Acetylcholinesterase inhibitors: Structure based design, synthesis, pharmacophore modeling, and virtual screening

Article abstract of DOI:10.1021/ci400196z

Acetylcholinesterase (AChE) is a main drug target, and its inhibitors have demonstrated functionality in the symptomatic treatment of Alzheimer's disease (AD). In this study, a series of novel AChE inhibitors were designed and their inhibitory activity was evaluated with 2D quantitative structure-activity relationship (QSAR) studies using a training set of 20 known compounds for which IC₅₀ values had previously been determined. The QSAR model was calculated based on seven unique descriptors. Model validation was determined by predicting IC₅₀ values for a test set of 20 independent compounds with measured IC₅₀ values. A correlation analysis was carried out comparing the statistics of the measured IC₅₀ values with predicted ones. These selectivity-determining descriptors were interpreted graphically in terms of principal component analyses (PCA). A 3D pharmacophore model was also created based on the activity of the training set. In addition, absorption, distribution, metabolism, and excretion (ADME) descriptors were also determined to evaluate their pharmacokinetic properties. Finally, molecular docking of these novel molecules into the AChE binding domain indicated that three molecules (6c, 7c, and 7h) should have significantly higher affinities and solvation energies than the known standard drug donepezil. The docking studies of 2H-thiazolo[3,2-a]pyrimidines (6a-6j) and 5H-thiazolo[3,2-a] pyrimidines (7a-7j) with human AChE have demonstrated that these ligands bind to the dual sites of the enzyme. Simple and ecofriendly syntheses and diastereomeric crystallizations of 2H-thiazolo [3,2-a]pyrimidines and 5H-thiazolo[3,2-a] pyrimidines are described. The solid-state structures for the HBr salts of compounds 6a, 6e, 7a, and 7i have been determined using single-crystal X-ray diffraction techniques, and X-ray powder patterns were measured for the bulk solid remaining after solvent was removed from solutions containing 6a and 7a. These studies provide valuable insight for designing more potent and selective inhibitors for the treatment of AD.

Full text of DOI:10.1021/ci400196z

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Article
Acetylcholinesterase Inhibitors: Structure Based Design,
Synthesis, Pharmacophore Modeling and Virtual Screening
Koteswara Rao Valasani, Michael O. Chaney, Victor W. Day, and Shirley ShiDu Yan
J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/ci400196z • Publication Date (Web): 18 Jun 2013
Downloaded from http://pubs.acs.org on June 21, 2013
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Acetylcholinesterase Inhibitors: Structure Based Design, Synthesis, Pharmacophore
Modeling and Virtual Screening
Koteswara Rao Valasani, Michael O. Chaney, Victor W. Day and Shirley ShiDu Yan*
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Acetylcholinesterase (AChE) is one
of the main drug targets and its
inhibitors
have
demonstrated
functionality in the symptomatic
treatment of Alzheimer's disease
(AD). Structure based design has
been used to identify the human
AChE inhibitors. Both 2D QSAR
and 3D pharmcophore models were
created. AChE molecular docking
studies
were
undertaken
to
determine whether they exhibit
significant binding affinity with the
binding site.
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Acetylcholinesterase Inhibitors: Structure Based Design, Synthesis,
Pharmacophore Modeling and Virtual Screening
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Koteswara Rao Valasani , Michael O. Chaney , Victor W. Day , and Shirley
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ShiDu Yan *
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Department of Pharmacology & Toxicology and Higuchi Bioscience Center, School of
Pharmacy, University of Kansas, Lawrence, KS 66047 (USA)
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Department of Chemistry, University of Kansas, Lawrence, KS 66045 (USA)
*
Correspondence should be addressed to Dr. Shirley Shidu Yan, 2099 Constant Avenue,
University of Kansas, Lawrence, KS 66047. E-mail: shidu@ku.edu.
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A B S T R A C T
Acetylcholinesterase (AChE) is one of the main drug targets and its inhibitors have demonstrated
functionality in the symptomatic treatment of Alzheimer's disease (AD). In this study, a series of
novel AChE inhibitors were designed
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and their inhibitory activity was
evaluated with 2D QSAR studies
using a training set of 20 known
compounds for which IC50 values
had previously been determined. The
QSAR model was calculated based
on 7 unique descriptors. Model
validation was determined by
predicting IC values for a test set of
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20 independent compounds with
measured IC values. A correlation
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analysis was carried out comparing
the statistics of the measured IC50 values with predicted ones. These selectivity-determining
descriptors were interpreted graphically in terms of principle component analyses (PCA). A 3D
pharmacophore model was also created based on the activity of the training set. In addition,
absorption, distribution, metabolism and excretion (ADME) descriptors were also determined to
evaluate their pharmacokinetic properties. Finally, molecular docking of these novel molecules
into the AChE binding domain indicated that three molecules (6c, 7c and 7h) should have
significantly higher affinities and solvation energies than the known standard drug donepezil.
The docking studies of 2H-thiazolo[3,2-a]pyrimidines (6a-6j) and 5H-thiazolo[3,2-a]
pyrimidines (7a-7j) with human AChE have demonstrated that these ligands bind to the dual
sites of the enzyme. Simple and ecofriendly syntheses and diastereomeric crystallizations of 2H-
thiazolo [3,2-a]pyrimidines and 5H-thiazolo[3,2-a] pyrimidines are described. The solid-state
structures for the HBr salts of compounds 6a, 6e, 7a and 7i have been determined using single-
crystal X-ray diffraction techniques and x-ray powder patterns were measured for the bulk solid
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remaining after solvent was removed from solutions containing 6a and 7a. These studies provide
valuable insight for designing more potent and selective inhibitors for the treatment of AD.
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. INTRODUCTION
Alzheimer’s disease (AD) is the most common cause of dementia in adults, resulting in a
disorder of cognition and memory due to neuronal stress and eventually in cell death. Alzheimer
brain is characterized by two pathological features: amyloid beta (Aβ) accumulation and the
formation of neurofibrillary tangles. Accumulation of Aβ is considered to be one of the primary
causes for the AD pathogenesis. Scientists have proposed several hypotheses for AD
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development . One of the oldest AD hypotheses, the cholinergic hypothesis , has led to the
development of cholinesterase inhibitors (ChEIs) that increase levels of acetylcholine (ACh)
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through inhibition of cholinesterases (ChEs) . The most predominant hypothesis, the amyloid
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hypothesis
postulates that increased production of β-amyloid peptide and its aggregation and
accumulation in a brain lead to neuronal cell death. Since it is known that ACh deficiency is
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associated with AD , inhibiting the biological activity of ChEs to increase ACh levels in the
brain is one of the major therapeutic strategies for the treatment of AD. Acetylcholinesterase
(AChE) inhibitors are the most frequently prescribed drugs for AD, which promote memory
function and delay the cognitive decline without altering the underlying pathology.
The deficiencies in cholinergic neurotransmission in AD have led to the development of
potent AChE inhibitors (AChEIs). A large number of naturally-occurring and synthetic AChE
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inhibitors have already been identified
as the first-line treatment for symptoms of this
disease and are prescribed for mild-to-moderate AD. Four AChEIs have been approved by the
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United States FDA and many other jurisdictions for the treatment of AD
: tacrine, donepezil,
rivastigmine, and galantamine. Tacrine is no longer in general use because of dosing, tolerability
and safety concerns. The clinical benefits of these agents include improvements, stabilization or
less-than-expected decline in cognition and other mental function. Slightly different mechanisms
of action have been reported for the available inhibitors. They appear to affect the ease of use
and tolerability more than drug effectiveness though, since neither systematic reviews, nor head-
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to-head studies, identify significant efficacy differences between the agents
. Subsequent
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clearly-reported, carefully-conducted, systematic, evidence-based reviews of these agents are
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available
. It is important to understand that none of these medications stop the disease
itself. At best, they only slow progression and do not appear to affect the basic destructive
disease process. When patients go off the drugs, the deterioration continues.
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Although all of the FDA-approved Alzheimer’s medicines have, in general, been shown
to somewhat improve a patient’s well-being, most patients will not experience significant
improvement. Studies have shown that only about 10 percent of patients are considered to be
“better” when assessed by their doctor or caregiver. The remaining 90% may not decline as
much as they would have without drug treatment but overall improvement will likely not be
noted. While head-to-head studies of the various medicines could provide meaningful
comparisons for some aspects of AD treatment, it is difficult to make head-to-head comparisons
in their ability to improve overall well-being.
The 3-D structure of AChE from native Torpedo californica (TcAChE) has been
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determined by X-ray crystallography (Protein Data Bank, PDB code: 2ACE) and is similar to
the structure of human AChE (hAChE). Both molecules are α/β serine hydrolases with 537
residues and a 12-stranded mixed β sheet surrounded by 14 α helices. The active sites in both
crystal structures are also similar. Docking simulations were performed to gain insight into the
recognition between the AChE and the ligands. For TcAChE, these experiments indicated that
recognition occurred in a deep, narrow groove approximately 20Ǻ long on the enzyme surface.
For TcAChE, this groove contains both the catalytic active site (CAS) with the Ser-His-Glu
catalytic triad (Ser203-His447-Glu334) and the peripheral anionic site (PAS) that utilizes Trp86,
Tyr133, Glu202, Phe338, and Tyr449. A substantial portion of the surface of this groove is lined
by fourteen highly conserved aromatic residues. The PAS is located at the aromatic-lined
entrance of the groove. This aromatic lined-entrance contains Tyr72, Tyr124, Trp279 and
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Tyr337 residues . Reversible inhibitors bind to the CAS or to the PAS and dimeric (dual)
inhibitors bind simultaneously to both of the sites. Non-catalytic roles of AChE have been
established in the past decade. AChE has been shown to play a key role in the acceleration of
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amyloid β (Aβ)-peptide deposition and promoting the formation of amyloid β-plaques . Dual-
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binding AChE inhibitors which bind to PAS have been shown to inhibit such processes . A
single molecule can therefore serve two important biological roles.
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Further studies indicated that the hydrophobic environment close to the PAS promotes
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the interaction of AChE with Aβ-peptide to form Aβ fibrils that lead to neurotoxicity
. These
reports suggest that AChEIs enhance the release of non amyloidogenic soluble derivatives of
amyloid precursor protein (APP) both in vitro and in vivo, thereby slowing the formation of
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amyloidogenic compounds in the brain. . AChEIs also increase the solubility of APP.
Numerous clinical trials have revealed the safety and efficacy of AChEIs in the treatment of AD.
Preclinical studies suggested that these AChEIs also attenuate neuronal cell death from neuronal
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cytotoxicity and therefore provide another treatment for AD.
Since it was also discovered that AChE augments the neurotoxic effect of Aβ peptide by
accelerating the formation of beta amyloid deposits in the brain, the role of Aβ peptide at the
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onset and during progression of AD is a matter of debate.
It is well known that the enzyme
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interacts with beta amyloid through the PAS and promotes the formation of fibrils. We have
therefore focused on developing compounds that are able to interact with both the CAS and PAS
of AChE as a potentially new therapeutic approach for the effective management of AD
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symptoms.
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Pyrimidine derivatives are widely used as treatment of AD at different stages
and
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they have previously been reported to be useful as gamma secretase modulators, treatments for
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diseases like AD associated with the deposition of beta-amyloid peptide in the brain , inhibitors
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for microtubule affinity regulating kinases
or compounds for the treatment or prevention of
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tauopathies .
Since pyrimidines are also components or building blocks for the synthesis of many
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important biologically active compounds
and the groove of AChE is lined with a high
percentage of aromatic side-chains, we concentrated on synthesizing molecules with aromatic
side chains attached to a pyrimidine moiety. Herein, we report the design, molecular docking
studies, QSAR studies, preADME predictions, 3D Pharmacophore modeling results, synthesis,
diastereomeric crystallization, single crystal XRD and powder XRD for AChEIs of pyrimidine
derivatives.
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. MATERIALS AND METHODS
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Construction of a 2D QSAR model
The QSAR suite of applications in MOE was used to calculate and analyze the data and build
numerical models of the data for prediction and interpretation purposes. Any QSAR model for a
given set of molecules correlates the activities with properties inherent to each molecule in the
set itself. A database of 40 compounds with known IC values was used to generate independent
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training and test data sets. Initially, a total of 7 QSAR descriptors were defined for the training
set compounds to carry out a correlation analysis and to construct the QSAR model based on
these properties. These descriptors are all independent variables and the IC values of the each
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compound were considered as dependent variable to predict the activity of each test set
compound.
Fitting the experimental data
The predicted activities were chosen as dependent variable in the test data set and a QSAR model
was constructed choosing this predicted activity and the remaining descriptors as model fields.
Regression analysis was performed for the training data set and Root Mean Square Error
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RMSE) and r values of the fit were reported. This fit model was saved as the QSAR model and
used for the prediction of activities of compounds of test data set.
Cross-Validating the Model
The above QSAR fit was used for both model validation and cross validation. This validation
procedure will evaluate the predicted activities and the residuals for the training set molecules.
The predicted, residual and Z-score values were calculated for both model and cross validations.
Graphical Analysis
The predictive ability of the model was assessed using a correlation plot by plotting the predicted
($PRED) values (X-axis) versus the predicted IC activities (Y-axis). This correlation plot was
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used to identify outliers that have a Z-score beyond the range of 2.
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Estimation and validation of predicted activities of test set
The QSAR model fit obtained above was used to evaluate the predicted (PRED Activity) values
of 20 test set compounds. Regression analysis was performed for the test data set and Root Mean
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Square Error (RMSE) and r values of the fit were reported.
Pruning the Descriptors
Pruning the descriptors is necessary to select the optimum set of molecules under consideration.
‘QuaSAR-Contingency,’a statistical application in MOE was used to describe the best molecules
in the data set. The results were analyzed using Principle Component Analysis (PCA) and the
purpose of which is to reduce the dimensionality of set of molecular descriptors by linearly
transforming the data or defying a property that would be important to drug design. A Three-
dimensional scatter graphical plot was generated using the first three Principal Components
(PCA1, PCA2 and PCA3).
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ADMET prediction
Absorption, Distribution, Metabolism, Excretion, & Toxicity (ADMET) properties of the 20
novel compounds were calculated using the preADMET online server
http://preadmet.bmdrc.org/). The ADMET properties, human intestinal absorption, in vitro
(
Caco-2 cell permeability, in vitro Maden Darby Canine Kidney (MDCK) cell permeability, in
vitro plasma protein binding and in vivo blood brain barrier penetration were predicted using this
program.
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Molecular Docking
Preparation of AChE protein
The three-dimensional structure of AChE was retrieved from the Protein Data Bank
(PDB:http://www.rcsb.org/pdb, PDB ID: 1B41) and loaded into the MOE software. All water
molecules and hetereo atoms were removed and polar hydrogens were added. Protonation of the
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D structure was done for all the atoms in implicit solvated environment (Born solvation model)
at a specified temperature of 300K, pH of 7 and with a salt concentration value of 0.1. A non-
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bonded cut off value of 10 - 12 A was applied to the Leonard-Jones terms. After the
protonation, the complete structure was Energy minimized in MMFF94x force field at a gradient
cut off value of 0.05. Molecular dynamics simulations were carried out at a constant temperature
of 300 deg K for a heat time of 10 pico seconds. The total simulations were carried out for a total
period of 10 nano seconds. The time step was considered as 0.001 and the temperature relaxation
time was set to 0.2 pico seconds. The position, velocity and acceleration were saved every 0.5
pico seconds
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Prediction of Binding site for Ligands
The binding site for docking of our ligand candidates was defined by the donepezil inhibitor
obtained from the AChE crystal structure (PDB:http://www.rcsb.org/pdb, PDB ID: 1B41). The
donepezil
molecule
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AChE
crystal
structure
(PDB:http://www.rcsb.org/pdb, PDB ID: 4EY7). It was positioned into the 1B41 structure by
alignment and superposition of the two proteins. The docking routine within MOE allows the
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user to define a binding region from the donepezil molecule. In our case we used r </= 10 A .
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Molecular Docking
The ligand data base generated from the list of all novel ligand molecules was docked into the
specified binding domain of the AChE receptor using alpha PMI (Principle Moments of Inertia)
placement methodology where Poses are generated by aligning ligand conformations principal
moments of inertia to a randomly generated subset of alpha spheres in the receptor site. Thirty
docked conformations were generated for each ligand and ranked by alpha HB scoring function
which is a linear combination of the geometric fit of the ligand to the binding site and hydrogen
bonding effects. From all the receptor-ligand complexes, the conformation with the lowest
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docking score was chosen for the analysis . The interaction of all ligand molecules in the
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binding domain cavity was analyzed from ligand interaction study of MOE. The ligand-receptor
complexes were analyzed by both London ꢀG free energy approximations and interaction
energies, ꢀE.
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Pharmacophore Model
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A pharmacophore defines both features and locations of important binding interactions between
a ligand and its receptor. Our pharmacophore model was constructed by overlapping the top 6
ligand candidates that calculated with the strongest binding affinity. The Unified scheme within
MOE was used to define the features thought to be important for ligand binding. The locations
of these features were determined by inspection of strong interactions of the ligands with the
AChE receptor.
Chemistry
General
All reagents were commercially available and used without further purification. Melting points
were determined in open capillary tubes on a Laboratory Devices Mel-Temp apparatus and are
1
13
uncorrected. H and C NMR spectra were recorded in d -DMSO on a Bruker DRX-500
6
spectrometer operating at 500 MHz, and 125 MHz, respectively and calibrated to the solvent
peak. Abbreviations used for the split patterns of proton NMR signals are: singlet (s), doublet
(d), triplet (t), quartet (q), quintet (qui), multiplet (m) and broad signal (br). High-resolution mass
spectrometry (HRMS) was recorded on a LCT Premier Spectrometer.
Synthesis of methyl 4-(4-hydroxy-3-(methoxycarbonyl) phenyl)-6-methyl-2-thioxo-1, 2, 3, 4-
tetrahydropyrimidine-5-carboxylate (4e)
To a stirred solution of ethyl acetoacetate (1 mmol), methyl 5-formyl-2-hydroxybenzoate (1
mmol) and thiourea (1 mmol) in ethanol (10 mL) was refluxed in the presence of poly
phosphoric acid (1 mmol %) for 8 h. The progress of the reaction was monitored by TLC
(dichloromethane: ethyl acetate, 1:1 v/v). After completion of the reaction, the reaction mixture
was cooled to room temperature, and it was poured into crushed ice (20 g) and formed the white
solid. The solid was filtered under suction, washed with ice-cold water and then recrystallized
from hot ethanol to afford the methyl 4-(4-hydroxy-3-(methoxycarbonyl) phenyl)-6-methyl-2-
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thioxo-1, 2, 3, 4-tetrahydropyrimidine-5-carboxylate (4e), white crystals; yield: 87 %; mp: 211-
2
13 °C; R 0.32; (dichloromethane: ethyl acetate, 1:1 v/v). IR: 3344, 3238, 2974, 2883, 1924,
f
-1 1
1714, 1668, 1568, 1527, 1348, 1253, 881, 736, 698 cm ; H NMR (DMSO-d )
δ
2.30 (s, 3H),
6
3.55 (s, 3H), 3.89 (s, 3H), 5.14 (d, J = 5.0 Hz, 1H), 6.98-7.00 (m, 1H), 7.33-7.35 (m, 1H), 7.64
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(
d, J = 5.0 Hz, 1H), 9.63-9.66 (m, 1H), 10.36-10.39 (m, 1H), 10.49 (s, 1H); C NMR (DMSO-
d ) 13.9, 17.2, 51.1, 52.5, 53.2, 59.6, 100.1, 112.9, 117.8, 127.9, 133.6, 134.2, 145.4, 159.4,
65.5, 168.8, 173.9.
δ
6
1
The same experimental procedure was adopted for the preparation of the remaining title
compounds 4a-4j
Ethyl 4-(4-hydroxy-3-(methoxycarbonyl) phenyl)-6-methyl-2-thioxo-1,2,3,4-tetrahydropyrimidine-
5
-carboxylate (4j)
White crystals, 84% yield; mp: 239-241 °C; R 0.30; (dichloromethane: ethyl acetate, 1:1 v/v).
f
Yield: 82%; IR: 3330, 3236, 2927, 2883, 1924, 1714, 1668, 1568, 1525, 1346, 1253, 1091, 1051,
-1 1
8
81, 738, 698 cm ; H NMR (DMSO-d )
δ
1.11 (t, 3H), 2.29 (s, 3H), 3.89 (s, 3H), 3.96-4.06
6
(
m, 2H), 5.14 (d, J = 5.0 Hz, 1H), 6.99 (d, J = 10.0 Hz, 1H), 67.34 (m, 1H), 7.65 (d, 1H), 9.63-
1
3
9.64 (m, 1H), 10.36 (d, 1H), 10.48 (s, 1H); C NMR (DMSO-d )
δ
13.9, 17.1, 52.5, 53.3, 59.6,
6
1
00.4, 112.8, 117.9, 127.9, 133.6, 134.6, 145.1, 159.3, 164.9, 168.8, 173.9. HRMS cald for
+
C H N O S (M+H) 350.0936; found 453.0900 (TOF MS ES ).
16
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2
5
Synthesis of ethyl 3-hydroxy-7-methyl-5-(3-nitrophenyl)-3-phenethyl-3, 5-dihydro-2H-
thiazolo [3, 2-a] pyrimidine-6-carboxylate (6a)
To a solution of ethyl 6-methyl-4-(3-nitrophenyl)-2-thioxo-1,2,3,4-tetrahydropyrimidine-5-
carboxylate (4a) (1 mmol) in water (5 mL), and tetrahydrofuran (2.5 mL) and 1-bromo-4-
phenylbutan-2-one (1 mmol) was added to this solution, and the reaction mixture was stirred for
8 h at room temperature. The progress of the reaction was monitored by TLC (dichloromethane:
ethylacetate1:1). After completion of the reaction, white solid was formed. The solid was filtered
off and washed with water and dried. The solid was recrystallized from methanol to get the pure
product of ethyl 3-hydroxy-5-(4-hydroxy-3-(methoxycarbonyl) phenyl)-7-methyl-3-phenethyl-
3,5-dihydro-2H-thiazolo[3,2-a]pyrimidine-6-carboxylate (6a). Color less solid, Rf 0.37;
(
dichloromethane: ethyl acetate, 1:1 v/v). Yield: 83%; m.p.: 217-220 ºC; IR: 3232, 2902, 2864,
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690, 2362, 1712, 1666, 1569, 1529, 1350, 1259, 1091, 748, 703 cm-1; H NMR (DMSO-d ) δ
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.18 (t, 3H), 2.27 (s, 3H), 2.39 (s, 2H), 2.67-2.85 (m, 2H), 3.54-3.58 (m, 1H), 3.96-4.19 (m, 3H),
5.80 (s, 1H), 6.922-6.95 (m, 1H), 7.12-7.32 (m, 5H), 7.64-7.70 (m, 1H), 7.78-7.89 (m, 1H), 8.14-
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8.20 (m, 2H); C NMR (DMSO-d )
δ
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22.3, 123.2, 123.7, 126.2, 127.7, 128.2, 128.4, 130.7, 140.0, 143.8, 147.4, 147.6, 163.4, 166.6.
+
HRMS cald for C H N O S (M+H) 468.1593; found 468.1574 (TOF MS ES ).
2
4
26
3
5
The same experiment procedure was followed for the remaining title compounds 6b-6j.
Synthesis of ethyl 7-methyl-5-(3-nitrophenyl)-3-phenethyl-5H-thiazolo [3, 2-a] pyrimidine-
6
-carboxylate (7a)
Ethyl 3-hydroxy-7-methyl-5-(3-nitrophenyl)-3-phenethyl-3, 5-dihydro-2H-thiazolo [3, 2-a]
pyrimidine-6-carboxylate (1mmol) in water (5 mL), and ethanol (3 mL) was taken in a reaction
flux and refluxed for 6h. The progress of the reaction was monitored by TLC (dichloromethane:
ethylacetate1:1). After completion of the reaction, the solvent was removed under reduced
pressure. The solid was recrystallized from methanol to afforded the title compound methyl 7-
methyl-5-(3-nitrophenyl)-3-phenethyl-5H-thiazolo [3, 2-a] pyrimidine-6-carboxylate (7a). Color
less solid, R 0.40; (dichloromethane: ethyl acetate, 1:1 v/v). Yield: 81%; m.p.: 236-238 ºC; IR:
f
-1 1
3
055, 2981, 2894, 2684, 2360, 1683, 1591, 1527, 1348, 1110, 1010, 748 cm ; H NMR (DMSO-
d ) 1.22 (t, 3H), 2.40 (s, 3H), 2.63-2.71 (m, 2H), 2.78-2.84 (m, 1H), 3.07-3.13 (m, 1H), 4.01-
4.19 (m, 2H), 6.64 (s, 1H), 7.09-7.25 (m, 6H), 7.71 (t, 1H), 7.78-7.80 (m, 1H), 8.21-8.25 (m,
δ
6
1
3
2
H); C NMR (DMSO-d ) δ 13.9, 18.3, 27.2, 32.0, 57.5, 60.6, 101.5, 108.7, 122.1, 124.1, 126.3,
6
1
28.2, 128.3, 131.1, 133.6, 139.4, 140.6, 141.7, 147.8, 161.4, 163.7. HRMS cald for
+
C H N O S (M+H) 450.1488; found 450.1475 (TOF MS ES ).
24
24
3
4
The same experimental method was adopted for the preparation of the remaining title
compounds (7b-j).
Powder Pattern and single crystal structure comparison for compound 6a
Room temperature x-ray powder patterns were obtained using monochromated CuKα radiation
(λ= 1.54178 Å) on a Bruker Proteum Diffraction System equipped with Helios multilayer optics,
an APEX II CCD detector and a Bruker MicroStar microfocus rotating anode x-ray source
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operating at 45kV and 60mA. The powders were mixed with a small amount of Paratone N oil
to form a paste that was then placed in a small (< 0.5 mm.) nylon kryoloop and mounted on a
goniometer head. The specimen was then positioned at the goniometer center-of-motion by
translating it on the goniometer head. Three overlapping 1 minute 180º φ-scans were collected
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using the Bruker Apex2 V2010.3-0 software package with the detector at 2θ = 30º, 60º and 90º
using a sample-to-detector distance of 50.0 mm. These overlapping scans were merged and
converted to a RAW file using the Pilot/XRD2 evaluation option that is part of the APEX2
software package. This RAW file was then processed using the Bruker EVA powder diffraction
software package.
Crystal data and structure determination of the synthesized compound
Colorless single-domain crystals of 2H-thiazolo [3,2-a]pyrimidines (6a) and (6e) and 5H-
thiazolo[3,2-a]pyrimidines (7a) and (7i) suitable for single-crystal x-ray diffraction studies were
grown from methanol. Crystallographic data and refinement results are summarized in Table 1
for 6a and 6e and in Table 2 for 7a and 7i. Full hemispheres of redundant diffracted intensities
[5237 (6a), 5233 (6e), 5237 (7a) or 4438 (7i) 2-5 second frames for each with an ω- or φ-scan
width of 0.50°] were measured at 100(2)K for single-domain specimens of all four compounds
using monochromated CuKα radiation (λ= 1.54178 Å) on a dual-detector Bruker Proteum Single
Crystal Diffraction System equipped with Helios high-brilliance multilayer optics, an APEX II
CCD (6a, 6e and 7a) or Platinum 135 (7i) CCD detector and a Bruker MicroStar microfocus
rotating anode x-ray source operating at 45kV and 60mA. Sample-to-detector distances of 50
mm (6a, 6e and 7a) and 180 mm (7i) were used to collect data. Lattice constants were
determined with the Bruker SAINT software package using peak centers for 9875 (6a), 9869
(
6e), 8270 (7a) and 9796 (7i) reflections. Integrated reflection intensities were produced for all
5
4
structures using the Bruker program SAINT and the data were corrected empirically for
variable absorption effects using equivalent reflections. The Bruker software package
SHELXTL was used to solve the structure using “direct methods” techniques. All stages of
2
weighted full-matrix least-squares refinement were conducted using F data with the SHELXTL
o
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The final structural models for all four structures incorporated anisotropic thermal
parameters for all nonhydrogen atoms and isotropic thermal parameters for all hydrogen atoms.
All hydrogen atoms were located in a difference Fourier and then included in the structural
model as individual isotropic atoms whose parameters were allowed to vary in least-squares
refinement cycles. The methyl groups for 7i were incorporated into the final structural model as
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rigid groups (using idealized sp -hybridized geometry and a C-H bond length of 0.98 Å) that
were allowed to rotate freely about their C-C bonds in least-squares refinement cycles; the
isotropic thermal parameters for the methyl hydrogen atoms were allowed to vary. The
structures of 6a, 6e, 7a, and 7i are shown in Figures 1-2 and 4-6, respectively. Tables of
fractional atomic coordinates, thermal parameters, bond lengths and angles, torsion angles and
hydrogen bonding parameters for the structures of 6a, 6e, 7a, and 7i are given in the
supplementary material.
3
. RESULTS AND DISCUSSION
AChE inhibitors design
5
6, 57
In order to develop drugs for Alzheimer’s treatment
, a series of compounds were designed
and their capacity to inhibit AChE activity was predicted by QSAR and molecular docking
studies. Pharmacokinetic properties like absorption, distribution, metabolism, and excretion
(ADME) were also defined to predict their adverse effects in the system. The QSAR analysis
helped to derive highly applicable models that permitted the design of novel and reactive
5
7
molecules. Preliminary structure–activity relationship (SAR) studies indicated that the
38, 58
pyrimidine moiety is required for inhibition of AChE activity.
This is consistent with
3
8-41
pyrimidine derivatives being widely used as treatment of AD at different stages.
Pyrimidine
derivatives have been useful for treating diseases associated with the deposition of beta-amyloid
3
9
peptide in the brain (such as Alzheimer’s disease ), and as microtubule affinity regulating
kinase inhibitors or in the treatment or prevention of tauopathies.
As acetylcholinesterase (AChE) plays a key role in the regulation of the cholinergic system,
inhibition of AChE has emerged as one of the most promising strategies for the treatment of AD.
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38, 59-61
Pyrimidine derivatives were therefore built and screened virtually using the docking
method.
The goal of the present work was to synthesize AChE inhibitor drugs with enhanced
bioavailability by increasing the number of aromatic substituents on the basic pyrimidine core.
This should increase affinity for the dual binding sites of AChE and increase the acetylcholine
level in the brain. The 5H-thiazolo [3,2-a]pyrimidines provide the minimum functionality
necessary to achieve good binding deep in the AChE dual active site. Since pyrimidine species
also provide remarkable enhancements of permeation across biological membranes and of oral
bioavailability, we set out to design and synthesize small drug molecules incorporating
substituted 2H-thiazolo [3,2-a]pyrimidine and 5H-thiazolo [3,2-a]pyrimidine moieties (Schemes
2) that might have the capacity to cross the BBB and inhibit AChE activity. To further enhance
the potential for inhibition, 5H-thiazolo[3,2-a]pyrimidines were designed to incorporate
significant intramolecular flexibility by linking polar groups having highly favorable enthalpic
interactions with conserved enzyme residues in the dual binding site.
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60
Chemistry
A series of novel 2H-thiazolo [3,2-a]pyrimidine and 5H-thiazolo[3,2-a]pyrimidine derivatives
were synthesized with variations at the aromatic rings and their linking group. As shown in
Scheme 2, various aromatic aldehydes, thiourea and ethylacetoacetate/methylacetoacetate (2)
were mixed with polyphosphoric acid (PPA) (5 mol %) in ethanol (10mL) in a one-pot, three-
component reaction. The reaction mixture was refluxed with stirring for 6-8 hours. PPA is an
extremely efficient catalyst for this reaction. All the reactions were carried out following this
general procedure. On each occasion, the spectral data (IR, NMR, and HRMS) of prepared
known compounds were identical with those reported in the literature. Further, the intermediate
dihydropyrimidines 4a-4j were reacted with 1-bromo-4-phenylbutan-2-one at room temperature
for 6-12 h to give a solid. This was filtered and washed with water to obtain compounds 6a-6j in
high yields (80–95%). Since this resulted in diastereomers having two chiral centers i.e 6a-6j, we
employed simple diastereomeric crystallization to separate them. Diastereomeric crystallization
6
2
is used so widely that it provides a measure for judging alternative processes. The salts formed
are diastereomers with different physical properties and may be separated in a number of ways,
for example by chromatography, but the most efficient method of separating such diastereomers
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is by crystallization. Many significant pharmaceuticals are resolved using diastereomeric
62
crystallization. This is a widely used technique in manufacturing processes for providing
single-isomer drugs produced by synthetic means. A study of a representative group of market
drugs shows that more than 65% are manufactured by methods involving diastereomeric
0
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63, 64
crystallization of salts.
We have preferentially isolated a single compound (diasteromer B) from the equilibrium
shown in Scheme 2 using diastereomeric crystallization of the HBr salt (the HBr was produced
from the reaction of 4a-4j with 5a-5j). Salts 6a and 6e were the principal crystalline material
that formed in methanol. This was verified by determining the solid-state structures for single
crystals of 6a and 6e using x-ray diffraction (Table 1) and obtaining an experimental PXRD
pattern for the bulk solid. This experimental powder pattern for the bulk was then compared
with a calculated powder using atomic coordinates for the (single) crystal structures for 6a and
6e (Figure 1 & 2).
Insert Scheme1, Figure 1-2 & Table 1
Figures 3 & 4 each show a black experimental powder pattern for the dry bulk material from the
crystallization vial that is superimposed with a red powder pattern calculated for the single
crystal structures of compounds 6a and 6e, respectively. Each black pattern was obtained with
some of the dry bulk solid from the crystallization vial that had been ground to a powder. Each
red pattern was calculated with atomic coordinates resulting from the single crystal structure
65
determination of compound 6a or 6e using the public-domain Mercury software package .
Clearly, the peaks for both sets of superimposed patterns occur at the same places and generally
have the same relative heights. This indicates the significant presence of just one crystalline
material (6a & 6e) in the bulk solid that resulted when all of the solvent evaporated. Both bulk
samples also contain a minor component that is an amorphous solid.
Insert Figure 3 & 4
Compounds 6a-6j were further refluxed for 6-8 h to form the compounds 7a-7j in high yields.
The synthetic route utilized to make our target “AChE inhibitors” compounds 6a-6j and 7a-7j is
shown in Scheme 1. The chemical structures of the new compounds were confirmed by
1
13
elemental analysis, IR, H NMR, C NMR spectral- and HRMS; the data are presented in the
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experimental section. Structures for compounds 6a, 6e, 7a (Figure 5 & Table 2) and 7i (Figure 6
&
Table 2) were further confirmed by single crystal XRD.
Insert Figure 5 -6 & Table 2
Insert Scheme 2 & Table 3
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QSAR study
Three-dimensional structures were built for compounds 6a-6j and 7a-7j and optimized in a MOE
working environment. Molecular dynamics simulations were carried out for each molecule and
molecular descriptors were determined followed by QSAR linear regression study (Table 4). The
correlation model showed a linear plot for both measured IC values and values predicted for
5
0
2
3, 38, 58, 61
the training set of molecules (Figure 7).
The correlation analysis showed an RMSD of
2
4.0 and r value of 0.86. This linearity for the model indicates the reliability of QSAR to
compare and predict the activity of a test set molecules (Figure 8).
QSAR Descriptors
Insert Table 4 & Figure 7 -8
Principal Component Analysis
A principal component analysis using the QSAR descriptors showed that the first two PCA
eigenvectors included 100% of the variance. All the data values were found to lie in the range of
-3 > PCA 1 < +3 and -2 > PCA 2 < +2, where each spot in the plot represents a molecule. Most
interestingly, the most active compounds in our data set, as shown in magenta, are distinctly
isolated from the other molecules within the region: 0 > PCA1< 3.0 and 0.5 > PCA2 < - 3.0
(Figure 9). This could provide an addition criterion for compound selection.
Insert Figure 9
Molecular docking of AChE inhibitors:
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Molecular modeling has often been proven to be a powerful tool for rationalizing ligand-target
interactions and for making this information available to virtual screening techniques. Molecular
modeling studies were performed using human AChE, since they represent the pharmacological
target for the development of new drugs for the treatment of AD. The crystal structure of AChE
protein (1B41) was loaded into MOE (Molecular Operating Environment (MOE, version
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012.10) with a resolution of 2.76 Å and a library was constructed for all the lead molecules .
6
7
The binding site of human AChE protein was identified from PDBSum and the residues D74,
W86, N87, G120, G121, G122, Y124, S125, G126, L130, E202, S203, F297, Y337, F338, Y341,
H447, G448, and I451, were found to be interacting residues as shown in Figures 10-15.
Docking of Donepezil with AChE (1B41)
As a validation of the docking procedure (Figure 10), the structure of the 1B41-Donepezil
complex was analyzed and the binding affinity (GBV/WSA scoring function) and Generalized
Born solvation energy were calculated.
Insert Figure 10
The binding affinity (GBV!/WSA scoring function) of Donepezil was calculated as -8.0 (+/- 0.3)
kcal/mole, and Generalized Born solvation energy as -28.2(+/- 1.0) kcal/mole. Donepezil
therefore binds with >3 kcal/mole greater solvation energy than our predicted lead compounds,
6c, 7c and 7h (Table 5). Donepezil also has a 0.3 - 0.6 kcal/mole lower calculated affinity than
compounds 6c, 7c and 7h but this is within the 2σ limit. However Donepizel has slightly higher
solvation energy than the other compounds. It’s tempting to suggest it gains additional binding
affinity by its desolvation stabilization within the aromatic lined “groove” site (PAS region) of
the human AChE receptor, as compared to our inhibitor candidates.
Therefore, the docking procedure that was used gives us information about important ligand-
receptor interactions and ligand affinities, using a protocol including molecular mechanics,
genetic algorithm, and Lamarckian GA calculations. On the basis of the obtained hits, 5H-
thiazolo [3,2-a]pyrimidine and 2H-thiazolo [3,2-a]pyrimidine derivatives emerged as promising
candidates. Selected conformers of compounds were docked into the human AChE structure
(PDB code 1B41), shown in Figures 11-15.
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Among all docking conformations, compounds 7c had the best least docking score of -8.6
kcal/mole and the next best docking scores were for compounds 6c and 7h with docking scores -
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three ligands had the first best least docking scores with stable ligand pose interactions in the
docking sphere followed by the remaining lead compounds.
Insert Figure 15 & Table 5
Pharmacophore Model
AChE Inhibitor 4 Feature Pharmacophore Model
Insert Figure 16 & Table 6
The Pharmacophore model selected 13 out of 20 compounds in the database as hits. These are
identified under “Comp ID”. The column “$PRED_HITS” gives a calculated % Inhibition value
from the QSAR model. The positive values are considered as active hits, which include
compounds 6c, 6d, 6h, 7c and 7h.
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ADME predictions
ADME properties are important conditions and major parts of pharmacokinetics. Viable drugs
should have perfect ADME properties for it to be approved as a drug in clinical tests. The
ADME predictions of the present 20 compounds show satisfactory results. Among the twenty,
compounds 6a-6j and 7a-7j show good intestinal absorption. All of them show moderate
permeability for in vitro Caco-2 cells and low permeability for in vitro MDCK cells. In vivo
blood-brain barrier penetration capacity was predicted to have middle absorption to the CNS
(Central Nervous System) for the compounds 6c, 6g, 6h, and 7a-7j whereas low absorption to
the CNS was observed for the compounds 6a, 6b, 6d, 6e, 6f, 6i, and 6j. Blood brain barrier
penetration is a crucial pharmacokinetic property because CNS-active compounds must pass
across it and CNS-inactive compounds must not pass across it to avoid CNS side effects.
Generally, the degree to which any drug binds to plasma protein influences not only the drug
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action but also its disposition and efficacy. Usually, the drug that is unbound to plasma proteins
will be available for diffusion or transport across cell membranes and thereby finally interact
with the target. Herein with respect to ADME, the percent of drug bound with plasma proteins
was predicted and the compounds 6a-6j and 7a-7j were predicted to bind strongly. The predicted
ADME properties and their values are shown in the table 7.
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4. CONCLUSIONS AND FUTURE DIRECTIONS
This study described the design, synthesis, diastereomeric crystallization, docking, 2D QSAR
and pharmacophore studies for a series of highly selective inhibitors of AChE. The
pharmacophore model reflected the binding mode and important interactions of the ligands
binding to the dual site of the enzyme. The ligand-oriented study used multiple contributions of
ligand features to build a quantitative pharmacophore model from a training set of 20 AChE
inhibitors with known IC50 values. The best pharmacophore model contained four basic
pharmacophore features with a correlation coefficient of 0.90: two hydrogen bond acceptors and
two hydrophobic interactions. This pharmacophore model was then applied to the novel set of
20 test molecules that have been synthesized and described in the chemistry section. Taken
individually, the docking, 2D QSAR and pharmacophore studies for the test set each indicated
that at least six of the twenty test compounds should be reasonable inhibitors of AChE. All test
compounds showed proper drug-like 2D QSAR and ADMET properties. The ligand-protein
complexes generated with molecular docking indicated that the six of the test molecules should
be good AChE inhibitors since they showed good binding affinity with the dual sites of the
enzyme receptor. Five of the twenty had good QSAR values and four of the twenty had good
pharmacophore values. However, only three of the twenty test compounds (6c, 7c and 7h) had
good docking, QSAR and pharmacophore values, Figure 17. It therefore seems that by
combining all three of these evaluation procedures, large numbers of new compounds can be
screened as possible inhibitors of AChE. Since the present results indicate that compounds 6c,
7c and 7h should be excellent candidates for inhibition of AChE, we plan to use them as a
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starting point for developing even more potent analogues for the treatment of the Alzheimer’s
disease.
Insert Figure 17
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ACKNOWLEDGMENTS
This study was supported by grant awards (R01GM095355, R37AG037319, and
PO1AG017490) from the National Institute of General Medical Sciences and the
National Institute on Aging. The authors thank the National Science Foundation (grant
CHE-0923449) and the University of Kansas for funds to purchase the x-ray
instrumentation and computers.
ASSOCIATED CONTENT
Supporting Information: Experimental details and spectroscopic data of synthesized
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compounds H, C, NMR chromatograms and crystal structures supporting tables. This material
is available free of charge via the Internet at http://pubs.acs.org.
ABBREVIATIONS
AChE, Acetylcholinesterase; ACh, acetylcholine; AD, Alzheimer’s disease; AChEIs,
Acetylcholinesterase inhibitors; Aβ, amyloid beta; QSAR, quantitative structure–activity
relationship; CoMFA, comparative molecular field analysis; ADMET, absorption, distribution,
metabolism and excretion and toxicity; FDA, Food and Drug Administration; BBB, blood brain
barrier; Caco2, human colon adenocarcinoma; MDCK, Madin-Darby canine kidney; SAR,
structure–activity relationship; CNS, central nervous system; MOE, molecular operating
environment; RMSE, Root mean square error; PCA, Principle Component Analysis; PDB,
Protein Data Bank; MMFF94x, The Merck Molecular Force Field;
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Figure 1. Crystal structure for HBr salt of 6a showing 50% probability displacement ellipsoids
and atom-numbering scheme
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