 68, 487−522. (3) Karlin, K. D.; Tyeklar, Z. Bioinorganic Chemistry of Copper; Chapman & Hall: New York, 1993. (4) Ma, Q.; Xu, Z.; Schroeder, B. R.; Sun, W.; Wei, F.; Hashimoto, S.; Konishi, K.; Leitheiser, C. J.; Hecht, S. M. Biochemical Evaluation of a 108-Member Deglycobleomycin Library: Viability of a Selection Strategy for Identifying Bleomycin Analogues with Altered Properties. J. Am. Chem. Soc. 2007, 129, 12439−12452. (5) Hazen, R. M.; Sholl, D. S. Chiral Selection on Inorganic Crystalline Surfaces. Nat. Mater. 2003, 2, 367−374. (6) Qing, G.; Zhao, S.; Xiong, Y.; Lv, Z.; Jiang, F.; Liu, Y.; Chen, H.; Zhang, M.; Sun, T. Chiral Effect at Protein/Graphene Interface: a Bioinspired Perspective to Understand Amyloid Formation. J. Am. Chem. Soc. 2014, 136, 10736−10742. (7) Sundaresan, V.; Abrol, R. Towards a General Model for Protein− Substrate Stereoselectivity. Protein Sci. 2002, 11, 1330−1339. (8) Koshland, D. E., Jr.; Nemethy, G.; Filmer, D. Comparison of Experimental Binding Data and Theoretical Models in Proteins Containing Subunits. Biochemistry 1996, 5, 365−385. (9) Li, M.; Howson, S. E.; Dong, K.; Gao, N.; Ren, J.; Scott, P.; Qu, X. Chiral Metallohelical Complexes Enantioselectively Target Amyloid β for Treating Alzheimer’s Disease. J. Am. Chem. Soc. 2014, 136, 11655−11663. (10) Takeuchi, Y.; Marchand, A. P. Applications of NMR Spectroscopy to Problems in Stereochemistry and Conformational Analysis; VCH Publishers: Deerfield Beach, FL, 1986. (11) Sawada, M. Chiral Recognition Detected by Fast Atom Bombardment Mass Spectrometry. Mass Spectrom. Rev. 1997, 16, 73−90. (12) Nikolaev, E. N.; Denisov, E. V.; Nikolaeva, M. I.; Futrell, J. H.; Rakov, V. S.; Winkler, F. J. Elucidation of Influence of Chirality on Formation and Decomposition of Ion Molecular Complexes in the Dialkyltartrate Class Using Mass Spectrometry. Adv. Mass Spectrom. 1998, 14, 279−313. (13) Tao, W. A.; Zhang, D.; Nikolaev, E. N.; Cooks, R. G. Copper(II)-Assisted Enantiomeric Analysis of D,L-Amino Acids Using

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CONCLUSION In this study, a series of rationally-designed peptides based on the human amyloidic (hAβ) 1−16 scaffold were used to demonstrate the utility of a versatile, label-free method for evaluating chiral recognition of L/D-His amino acids by metals with the α-HL nanopore. It is apparent that the fine-tuning in the relative orientation of the L/D imidazole rings and the metal coordination bond length act as a conformational switch to induce and stabilize certain conformations of the peptide metalbinding pocket, and thus alter the metal affinity toward peptides. Despite the relatively low affinity of Aβ to metals as compared to metalloproteins, its flexibility and reduced size constitute advantages in the realm of metal sensing. That is, although disordered in aqueous solution, the flexible Aβ can adopt a 3D structure if it interacts with metals, and this change of topology together with overall size comparable to the inner volume of the α-HL make Aβ highly suitable for metal sensing with protein nanopores. Thus, metal sensing is transduced through conformational changes of the peptide, which can be detected by the α-HL. With further refinement, the presented approach can be easily extended for chiral analysis of other biological molecules of interest without resorting to expensive chemical labeling strategies or employing expensive techniques, in which cleverly rational designed peptide substrates may prove to be ideal candidates for chiral analysis able to unravel the thermodynamic contributions to chiral recognition by various functional groups through nanopore-based singlemolecule biosensors or enantiopurity testing of substrate stereoisomers and chiral separation technologies. 394

dx.doi.org/10.1021/la504243r | Langmuir 2015, 31, 387−396

Langmuir

Article

(36) Faller, P.; Hureau, C. Bioinorganic Chemistry of Copper and Zinc Ions Coordinated to Amyloid-β Peptide. Dalton Trans. 2009, 7, 1080−1094. (37) Stellato, F.; Menestrina, G.; Dalla Serra, M.; Potrich, C.; Tomazzolli, R.; Meyer-Klaucke, W.; Morante, S. Eur. Biophys. J. 2006, 35, 340−351. (38) Hong, L.; Carducci, T. M.; Bush, W. D.; Dudzik, C. G.; Millhauser, G. L.; Simon, J. D. Quantification of the Binding Properties of Cu2+ to the Amyloid Beta Peptide: Coordination Spheres for Human and Rat Peptides and Implication on Cu2+-Induced Aggregation. J. Phys. Chem. B 2010, 114, 11261−11271. (39) Bush, A. I.; Pettingell, W. H.; Multhaup, G.; Paradis, M. D.; Vonsattel, J. P.; Gusella, J. F.; Beyreuther, K.; Masters, C. L.; Tanzi, R. E. Rapid Induction of Alzheimer Aβ Amyloid Formation by Zinc. Science 1994, 265, 1464−1467. (40) Huang, J.; Yao, Y.; Lin, J.; Ye, Y. H.; Sun, W. Y.; Tang, W. X. The Solution Structure of Rat Aβ (1-28) and its Interaction with Zinc Ion: Insights into the Scarcity of Amyloid Deposition in Aged Rat Brain. J. Biol. Inorg. Chem. 2004, 9, 627−635. (41) Minicozzi, V.; Stellato, F.; Comai, M.; Serra, M. D.; Potrich, C.; Meyer-Klaucke, W.; Morante, S. Identifying the Minimal Copper- and Zinc-binding Site Sequence in Amyloid-β Peptides. J. Biol. Chem. 2008, 283, 10784−10792. (42) Eisenberg, D.; Weiss, R. M.; Terwilliger, T. C.; Wilcox, W. Hydrophobic Moments and Protein Structure. Faraday Symp. Chem. Soc. 1982, 17, 109−120. (43) Silva, K. I.; Saxena, S. Zn(II) Ions Substantially Perturb Cu(II) Ion Coordination in Amyloid-β at Physiological pH. J. Phys. Chem. B 2013, 117, 9386−9393. (44) Jiang, D.; Zhang, L.; Gacho Grant, G. P.; Dudzik, C. G.; Chen, S.; Patel, S.; Hao, Y.; Millhauser, G. L.; Zhou, F. The Elevated Copper Binding Strength of Amyloid-β Aggregates Allows the Sequestration of Copper from Albumin: A Pathway to Accumulation of Copper in Senile Plaques. Biochemistry 2013, 52, 547−556. (45) Sacco, C.; Skowronsky, R. A.; Gade, S.; Kenney, J. M.; Spuches, A. M. Calorimetric Investigation of Copper(II) Binding to Aβ Peptides: Thermodynamics of Coordination Plasticity. J. Biol. Inorg. Chem. 2012, 17, 531−541. (46) Tougu, V.; Karafin, A.; Palumaa, P. Binding of Zinc(II) and Copper(II) to the Full-Length Alzheimer’s Amyloid-Beta Peptide. J. Neurochem. 2008, 104, 1249−1259. (47) Chen, W. T.; Liao, Y. H.; Yu, H. M.; Cheng, I. H.; Chen, Y. R. Distinct Effects of Zn2+, Cu2+, Fe3+, and Al3+ on Amyloid-Beta Stability, Oligomerization, and Aggregation: Amyloid-Beta Destabilization Promotes Annular Protofibril Formation. J. Biol. 2011, 286, 9646−9656. (48) Maiti, N. C.; Jiang, D. L.; Wain, A. J.; Patel, S.; Dinh, K. L.; Zhou, F. M. Mechanistic Studies of Cu(II) Binding to Amyloid-Beta Peptides and the Fluorescence and Redox Behaviors of the Resulting Complexes. J. Phys. Chem. B 2008, 112, 8406−8411. (49) Barnham, K. J.; Haeffner, F.; Ciccotosto, G. D.; Curtain, C. C.; Tew, D.; Mavros, C.; Beyreuther, K.; Carrington, D.; Masters, C. L.; Cherny, R. A.; Cappai, R.; Bush, A. I. Tyrosine Gated Electron Transfer is Key to the Toxic Mechanism of Alzheimer’s Disease βAmyloid. FASEB J. 2004, 18, 1427−1429. (50) Smith, D. P.; Smith, D. G.; Curtain, C. C.; Boas, J. F.; Pilbrow, J. R.; Ciccotosto, G. D.; Lau, T. L.; Tew, D. J.; Perez, K.; Wade, J. D.; Bush, A. I.; Drew, S. C.; Separovic, F.; Masters, C. L.; Cappai, R.; Barnham, K. J. Copper-Mediated Amyloid-Beta Toxicity is Associated with an Intermolecular Histidine Bridge. J. Biol. Chem. 2006, 281, 15145−15154. (51) Mereuta, L.; Roy, M.; Asandei, A.; Lee, J. K.; Park, Y.; Andricioaei, I.; Luchian, T. Slowing Down Single-Molecule Trafficking Through a Protein Nanopore Reveals Intermediates for Peptide Translocation. Sci. Rep. 2014, 4, 3885. (52) Apetrei, A.; Mereuta, L.; Luchian, T. The RH 421 Styryl Dye Induced, Pore Model-Dependent Modulation of Antimicrobial Peptides Activity in Reconstituted Planar Membranes. Biochim. Biophys. Acta, Gen. Subj. 2009, 1790, 809−816.

the Kinetic Method: Chiral Recognition and Quantification in the Gas Phase. J. Am. Chem. Soc. 2000, 122, 10598−10609. (14) Bayley, H.; Martin, C. R. Resistive-Pulse SensingFrom Microbes to Molecules. Chem. Rev. 2000, 100, 2575−2594. (15) Majd, S.; Yusko, E. C.; Billeh, Y. N.; Macrae, M. X.; Yang, J.; Mayer, M. Applications of Biological Pores in Nanomedicine, Sensing, and Nanoelectronics. Curr. Opin. Biotechnol. 2010, 21, 439−476. (16) Wang, G.; Wang, L.; Han, Y.; Zhou, S.; Guan, X. Nanopore Stochastic Detection: Diversity, Sensitivity, and Beyond. Acc. Chem. Res. 2013, 46, 2867−2877. (17) Gu, L. Q.; Shim, J. W. Single Molecule Sensing by Nanopores and Nanopore Devices. Analyst 2010, 135, 441−451. (18) Howorka, S.; Siwy, Z. Nanopore Analytics: Sensing of Single Molecules. Chem. Soc. Rev. 2009, 38, 2360−2384. (19) Reiner, J. E.; Balijepalli, A.; Robertson, J. W. F.; Campbell, J.; Suehle, J.; Kasianowicz, J. J. Disease Detection and Management via Single Nanopore-Based Sensors. Chem. Rev. 2012, 112, 6431−6451. (20) Movileanu, L. Interrogating Single Proteins through Nanopores: Challenges and Opportunities. Trends Biotechnol. 2009, 27, 333−341. (21) Luchian, T.; Shin, S. H.; Bayley, H. Single-Molecule Covalent Chemistry with Spatially Separated Reactants. Angew. Chem., Int. Ed. 2003, 42, 3766−3771. (22) Luchian, T.; Shin, S.-H.; Bayley, H. Kinetics of a Three-Step Reaction Observed at the Single Molecule Level. Angew. Chem., Int. Ed. 2003, 42, 1926−1929. (23) Shin, S. H.; Luchian, T.; Cheley, S.; Braha, O.; Bayley, H. Kinetics of a Reversible Covalent−Bond Forming Reaction Observed at the Single Molecule Level. Angew. Chem., Int. Ed. 2002, 41, 3707− 3709. (24) Gu, L.-Q.; Braha, O.; Conlan, S.; Cheley, S.; Bayley, H. Stochastic Sensing of Organic Analytes by a Pore-Forming Protein Containing a Molecular Adapter. Nature 1999, 398, 686−690. (25) Asandei, A.; Mereuta, L.; Luchian, T. The Kinetics of Ampicillin Complexation by γ Cyclodextrins. A Single Molecule Approach. J. Phys. Chem. B 2011, 115, 10173−10181. (26) Asandei, A.; Apetrei, A.; Luchian, T. Uni-molecular Detection and Quantification of Selected β-Lactam Antibiotics with a Hybrid αHemolysin Protein Pore. J. Mol. Recognit. 2011, 24, 199−207. (27) Mereuta, L.; Schiopu, I.; Asandei, A.; Park, Y.; Hahm, K. S.; Luchian, T. Protein Nanopore-Based, Single-Molecule Exploration of Copper Binding to an Antimicrobial-Derived, Histidine-Containing Chimera Peptide. Langmuir 2012, 28, 17079−17091. (28) Wang, G.; Wang, L.; Han, Y.; Zhou, S.; Guan, X. Nanopore Detection of Copper Ions Using a Polyhistidine Probe. Biosens. Bioelectron. 2014, 53, 453−458. (29) Asandei, A.; Schiopu, I.; Iftemi, S.; Mereuta, L.; Luchian, T. Investigation of Cu2+ Binding to Human and Rat Amyloid Fragments Aβ (1−16) with a Protein Nanopore. Langmuir 2013, 29, 15634− 15642. (30) Asandei, A.; Iftemi, S.; Mereuta, L.; Schiopu, I.; Luchian, T. Probing of Various Physiologically Relevant Metals-Amyloid-β Peptide Interactions with a Lipid Membrane-Immobilized Protein Nanopore. J. Membr. Biol. 2014, 247, 523−530. (31) Baran, C.; Smith, G. S.; Bamm, V. V.; Harauz, G.; Lee, J. S. Divalent Cations Induce a Compaction of Intrinsically Disordered Myelin Basic Protein. Biochem. Biophys. Res. Commun. 2010, 391, 224− 229. (32) Boersma, A. J.; Bayley, H. Continuous Stochastic Detection of Amino Acid Enantiomers with a Protein Nanopore. Angew. Chem., Int. Ed. 2012, 51, 9606−9609. (33) Kang, X. F.; Cheley, S.; Guan, X.; Bayley, H. Stochastic Detection of Enantiomers. J. Am. Chem. Soc. 2006, 128, 10684−10685. (34) Steffensen, M. B.; Rotem, D.; Bayley, H. Single-Molecule Analysis of Chirality in a Multicomponent Reaction Network. Nat. Chem. 2014, 6, 603−607. (35) Pagel, K.; Seri, T.; von Berlepsch, H.; Griebel, J.; Kirmse, R.; Böttcher, C.; Koksch, B. How Metal Ions Affect Amyloid Formation Cu2+ and Zn2+ Sensitive Peptides. ChemBioChem 2008, 9, 531−536. 395

dx.doi.org/10.1021/la504243r | Langmuir 2015, 31, 387−396

Langmuir

Article

(53) Asandei, A.; Apetrei, A.; Park, Y.; Hahm, K. S.; Luchian, T. Investigation of Single-Molecule Kinetics Mediated by Weak Hydrogen Bonds within a Biological Nanopore. Langmuir 2011, 27, 19−24. (54) Grosberg, A. Y.; Rabin, Y. DNA Capture into a Nanopore:Interplay of Diffusion and Electrohydrodynamics. J. Chem. Phys. 2010, 133, 165102. (55) Abelein, A.; Abrahams, J. P.; Danielsson, J.; Graslund, A.; Jarvet, J.; Luo, J.; Tiiman, A.; Warmlander, S. K. T. S. The Hairpin Conformation of the Amyloid β Peptide is an Important Structural Motif along the Aggregation Pathway. J. Biol. Inorg. Chem. 2014, 19, 623−634. (56) Jackson, M. B. Molecular and Cellular Biophysics; Cambridge University Press: New York, 2006. (57) Sokołowska, M.; Bal, W. Cu(II) Complexation by ‘‘NonCoordinating’’ N-2-Hydroxyethylpiperazine-N0-2-Ethanesulfonic Acid (HEPES Buffer). J. Inorg. Biochem. 2005, 99, 1653−1660. (58) Zou, J.; Sugimoto, N. Complexation of Peptide with Cu2+ Responsible to Inducing and Enhancing the Formation of α-Helix Conformation. Biometals 2000, 13, 349−359. (59) Munishkina, L. A.; Fink, A. L. Fluorescence as a Method to Reveal Structures and Membrane-Interactions of Amyloidogenic Proteins. Biochim. Biophys. Acta, Biomembr. 2007, 1768, 1862−1885.

396

dx.doi.org/10.1021/la504243r | Langmuir 2015, 31, 387−396