Combinatorial Chemistry & High Throughput Screening, 2010, 13, 000-000 1

1386-2073/10 $55.00+.00 © 2010 Bentham Science Publishers Ltd.

Miniaturization and Validation of the Ellman’s Reaction Based Acetylcholinesterase Inhibitory Assay into 384-Well Plate Format and Screening of a Chemical Library

P.P. Järvinen*,1,2, A. Fallarero3, S. Gupta4, C.G. Mohan4, A.I. Hatakka2 and P.M. Vuorela*,3

1Division of Pharmaceutical Biology, Faculty of Pharmacy, University of Helsinki, Viikinkaari 5E, P.O. Box 56, FIN- 00014, Helsinki, Finland 2Department of Applied Chemistry and Microbiology, Faculty of Agriculture and Forestry, University of Helsinki, Viikinkaari 9, P.O. Box 56, FIN- 00014, Helsinki, Finland 3Division of Pharmacy, Department of Biochemistry and Pharmacy, Faculty of Mathematics and Natural Sciences, Åbo Akademi University, Tykistökatu 6A, FIN- 20520, Turku, Finland 4Centre for Pharmacoinformatics, National Institute of Pharmaceutical Education & Research (NIPER), S.A.S. Nagar, Mohali, Phase X, 160062 Punjab, India

Abstract: The aim of this study was to screen for acetylcholinesterase (AChE) inhibitors from a large chemical library of commercially available compounds. For this purpose, the Ellman’s reaction based assay was miniaturized into 384-well plate format, and two modifications of the kinetic protocol were studied with the aim of developing a rapid screening platform that could ensure high efficiency in finding true hits. It was proven that when starting the kinetic reaction by addition of the substrate, better assay performance was achieved and more practical benefits obtained. Using the optimized automated protocol, a chemical library of 56320 compounds was screened. A total of 350 positive hits were identified and their IC50 calculated. Three highly active compounds were identified with IC50 values close or even lower to physostigmine (< 0.1 μM). The activity towards butyrylcholinesterase (BChE) of these three most active hits was also evaluated. The most active hit (IC50(AChE) = 0.019 M), was identified as a new inhibitor, belonging to ChemDiv chemical library: (N-[3-(3,5-dimethyl-1-piperidinyl)propyl]-5-ethyl-2-methyl-8-oxo-thieno[2',3':4,5]pyrrolo[1,2-d] [1,2,4] triazine-7(8H)-acetamid), with no other biological activities reported until now. The interactions of this hit with both cholinesterases were further analyzed using computational docking studies. To our knowledge, this is the largest published screening campaign of commercially available compounds that has focused on finding new AChE inhibitors. The miniaturized 384-well plate format of the Ellman’s method was proven to be robust and to perform reliably.

Keywords: Acetylcholinesterase, butyrylcholinesterase, inhibition, high-throughput screening, miniaturization, Ellman's method.

1. INTRODUCTION

Alzheimer's disease (AD) is the most common form of dementia. The ultimate goal of research is to find disease-modifying agents (i.e. antiamyloid, neuroprotective and restorative) with ability to alter the pathophysiology of the disease and to cause a significant reduction in its progression rate [1]. However, in spite of the tremendous efforts invested to understand the mechanisms behind the disease and further to develop these novel disease- modifying treatments, cholinesterase inhibitors remain the first-line standard therapy for symptomatic relief of mild to moderate AD, accounting for 3 out of the 4 drugs currently approved for the treatment of the disease [2, 3]. Interest in cholinesterase inhibitors has increased due to findings supporting cholinesterase’s involvement in -amyloid peptide fibril formation during AD pathogenesis [4-6]. In fact, several

*Address correspondence to this author at the Division of Pharmacy, Department of Biochemistry and Pharmacy, Faculty of Mathematics and Natural Sciences, Åbo Akademi University, Tykistökatu 6A, FIN- 20520, Turku, Finland; Tel: +358 2 215 4267; Fax: +358 2 215 4010; E-mail: pia.vuorela@abo.fi.

types of acetylcholinesterase (AChE) inhibitors have been shown to inhibit AChE-induced A aggregation [7-9].

Different approaches to screen novel AChE inhibitors can be found in the literature. Guided by the fact that potent acetylcholinesterase inhibitors have been obtained from plants (i.e. physostigmine, galanthamine), screening studies of natural preparations or chemical libraries based on natural compounds have been conducted by several groups (e.g., [10-13]). Another strategy has been the in silico virtual screening of large chemical libraries which has lead to the identification of potent hits followed by the experimental assessment of their activities (e.g., [14-16]). In all those cases described above, a reduced number of compounds or preparations have been experimentally tested at once (< 200), indicating that previously conducted screenings on cholinesterase inhibitors have been low throughput in scale. This is a particularly contrasting situation if we compare to the large number of chemicals that are routinely screened against other relevant protein targets, in academic as well as industrial settings (e.g., [17]).

The first obvious concern when attempting to conduct screening approaches is availability of the methods. For the

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determination of AChE inhibitory activity, several methodologies have been described [18]. Among these, the assay based on the Ellman’s reagent chromogenic probe has been extensively applied (e.g., [13, 19-24]). Since the publication in 1961 [25], this method has become the methodological keystone of AChE quantification, which has been attributed to the simplicity and accuracy of the assay. Some limitations have been eventually identified, for example the fact that it is a discontinuous method, does not have a low detection limit and is often subject to background perturbations. This has consequently motivated various efforts towards the development of other colorimetric, fluorescent or chemiluminescence probes. For example, the detection limit has been improved by using a 1,2-dioxetane chemiluminescent probe [26]. Also, fluorescent alternatives to Ellman’s reagent [27] as well as continuous fluorometric or colorimetric assays have been published [28, 29]. However, none of these recent methods lack of problems (i.e. they are highly laborious; reagents have poor solubility in aqueous solutions) and none of them have been as extensively validated as the traditional Ellman’s method. In fact, in a recent methodological study, Di Giovanni et al. [13] concluded that Ellman’s reaction based method in 96-well plate format can be regarded the effective and reliable method of choice within screening approaches.

In this project, we sought to utilize this traditional Ellman’s reaction based assay to conduct a higher throughput screening study for AChE inhibitors. To deal with a large chemical library (> 56,000 compounds), the assay is needed to be performing in an automation-friendly, fast way, compatible with higher density well-plate formats. Similarly, strategies to cope with the limitations of the Ellman’s method (e.g., background perturbations) are needed to be taken. Accordingly, the aims of this study were to miniaturize the Ellman’s reaction based assay into 384-well plate format and to use the miniaturized platform for the screening of a chemical library containing 56,320 commercially available compounds. During the assay development stage, two modifications of the Ellman’s reaction based assay were studied, in which the reaction was initiated either by adding the enzyme or the substrate. The final goal was to provide a fast platform which is able to ensure high assay robustness and reliability in finding true hits. Three compounds were found with IC50 values close or even lower to the known acetylcholinesterase inhibitor, physostigmine (IC50 < 0.1 M). These identified hits were additionally followed-up in order to establish their target selectivity in vitro.

2. EXPERIMENTAL METHODS

2.1. Chemicals

Acetylcholinesterase (EC 3.1.1.7, type VI-S from electric eel), butyrylcholinesterase (EC 3.1.1.8, from horse serum), acetylthiocholine iodide (ATCI), S-butyrylthiocholine chloride (BTCCl) and 5,5’-dithio-bis(2-nitrobenzoic acid) (DTNB, Ellman’s reagent) were purchased from Sigma-Aldrich (St. Louis, MO, USA) while physostigmine was from Fluka Chemie (Buchs, Switzerland). Tris-HCl, MgCl2•6H2O and bovine serum albumin (BSA, Albumin fraction V from bovine serum) were obtained from Merck (Darmstadt, Germany) and NaCl from Farmitalia Carlo Erba

(Milano, Italy). Compounds used during the screening campaign belonged to the commercial libraries of ChemDiv Inc. (San Diego, CA, USA), ChemBridge Corporation (San Diego, CA, USA) and Tripos (St Louis, MO, USA).

2.2. Miniaturization of the AChE Microplate Assay into

384-Well Plate Format

The AChE assay based on Ellman’s reagent was modified into 384-well plate format to study the AChE inhibition [19, 25]. In this assay, AChE catalyses the hydrolysis of acetylthiocholine iodide (ATCI) and the resultant product, thiocholine, reacts with the Ellman’s reagent (DTNB) to generate a coloured anion that is detected spectrophotometrically. ATCI is a pseudosubstrate of AChE, whose rate of hydrolysis almost equals that of acetylcholine itself. In our experiments, final concentrations of DTNB, ATCI and AChE on the assay plates were 1.36 mM, 2.7 mM and 0.02 U/mL, respectively. DTNB was dissolved in 50 mM Tris-HCl buffer (pH 8) containing 0.1 M NaCl, and 0.02 M MgCl2•6H2O. AChE was dissolved in 50 mM Tris-HCl buffer (pH 8) containing 0.1 % (w/v) BSA while ATCI was dissolved in water. The total volume in each well in 384-well plates was 55 L. The absorbance changes were detected at 405 nm using a FLUOstar fluorometer (BMG Labtech, Germany). The plates were measured three times: one background measurement and two measurements after starting the reaction. To start the reaction, two different approaches were utilized. The reaction was initiated either with the enzyme (AChE) or the substrate (ATCI).

2.3. Automated Screening of the Chemical Library in 384-Well Plate Format

During the automated screening of the chemical library, the reaction was initiated by the addition of the substrate. A mixture of DTNB and AChE solutions (2.5:2) was dispensed (45 μl) into the assay plates using an automated 96 channel head (Biomek FX, Beckman Coulter, Fullerton, CA, USA). A pin tool was used to transfer chemicals from the library plates (concentration of 1 mM) to the assay plates, in which the final concentration of compounds was estimated to be 2.5 μM. Then, the reaction was started with the substrate ATCI (10 μL, final concentration 2.7 mM). In all screening plates, a positive control (physostigmine) was included. The effect on the AChE activity registered for each compound was compared to the solvent (negative) control and expressed as inhibition percentage. The hit limit, estimated for each plate separately, was set at 4 SDs below average of the plate. All the compounds found positive in the primary campaign (350) were later subjected to a concentration-response study aimed to establish IC50 values. For that, cherry picking was performed in automated conditions (Hamilton Star robotic workstation, USA) and serial dilutions within 0.001- 10 M concentration range were performed.

2.4. Follow-Up Studies of the Most Active Hits

The butyrylcholinesterase inhibitory effect produced by the three most active hits was measured using the same concentration range (0.001- 10 M). For that purpose, the method described in Fallarero et al. [30] in 96-microtiter well plates was utilized. The occurrence of interactions

Miniaturization and Validation of the Ellman’s Reaction Combinatorial Chemistry & High Throughput Screening, 2010, Vol. 13, No. 3 3

between the most active hit and both cholinesterases were also assessed through an in silico approach involving docking studies. Molecular docking was performed using the FlexX module in the SYBYL7.1 software, and binding mode analysis was made using the ligand-receptor interaction module of MOE software (Chemical Computing Group, Canada).

2.5. Statistical Analysis

The distributions of the controls data (maximum and minimal signals) were studied using Kolmogorov-Smirnov (KS) test, to detect any deviations from a Gaussian distribution. Assay quality was also evaluated utilizing statistical parameters: screening window coefficient (Z' factor), signal-to-background (S/B) [31] and signal-to-noise (S/N) ratios [32]:

Z’ = 1 [(3 SDs+3 SDb) / |Xs Xb|],

S/B = Xs / Xb and

S/N = (Xs Xb) / (SDs2+SDb

2)1/2

where: Xs; SDs corresponded to average and standard deviation of the maximum AChE activity signal i.e. absorption detected at the second measurement point in solvent control wells after adding the substrate and Xb; SDb corresponded to average and standard deviation of the background signal i.e. the absorption at the first measurement point in solvent control wells after adding the substrate. Acceptance limits for the three parameters were defined and used to monitor changes in assay performance during the screening campaign. All the data processing was conducted using Microsoft Office Excel 2003 (Microsoft, Redmond, WA, USA) and GraphPad Prism v. 4.0 (GraphPad, La Jolla, CA, USA).

3. RESULTS AND DISCUSSION

3.1. Assay Miniaturization into 384-Well Plate Format

Ellman’s reaction based assay is one of the most widely used methods for assessing acetylcholinesterase activity [33]. The first objective of this project was to attempt the miniaturization of this assay into the 384-well plate format to be able to conduct a larger screening campaign involving more than 56,000 compounds.

As part of the optimization process, the performance of the two existing variants of the protocol was compared. In their original report, Ellman et al. [25] showed that accurate measurements of the enzyme activity could be obtained either by starting the reaction with the enzyme (what they called “general method”) or by starting the reaction with the substrate (what they used when measuring AChE activity in blood or tissue samples). One of their important observations was that the substrate could be hydrolyzed at an appreciable rate without the enzyme and therefore a non-enzymatic hydrolysis should be measured and subtracted when the reaction was made according to the first variant.

The comparison of these two assay variants in 384-well plate format using statistical parameters that characterize screening assays was then conducted (Fig. 1 and Table 1). As seen in Fig. (1), the minimal and the maximal signals in

both assay variants followed a binomial distribution, which theoretically permitted the calculation of Z’, S/B and S/N parameters [31]. Obtained parameters (Table 1) allowed concluding that both assays can be used for screening procedures (Z’ > 0.5). However, after a detailed examination of both alternatives, some differences were detected. When starting the reaction with enzyme (Fig. 1, dashed line) smaller signal window was registered. This was mainly attributed to the increase in the minimal (background) signal, associated to the occurrence of non-enzymatic hydrolysis of the substrate before the enzyme is added to start the enzymatic reaction. In contrast, when starting the reaction with the substrate (Fig. 1, solid line), reduction on the minimal signal values occurred and this therefore improved the signal window of the assay. Similarly, all the calculated statistical parameters improved when the reaction was started by the substrate (second variant of the assay) (Table 1). Thus, if the first variant is used, namely if the substrate and the DTNB are mixed in the beginning of the assay performance, the formation of the end product could start before initiation of reaction with the enzyme. In this case, at least four measurements would be needed to subtract the rate of spontaneous hydrolysis: two measurements before adding the enzyme and two after that. Thus, in order to reduce the measurement steps (to three) the reaction was started with the substrate only after which the formation of the end product started.

Fig. (1). Frequency distributions of the maximal and minimal signals using the two variants of the kinetic assay (reaction started with AChE: dashed line; reaction started with ATCI: solid line). Values were obtained from three plates (n=72).

Table 1. Statistical Parameters Z’, S/B and S/N Calculated

for the Two Variants of the Kinetic Assay

Statistical Parameters Assay Variants

Z’ S/B S/N

Reaction initiated with s ubstrate (ATCI)

0.9 ± 0.02 18.5 ± 1.7 40.8 ± 5.7

Reaction initiated with enzyme (AChE)

0.8 ± 0.03 6.0 ± 0.2 22.2 ± 6.0

The reaction was initiated either with the enzyme (AChE) or the substrate (ATCI). Values are expressed as mean ± SD, calculated from three plates (n=24).

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The second reason for choosing the second variant of the assay was the fact that we could avoid the dispensing of small amount of foaming enzyme solution with the dispenser in the microplate reader. In that regard, accuracy and repeatability in dispensing microliters of aqueous substrate solution was observed to be better. This second variant was also repeatable and stable regardless of the variations on the times before starting the reaction with the substrate (data not shown). When conducting a large screening campaign (with tens of plates a day), it is difficult to maintain a constant time between addition of reagents. In this case, the pre-incubation of the enzyme with the DTNB for different time periods (instead of the substrate, which could then be spontaneously hydrolyzed) had no negative impact on the stability and robustness of the measured signal.

3.2. Automated Screening of a Commercial Chemical Library in 384-Well Plate Format

Using this second variant of the assay in 384-well plate format, a library of 56,320 compounds was screened. An overall hit rate of 0.67 % was obtained, and a total of 350 positive hits were followed up and their IC50 calculated, as it is presented in Fig. (2) (grey bars). This large amount of data has been further exploited to understand the structural- activity relationships of AChE inhibitors and improve the performance of QSAR programs (Gupta et al. unpublished results). Most of the primary hits were found to display IC50 values between 1 and 10 μM.

Fig. (2). Comparison of hit rates (according to potency categories) in kinetic and endpoint measurements. Numbers of hits identified in the kinetic approach and endpoint measurements are indicated with grey and white bars, respectively.

To critically evaluate this screening approach utilizing three point kinetic measurements, inhibition percentages were also calculated for the hits using only the endpoint of the measurement (Fig. 2; white bars). Kinetic multi-point measurement could be considered laborious and time

consuming for large throughput screening, but over-simplified assay set-up (in this case single endpoint measurement) can influence the interpretation of the inhibition potency of a compounds and mislead to false-negative results. All the hits in the categories “IC50 < 0.1 μM” and “1 μM > IC50 0.1 μM” defined in the kinetic measurements would also have been identified as hits in the endpoint measurement. However, as much as 24.6 % of the hits in the lower potency categories would not have been identified using the endpoint measurement. The most potent false-negative hit would have been a compound that displayed an IC50 of 1.35 μM. These findings confirm the importance of utilizing a kinetic approach when Ellman’s assay is the selected screening platform, as it is more accurate than the single endpoint approach, especially for the less potent compounds. From the practical viewpoint, time could have been saved by choosing endpoint measurement, but the quality of the hit detection would have then been compromised.

The three most active hits were identified (compounds 1, 2, 3) (Fig. 3), which displayed IC50(AChE) values of 0.063; 0.019 and 0.069 μM, respectively, within the same range of IC50 value obtained for the known AChE inhibitor, physostigmine (0.04 μM) at the used substrate concentration of 2.7 mM. Two of these compounds were new (compounds 2, 3) and the third turned out to be the known AChE inhibitor, tacrine (compound 1), which unexpectedly served as a reference molecule. The effect at different concentrations was also studied in the assay format in which the reaction was started by adding the enzyme. Potency of the three best hits was similar, and thus confirmed to be independent of the assay variant.

N

N

S

NN

NO

O

N

NH2

N

N

N

NH

O

NS

O

Compound (1)

Compound (2)

Compound (3)

Fig. (3). Chemical structures of the most potent compounds. All three compounds belong to ChemDiv compound collection: compound (1) (tacrine, ID: C066-2825); compound (2) (ID: C785-3067) and compound (3) (ID: E017-0008).

Miniaturization and Validation of the Ellman’s Reaction Combinatorial Chemistry & High Throughput Screening, 2010, Vol. 13, No. 3 5

The selectivity of the cholinesterase inhibition was studied for these three most potent hits. Tacrine was more potent BChE inhibitor (IC50(BChE) = 0.0108 M) in agreement to previous literature reports (e.g., SI = 0.18 [34] and SI = 0.21 [35]). On the contrary, compound (2) (C785-3067) and compound (3) (E017-0008) were more potent AChE inhibitors displaying only moderate BChE inhibition with IC50(BChE) values of 13.27 M and 23.58 M, respectively. The literature provides diverse results and viewpoints concerning the benefits of selectivity of inhibition. FDA-approved cholinesterase inhibitors vary in selectivity since rivastigmine is a non-selective cholinesterase inhibitor and galanthamine and donepezil are selective AChE inhibitors [5]. Based on the clinical data published so far, there is no direct evidence of important differences in efficacy in mild to moderate AD between these three FDA-approved compounds, but more data are required to make any final conclusions [36].

Computational studies were performed to get more information on the possible interactions operating between the compounds (1, 2 and 3) and both cholinesterases. AChE and BChE share 65% sequence homology and the overall structures of the two are similar with the active site, a middle gorge interaction site and the peripheral anionic site (PAS) [37]. The docking analysis confirmed that the compounds (1, 2 and 3) are able to bind to both cholinesterases.

The most potent hit (compound 2), identified as: N-[3-(3,5-dimethyl-1- piperidinyl)propyl]-5-ethyl-2-methyl-8-oxo-thieno [2',3':4,5] pyrrolo [1,2-d] [1,2,4] triazine-7(8H)-acetamid was studied in deeper detail. This hit apparently binds at the entrance of the gorge site of AChE, due to the -

stacking interactions between thiophene and pyrrole ring of the compound (2) and aromatic Trp279 in AChE (Fig. 4). In addition, hydrogen bonding interactions can occur between the carbonyl group of compound (2) and the amide (N-H) group of Phe288 at the same AChE site. Compound (2) apparently does not make any contact at the PAS of the BChE. The ionizable nitrogen in the piperidine ring of compound (2) and the hydroxyl group of Tyr121 in the middle of the gorge site of AChE form a cation- interaction. This type of interaction is not observed in BChE which could also help explaining the observed selectivity of compound (2) towards AChE. AChE is able to accelerate amyloid formation through PAS especially the site of surface loop between residues 275-308 [6, 38, 39]. Proposed interaction of compound (2) with Trp279 in AChE suggests the possibility to interfere with amyloid fibrillogenesis in addition to inhibit the catalytic function of the enzyme.

The search for prior bioactivity reports on cholinesterase inhibition of compound (2) did not render results, suggesting that this molecule is a new inhibitor. Also, according to extensive literature searching, no other biological activity has been published. Compound (2) seems to exhibit favourable physico-chemical properties. This hit, that belongs to ChemDiv commercial compound collection (ID: C785-3067), fulfils the desired properties for oral absorption proposed by Lipinski et al. [40]. It has a molecular weight of 443.61 g/mol, estimated lipophilicity (expressed as clogP) of 3.37 and the hydrogen bond acceptors and donors equals to 7 and 1, respectively (data obtained from ChemDiv data base).

All these elements point out to the promising application of this molecule as a drug lead.

Fig. (4). Docking analysis of compound (2) in AChE enzyme (PDB code: 1EVE) (A) and in BChE enzyme active sites (PDB code: 1P0I) (B).

4. CONCLUSIONS

In this contribution, a miniaturized Ellman’s reaction based assay was set up in 384-well plate format. The use of Ellman’s reaction, traditional method for AChE quantification, was proven to successfully meet the demands of a high-throughput setting. The application of kinetic approach and the use of an assay variant in which the reaction is started with the addition of the substrate, resulted into a robust screening platform that performs reliably. The fact that tacrine was identified as a hit in a random screening campaign using a commercially available collection of more than 56,000 molecules, emphasizes the quality of the

6 Combinatorial Chemistry & High Throughput Screening, 2010, Vol. 13, No. 3 Järvinen et al.

optimized assay. To the best of our knowledge, this is the largest published screening campaign of commercially available compounds conducted in an academic setting that has resulted on finding AChE inhibitors. One of the hits (compound 2) was identified as a new potent cholinesterase inhibitor with potency value (IC50) in nanomolar range. This compound seems to fulfil the desired properties for oral absorption proposed by Lipinski et al. [40]. Accordingly, this hit may represent a suitable choice of bioactive molecule for further applications as a drug lead. Equally important is the fact that highly potent compounds acting in the nanomolar range could be used as tools to understand the structure-activity relationships of cholinesterase inhibitors. To the extent of our knowledge, compound (2) has not been reported to have any biological activities before.

ACKNOWLEDGEMENTS

We acknowledge the contribution of Juhani Lahdenperä and High Throughput Center (Biomedicum Helsinki, University of Helsinki) for the technical support and discussions during the screening. We also acknowledge the contribution of ChemDiv specialist, Irina Tyrnova, for providing chemical data on the most active hit that was identified from their chemical library. This research was supported by the grant (project nr. 53305) from the Academy of Finland to the Center of Excellence on Microbial Resources (A. Hatakka, P. Järvinen (formerly P. Oinonen)). Financial support of Tor, Joe och Pentti Borgs minnesfond to the research project is also greatly appreciated (A. Fallarero). P. Järvinen wishes to thank Finnish Cultural Foundation for personal funding.

ABBREVIATIONS

AChE = Acetylcholinesterase

IC50 value = Concentration causing 50 % inhibitory effect

BChE = Butyrylcholinesterase

AD = Alzheimer's disease

ATCI = Acetylthiocholine iodide

BTCCl = S-butyrylthiocholine chloride

DTNB = 5,5’-dithio-bis(2-nitrobenzoic acid), Ellman's reagent

BSA = Bovine serum albumin

Z’ = Screening window coefficient

S/B = Signal-to-background ratio

S/N = Signal-to-noise ratio

Xs = Average of the signal

SDs = Standard deviation of the signal

Xb = Average of the background

SDb = Standard deviation of the background

QSAR = Quantitative structure-activity relationship

FDA = US Food and Drug Administration

PAS = Peripheral anionic site

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Received: April 17, 2009 Revised: July 1, 2009 Accepted: July 8, 2009