Research article Received: 30 May 2014,

Revised: 20 April 2015,

Accepted: 28 April 2015,

Published online in Wiley Online Library: 11 June 2015

(wileyonlinelibrary.com) DOI: 10.1002/jmr.2482

A surface acoustic wave sensor functionalized with a polypyrrole molecularly imprinted polymer for selective dopamine detection Naima Maouchea, Nadia Ktarib, Idriss Bakasc, Najla Fouratid*, Chouki Zerroukid, Mahamadou Seydouc, François Maurelc and Mohammed Mehdi Chehimic,e A surface acoustic wave sensor operating at 104 MHz and functionalized with a polypyrrole molecularly imprinted polymer has been designed for selective detection of dopamine (DA). Optimization of pyrrole/DA ratio, polymerization and immersion times permitted to obtain a highly selective sensor, which has a sensitivity of 0.55°/mM (≈550 Hz/mM) and a detection limit of ≈ 10 nM. Morphology and related roughness parameters of molecularly imprinted polymer surfaces, before and after extraction of DA, as well as that of the non imprinted polymer were characterized by atomic force microscopy. The developed chemosensor selectively recognized dopamine over the structurally similar compound 4-hydroxyphenethylamine (referred as tyramine), or ascorbic acid,which co-exists with DA in body fluids at a much higher concentration. Selectivity tests were also carried out with dihydroxybenzene, for which an unexpected phase variation of order of 75% of the DA one was observed. Quantum chemical calculations, based on the density functional theory, were carried out to determine the nature of interactions between each analyte and the PPy matrix and the DA imprinted PPy polypyrrole sensing layer in order to account for the important phase variation observed during dihydroxybenzene injection. Copyright © 2015 John Wiley & Sons, Ltd. Keywords: surface acoustic wave (SAW) sensor; molecularly Imprinted Polymer (MIP); dopamine; atomic force microscopy (AFM); DFT calculations

INTRODUCTION

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* Correspondence to: Najla Fourati, SATIE, UMR 8029, CNRS, ENS-Cachan, Cnam, 292 rue Saint Martin, 75003 Paris, France. E-mail: [email protected] a N. Maouche Laboratoire d’Electrochimie et Matériaux, Université Sétif -1, 19000, Algeria b N. Ktari Laboratoire Méthodes et Techniques d’Analyse, Institut National de Recherche et d’Analyse Physico-chimique, BiotechPole Sidi-Thabet, 2020, Ariana, Tunisia c I. Bakas, M. Seydou, F. Maurel, M. M. Chehimi Université Paris Diderot, Sorbonne Cité, ITODYS, UMR 7086 CNRS, 15 rue Jean Antoine de Baïf, 75205, Paris, Cedex13, France d N. Fourati, C. Zerrouki SATIE, UMR 8029, CNRS, ENS-Cachan, Cnam, 292 rue Saint Martin, 75003, Paris, France e M. M. Chehimi Université Paris Est, ICMPE, SPC, PoPI team, UPEC, 2-8 rue Henri Dunant, 94320, Thiais, France

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Dopamine (DA), which belongs to the catecholamine family of neurotransmitters, is crucially important in humans. It is produced in adrenal glands and several areas of the brain and is the most abundant of the catecholamines involved in brain– body integration (Jackowska and Krysinski, 2013). Low levels or practically complete depletion of DA in the central nervous system is implicated as a major cause of several neurological diseases, such as schizophrenia and Parkinson’s (Devlin, 1992). Various analytical techniques have been investigated to detect neurotransmitters in general and DA in particular: spectrophotometry (Berzas et al., 1997; Zhu et al., 1997; Cruz Vieira and Fatibello-Filho, 1998; Li et al., 2007), mass spectrometry (Hunt and Crow, 1978; Vuorensola et al., 2003; Loutelier-Bourhiset al., 2004), high performance liquid chromatography (Imperato and Chiara, 1984; Takeuchi et al., 2006; Muzzi et al., 2008) and ion chromatography (Guan et al., 2000; Zhang et al., 2012; Heidbreder et al.,2001). Although these methods are selective, they require sophisticated and expensive instrumentation and are time-consuming. Research has therefore been orientated towards the development of electrochemical biosensors because they can exhibit high temporal resolution, fast response, high sensitivity and low cost (Forzani, Rivas and Solís, 1995; Kaur et al., 2013; Li et al., 2014; Liu et al., 2014; MeijiaoLv et al., 2014). However, these sensors suffer from DA’s electroxidization, whose products may adsorb onto the electrode surface contaminating it (Hadi and Rouhollahi., 2012), and from the interference

of other electroactive neurotransmitters, mainly ascorbic acid (AA) (Wightman, 2006; Perry et al., 2009). To overcome these inconvenience, we have investigated surface acoustic wave (SAW) sensors to detect DA. In fact, besides being reliable, selective and sensitive, these devices are purely gravimetric; their output signals are thus only dependant on molecules recognition by the functionalized layers deposited on the SAW sensing area. SAW sensors are also label-free devices

N. MAOUCHE ET AL. able to determine kinetic parameters of a recognition process, providing thus real time additional information about the progress of a considered reaction (Zerrouki et al., 2010). In contrast to the extensive literature, describing the electrochemical detection of DA, only a few works report gravimetric sensing of this molecule. Pietrzyk et al. (2010) have functionalized the platinum electrode of an electrochemical quartz crystal microbalance, operating at 10 MHz, with a film of molecularly imprinted polymer (MIP) of poly[bis(2,2′-bithienyl)methane] bearing either a 3,4-dihydroxyphenyl or benzo-18-crown-6 substituent. The lower limit of detection was 10 nM DA, and the sensitivity was at about 123 Hz/mM. The optimum mean thickness of the MIP film was ∼ 220 nm. In a previous work (Fourati et al., 2014), we have functionalized the gold-sensing area of a SAW sensor with a thin film of cobalt phthalocyanine (CoPc). The developed chemsensor presents a sensitivity of 1.6°/nM (≈1600 Hz/nM) and has a low limit of detection of order of 0.1 nM. In the present study, we report the development of another reliable and selective DA chemsensor. The difference between the two works is related to the nature of the selective layer and the surface’s functionalization mode: a CoPc film deposited by molecular beam epitaxy in the previous study and an electropolymerized thin film of dopamine-imprinted polypyrrole (PPy) polymer in this one. In essence, molecular imprinting is a technique that involves the formation of molecular cavities in a synthetic polymer matrix that are complementary in a functional and structural character to a preselected template molecule or ion (Haupt et al., 2012; Lépinay et al., 2012; Malitesta et al., 2012; Nicholls et al., 2013). MIPs have been successfully applied in various biomedical, biotechnological and chemical applications, mainly because of their mechanical and chemical stability, easy control of film thickness and good reproducibility (Blanco-Lopez et al., 2004; Song et al., 2010; Verheyen et al., 2011; Gam-Derouich et al., 2012; Lattach et al., 2012; Li et al., 2012; Jo et al., 2013; Yuling et al., 2013; Whitcombe et al., 2014). Selectivity tests were performed with AA, which coexists with DA in a neural biological environment, and with 1,2 dihydroxybenzene (DHB) and tyramine (TA), which are DA structurally similar molecules. In recent years, various theoretical and computational models have been developed as tools to aid in the design of MIPs or to provide insight into the features that determine MIP performance (Levi et al., 2011; Nezhadali and Mojarrab., 2014). In our case, quantum chemical calculations, based on the density functional theory (DFT), have been investigated to confirm MIP affinity towards DA and to understand the nature of the interactions involved between pyrrole (Py) and the different investigated analytes in the absence and presence of water. Atomic force microscopy (AFM) was performed to characterize all the investigated thin films: the MIP (before and after dopamine extraction) and the non-imprinted Ppy polymer (NIP).

EXPERIMENTAL Chemicals

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Pyrrole, lithium perchlorate (LiClO4), (DA, AA, DHB, TA, phosphate buffered saline BioReagent pH 7.4 for molecular biology, methanol (MeOH), acetic acid (AcCOOH) H2SO4 (95%) and H2O2 (30%) were purchased from Sigma Aldrich. Py was purified before its use by filtering through basic alumina column and stored in dark

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under argon at
4 °C. Lithium perchlorate was used as a supporting electrolyte for electrochemical measurements. DA, AA, DHB and TA were used as received.

Computational approach Calculation of minimum structures, electronic and free energies, corresponding to the isolated and complex stable conformations, were carried out using the B3LYP density functional and6-311++G** basis set, which allows a better description of intermolecular hydrogen bonds and π–π interactions (Lee et al., 1988). The tight termination criteria optimization procedure (Berny algorithm), as implemented in Gaussian 09 (Gaussian, Wallingford, CT, USA), is used (Frisch et al., 2009). Binding energies ΔET-X were calculated as the difference between the energy of relaxed complex and the sum of energies from relaxed isolated systems: ΔE T
X ¼ E T
X
ðE T þ E X Þ where T ¼ pyrroleðPyÞ; bipyrroleðBiPYÞ or tripyrrole ðTPyÞ; and X ¼ DA; AA; TA or DHB: The basis set superposition error is not corrected here, so interactions energies are overstated. Solvent (water) effect is taken into account by polarizable continuum model with Kohn Sham united atomic topologies cavities as implemented in Gaussian 09 (Barone et al.,1997). Free energies of complex in solution were derived by mean of thermodynamic cycle applied to systems in gas phase with correction for solvation energies.

Instrumentation Electrochemical measurements Electrochemical measurements were performed with Bio-logic (Bio-logic Science Instruments, Claix, France) apparatus with Eci-Lab software. A conventional three-electrodes system was used with a steel grid as auxiliary electrode and a saturated calomel electrode as the reference one, the working electrode was the SAW sensing area (S = 22 mm2). All experiments were carried out at room temperature. Prior to any experiment, a drop of 50 μl of a piranha solution (98% H2SO4/30% H2O2 1:1 V/V) was deposited on the SAW sensor sensing area for 30 min to clean and activate it. The device was then copiously rinsed with deionized double distilled water and then with ethanol.

Gravimetric measurements The developed sensor consists of a dual delay line fabricated on a 36° rot lithium tantalate piezoelectric substrate. Interdigital transducer electrodes, the transmitter and receiver were of the same design and fabricated from evaporated chromium/gold (20 nm/80 nm) layers with a periodicity of λ = 40 μm, which corresponds to an operating frequency of about 104 MHz. A dual-delay-lines configuration was used to cancel viscosity, temperature and pressure fluctuations. A homemade pulse measurement system was used to monitor phase and/or amplitude shifts of the sensing line according to the reference one (Bergaoui et al., 2011).

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A SAW SENSOR FUNCTIONALIZED WITH A PPY-MIP FOR DOPAMINE DETECTION AFM measurements Atomic force microscopy measurements were carried out with a Nanosurf (Liestal, Switzerland) easyScan 2 Flex AFM system in the dynamic force mode, with cantilever’s resonance frequency of about 165 kHz. Commercially available tips [ACLA silicon AFM probes, from AppNANO (Mountain View, CA, USA)] with typical curvature radius of ≈ 6 nm, were used. The scanning of the different films was performed under ambient temperature. Electrosynthesis of polypyrrole imprinted dopamine Molecularly imprinted polymers were prepared by chronoamperometry (CA) electropolymerization using a DA template solution, which was 10
1 M in LiClO4 and 10
2 M in Py, as was described in a previously published paper (Maouche et al., 2012). Thin films of polypyrrole non-imprinted polymers (NIPs) have also been prepared under identical electrodeposition conditions but without DA. The choice of potentiostatic conditions for MIPs’ deposition was selected to avoid polymer reduction and DA oxydoreduction activity, which can result from potentiodynamic procedure altering thus MIPs’ formation. Moreover, CA technique offers the possibility to obtain, in an easy way, quantitative information and to control film growth (Sadki et al., 2000).

On the contrary, a high initial Py/DA ratio will dilute the imprints in the vicinity of the film, producing low current values. In this work, and following this optimization, a stochiometry of Py/DA = 10/1 was chosen. Figure 1b illustrates the effect of CA polymerization durations on the efficiency of dopamine detection (the analysed MIPs were prepared as follows: Py/DA = 10/1, DA immersion time = 20 min). Results show that a better detection was obtained for a 5 s electropolymerized MIP. The thickness of this film, estimated from charges values according to Panasyuk et al., (1999), was found equal to 54 nm. The last optimisation step concerns the follow-up of the immersion time efficiency of DA. A third series of MIPs has thus been considered (Py/DA = 10/1, electropolymerization time = 5 s). Results presented in Figure 1c (determined from measurements carried out with the SWV technique) show that from 5 to 20 mn, the current intensity increases with incubation time and that it remains constant beyond this value. A period of 20 mn is thus sufficient to saturate all recognition sites by DA molecules. According to these results, we have chosen the following parameters to synthesize MIPs: DA/Py = 1/10, CA duration = 5 s, DA incubation time = 20 min. Sensor performance evaluation

RESULTS AND DISCUSSION Film preparation and optimization studies The currents attributed to DA oxidation were measured by either cyclic voltametry (CV) or square wave voltammetry (SWV) (Maouche et al., 2012). The latter procedure was achieved using the following parameters: sweet rate = 100 mV/s, time = 10 ms, pulse amplitude = 50 mV, pulse step = 2 mV, potential varied from
0.2 V to 0.6 V versus SCE. To study the starting mixture stochiometry effects, we have considered five MIPs electropolymerized by CA as described earlier. An (MeOH/AcCOOH: 70/30 V/V) solution was used to extract the templates from the vicinity of the realized films. MIPs were then immersed in a solution of DA 10
6 M for a given time before its further detection. The plot of DA oxidation current versus the ratio of Py/DA shows that the maximum recaptured amount of DA is obtained with an initial ratio of Py/DA equal to 10 (Figure 1a). This result suggests that, contrary to literature (Urraca et al., 2004), low monomer/template ratios do not give performant MIPs, as DA molecules are not sufficient to form enough recognition sites. 30

30

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Dopamine recognition Phase variations versus time after the injection of DA at a low concentration (2.10
7 M) and at the saturation value (10
3 M) are plotted in

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Before checking the sensing properties of the MIP, DA molecules were extracted from the vicinity of the realized film. For this purpose, a continuous flow of a protic solution (MeOH/ AcCOOH:70/30 V/V) was pumped, using a peristaltic pump, over the sensing area of the SH-SAW sensor at a constant flow rate of 0.19 mL min
1. A follow up of phase variations versus time (Figure 2a) indicates that DA molecules were removed from the MIP matrix by breaking the hydrogen bonds linking DA to PPy (Dutta et al., 2011). Moreover, the combination of a microfluidic system with powerful extractor solvents (ES) reduces drastically the time of extraction (less than 10 min), compared with the 8 h and 12 h necessary to extract DA from the MIP with the Soxhlet method (using the same ES: MeOH/AcCOOH: 70/30 V/V) and NaOH 10-2 M, respectively (Pietrzyk et al., 2010). A continuous phosphate buffered saline solution flow was then pumped before DA injection. Measurements were done at 25 °C, and signals were allowed to stabilize prior to any injection.

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Figure 1. Plot of dopamine (DA) oxidation current variations versus (a) pyrrole/DA molar ratio in a preparation mixture, (b) chronoamperometry polymerization time for molecularly imprinted polymer preparation; (c) immersion time for dopamine detection. Currents values were obtained by cyclic voltametry for (a) and (b) and by square wave voltammetry for (c).

N. MAOUCHE ET AL.

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Figure 2. Gravimetric response of the surface acoustic wave-coated molecularly imprinted polymer substrate:(a) when exposed to the MeOH/AcCOOH
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3 extraction solution, (b) after the injection of a solution of dopamine (DA) 2.10 M (c) after the injection of a solution of DA 10 M.

Figures 2b and 2c, respectively. In both cases, DA injection leads to a significant decrease of phase values, indicating that the functionalized cavities of the MIP have recognized the further analytes. The same gravimetric tests have been carried out with a SAW transducer coated with a thin NIP. No phase shifts have been recorded, indicating that the sensing of DA molecules by the MIP film is because of the imprinted cavities, which serve as specific recognition elements. Sensitivity of the developed MIP-SAW sensor, calculated from the slope of the phase/concentration curve, was found equal to 0.55°/mM (≈550 Hz/mM). This value is approximately 4.5 times higher than that by Pietrzyk et al. (2010), indicating that the

PPy-MIP-SAW developed sensor is more sensitive to DA, thanks mainly to a higher operating frequency. Analysis of the sensor’s response indicates a quasi-linear phase variations versus DA concentrations until a DA saturation value of 10
3 M. The MIP-SAW detection limit was estimated at 10 nM, a value inferior to that of 26 nM, characteristic of living systems (Jackowska and Krysinski, 2013). The use of the present system in disease diagnosis is therefore possible in further works. Figures 2b and 2c highlight also the fact that the recognition kinetic of the analytes by the MIP is DA concentration-dependent. Fits of phase variations curves, with an exponential decay function, have permitted to estimate time constants to (3075

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Figure 3. Atomic force microscopy images of a 5 s electropolymerized molecularly imprinted polymer before dpoamine extraction (a) 100 μm scan in two-dimension (b) 100 μm scan in three-dimension (c) a zoom on a ring and (d) its corresponding height profile.

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J. Mol. Recognit. 2015; 28: 667–678

A SAW SENSOR FUNCTIONALIZED WITH A PPY-MIP FOR DOPAMINE DETECTION ± 15 s) and (75 ± 2 s) for lower and higher concentrations, respectively. A possible explanation for this behaviour is that for low DA concentrations, target molecules bind progressively to the diverse imprints of the MIP, starting from the surface and going progressively in the bulk, requiring thus a rather long time (≈2 h). For high DA concentrations, the majority of surface imprints are occupied instantly after DA injection. The ‘top’ of the MIP is thus saturated, reducing therefore the possibility of DA access into the vicinity of the MIP. Consequently, for a DA concentration of

10
3 M, signals of phase are stabilized 10 mn after DA injection, which corresponds to the tenth of the necessary time when DA concentration is equal to 2.10
7 M. Comparison between Figures 2a and 2c shows that phase variations are more important in the case of DA template extraction than its further recognition by the MIP. This difference may be attributed to two effects, which can have separate or synergetic consequences: (i) the deeper recognition sites are less accessible; consequently, they do not participate to the detection process

Figure 4. Atomic force microscopy images of the 5 s electropolymerized molecularly imprinted polymer before extraction (a) 1 μm scan and (b) its corresponding height profile (cross section).

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Figure 5. Atomic force microscopy images of the 5 s electropolymerized molecularly imprinted polymer after extraction (a) 100 μm scan in two-dimension (b) 100 μm scan in three-dimension (c) a zoom on a ring and (d) its corresponding height profile (cross section).

N. MAOUCHE ET AL. and (ii) extraction degrades partially both DA imprints and the MIP morphology. Films topographies have thus been investigated by means of AFM. Before extraction, the large-scan AFM images show some particular shapes with rings like, having about 230 nm height and an apparent diameter of 15 μm (Figure 3). The rms roughness Sq of the film is of 87.3 nm for spatial frequency range 10
2–10 μm
1. The maximum surface peak height Sp and maximum surface valley depth Sv are about 1.67 μm and 433 nm, respectively. For the small scan, that is, a spatial frequency range 10–103 μm
1, the images show a granular aspect associated to a lower rms roughness of 42.6 nm (Figure 4). After extraction, the large-scan AFM images show that the rings like disappear and that the rms roughness increases drastically (255.3 nm). Sp, and Sv values are about 1.75 μm and 853 nm,

respectively. By comparing these statistical parameters with those before extraction, we noticed an increase of Sq and Sv values of 192% and 98%, respectively (Figure 5). The difference is also visible for the small scan (Figure 6), as we observe an increase of both particle size and rms roughness (57.8 nm). The morphological differences, highlighted by AFM images, between the ‘extracted’ and ‘non-extracted’ MIPs suggest that the first extraction causes a removal of both DA templates from the vicinity of the polypyrrole matrix, and some polymer chains which were not strongly attached to the MIP. AFM investigations suggest also that for imprinted polymers, the target ‘foot print’ has to be close to the surface for high accessibility; that is, the film must be as thin as possible to enhance sensitivity (Blanco-Lopez et al., 2004; Suryanarayanan et al., 2010).

Figure 6. Atomic force microscopy images of the 5 s electropolymerized molecularly imprinted polymer after extraction (a) 1 μm scan and (b) its corresponding height profile (cross section).

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Figure 7. Atomic force microscopy images of the electropolymerized non-imprinted polypyrrole polymer (a) 100 μm scan in two-dimension (b) 100 μm scan in three-dimension (c) 1 μm scan in 3D and (d) its corresponding height profile (cross section).

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J. Mol. Recognit. 2015; 28: 667–678

A SAW SENSOR FUNCTIONALIZED WITH A PPY-MIP FOR DOPAMINE DETECTION Surface characterization of the NIP film has also been carried out. AFM images (Figure 7) show an obvious difference, compared with MIP, at large scale and particularly for small scan sizes as the granular aspect disappears, and a relatively continuous structure takes place. The rms roughnesses were found equal to 113.4 nm and 46.4 nm for large and small scans respectively. For the large scan, Sp and Sv values, equal to 1.67 μm and 313 nm, respectively, are comparable with those characterizing the non-extracted MIP. Selectivity tests Selectivity tests were first made with AA, which largely coexists with DA in brain tissue, and which is the main interfering agent in electrochemical sensing, because it has an overlapping oxidation potential on the solid electrodes, making very difficult a direct detection of DA (Zare et al., 2006). Figure 8a shows that the injection of AA (2.10
6 M) causes phase values to decrease. However, compared with DA 2. 10
7 M (Figure 2b), AA output signals are lower of about one order of magnitude. Additionally, the presence of oscillations indicates that the binding is not very strong. Injection of 10
3 M of AA solution causes a comparable phase shift with that of 2.10
6 M (Figure 8b), which means that the recognition is not concentration-dependent, contrarily to the DA one (Figures 2b and 2c). Two pertinent parameters can thus been used to differentiate between DA and AA detection: phase values and the shape of the temporal variation of phase curve. Selectivity tests were also performed with TA and DHB. No significant phase shifts were recorded for concentrations lower than 10
3 M. Percentages of phase variations after the injection of a 10
3 M solution of DA, AA, TA and DHB are presented in Figure 9. The low percentages obtained in the cases of TA and AA indicate that the developed MIP-SAW does not recognize these molecules. This is because the imprinted site should hold the ‘spatial advantage’ based on the memory effect of the MIP formation, which should be selective to DA (Dutta et al., 2011). In the case of DHB, the gravimetric output signal was important (75% of that of DA) in spite of the fact that its molecular structure is less similar to the DA than TA. Quantum chemical calculations, based on the DFT, have thus been performed to understand the nature of the involved interactions between DA, AA, TA and the monomers of the MIP matrix, in one hand,

Figure 9. Percentage of phase variation for dopamine, dihydroxybenzene, ascorbic acid and tyramine molecules. All the analytes were injected at the
3 same concentration of 10 M.

and to comprehend the significant phase variation following the injection of DHB, in the other hand. Theoretical selection of templates As reported in previous studies (Nagy et al., 2005), the primary amines DA and TA are in their protonated forms at pH = 7.4 (our buffer medium). We have begun by searching the most stable conformations of protonated DA, AA, DHB and protonated TA, by applying a scan with a pitch of 10° in the range from
180° to 180°, on the dihedral angle, which defines the tail position relative to the ring. The most stable conformations correspond to a dihedral angle of 54°, 53° and
60° for DA, TA, and AA, respectively (Figure 10). For TA and DA, the stabilization lies in the electrostatic interaction between protonated amine group and the aromatic ring. These conformations were selected to complex with the matrix. Figure 11 represents the most stable structures that are formed between Py and the investigated molecules. The interaction energies in the solvent are equal to
77.1,
37.8,
70.7 and
32.6.5 kJ/mol for DA, AA, TA and DHB, respectively. These values are close to that found for hydrochlorothiazide (HCT) and Py interactions (Nezhadali and Mojarrab, 2014). They

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Figure 8. Phase shifts versus time after the injection of ascorbic acid (AA) solution: (a) [AA] = 2.10

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Figure 10. Optimized conformations of: (a) protonated dopamine, (b) ascorbic acid, (c) protonated tyramine, (d) dihydroxybenzene, (e) bipyrrole and (f) pyrrole. Carbon atoms are in grey, oxygen in red, nitrogen in blue and hydrogen in white.

Figure 11. Optimized geometries for the most stable complexes between pyrrole and (a) dopamine, (b) ascorbic acid, (c) tyramine and (d) dihydroxybenzene molecules.

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are also of the same order of magnitude than those corresponding to the interaction between indole and selected monomers (Liu et al., 2014). In the case of DA and TA, the interaction with Py is because of an electrostatic interaction (NH+3 –π) between the protonated amine group and the Py aromatic ring. The

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equilibrium distances between the groups are 2.57 and 2.22 Å for DA and TA, respectively. In addition to this interaction, a weak hydrogen bond (N–H…O–H = 2.23 Å) appears between the monomer and DA template. The kind of interaction is different for AA, where two types of intermolecular bonds take place. The first one is a

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A SAW SENSOR FUNCTIONALIZED WITH A PPY-MIP FOR DOPAMINE DETECTION (NH…O¼C) hydrogen bond and the second one is an ΟΗ–π interaction between the OH alcohol group and Py aromatic ring. The latter is less important than that existing between the positive charge and aromatic ring interaction as we found for DA or TA and could be significantly affected by steric hindrance, particularly when the polymer is well formed. In order to take into account the conformational strain of the polymer, we investigated the bipyrrole (biPy) interaction with the considered analytes. The most stable conformations of bipyrrole and analytes complexes are presented in Figure 12. Calculations show an increase of interaction energies in solvent (water) for all the investigated analytes and that biPy–DA is the

most stable complex. The new interaction energies values were found equal to
96.5,
56.5,
79.7 and
31.9 kJ/mol for DA, AA, TA and DHB, respectively. Figure 12 highlights also the fact that both (NH+3 –π) and (NH…OH) bonds are shorter than those of Py-DA, indicating thus a greater molecular interaction between BiPy–DA system. It is also important to note that this strong interaction does not affect biPy dihedral angle, which derived with only 5° from its original value. For the most stable BiPy-AA complex, one C = O….HN (2.04 Å) hydrogen bond and one π– π interaction take place with the Py aromatic ring. The latter flattens the biPy and changes significantly its dihedral angle, which derives of about 20° from

Figure 12. Optimized geometries for the most stable complexes between bipyrrole (left) and tripyrrole (right) and dopamine (a), ascorbic acid (b), tyramine (c) and dihydroxybenzene (d) molecules.

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Figure 13. Top: Calculated interaction energy between pyrrole (a), bipyrrole (b) tripyrrole (c) and the different analytes. Bottom: normalized interaction energy per molecular volume unit for pyrrole (d), bipyrrole (e) and tripyrrole (f).

N. MAOUCHE ET AL. original value. As observed for Py, the steric hindrance affects significantly the involved interactions. For the most stable BiPy-TA, the interaction is similar to that observed in Py-TA. However, the protonated amine group seems to interact with both the two pyrollic rings. The interatomic distance increases in line with the interaction energy. For the BiPyDHB complex, the biPy conformation changes in order to form two hydrogen bonds of the same nature and different force NH…OH (2.08 and 2.17 Å) with the DHB molecule. Finally, and in order to be more close to the polymer structure, we have analyzed the interaction between both biPy and Py (triPy) and the different analytes. The solvation interaction energies increase up to
158.7,
94.4,
105.5 and
66.2 kJ/mol for DA, AA, TA and DHB, respectively. These increases are related to the new electrostatic or hydrogen bonds, which take place between monomers and polymer templates as shown in Figure 12. The affinity monomers for the analytes can be linked to several parameters: molecular structures, force of interaction between the molecules, solvent effects and the molecular density (molecules per volume unit). Considering molecular tridimensional structures, the calculated volume at B3LYP/6-311 + G* level for DA, TA and AA and DHB were found to be equal to 109.93, 114.35, 102.39 and 55 cm3/mol, respectively. These results indicate that the surface coverage rate must be considered in order to compare the theoretical calculations and experimental measurements. In Figure 13, we have represented both theoretical interaction energy and interaction energy per volume unit. One can observe that by taking into consideration the molecular size, DHB interaction energy becomes more important and close to that of DA. These theoretical results, based on interaction energies per volume unit, are in a good agreement with experimental observations, in particular for the trimer, and permit to explain the important phase shift recorded after DHB injection.

CONCLUSION Thin layers of molecularly imprinted polypyrrole were electrodeposited on the gold sensing area of a 104 MHz SAW sensor. Parameters influencing film properties, such as Py/DA ratio, polymerization time and immersion duration, were optimized by electrochemical measurements. Monitoring phase variations versus time indicate that the developed sensor presents a sensitivity towards DA of 0.55°/mM and a detection limit of order of 10 nM, associated to high selectivity in comparison with AA and TA. Quantum chemical calculations, based on the DFT were performed to understand the nature of the involved interactions between the different templates and Py, biPy and triPy of the MIP matrix. In all the cases, the corresponding complex with DA was found to be the most stable among all investigated systems. In addition, DFT calculations suggest that the important phase signal obtained in the case of DHB can be correlated with the interaction energy/molecular volume of the analyte. By weighting the computed interaction energies per molecular volume for each analyte, we found a good agreement between experimental investigations and calculations for triPy. TriPy is therefore sufficient to represent the Ppy matrix. This work highlights also the importance to combine theoretical and experimental results and demonstrates the need to take into account the surface coverage rate in studies involving MIPs.

Acknowledgement Quantum chemical calculations were performed using HPC resources from GENCI-[CCRT/CINES/IDRIS] (Grant 2015-[c2015087006]).

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