Transcript Diapositiva 1

VNIVERSITAT
D VALÈNCIA
E
ESCOLA POLITÈCNICA
SUPERIOR DE GANDIA
BIOPARTITIONING MICELLAR
CHROMATOGRAPHY TO PREDICT BLOOD TO
LIVER, BLOOD TO LUNG AND BLOOD TO FAT
PARTITION COEFFICIENTS OF DRUGS
Y. Martín Biosca, S. Torres-Cartas*, R.M. VillanuevaCamañas, M.J. Medina Hernández and S. Sagrado
Dpto. Química Analítica, Universitat de València, C/ Vicente Andrés Estellés
s/n, E-46100 Burjassot (Valencia), Spain
* Dpto. Química, Escuela Politécnica Superior de Gandia, Ctra. NazaretOliva, s/n, E- 46730 Gandia (Valencia) Spain
BIOPARTITIONING MICELLAR CHROMATOGRAPHY TO PREDICT BLOOD TO LIVER,
BLOOD TO LUNG AND BLOOD TO FAT PARTITION COEFFICIENTS OF DRUGS
INTRODUCTION
Distribution of organic compounds between blood and tissues
is of crucial importance in the understanding of potential toxic
effects and in pharmacokinetic analysis. Several procedures
have been developed for measuring drug partition coefficients
from blood to different tissues (liver, lung, brain, muscle…).
Retention
data
obtained
in
biopartitioning
micelar
chromatography (BMC) is useful in constructing good models
(attributed to the fact that the characteristics of the BMC system
are similar to the characteristics of biological barriers).
The capability of BMC as an in-vitro technique to describe
distribution of organic compounds between blood and tissues is
evaluated. Values of in vitro blood to liver, blood to lung and
blood to fat partition coefficients of a heterogeneous set of
compounds have been collected from the literature. Adequate
correlations between the BMC retention data of compounds,
obtained using a solution of Brij35 as micellar mobile phase, and
their partition coefficients in different tissues are achieved.
BIOPARTITIONING MICELLAR CHROMATOGRAPHY TO PREDICT BLOOD TO LIVER,
BLOOD TO LUNG AND BLOOD TO FAT PARTITION COEFFICIENTS OF DRUGS
EXPERIMENTAL
Stationary phase: Kromasil octadecyl-silane
C18 column (5 m, 150 x 4.6 mm i.d.)
(Scharlab, Barcelona, Spain).
BMC method
EXPERIMENTAL
Mobile phase: Brij35 0.04 M at pH 7.4;
M phosphate buffer.
0.05
HPLC conditions: flow 1 mL·min-1; detection at
220 nm; loop 20 L; T 35.5 ºC.
Drugs included in this study were chosen in order
to cover a broad range of physico-chemical properties.
All retention factor values (k) were averages of a least
triplicate determinations.
SOFTWARE, AND DATA PROCESSING
Microsoft® Excel 2000 software were used to perform the statistical analysis of the
regressions.
The Unscrambler Version 7.6 by CAMO was used to perform multivariate analysis.
EPI SuiteTM (ACD LabsTM, Advanced Chemistry Development Inc. Demo version) was used
for parameters estimation: octanol-water partition coefficient (logP), molar refractivity
(MR), polarizability (Pol), molar volumen (MV), parachor (Pr) and water solubility.
BIOPARTITIONING MICELLAR CHROMATOGRAPHY TO PREDICT BLOOD TO LIVER,
BLOOD TO LUNG AND BLOOD TO FAT PARTITION COEFFICIENTS OF DRUGS
RESULTS AND
DISCUSSION
Table 1. k and blood to lung, blood to fat and blood to
liver logP of drugs.
Log P from blood to
k ± sd
Alprazolam
Atenolol
Barbital
Bisoprolol
Butethal
Buthetal
Chlorpromazine
clomipramine
Diazepan
Fentanyl
Fluoxetine
Haloperidol
Hexobarbital
Hydroxyzine
Imipramine
Lidocaine
Lorazepam
Metoprolol
Midazolam
Oxprenolol
Pentazocine
Pentotal
Phenobarbital
Phenytoin
Pindolol
Pyrene
Salicylic Acid
Theophylline
Timolol
Valproic acid
29.53 ± 0.07
1.48 ± 0.05
5.782 ± 0.014
5.37 ± 0.06
24.55 ± 0.03
17.82 ± 0.08
340 ± 11
250 ± 11
44.63 ± 0.04
67.064 ± 0.31
45.3 ± 0.5
102.2 ± 0.7
23.158 ± 0.009
60.9 ± 0.5
187 ± 9
21 ± 0.8
30.99 ± 0.04
5.73 ± 0.13
54.98 ± 0.06
13.58 ± 0.17
25.30 ± 0.14
43.0 ± 0.3
19.416 ± 0.008
34.49 ± 0.11
5.92 ± 0.02
72.0 ± 0.7
4.24 ± 0.05
2.3275 ± 0.0012
3.39 ± 0.05
1.47 ± 0.04
Lung [1]
Fat [2]
0.32
0.28
0
1.62
0.18
0.18
1.81
2.16
0.52
1.14
1.24
1.73
0.45
1.06
2.11
0.58
0.44
1.06
0.6
1.27
1.43
0.08
-0.08
-0.1
1.01
0.35
-0.72
-0.15
1.43
-0.38
-0.14
0.25
0.250
1.13
1.430
0.2
1.02
0.01
0.94
-0.2
0.400
0.95
-0.52
0.26
-0.190
-0.820
Liver [3]
1.02
0.57
1.360
0.47
0.470
0.65
0.580
0.770
0.78
0.7
1.71
1.06
1.08
1.63
0.77
1.02
0.370
0.360
0.26
0.36
0.370
-0.65
0.950
0.260
BIOPARTITIONING MICELLAR CHROMATOGRAPHY TO PREDICT BLOOD TO LIVER,
BLOOD TO LUNG AND BLOOD TO FAT PARTITION COEFFICIENTS OF DRUGS
Blood to lung partition
coefficient-retention
relationship (an example)
PC2
· Solubility
· kBMC
· logPLung
· MV
· logP
· Pr
MR ·
· Pol
MW ·
PC1
Figure 1. PLS loading plot corresponding to the first
two latent variables (y-block in pink and X-block in
blue).
In order to study the
importance of some
physico-chemical variables
in the construction of a
regression model for
predicting blood to lung
partition coefficients for
drugs (Table 1), a partial
least squares analysis
(PLS) was performed. The
loading plot corresponding
to the first two latent
variables is shown in
Figure 1.
BIOPARTITIONING MICELLAR CHROMATOGRAPHY TO PREDICT BLOOD TO LIVER,
BLOOD TO LUNG AND BLOOD TO FAT PARTITION COEFFICIENTS OF DRUGS
Blood to lung partition
coefficient-retention
relationship
k
logP
MR
MV
Pr
Pol
MW
Solubility
Figure 2.- The PLS-model regression
coefficients together their uncertainty limits
for the two latent variables model
Non-significant variables
were eliminated step by
step (Figure 2), reanalyzing each time the
PLS model. Finally a PLS
model was obtained by
selecting the variables:
kBMC and molar volume
(MV). This model
accounts for 82 and 80%
of variance in calibration
and cross-validation,
respectively.
BIOPARTITIONING MICELLAR CHROMATOGRAPHY TO PREDICT BLOOD TO LIVER,
BLOOD TO LUNG AND BLOOD TO FAT PARTITION COEFFICIENTS OF DRUGS
Plot of logP
2,2
MLR
1,7
estimated logPlung
observed
Blood to lung partition
coefficient-retention
relationship
1,2
0,7
0,2
-0,3
-0,8
-0,8
-0,3
0,2
0,7
1,2
1,7
2,2
predicted
in-vitro logPlung
Figure 3.- Validation plot of the QRAR model
logPLung = (-1.7  0.6) + (0.003  0.002) * k + (0.010  0.002) * MV
N = 30; r2 = 0.81; S.E. = 0.33
As can be observed, in Figure 3 the ability of the proposed model to
describe and predict logPLung was adequate.
References
MLR vs. PLS coef.
[1] M. H. Abraham and a. Ibrahim, Eur. J. Med. Chem. 4 (2006) 1403-1438..
[2] M. H. Abraham et. al. Eur. J. Med. Chem. (2007), doi:10.1016/j.ejmech.2006.12.01.
[1] Michael H. Abraham et. al. Eur. J. Med. Chem. (2007), doi:10.1016/j.ejmech.2006.12.011.
VNIVERSITAT
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ENANTIOSELECTIVE BINDING OF ANTIHISTAMINES TO
HUMAN SERUM ALBUMIN BY AFFINITY
ELECTROKINETIC CHROMATOGRAPHY–PARTIAL FILLIG
TECHNIQUE
Mª Amparo Martínez Gómez, S. Sagrado, R.M. Villanueva Camañas
and M.J. Medina Hernández
Dpto. Química Analítica, Universitat de València, C/ Vicente Andrés Estellés s/n,
E-46100 Burjassot (Valencia), Spain.
ENANTIOSELECTIVE BINDING OF ANTIHISTAMINES TO HUMAN SERUM ALBUMIN BY
AFFINITY ELECTROKINETIC CHROMATOGRAPHY–PARTIAL FILLIG TECHNIQUE
INTRODUCTION
A new methodology to evaluate the enantioselective binding to
HSA of highly protein-bound drugs was proposed. This methodology
consists in ultrafiltrating samples containing HSA and racemic drug
and analysing the bound drug fraction using AEKC-partial filling
technique (PFT) and HSA as chiral selector. The protein binding
values, the affinity constants to HSA and the binding sites of the
enantiomers
of
four
antihistamines,
brompheniramine,
chlorpheniramine, hydroxyzine and orphenadrine, on the HSA
molecule were evaluated.
REFERENCES
[1] J.J.Martínez-Plà, M.A. Martínez-Gómez, Y. Martín-Biosca, S. Sagrado, R.M. Villanueva-Camañas, M.J. Medina-Hernández, Electrophoresis 25
(2004) 3176-3185.
[2] M.A. Martínez-Gómez, S. Sagrado, R.M. Villanueva-Camañas, M.J. Medina-Hernández, Analytica Chimica Acta 592 (2007) 202–9.
ENANTIOSELECTIVE BINDING OF ANTIHISTAMINES TO HUMAN SERUM ALBUMIN BY
AFFINITY ELECTROKINETIC CHROMATOGRAPHY–PARTIAL FILLIG TECHNIQUE
EXPERIMENTAL AND METHODOLOGY
SAMPLE
Incubation
30 min
at 36.5ºC Ultrafiltration
•Drug enantiomer (65-270 μM)
•HSA (475 μM)
•(-)-Sulpiride (I.S.) (80 μM)
•Phosphate buffer 67 mM pH 7.4
• HP 3D CE system, diode array detector and
HP 3DCE Chemstation software
• Fused-silica capillary of 50 m i.d and 363
m o.d. with total and effective length of
65 and 56.5 cm, respectively.
•Temperature 30º C, voltage 15 kV and
detection wavelength, 225 nm
Unbound drug fraction
Bound drug fraction
Precipitation of HSA
with MeOH (centrif.)
CHIRAL ANALYSIS
Optimum experimental conditions for
enantioresolution of drugs and resolution values
[HSA]
Drug
pH
SPL (s)
Rs
(μM)
Brompheniramine 8.50
180
180
2.50
Chlorpheniramine 8.25
160
150
1.49
Hydroxyzine
7.00
180
150
1.41
Orphenadrine
7.80
160
150
1.12
ENANTIOSELECTIVE BINDING OF ANTIHISTAMINES TO HUMAN SERUM ALBUMIN BY
AFFINITY ELECTROKINETIC CHROMATOGRAPHY–PARTIAL FILLIG TECHNIQUE
SITE III: Digitoxin
SITE II
Diazepam
SITE I
Warfarin
The binding sites of
antihistamines in the HSA
molecule were identified
using warfarin, diazepam
and digitoxin as marker
ligands representatives of
sites I, II and III,
respectively in the HSA
molecule.
ENANTIOSELECTIVE BINDING OF ANTIHISTAMINES TO HUMAN SERUM ALBUMIN BY
AFFINITY ELECTROKINETIC CHROMATOGRAPHY–PARTIAL FILLIG TECHNIQUE
Compound
Binding Model
Enantiomer I
Enantiomer II
KE1 (M-1)
Binding Site KE2 (M-1)
Binding site
Enantioselectivity
ES
Brompheniramine
Competitive
(9.39±0.10)·102
Site II
Diazepam
(2.60±0.17)·103
Site II
Diazepam
2.8 ± 0.2
Chlorpheniramine
Competitive
(9.20±0.20)·102
Site II
Diazepam
(1.69±0.17)·103
Site II
Diazepam
1.8 ± 0.3
Hydroxyzine
Independent
(5.3±0.5)·103
Non defined (6.3±0.4)·103
Site I
Warfarine
1.2 ± 0.6
Orphenadrine
Independent
(1.26±0.13)·103
Site III
Digitoxin
Non defined
13.3 ± 0.1
(1.67±0.11)·104
Table 1 shows the estimated affinity constants obtained for each drug
enantiomer evaluated using the results obtained at five concentration levels.
Both enantiomers of brompheniramine and chlorpheniramine bind to the site
II in the HSA molecule so, enantiomers follow a competitive binding model.
On the contrary, enantiomers of orphenadrine and trimeprazine bind to
different binding sites, following an independent binding model.
Enantioselectivity (ES) values were in all cases higher than 1 indicating
that a certain degree of enantioselective binding of antihistamines to HSA
exists. The results obtained represent the first evidence of the
enantioselective binding of antihistamines to HSA, the major plasmatic
protein.
VNIVERSITAT
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STEREOSELECTIVE PLASMA PROTEIN BINDING
OF BASIC DRUGS BY CAPILLARY
ELECTROPHORESIS
Mª Amparo Martínez Gómez, S. Sagrado, R.M. Villanueva Camañas
and M.J. Medina Hernández
Dpto. Química Analítica, Universitat de València, C/ Vicente Andrés Estellés s/n,
E-46100 Burjassot (Valencia), Spain.
STEREOSELECTIVE PLASMA PROTEIN BINDING
OF BASIC DRUGS BY CAPILLARY ELECTROPHORESIS
INTRODUCTION
The stereoselective binding of antihistamines (brompheniramine,
chlorpheniramine, hydroxyzine, orphenadrine and phenindamine),
phenothiazines (promethazine and trimeprazine) and a local anaesthetic
(bupivacaine) to human plasma proteins was evaluated. The results
obtained represent the first evidence of the enantioselective binding of
brompheniramine,
hydroxyzine,
orphenadrine,
phenindamine,
promethazine and trimeprazine to human plasma proteins.
REFERENCES
[1] J.J.Martínez-Plà, Y. Martín-Biosca, S. Sagrado, R.M. Villanueva-Camañas, M.J. Medina-Hernández, J.Chromatogr. A 1048 (2004) 111-118.
[2] M.A. Martínez-Gómez, S. Sagrado, R.M. Villanueva-Camañas, M.J. Medina-Hernández, Analytica Chimica Acta 592 (2007) 202–209.
[3] M.A. Martínez-Gómez, S. Sagrado, R.M. Villanueva-Camañas,
M.J. Medina-Hernández, Analytica Chimica Acta 582 (2007) 223–228.
STEREOSELECTIVE PLASMA PROTEIN BINDING
OF BASIC DRUGS BY CAPILLARY ELECTROPHORESIS
EXPERIMENTAL AND METHODOLOGY
SAMPLE
Incubation
30 min
at 36.5ºC
Ultrafiltration
Bound drug fraction
Precipitation of HSA
with ACN
•Drug enantiomer (92-347 μM)
•Plasma
•(-)-Sulpiride (I.S.) (80 μM)
•Phosphate buffer 67 mM pH 7.4
• HP 3D CE system, diode array detector and HP
Unbound drug fraction
CHIRAL ANALYSIS
3DCE
Chemstation software
• Fused-silica capillary of 50 m i.d and 363 m o.d. with total and effective length of 65 and
56.5 cm, respectively.
•Temperature 30º C, voltage 15 kV and detection wavelength, 225 nm
STEREOSELECTIVE PLASMA PROTEIN BINDING
OF BASIC DRUGS BY CAPILLARY ELECTROPHORESIS
Optimum experimental conditions for enantioresolution
of drugs and resolution values
Drug
pH
[HSA] (μM)
SPL (s)
Rs
Brompheniramine
8.50
180
180
2.50
Chlorpheniramine
8.25
160
150
1.49
Hydroxyzine
7.00
180
150
1.41
Orphenadrine
7.80
160
150
1.12
Phenindamine
6.80
140
150
1.75
Promethazine
7.60
170
170
2.00
Trimeprazine
7.50
170
190
1.53
Bupivacaine
8.00
140
180
1.52
STEREOSELECTIVE PLASMA PROTEIN BINDING
OF BASIC DRUGS BY CAPILLARY ELECTROPHORESIS
5
RESULTS
AND DISCUSSION
4
4,5
Figure 1
A
3
2
1
//
0
06
7
8
3
Absorbance (mAU)
Absorbance (mAU)
3,5
9
3
2
2
1,5
1
1
0,5
0
//
070
Absorbance (mAU)
C
2
1
//
0
11
0
12
13
Time (min)
2
1
1
00
0
8
//
9
E
1
08
//
10
Time (min)
12
9,5
D
9
10
10
11
Time (min)
2
10
9
23
3
0
9
8,5
3
8
14
8
8
Time (min)
Absorbance (mAU)
Absorbance (mAU)
Time (min)
3
B
2,5
14
12
11
12
10
Figure 1 shows the
experimental
electropherograms
10,5
11
corresponding to the
analysis of the bound
fractions of:
(A) 242 μΜchlorpheniramine
(B) 201μΜ orphenadrine
(C) 180μΜ hydroxyzine
(D) 100μΜ promethazine
(E) 312 μΜ bupivacaine
STEREOSELECTIVE PLASMA PROTEIN BINDING
OF BASIC DRUGS BY CAPILLARY ELECTROPHORESIS
Table 1
Compound
C tot (μM)
Chlorpheniramine
124
242
346
92
180
261
120
243
347
125
218
312
120
240
345
100
200
290
104
201
288
97
194
277
Hydroxyzine
Phenindamine
Bupivacaine
Brompheniramine
Promethazine
Orphenadrine
Trimeprazine
PB (%)
E1
E2
76±2 83±5
80±2 82±2
80±2 82±2
99±5 100±3
92±3 98±2
93±3 96±2
29±3 71±6
29±3 71±3
32±2 72±2
84±3 98±3
78±3 97±3
85±2 96±2
89±5 92±4
65±2 73±2
43±2 50±2
71±3 100±3
33±2 47±2
24±2 35±2
65±6 99±5
81±5 96±2
99±2 100±2
48±6 84±2
51±4 87±3
61±5 89±2
ES
1.09±0.08
1.02±0.02
1.01±0.02
1.01±0.02
1.06±0.03
1.03±0.02
2.49±0.02
2.51±0.12
2.25±0.09
1.17±0.08
1.24±0.02
1.14±0.02
1.01±0.05
1.15±0.03
1.16±0.04
1.40±0.12
1.43±0.02
1.50±0.13
1.53±0.06
1.18±0.09
1.00±0.02
1.8±0. 2
1.7±0.2
1.5±0.2
Table 1 shows the protein-binding
(PB) values of each drug
enantiomer and the
enantioselectivity (ES) values
obtained at 3 concentrations.
In general, the first eluted
enantiomer (E1) presented lower
affinity towards plasma proteins
than the second enantiomer (E2)
Saturation of binding sites of
proteins was observed for
brompheniramine and
promethazine.
The different behaviour between
the enantiomers of orphenadrine
and trimeprazine indicated that
the enantiomers follow an
independent binding model.
Decreased order of ES was:
Phenindamine>trimeprazine>pro
methazine≈orphenadrine>
Bupivacaine>chlorpheniramine≈h
ydroxyzine≈brompheniramine
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SCREENING OF ACETYLCHOLINESTERASE
INHIBITORS BY CAPILLARY
ELECTROPHORESIS AFTER ENZYMATIC
REACTION AT CAPILLARY INLET
Y. Martín-Biosca, L. Asensi-Bernardi, R.M. Villanueva-Camañas, S.
Sagrado and M.J. Medina-Hernández
Dpto. Química Analítica, Universitat de València, C/ Vicente Andrés Estellés
s/n, E-46100 Burjassot (Valencia), Spain
SCREENING OF ACETYLCHOLINESTERASE INHIBITORS BY CAPILLARY
ELECTROPHORESIS AFTER ENZYMATIC REACTION AT CAPILLARY INLET
INTRODUCTION
Alzheimer’s disease (AD) is an age-related neurodegenerative
disorder that causes dementia characterized by a low level of the
neurotransmitter acetylcholine in the brain. The current clinical
treatment of AD is mainly based on acetylcholinesterase (AChE)
inhibitors, such as tacrine, donepezil, rivastigmine, and
galantamine, which pharmacological effect is to inhibit the activity
of AChE, so as to keep a normal level of acetylcholine in the nerve
system.
Capillary electrophoretic systems have been successfully applied
for in-line enzymatic reactions by a methodology known as
electrophoretically mediated microanalysis (EMMA) [1,3]. In this
methodology, all the different steps (i.e. mixing, incubation,
separation and in-line quantitation) are combined in the capillary,
which is used as a microreactor for the enzymatic reaction. The
aim of the present work is to develop a simple EMMA method for
screening of AChE inhibitors in the early stage of drug discovery.
SCREENING OF ACETYLCHOLINESTERASE INHIBITORS BY CAPILLARY
ELECTROPHORESIS AFTER ENZYMATIC REACTION AT CAPILLARY INLET
EXPERIMENTAL
Instrumentation
A 50 m i.d. (363 m o.d.)
fused-silica capillary with
total and effective length of
56 and 47.5 cm respectively
was
employed
(Agilent
Technologies, Germany)
A Hewlett-Packard HP
3DCE capillary
electrophoresis system
CE
conditions:
15
kV;
detection at 230 nm; T 37º C;
hydrodynamical injection
Background electrolyte: 30
mM borate-phosphate buffer,
pH 8.0
SCREENING OF ACETYLCHOLINESTERASE INHIBITORS BY CAPILLARY
ELECTROPHORESIS AFTER ENZYMATIC REACTION AT CAPILLARY INLET
EMMA procedure
Substrate
Enzyme
Product
+ Inhibitor
Figure 1.- AChE catalyzed reaction
The enzyme activity was directly assayed by measuring the peak
area of produced thiocholine (TCh) with UV detection at 230 nm
SCREENING OF ACETYLCHOLINESTERASE INHIBITORS BY CAPILLARY
ELECTROPHORESIS AFTER ENZYMATIC REACTION AT CAPILLARY INLET
+
-
Figure 2.- Schematic illustration of
EMMA technique for AChE acitvity assay.
The enzyme solution and the
substrate solution, with or without
inhibitor, were introduced into the
inlet part of the capillary by a
sandwich injection mode:
1) Water, 20 mbar for 2 sec
2) AChE, 50 mbar for 2 sec
3) Substrate (with or without
inhibitor), 50 mbar for 2 sec
4) AChE, 50 mbar for 2 sec
5) Water, 20 mbar for 2 sec
6) Waiting time (mixing and
incubation time): 1 min
7) A voltage of 15 kV was applied
to separate the product TCh from
the unreacted substrate
NOTE: I.S. in all solutions
SCREENING OF ACETYLCHOLINESTERASE INHIBITORS BY CAPILLARY
ELECTROPHORESIS AFTER ENZYMATIC REACTION AT CAPILLARY INLET
DAD1 A, Sig=230,16 Ref=off (ACHE\25050731.D)
DAD1 A, Sig=230,16 Ref=off (ACHE\25050734.D)
mAU
18
Product (TCh)
Blank-area
16
14
x-area
12
Substrate (AThCh)
10
8
Alprenolol (IS)
6
4
2
0
1
2
3
4
Time (min)
5
min
Figure 3.- Typical electropherogram obtained after EMMA methodology applied with
(red) and without (blue) the inhibitor edrophonium (100 µM) added to the substrate
plug. Conditions: concentration of AChE, 0.4 mg/mL; AThCh, 10 mM; MgSO4 in the substrate solution, 20 mM.
SCREENING OF ACETYLCHOLINESTERASE INHIBITORS BY CAPILLARY
ELECTROPHORESIS AFTER ENZYMATIC REACTION AT CAPILLARY INLET
RESULTS AND DISCUSSION
(an example)
A
B
300
0.08
edrophonium
edrophonium
edrophonium
edrophonium
200
0 
50 
100 
500 
0.06
0.04
1/V
Peak area
To estimate Ki
Characterize:
mixed-mode
inhibitor
0.02
100
edrophonium
edrophonium
edrophonium
edrophonium
0
0
0 
50 
100 
500 
-0.02
0.0
5.0
10.0
15.0
[Substrate], mM
20.0
25.0
0
200
400
600
1/[AThCh] (M-1)
Figure 4.- (A) Michaelis-Menten and (B) corresponding Lineweaver-Burk plots
obtained using the inhibitor edrophonium .
SCREENING OF ACETYLCHOLINESTERASE INHIBITORS BY CAPILLARY
ELECTROPHORESIS AFTER ENZYMATIC REACTION AT CAPILLARY INLET
The percentage of inhibition was determined
according to the following equation:
100
 x

Inhibition%  100  
 100 
 blank

x: peak area of the product (TCh) determined
at a given concentration of inhibitor
blank: peak are of the product (TCh)
whitout inhibitor being present
Inhibition %
80
The measured IC50 for edrophonium
(concentration of compound at which the
reaction was inhibited by 50%) with the
EMMA assay was aproximately 100 M at
a concentration of substrate 10 mM.
60
AThCh 2 m
AThCh 6 m
AThCh 10 m
AThCh 16 m
AThCh 20 m
40
The proposed methodology is rapid,
simple, automatic and can be very useful
for screening of AChE inhibitors in the
early stage of drug discovery.
20
0
0
100
200
300
400
[edrophonium], M
500
600
Figure 5.- Inhibition plot of edrophonium
obtained using the proposed EMMA
methodology for several substrate
concentrations.
References
1. J. Zhang, J. Hoogmartens and A. Van Schepdael, Electrophoresis 2006,
27, 35-43.
2. M. Telnarová, S. Vytisková, R. Chaloupková and Z. Glatz, Electrophoresis
2004, 25, 290-296.
3. M. Telnarová, S. Vytisková, M. Monincová and Z. Glatz, Electrophoresis
2004, 25, 1028-1033.