Affinity of aporphines for the human 5-HT2A receptor: Insights from homology modeling and molecular docking studies

Article abstract of DOI:10.1016/j.bmc.2010.06.043

Analogs of nantenine were docked into a modeled structure of the human 5-HT_2A receptor using ICM Pro, GLIDE, and GOLD docking methods. The resultant docking scores were used to correlate with observed in vitro apparent affinity (K_e) data. The GOLD docking algorithm when used with a homology model of 5-HT_2A, based on a bovine rhodopsin template and built by the program MODELLER, gives results which are most in agreement with the in vitro results. Further analysis of the docking poses among members of a C1 alkyl series of nantenine analogs, indicate that they bind to the receptor in a similar orientation, but differently than nantenine. Besides an important interaction between the protonated nitrogen of the C1 alkyl analogs and residue Asp155, we identified Ser242, Phe234, and Gly238 as key residues responsible for the affinity of these compounds for the 5-HT_2A receptor. Specifically, the ability of some of these analogs to establish a H-bond with Ser242 and hydrophobic interactions with Phe234 and Gly238 appears to explain their enhanced affinity as compared to nantenine.

Full text of DOI:10.1016/j.bmc.2010.06.043

Bioorganic & Medicinal Chemistry 18 (2010) 5562–5575
Contents lists available at ScienceDirect
Bioorganic & Medicinal Chemistry
journal homepage: www.elsevier.com/locate/bmc
Affinity of aporphines for the human 5-HT2A receptor: Insights from
homology modeling and molecular docking studies
Stevan Pecic a, Pooja Makkar b, Sandeep Chaudhary a, Boojala V. Reddy b, Hernan A. Navarro c,
Wayne W. Harding a,
*
a Department of Chemistry, Hunter College, City University of New York, 695 Park Avenue, New York, NY 10065, USA
b Department of Computer Science, Queens College, City University of New York, 6530 Kissena Blvd., New York, NY 11367, USA
c Center for Organic and Medicinal Chemistry Research Triangle Institute, Research Triangle Park, North Carolina, NC 27709, USA
a r t i c l e i n f o
a b s t r a c t
Article history:
Analogs of nantenine were docked into a modeled structure of the human 5-HT2A receptor using ICM Pro,
GLIDE, and GOLD docking methods. The resultant docking scores were used to correlate with observed
in vitro apparent affinity (Ke) data. The GOLD docking algorithm when used with a homology model of
5-HT2A, based on a bovine rhodopsin template and built by the program MODELLER, gives results which
are most in agreement with the in vitro results. Further analysis of the docking poses among members of
a C1 alkyl series of nantenine analogs, indicate that they bind to the receptor in a similar orientation, but
differently than nantenine. Besides an important interaction between the protonated nitrogen of the C1
alkyl analogs and residue Asp155, we identified Ser242, Phe234, and Gly238 as key residues responsible
for the affinity of these compounds for the 5-HT2A receptor. Specifically, the ability of some of these ana-
logs to establish a H-bond with Ser242 and hydrophobic interactions with Phe234 and Gly238 appears to
explain their enhanced affinity as compared to nantenine.
Received 20 April 2010
Revised 8 June 2010
Accepted 14 June 2010
Available online 20 June 2010
Keywords:
Nantenine
Aporphine
Serotonin
MDMA
5-HT2A
Published by Elsevier Ltd.
1. Introduction
receptor may be used for treatment of sleep disorders and arousal.4
The utility of antagonists in the treatment of depression and cer-
At present there are 13 distinct serotonin G-protein-coupled
receptors that are divided into six families, based on pharmacol-
ogy, amino acid sequences, gene organization, and second messen-
ger coupling pathways.1,2 The serotonin 5-HT2A receptor is of
significant clinical interest because of its involvement in cardiovas-
cular function and in certain mental disorders.3 Agonists at this
tain psychotic conditions has already been well explored.5,6 The
investigation of 5-HT2A antagonists as potential drug-abuse thera-
peutics is topical in the recent literature.7,8
Aporphines have been relatively unexplored as 5-HT2A receptor
ligands, but it is known that they bind to several other CNS recep-
tors. The aporphine natural product nantenine is a moderate
5-HT2A receptor antagonist and functions in vivo as an antagonist
to a range of behavioral and physiological effects of MDMA
(‘Ecstasy’).9 Very little is known about the structural requirements
for affinity and activity of nantenine at the 5-HT2A receptor. As part
of our ongoing efforts to develop novel aporphine-based 5-HT2A
antagonists as potential MDMA antagonists, we prepared a series
of analogs based on nantenine and evaluated their affinity and
activity at the 5-HT2A receptor.10,11 The analogs were specifically
designed to investigate the role of molecular rigidity, N-substitu-
tion and substitution at the C1 position on 5-HT2A affinity and
activity. This study resulted in the identification of C1 analogs with
up to 12-fold increase in 5-HT2A apparent affinity (Ke) as compared
to nantenine.11
Abbreviations: 5-HT, 5-hydroxytryptamine, serotonin; AcOH, acetic acid; Boc,
tert-butoxycarbonyl; BLAST, Basic Local Alignment Search Tool; BRho, bovine
rhodopsin; CDI, 1,10-carbonyldiimidazole; D, aspartic acid; DCM, dichloromethane,
methylene chloride; DMA, N,N-dimethylacetamide; DMAP, 4-(dimethylamino)pyr-
idine; DME, 1,2-dimethoxyethane; DMF, dimethylformamide; DMSO, dimethyl
sulfoxide; ECL, extracellular loop; ee, enantiomeric excess; ESI-MS, electrospray
ionization mass spectrometer; GA, Genetic Algorithm; GPCR, G-protein-coupled
receptor; ICM, Internal Coordinate Mechanics; HPLC, high-performance liquid
chromatography; HAda2a, human adenosine A2A receptor; HAdrb2, human b2-
adrenergic receptor; ICL, intracellular loop; MC, Monte Carlo; MDMA, 3,4-methyl-
enedioxy-N-metamphetamine; PDB, Protein Data Bank; Phe, F, phenylalanine;
RMSD, root-mean-square deviation; SAR, structure–activity relationship; SAVES,
Structural Analysis and Verification Server; Ser, S, serine; SRho, squid rhodopsin;
TAdrb1, turkey b1-adrenergic receptor; THF, tetrahydrofuran; TM, transmembrane;
TMSCl, tert-methylsilyl chloride; Trp, W, tryptophan; Tyr, Y, tyrosine; Val, V, valine;
ZEGA, Zero Gap; Zrms, Z-score RMS; Zsm, Z-score standard mean; Zstd, Z-score
standard deviation.
In order to understand the possible binding modes of nantenine
and nantenine analogs at the human 5-HT2A receptor (to comple-
ment future drug design efforts), we have conducted a docking
study with our library of compounds. Since the crystal structure
* Corresponding author. Tel.: +1 212 772 5359; fax: +1 212 772 5332.
E-mail address: whardi@hunter.cuny.edu (W.W. Harding).
0968-0896/$ - see front matter Published by Elsevier Ltd.
doi:10.1016/j.bmc.2010.06.043

S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
5563
of the 5-HT2A receptor has not been solved, our approach necessi-
tated the use of a homology modeling paradigm. Although other
homology models for the 5-HT2A receptor have been previously de-
scribed3,12,13 we decided to build and evaluate a number of homol-
ogy models using various in silico tools in order to determine
which model was best in line with our in vitro data. Four homology
models were built based on bovine rhodopsin (PDB code: 1U19)
and human b2-adrenoceptor (PDB code: 2RH1) templates using
two programs for molecular modeling—MODELLER and ICM Pro.
To determine the extent to which our in vitro results correlated
with each homology model, we then performed docking/scoring
experiments, using three docking programs: ICM Pro, GLIDE, and
GOLD.
Based on these experiments we have determined that the
homology model built by MODELLER and based on a bovine rho-
dopsin template together with a GOLD docking algorithm is in
the best agreement with our in vitro results. These studies have
provided useful insights into the possible binding modes of nante-
nine analogs at the 5-HT2A receptor—a significant prelude in our
quest towards potent aporphine-derived 5-HT2A antagonists. Re-
sults from our studies are presented herein.
intermediate amine which was subsequently converted to amides
5a and 5b. These amides were then subjected to Bischler–Napier-
alski cyclization to afford intermediate dihydroisoquinoline prod-
ucts that were sequentially reduced and N-methlyated to provide
the target seco-ring C derivatives 6a and 6b.
Compounds 8a–d were prepared as shown in Scheme 2. We ini-
tially attempted removal of the Boc group of 7 with TFA.14 How-
ever with these conditions only a 50% yield of the amine 8a was
obtained. After some experimentation with other acidic cleavage
conditions, we found that anhydrous ZnBr2 in DCM gave the ex-
pected product in excellent yield. Treatment of 8a with acetalde-
hyde under reductive amination conditions gave 8b. Compound
8c was prepared by reacting 8a with acetyl chloride, while 8d
was obtained after reaction of 8a with methanesulfonyl chloride.
2.2. 5-HT2A receptor affinities from functional inhibition assays
Apparent 5-HT2A receptor affinity (Ke) data were obtained for
each of the target nantenine analogs using a FLIPR (Fluorometric
Imaging Plate Reader) assay and are presented in Table 2. Ke values
give an indirect measure of compound affinity. Ke and Ki values
usually display the same trend in rank-order within a series of
compounds15 and thus it is acceptable to use Ke (instead of Ki) val-
ues in evaluations of compound affinity. Others have shown in
binding studies with 5-HT2A antagonists that there is good correla-
tion between antagonist affinity determined in a FLIPR assay and
those reported in radioligand binding assays and that the rank-or-
der of potency is maintained.16 A functional assay was used instead
of receptor binding because we could obtain functional and affinity
data from the same assay.
2. Results and discussion
2.1. Chemistry
The structures of the nantenine analogs used for our docking
study, 6a–b, 9, 10, 8a–d, and 11a–f are shown in Table 1. Com-
pounds 9, 10, and 11a–f were prepared as reported by us
elsewhere.11
Compounds 6a–b were prepared as outlined in Scheme 1. Com-
mercially available bromo-aldehyde 1 was coupled to 3,4-(methyl-
enedioxyphenyl) boronic acid (2) under Suzuki conditions
affording the biaryl aldehyde, 3. A nitro-aldol reaction on aldehyde
3 followed by reduction of the resulting nitrostyrene (4), gave an
2.3. SAR studies
The apparent affinities of seco-C-ring analogs 6a–b were
>10,000 nM, suggesting together with the results for compounds
Table 1
Structures of nantenine analogs evaluated
O
O
O
O
O
O
O
O
O
NR2
N
N
N
N
R3O
R1
O
O
O
O
O
O
O
O
O
O
6a-b
9
10
8a-d
11a-f
R1
R2
R3
Compound
–H
–CH3
—
6a
6b
9
10
8a
8b
8c
8d
—
—
–H
–CH2CH3
–COCH3
–SO2CH3
—
—
—
–CH3
–CH2CH3
–CH2CH2CH3
Nantenine
11a
11b
–CH2CH2CH2CH3
–CH2CH2CH2CH2CH3
–CH2-Cyclopropyl
–Benzyl
11c
11d
11e
11f

5564
S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
O
CHO
O
O
CHO
b
O
O
NO2
O
O
O
O
HN
R
N
O
+
c
a
f-h
Br
1
then d or e
O
R
B(OH)2
O
O
O
3
O
4
O
O
O
O
5a
R = H
6a
R = H
6b R = CH3
O
5b R = CH3
2
O
Scheme 1. Reagents and conditions: (a) Pd(PPh3)4, DME, K2CO3, reflux, 24 h; (b) CH3NO2, NH4OAc, reflux, 4 h; (c) LiBH4, TMSCl, THF, reflux; (d) HCOOEt, Et3N, DCM for 5a;
(e) acetyl chloride, Et3N, for 5b; (f) POCl3, MeCN, 50 °C, 12 h; (g) NaBH4, MeOH, 0 °C, 4 h; (h) HCHO, NaBH(OAc)3, DCM, rt, 24 h.
O
O
O
O
O
O
b, c or d
a
NBoc
NR
NH
7
8b R=CH2CH3
8c R=COCH3
8d R=SO2CH3
O
8a
O
O
O
O
O
Scheme 2. Reagents and conditions: (i) ZnBr2, DCM, rt, 24 h; (ii) acetaldehyde, NaBH(OAc)3, DCM, rt for 8b; (iii) acetyl chloride, Et3N, DCM, 0 °C for 8c; (iv) methanesulfonyl
chloride, Et3N, DCM for 8d.
Table 2
Results of docking experiments with the ICM Pro, GLIDE, and GOLD
Compound
Ke (nM)
HAdrb2_ICMa
ICM score
BRho_ICMb
ICM score
HAdrb2_MODELLERc
GLIDE score
BRho_MODELLERd
GLIDE score
HAdrb2_MODELLER
GOLD score
BRho_MODELLER
GOLD score
Ketanserin
Nantenine
6a
6b
9
10
8a
8b
8c
32
850
>10,000
>10,000
5180
>10,000
>10,000
>10,000
>10,000
>10,000
890 430
297 130
274 80
171 50
ꢀ75.82
ꢀ54.93
ꢀ48.30
ꢀ50.94
ꢀ54.32
Ne
ꢀ72.28
ꢀ11.43
ꢀ11.23
ꢀ12.03
N
ꢀ4.30
ꢀ8.03
ꢀ8.50
ꢀ8.47
ꢀ8.76
ꢀ9.05
ꢀ8.31
ꢀ8.22
N
27.34
27.19
29.72
N
31.44
N
30.84
33.83
N
30.63
23.42
N
N
N
N
N
N
N
6
N
N
N
ꢀ47.69
ꢀ13.53
N
N
N
N
N
N
ꢀ10
ꢀ51.64
ꢀ13.81
ꢀ13.48
N
N
N
N
8d
N
N
N
N
11a
11b
11c
11d
11e
11f
ꢀ55.14
ꢀ65.37
ꢀ68.37
ꢀ70.39
ꢀ64.75
ꢀ69.79
ꢀ11.45
ꢀ8.94
ꢀ11.20
ꢀ12.06
ꢀ12.21
ꢀ13.44
ꢀ8.30
ꢀ9.09
ꢀ5.01
ꢀ5.05
ꢀ8.03
ꢀ11.67
30.19
31.78
32.53
33.17
33.30
35.64
24.22
22.98
29.10
30.52
29.06
29.48
ꢀ51.87
ꢀ54.23
N
N
N
68
4600
8
a
b
c
5-HT2A receptor homology model built by ICM Pro based on a human b2-adrenoceptor template.
5-HT2A receptor homology model built by ICM Pro based on a bovine rhodopsin template.
5-HT2A receptor homology model built by MODELLER based on a human b2-adrenoceptor template.
5-HT2A receptor homology model built by MODELLER based on a bovine rhodopsin template.
N, not in the binding pocket or no key Asp155-NH3þ interaction (determined by visual inspection).
d
e
9 (Ke = 5180 nM) and 10 (Ke > 10,000 nM) that the intact aporphine
core is required for 5-HT2A receptor affinity.
reported by us.11 Briefly, these SAR studies indicate that the C1 po-
sition may be tolerant of bulky lipophilic groups and that this site
may be a key position to modify in order to improve affinity for the
5-HT2A receptor. The enhanced affinity of members of the C1 series
of analogs compared with the parent molecule suggested to us that
they may interact differently with the 5-HT2A receptor.
Removal of the methyl group from position N6 (i.e., compound
8a) also led to a noticeable decrease in affinity as compared to
nantenine. Placing a slightly bulkier ethyl group instead of a
methyl group at the same position, (compound 8b), gave similar
results as compound 8a. Compounds 8c–d showed decreased affin-
ity, likely because of the absence of a basic nitrogen atom in these
compounds; it has been previously proposed that the nitrogen of
nantenine is involved in an ionic bond with Asp155 of helix 3 in
the 5-HT2A receptor and that this interaction is important for bind-
ing of nantenine to the receptor.17 In summary, for the less rigid
and N-analogs only compound 9 showed any appreciable (though
quite weak) affinity for the receptor.
2.4. Molecular modeling
Scheme 3 summarizes the general approach we have taken in
this study.
2.4.1. Selection of templates
The main challenge in homology modeling is to find a suitable
template. Since the crystal structure of the 5-HT2A receptor is still
not solved, and the direct determination, by X-ray crystallography
The effects of substituent changes at the C1 position (i.e., com-
pounds 11a–f) on the affinity of nantenine have already been

S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
5565
Scheme 3. Flowchart summarizing the approach used in this study.
of the atomic structure of any member of the serotonin receptor
family has not yet been accomplished, the only way to achieve
our objective is to use a similar GPCR structure as a template to
build a homology model. We searched for templates using BLAST18
(Basic Local Alignment Search Tool)—see Section 4. Currently there
are four available crystal structures of mammalian GPCRs: turkey
b1-adrenergic receptor (PDB code: 2VT419), human adenosine
A2A receptor (PDB code: 3EML20), human b2-adrenergic receptor
(PDB code: 2RH121), and bovine rhodopsin (PDB code: 1U1922).
In a recent report, Mobarec et al. suggested that a good template
to use to build a homology model for the serotonin 5-HT2A receptor
is either the crystal structure of a turkey b1-adrenergic receptor or
human b2-adrenergic receptor.23
which is a typical representative of the neurotransmitter GPCRs.
On the other hand, the high resolution of its crystal structure and
the specific arrangement of the seven transmembrane helices stabi-
lized by a series of intramolecular interactions make bovine rhodop-
sin a very good structural template for generating molecular models
of the 5-HT2A receptor. Until very recently, there were no experi-
mental structures available for any neurotransmitter GPCRs. A high
resolution (2.40 Å) of the human b2-adrenergic receptor has been
reported.24 It has better sequence similarity with the 5-HT2A recep-
tor (almost 30%) and it is functionally closer to the family of seroto-
nin receptors, since it also belongs to the group of neurotransmitter
GPCRs. Disadvantages are that this crystal structure has been solved
at lower resolution than the one at bovine rhodopsin, and there are
only a few 5-HT2A receptor homology models built using this struc-
ture as a template.12
Although other GPCR structures are modeled in the literature
using bovine rhodopsin as a template, there are some disadvantages
of using this template; for example, it shares a low sequence similar-
ity to 5-HT2A receptor (less than 20%) and it is a retinal-binding pro-
tein, functionally completely different from the 5-HT2A receptor,
As a template for building the 5-HT2A receptor homology model
we selected two different available GPCR crystal structures. The
first one is bovine rhodopsin (PDB code: 1U19) since it has been

5566
S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
shown in many previous reports3,13,25,26 that this structure is a reli-
able template for 5-HT2A receptor homology models and also be-
cause its crystal structure is solved at high resolution of 2.20 Å as
compared to other known structures. The structures resolved be-
low 2.5 Å are normally regarded as very good molecules for dock-
ing, yielding good results for most typical applications.27 We also
selected the human b2-adrenergic receptor (PDB code: 2RH1) as
a second template, because to date 2RH1 is the best resolved struc-
ture (2.40 Å) of any GPCR neurotransmitter receptor.23 The other
BLASTP hit structures were omitted because of their low
resolution.
study we used several different programs for evaluation that are
available via the server of the UCLA-DOE Institute for Genomics
and Proteomics. This Institute offers a service called Structural
Analysis and Verification Server (SAVES)33 that encompass five
verification tools for model evaluation: PROCHECK,34 WHAT_
CHECK,33 ERRAT,35 VERIFY_3D,36 and PROVE.37 We evaluated each
modelusingthe abovemethodsand selectedthe final modelfor each
template(see Section 4 for details), which fits best within the criteria
for selection of each method. From 20 5-HT2A receptor homology
models, whichwere builtby MODELLER32 basedon a bovinerhodop-
sin template (1U19), we selected one homology model (hereinafter
called BRho_MODELLER). A selected model, out of 20 homology
models built by MODELLER, based on human b2-adrenoceptor
template (2RH1), was named HAdrb2_MODELLER. Using ICM Pro
software, two homology models, one for each template, were built,
and both showed good evaluation scores; hence we decided to also
use these for the purpose of docking experiments. We named
them according to the origin of their templates, bovine rhodopsin
and human b2-adrenoceptor—BRho_ICM and HAdrb2_ICM,
respectively.
Only one group (Indra et al.17) has tried to explain a binding
mode of ( )-nantenine at the 5-HT2A receptor.17 However, this
study described a homology model of a rat 5-HT2A receptor. (Since
our in vitro data was based on human rather than rat 5-HT2A recep-
tor data, we have constructed homology models based on the
human 5-HT2A receptor.) The Indra model proposes that Asp155, a
residue in transmembrane helix 3 (TM3) that is strongly conserved
across the family of serotonin receptors, forms a strong H-bond via
N6 of nantenine. The oxygen atom of the C1 methoxy group inter-
acts via H-bonding with Asn343, a residue from TM6, also strongly
conserved in many GPCRs. It is hypothesized that this interaction
may be directly involved in 5-HT2A receptor antagonism.17
2.4.5. Energy minimization
The four selected homology models were relaxed with 500
steps of steepest descent energy minimization using Charmm
and using the Discovery Studio 2.0, we calculated the RMSD values
for the each homology model and their appropriate template struc-
2.4.2. Alignment
Alignments of the target sequence to the template structures
were made using the ClustalX28 alignment tool and the ICM Pro se-
quence alignment program29, both using their default parameters.
The sequence alignment of the human 5-HT2A receptor using
ClustalX shows good sequence identity with the bovine rhodopsin
template (19.5%) with more than 45% sequence similarity. The
same human 5-HT2A receptor sequence has, compared with the
bovine rhodopsin sequence, a higher sequence identity with
the human b2-adrenergic receptor template (almost 28%) with
more than 48% sequence similarity. Although the ICM Pro align-
ment program is based on a different algorithm and method (it
uses ZEGA algorithm with zero gap penalties30) than ClustalX,
the sequence of the human 5-HT2A receptor nevertheless showed
19% sequence identity with the bovine rhodopsin template which
is almost the same as we determined using ClustalX. Also compa-
rable results (30% identity) were obtained when the ICM Pro align-
ment program was used for the b2-adrenergic receptor template
and 5-HT2A receptor sequence (see Section 4). Since the secondary
structure elements are well-conserved among these sequences, the
alignments were then manually refined to ensure a perfect align-
ment of the highly conserved residues of the GPCR superfamily,
according to Baldwin et al.31
ture. The structural superposition of Ca trace of the 5-HT2A recep-
tor homology models with respect to the templates, gave us the
RMSD values: 1.53 for BRho_MODELLER, 2.69 for HAdrb2_MODEL-
LER, 3.73 for the BRho_ICM, and 2.40 for the HAdrb2_ICM (see Sec-
tion 4). All selected homology models share a close homology with
the template as indicated by their RMSD value of their backbone
atoms with respect to the template. The resulting, energy mini-
mized homology models were subsequently used for the docking
experiments.
2.4.6. Docking
There are many commercially available docking software, each
using a different combination of searching methods and algo-
rithms, and scoring functions. We used three programs for docking
experiments and compared the docking scores with our in vitro re-
sults. We selected the ICM Pro docking29 algorithm, GLIDE,38,39 and
GOLD40 methods for the purpose of docking of our analogs. Each
compound that was used for the docking experiment was prepared,
converted to a 3D structure and energy minimized using Chem3D
Ultra41 or LigPrep (developed and distributed by Schrodinger
Inc.—www.schrodinger.com; described in detail in Section 4). The
results from our docking study are summarized in Table 2. After
we performed docking using the different programs and obtained
the docking scores, each structure was visually inspected to be as-
sured that the molecules were actually docked into the expected
binding site and that interactions with key residues of the active site
were maintained. All final receptor–analog complexes, obtained
from the three different programs, were saved as PDB files and visu-
alized in Discovery Studio 2.0 and ICM Pro. H-bonds, hydrophobic
interactions and distances for each 3D structure were calculated
and plotted by LigPlot42 v4.4.2., a program for schematic 2D
diagrams of ligand and receptor plots.
2.4.3. Model construction
3D-Model building was performed with the modeling suite, Dis-
covery Studio 2.0, which uses MODELLER32 for building protein
structures. Twenty models were built for each of the templates
using the homology module of Discovery Studio and one model
for each template was built by the ICM Pro 3.6 model building soft-
ware.29 The conserved disulfide bond between residues C148 at the
beginning of TM3 and C228 in the middle of extracellular loop 2
(ECL2), a feature common in many GPCR receptors, was also cre-
ated and was kept during the building of homology models in both
programs.
A model of the human 5-HT2A receptor has been constructed
using an in silico activated bovine rhodopsin template.13 The major
difference between our bovine rhodopsin homology model of the
5-HT2A receptor and that previously reported is the presence of a
network of polar interactions ‘ionic lock’ that is present between
residues Arg135 (in TM3) and Glu247 (in TM6), which bridges
these two transmembrane helices, stabilizing the inactive-state
conformation. The crystal structures of other GPCRs have revealed
2.4.4. Model evaluation
Evaluation methods check whether a model satisfies standard
steric and geometric criteria. Each of the tools used in the construc-
tion of a model (e.g., template selection, alignment, model building,
and refinement) has its own internal measures of quality. In order to
evaluate and select the best homology model for the purpose of our

S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
5567
that these polar interactions are broken in the ligand-activated
GPCR crystal structures, for example, human b2-adrenoceptor, tur-
key b1-andrenoceptor, and human adenosine A2A. Recent crystal-
lographic evidence suggests that the conformation of the activated
form of bovine rhodopsin does not significantly change in the li-
gand binding region; thus, rhodopsin represents a good template
for homology models of other GPCRs used in docking calculations
of both agonists and antagonists because both ground-state and
photoactivated rhodopsin are structurally similar.43 Therefore, we
did not include this network of polar interactions in our model.
Since 3D-coordinates and the information on model quality
through any of the verification tools (Procheck, Verify_3D, Errat,
etc.) were not available for the previously constructed model, we
are unable to perform any detailed structural comparisons of the
models. Others have also built homology models of BRho with
the MODELLER program.44
Figure 1. Correlation of GOLD score and affinity data for BRho_MODELLER.
Recently, a 5-HT2A receptor homology model based on a human
b2-adrenoceptor was reported by Bruno et al.45 Using this GPCR as
a template is considered more suitable than the bovine rhodopsin
template since sequence identity of the human 5-HT2A receptor
with human b2-adrenoceptor is much better (around 30%), than
with the bovine rhodopsin template (below 20%), and also because
both b2 and 5-HT2A receptors are members of the amine group of
class A GPCRs. Mobarec et al. proposed that generating a 5-HT2A
receptor homology model based on this template will produce a
better homology model.23 We decided to use this template as our
second template. Comparing the alignment constructed by us with
the alignment constructed by Bruno et al. was consistent, including
the disulfide bridge between C148 on TM3 and C227 on ECL2. Since
Procheck results for their model were included, we compared them
with our Procheck results, and our results show that fewer residues
of our model fall outside the allowed region of the Ramachandran
plot. One major difference in the construction of our model is that
we included an artificial intracellular loop 3 (ICL3), whereas this
was omitted in the Bruno model. Others have also constructed
homology models of the human b2-adrenoceptor with
MODELLER.46,47
As shown in Table 2, the best overall agreement between the
in vitro experimental findings and the docking scores are obtained
by using a homology model that was built by MODELLER based on
a bovine rhodopsin template (BRho_MODELLER) with the GOLD
docking program. None of the models gave very good correlation
values for the C1 analogs when nantenine and compounds 11a–f
were included in the data set (Figs. 1 and 2 and Table 3). However,
analogs which had low apparent affinity (Ke > 10,000)
were predicted not to bind with the BRho_MODELLER/GOLD
combination whereas analogs with good to poor apparent affinity
(50 < Ke < 5000, i.e., nantenine and the C1 analogs 11a–f) gave rea-
sonable and measurable GOLD scores with BRho_MODELLER. In
contrast, for example, the HAdrb2_MODELLER/GOLD combination
gave binding poses and scores for flexible analogs 6a and 9 as well
as the N-analogs 8a and 8b whereas the BRho_MODELLER/GOLD
indicated that these analogs would have no affinity, which is in line
with the in vitro data. Interestingly, if we considered only analogs
11a–e (i.e., C1 alkyl analogs excluding the benzyl analog), we ob-
tained a very good correlation (r2 = 0.928 in a plot of Ke vs docking
score) for the HAdrb2_MODELLER/GOLD combination. Therefore,
in the evaluation of a more diverse set of nantenine analogs it
appears that the BRho_MODELLER/GOLD combination performs
better than the HAdrb2_MODELLER/GOLD combination, although
the latter may be more suited for a restricted set of C1 alkyl cong-
eners. Although the correlation is low, the BRho_MODELLER/GOLD
combination appears to provide the best gross approximation of
affinity or lack thereof in the entire series of compounds and we
therefore proceeded to look in detail at potential binding modes
with the BRho_MODELLER model.
Figure 2. Correlation of GOLD score and affinity data for HAdrb2_MODELLER.
Table 3
r2 values for compoundsa docked with various models
Model/scoring
r2
r2
HAdrb2_ICM/ICM
0.043b
0.357b
0.576b
0.201b
0.039b
0.747c
0.012c
0.106c
0.928c
0.381c
HAdrb2_MODELLER/GLIDE
BRho_MODELLER/GLIDE
HAdrb2_MODELLER/GOLD
BRho_MODELLER/GOLD
a
b
c
C1 analogs.
Nantenine and 11a–f.
Compounds 11a–e only.
Binding modes of nantenine as well as C1 analogs were further
examined in order to begin to understand the trend in apparent
affinity values observed in this series of compounds. Figures 3–9
show 3D and 2D representations (generated with ICM Pro and Lig-
Plot, respectively) of important interactions of nantenine and the
analogs in the 5-HT2A receptor (for the BRho_MODELLER homology
model). Table 4 summarizes the key interactions for the C1
analogs. We observed that C1 analogs 11a–f are binding in the 5-
HT2A receptor pocket differently than nantenine, while still main-
taining similarity in orientation among them. Figure 3 shows that
nantenine has a H-bond between the protonated N6 atom and
Asp155, as well as a second key interaction between the oxygen
atom of the C1 methoxy group and Asn343 located in TM6. This
is in agreement with a previous study done by Indra et al. although
we used a different protein source (human vs rat 5-HT2A receptor)
and methods for homology modeling and docking experiments.
The congruence of these results is perhaps not surprising given
the high degree of sequence similarity between rat and human
5-HT2A receptors.25
Visual inspection of the binding mode of the C1 analogs with
highest affinity—11d (Ke = 171 nM) and 11e (Ke = 68 nM), revealed

5568
S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
Figure 3. Binding pose of nantenine represented with: (a) ICM Pro and (b) Ligplot.
Figure 4. Binding pose of 11a represented with: (a) ICM Pro and (b) Ligplot.
a different orientation of these molecules in the receptor as
compared to nantenine (Figs. 7 and 8). For both of these com-
pounds there is a protonated N6/Asp155 H-bond and a H-bond be-
tween Ser242 and one of the oxygen atoms located in the
methylenedioxy ring. Ser242 has also been reported to be impor-
tant as a H-bonding residue for other high affinity 5-HT2A ligands
both as H-bond acceptor and as a H-bond donor. For example,
the partial agonist LSD is reported to interact with the hydroxyl
group of Ser242 through H-bonding via its N1 hydrogen atom.
Ser242 also plays a H-bonding role in the binding of a series of ben-
zofuranone 5-HT2A antagonists to the receptor via its H-bond do-
nor capacity to an oxygen atom in the ligand. The H-bonding
interaction between the C1 oxygen atom and Asn343 which is
present in nantenine is absent in the binding poses of 11d and
11e as well as the other C1 analogs. In addition to the strong stabi-
lizing H-bond interactions, the higher affinity of 11d and 11e might
also be accounted for by strong hydrophobic interactions that are
formed between the spatially close residues Phe234 and Gly238
(located in TM5) and the C1 alkyl groups in 11d and 11e, respec-
tively. Like 11d and 11e, compounds 11b and 11c (Figs. 5 and 6,
respectively), also form H-bonds with Asp155 and Ser242, and
their C1 side chains make important hydrophobic interactions with
Phe234 but not with Gly238. Absence of the Gly238 hydrophobic
interaction probably has some bearing on the slightly lower
in vitro affinity of these two nantenine analogs (Ke = 297 nM for
11b and Ke = 274 nM for 11c), as compared to the most potent ana-
log from this series, compound 11e. Some of the analogs also had
contacts with hydrophobic residues in TM4 (Ile206 and Ile210).
However, these TM4 interactions by themselves do not account en-
tirely for the higher affinity seen with 11e; they were absent in 11d
but did not severely affect its affinity. Compound 11f, which had
the lowest affinity among C1 congeners (Ke = 4600 nM), showed
only one H-bonding interaction (via protonated N6 and Asp155),
and also hydrophobic interactions between its aromatic ring in
the C1 benzyl side chain and Phe234 and Gly238 residues
(Fig. 9). The lack of a strong stabilizing Ser242 H-bonding interac-

S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
5569
Figure 5. Binding pose of 11b represented with: (a) ICM Pro and (b) Ligplot.
Figure 6. Binding pose of 11c represented with: (a) ICM Pro and (b) Ligplot.
tion as seen in other analogs may be partially responsible for its
lower affinity. It is interesting that compound 11a has a similar
affinity to nantenine but binds in a different manner. It still utilizes
Asp155 for H-bonding to the protonated N6 but lacks the Asn343
H-bond seen with nantenine. A number of hydrophobic interac-
tions stabilize the molecule in the binding site including interac-
tions with residues in TM6 and TM7 (Met345 and Val366,
respectively) not seen in any of the other analogs. It is also note-
worthy that whereas other analogs (11b–e) utilize Ser242 for
H-bonding, 11a utilizes Ser242 for hydrophobic interactions.
Overall, it is apparent that for this series of compounds, the
Asn343 H-bond interaction seen with nantenine is not required
for affinity to the receptor. However, it is clear that H-bonding with
the highly conserved Asp155 is required for any appreciable affin-
ity to the receptor; in that regard it seems to be necessary but not
sufficient for high affinity.
Sowdhamini and co-workers recently reported the construction
of a homology model of the human 5-HT2A receptor based on a
human b2-adrenoceptor template.48 In this study they docked
a number of known 5-HT2A antagonists and inverse agonists
(ketanserin, haloperidol, clozapine, and risperidone) using the pro-
gram Autodock 4.0. In the case of the antagonists ketanserin and
haloperidol, the helix regions TM3, TM5, TM6, TM7 as well as
ECL2 were involved in binding, whereas for the inverse agonists
clozapine and risperidone TM3, TM5, TM6, ECL2, and ECL3 were
involved. It has been suggested that 5-HT2A ligands may bind in
two different spatially-allowed sites of the receptor.3 One site is
bordered by transmembrane helices TM3, TM4, TM5, and TM6. A

5570
S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
Figure 7. Binding pose of 11d represented with: (a) ICM Pro and (b) Ligplot.
Figure 8. Binding pose of 11e represented with: (a) ICM Pro and (b) Ligplot.
second site is flanked by TM1, TM2, TM3, and TM7. Asp155 (TM3)
is a key residue in both sites and forms a H-bond contact to a pro-
tonated amine functionality of typical ligands. The results obtained
in our work suggest that nantenine and the C1 alkyl analogs bind in
the site bordered by TM3–TM6 and utilize the key Asp155 interac-
tion but are oriented differently as shown diagrammatically in Fig-
ure 10. Based on the residues that are used to establish key
interaction to the ligands, the analogs also appear to bind in a man-
ner different from that reported for other known antagonists such as
ketanserin and haloperidol which supports the assertion that the
structure of the ligand impacts its orientation and preference for
residues in certain helices that are utilized for binding.48 Indeed it
is clear that the binding pocket is tolerant of a variety of structural
classes of ligands which may adopt different orientations between
classes as well as within a given class as seen here with nantenine
and its analogs.
Taken together, the results above suggest that the binding ori-
entation of C1 analogs when compared to nantenine may be differ-
ent, and that both H-bond and hydrophobic interactions are
important for achieving high affinity to the receptor in this series.
It is apparent that the pendant groups of nantenine C1 analogs pro-
ject into a hydrophobic region on TM5 which include the residues
Phe234 and Gly238. Given these insights, as well as information
obtained from our SAR studies, it will be interesting to undertake
in silico screening of a series of C1 aporphines with various hydro-
phobic substituents (branched alkyl, cycloalkyl, substituted aryl,

S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
5571
Figure 9. Binding pose of 11f represented with: (a) ICM Pro and (b) Ligplot.
Table 4
Residues interacting with nantenine and C1 analogs
TM
Residues
Nantenine
11a
11b
11c
11d
11e
11f
3
3
3
3
3
3
Ile152
Ile152
Ile152
Ile152
Asp155
Val156
Ser159
Thr160
Ile163
Asp155a,b,c
Val156
Ser159
Thr160
Ile163a
Asp155
Asp155
Val156
Asp155
Val156
Ser159
Asp155
Val156
Ser159
Asp155
Asp155
Val156
Ser159
Ile163
Ile163
4
4
Ile206
Ile210
Ile206
Ile210
Ile206
Ile210
Ile206
Ile210
Ile210
5
5
5
5
5
5
5
Leu228
Phe234
Gly238
Ser239
Ser242
Phe243a,b
Ser 244
Pro338a,b,c
Phe339a
Phe340a
Ile341
Leu228
Gly238
Ser242
Leu228
Phe234
Leu228
Phe234
Leu228
Phe234
Gly238
Leu228
Phe234
Gly238
Gly238
Ser239
Ser242
Ile341
Ser242
Ile341
Ser242
Ser242
Ile341
Phe243
Pro338
Ser244
6
6
6
6
6
6
6
Phe339
Phe340
Ile341
Thr342
Thr342
Asn343
Met345
Thr342
Asn343
Met345
Val366
7
7
Val366
Gly369a
Gly369
a
b
c
Conserved among human 5-HT receptors.
Conserved among amine GPCRs.
Conserved among all GPCRs.48
etc.) and to subsequently synthesize and evaluate the compounds
in vitro.
We did not obtain correlation between the in vitro affinity data
and docking scores, so at this time it is clear that the model cannot
be utilized in a predictive fashion for similar aporphine com-
pounds. (This is not completely surprising since no scoring pro-
gram can correctly rank every protein–ligand complex.) The
tolerability of the receptor for more than one binding modes of
the same compound is one possible reason for this lack of correla-
tion. For example, several possible binding modes have been re-
ported for ketanserin.44,48 Another possible reason for the low
correlation observed is that we used a relatively small library of

5572
S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
machine with TMS as internal standard and CDCl3 as solvent unless
stated otherwise. Chemical shift (d) values are reported in ppm and
coupling constants in Hertz (Hz). Melting points were obtained on
a Mel-Temp capillary electrothermal melting point apparatus.
Reactions were monitored by TLC with Analtech Uniplate silica
gel G/UV 254 precoated plates (0.2 mm). TLC plates were visual-
ized by UV (254 nm) and by staining with phosphomolybdic acid
reagent followed by heating. Flash column chromatography was
performed with silica gel 60 (EMD Chemicals, 230–400 mesh,
0.04–0.063 lm particle size). All compounds evaluated were
P95% pure as determined by analytical HPLC performed with an
Agilent 1200 system equipped with PDA detector, Eclipse XDB-
C18 column (4.6 ꢁ 150 mm) and eluted with methanol/water
(80:20) at a flow rate of 1 mL/min.
Figure 10. Orientation of nantenine and C1 alkyl analogs in the 5-HT2A receptor
with key TM residue interactions (H-bond, yellow; hydrophobic, blue; H-bond plus
hydrophobic, green).
4.2. Chemistry
4.2.1. 3-(Benzo[d][1,3]dioxol-5-yl)-4,5-dimethoxybenzaldehyde (3)
A mixture of Pd(PPh3)4 (2.35 g, 2.03 mmol) and commercially
available 5-bromoveratraldehyde 1 (5.00 g, 20.60 mmol) in DME
(250 mL) was stirred for 15 min at 20 °C under argon. Two molar
aqueous K2CO3 (71.5 mL, 142.80 mmol) was added to the mixture,
followed by boronic acid 8 (6.77 g, 40.80 mmol) in DME. The mix-
ture was refluxed for 18 h and then cooled to rt. The reaction mix-
ture was treated with water and ethyl acetate and the layers
separated. The organic extract was washed sequentially with 1 M
NaOH and water and dried over Na2SO4. The solvent was evapo-
rated to give crude 3, which was purified by column chromatogra-
phy (hexanes/EtOAc, 4:1). Compound 3 (5.66 g, 19.80 mmol, 96%)
was obtained as a pale yellow oil: 1H NMR (500 MHz, CDCl3): d
9.92 (s, 1H), 7.44 (d, 1H, J = 2.0 Hz), 7.42 (d, 1H, J = 2.0 Hz), 7.06
(d, 1H, J = 1.7 Hz), 7.00 (dd, 1H, J = 8.0, 1.7 Hz), 6.89 (d, 1H,
J = 8.0 Hz), 6.02 (s, 2H), 3.97 (s, 3H); 3.71 (s, 3H); 13C NMR
(125 MHz, CDCl3): d 191.2, 153.7, 151.9, 147.5, 147.2, 135.7,
132.3, 130.8, 127.2, 122.7, 109.7, 109.3, 108.3, 101.2, 60.7, 56.1;
HRESIMS calcd for C16H14O5 [M]+ 286.0841; found 286.0841.
analogs with measurable affinity. For these reasons, it will be use-
ful to synthesize and evaluate a larger set of nantenine analogs
towards refinement of the model. Nevertheless, it will also be valu-
able to conduct in silico screening of known non-aporphinoid 5-
HT2A ligands to test the applicability of our model in identifying
agonists, partial agonists, antagonists and inverse agonists at this
receptor. In the case of future generations of C1 alkyl analogs, given
the good correlation seen with the HAdrb2_MODELLER/GOLD
docking/scoring method, it will also be informative to evaluate
these analogs using this method as a means of comparison of po-
tential binding modes. For the antagonist ketanserin, we obtained
a docking score predictable of high affinity for BRho_Modeller/
GOLD combination (Table 2) which is promising. Clearly however,
further evaluations on a structurally diverse set of ligands needs to
be undertaken to determine the predictive value and robustness of
our model for a broader set of compounds. Additionally, site-direc-
ted mutagenesis studies are required to shed light on the impor-
tance of the key residues identified in the affinity of the analogs.
These are worthwhile avenues to pursue in future and the results
presented here represent a good foundation for these directions.
4.2.2. (E)-5-(2,3-Dimethoxy-5-(2-nitrovinyl)phenyl)benzo[d]
[1,3]dioxole (4)
3. Conclusions
A mixture of aldehyde 3 (5.31 g, 18.56 mmol), ammonium ace-
tate (1.43 g, 18.56 mmol), nitromethane (4.98 mL, 92.82 mmol),
and glacial AcOH (100 mL) was refluxed for 4 h. After cooling to
rt, the product was filtered and recrystallized from EtOH to afford
4 as a yellow solid (5.15 g, 15.65 mmol, 84%): mp 124–127 °C. 1H
NMR (500 MHz, CDCl3): d 7.97 (d, 1H, J = 13.6 Hz), 7.55 (d, 1H,
J = 13.6 Hz), 7.14 (d, 1H, J = 2.1 Hz), 7.02 (d, 1H, J = 1.7 Hz), 7.01
(d, 1H, J = 2.1 Hz), 6.96 (dd, 1H, J = 8.0, 1.7 Hz), 6.88 (d, 1H,
J = 8.0 Hz), 6.02 (s, 1H), 3.95 (s, 3H); 3.68 (s, 3H); 13C NMR
(125 MHz, CDCl3): d 153.0, 150.3, 147.8, 147.5, 139.2, 136.6,
136.6. 130.9, 125.9, 125.1, 122.9, 111.0, 109.9, 108.5, 101.4, 61.0,
56.3; HRESIMS calcd for C17H15NO6 [M+H]+ 330.0899; found
330.0971.
We built four homology models and compared results of our
in vitro data (5-HT2A apparent affinity of nantenine analogs) with
the docking scores obtained for the analogs with each homology
model. A bovine rhodopsin template built with MODELLER and
evaluated by the GOLD docking algorithm gave docking scores in
best gross agreement with our in vitro data although the correla-
tion was poor. Our molecular docking studies showed that C1
nantenine analogs 11a–f bind in a different manner than nante-
nine, but in a similar orientation among them. Visual inspection
of the final poses of the high affinity compounds revealed two
key H-bond interactions—one between Asp155 and protonated
nitrogen, and the other between Ser242 and an oxygen atom in
the methylenedioxy ring of the nantenine analogs. Hydrophobic
interactions between the alkyl group at C1 and the residues
Phe234 and Gly238 seem to be crucial for the enhanced affinity
of this series at the 5-HT2A receptor. Our findings presented here
will be useful in the future design of high affinity 5-HT2A ligands
based on the nantenine aporphine core structure.
4.2.3. N-(3-(Benzo[d][1,3]dioxol-5-yl)-4,5-dimethoxyphenethyl)-
formamide (5a)
TMSCl (5.00 mL, 24.2 mmol) was added to a vigorously stirred
suspension of LiBH4 (0.35 g, 7.62 mmol) in anhyd THF (15 mL) over
a period of 2 min. After the gas evolution had ceased, the trimeth-
ylsilane was removed by purging the solution with argon. Then,
over a period of 5 min, a solution of 4 (1.00 g, 3.04 mmol) in anhyd
THF (15 mL) was added and the mixture was heated for 18 h at re-
flux. After cooling to rt, the mixture was quenched carefully with
methanol (25 mL) at 0 °C. The solvent was removed with a rotatory
evaporator, the resulting residue dissolved in 20% aq KOH (50 mL),
and extracted with DCM (3ꢁ 50 mL). The combined extracts were
dried (Na2SO4) and then concentrated under reduced pressure.
4. Experimental
4.1. General methods and instrumentation
HRESIMS spectra were obtained using an Agilent 6520 Q-TOF
instrument. NMR data were collected on a Bruker 500 MHz

S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
5573
This gave a crude oily primary amine product. The crude amine,
ethyl formate (0.62 mL, 7.8 mmol) and triethylamine (0.86 mL,
6.20 mmol) were heated to reflux for 48 h. Removal of excess ethyl
formate and triethylamine under reduced pressure gave a dark-
brown oil, that was purified by column chromatography (MeOH/
DCM, 1:99). Compound 5a (0.92 g, 2.80 mmol, 92% from 4) was ob-
tained as an orange-red oil: 1H NMR (500 MHz, CDCl3): d 8.12 (s,
1H), 7.05 (s, 1H), 6.98 (d, 1H, J = 8.0 Hz), 6.85 (d, 1H, J = 8.0 Hz),
6.73 (br s, 2H), 5.98 (s, 2H), 3.88 (s, 3H), 3.56 (m, 5H), 2.82 (t,
2H, J = 6.9 Hz); 13C NMR (125 MHz, CDCl3): d 161.4, 153.1, 147.4,
146.8, 135.4, 134.4, 133.6, 131.9, 122.7, 122.6, 111.7, 109.9,
108.2, 101.2, 60.6, 56.1, 39.3, 35.5; HRESIMS calcd for C18H20NO5
[M+H]+ 330.1263; found 330.1333.
(125 MHz, CDCl3): d 151.0, 147.3, 146.5, 144.8, 134.0, 129.8, 129.5,
125.8, 122.6, 111.6, 110.0, 108.2, 101.0, 60.8, 56.5, 55.8, 52.6, 46.3,
29.8; HRESIMS calcd for
327.1471.
C
19H21NO4 [M]+ 327.1478; found
4.3.2. 8-(Benzo[d][1,3]dioxol-5-yl)-6,7-dimethoxy-1,2-dimethyl-
1,2,3,4-tetrahydroisoquinoline (6b)
Mixture of atropisomers. Prepared from 5b in 90% overall yield
as bright yellow crystals: mp 101–104 °C. 1H NMR (500 MHz,
CDCl3): d 6.87–6.84 (m, 1H), 6.76–6.67 (m, 1H), 6.66–6.65 (m,
2H), 6.03–6.00 (m, 2H), 3.87 (s, 3H), 3.78–3.71 (m, 4H), 3.08–3.07
(m, 2H), 2.77–2.71 (m, 2H), 2.38–2.46 (m, 3H), 0.97–0.94 (m,
3H); 13C NMR (125 MHz, CDCl3) (doubling of signals observed;
average values for atropisomeric shifts reported): d 151.0, 147.3,
146.5, 145.1, 134.6, 130.8, 129.9, 128.6, 123.3, 112.0, 110.6,
108.1, 101.0, 60.8, 55.7, 55.0, 44.1, 42.0, 26.3, 16.2; HRESIMS calcd
for C20H23NO4 [M]+ 341.1627; found 341.1628.
4.2.4. N-(3-(Benzo[d][1,3]dioxol-5-yl)-4,5-dimethoxyphenethyl)-
acetamide (5b)
The crude primary amine (0.95 g), prepared as described above
from compound 4 (1.00 g, 3.03 mmol), acetyl chloride (0.35 mL,
5.5 mmol) and triethylamine (1.35 mL, 10.00 mmol) were mixed
with dichloromethane (10 mL) and stirred for 6 h at 0 °C. The reac-
tion was treated with saturated sodium bicarbonate, extracted
with DCM (3ꢁ 35 mL), dried over Na2SO4 and concentrated under
reduced pressure to give a yellow oil, that was subsequently puri-
fied by column chromatography (MeOH/DCM, 1:99). Compound 5b
(0.92 g, 88% from compound 4) was obtained as an orange-red oil:
1H NMR (500 MHz, CDCl3): d 8.12 (s, 1H), 7.06 (br s, 1H), 6.98 (d,
1H, J = 8.0 Hz), 6.86 (d, 1H, J = 8.0 Hz), 6.73 (br s, 1H), 5.98 (s,
2H), 5.71 (br s, 1H), 3.88 (s, 3H), 3.58 (s, 3H), 3.51 (dd, 2H,
J = 13.2, 6.5 Hz), 2.78 (t, 2H, J = 7.0 Hz), 1.95 (s, 3H); 13C NMR
(125 MHz, CDCl3): d 170.1, 153.1, 147.4, 146.8, 145.0, 135.4,
134.7, 131.9, 122.6, 122.5, 111.7, 109.8, 108.1, 101.0, 60.5, 56.0,
40.7, 35.6, 23.4; HRESIMS calcd for C19H22NO5 [M+H]+ 344.1415;
found 344.1488.
4.3.3. 1,2-Dimethoxy-5,6,6a,7-tetrahydro-4H-benzo[de][1,3]
benzodioxolo[5,6-g]quinoline (8a)
Compound
7 (0.50 g, 1.18 mmol) in dry dichloromethane
(10 mL) was stirred with anhydrous ZnBr2 (1.06 g, 4.71 mmol) un-
der argon at room temperature for 4 h. The reaction mixture was
then quenched by adding a solution of saturated sodium bicarbon-
ate (50 mL) and was extracted with DCM (2ꢁ 60 mL), dried over
Na2SO4 and concentrated to give 8a as yellow oil. We found this
compound to be unstable; for long-term storage 8a was converted
to its hydrochloride salt by treatment with HCl in ether. Data for
the hydrochloride salt follows: 1H NMR (500 MHz, DMSO-d6): d
7.76 (s, 1H), 7.03 (s, 1H), 6.90 (s, 1H), 6.06 (s, 2H), 4.20 (br d, 1H,
J = 11.0 Hz), 3.83 (s, 3H), 3.60 (s, 3H), 3.33 (s, 2H), 3.23 (dt, 1H,
J = 12.6, 4.5 Hz), 3.13 (m, 1H), 2.97 (dd, 1H, J = 14.2, 4.5 Hz), 2.90
(dd, 1H, J = 14.2, 1.1 Hz), 2.80 (t, 1H, J = 14.2 Hz); 13C NMR
(125 MHz, DMSO-d6): d 152.8, 146.7, 146.6, 144.5, 128.2, 126.8,
125.8, 124.5, 121.6, 111.6, 108.7, 108.1, 101.3, 59.9, 55.9, 51.8,
40.3, 33.0, 25.1; HRESIMS: calcd for C19H19NO4 [M]+ 325.1314;
found 325.1313.
4.3. General procedure for synthesis of compounds 6a and 6b
To a stirred solution of amide 5 (1.40 mmol) in acetonitrile
(5 mL) was added POCl3 (0.65 mL, 7.00 mmol) at rt, and the result-
ing mixture was heated at 50 °C for 12 h. The reaction mixture was
concentrated, and the quaternary salt was dissolved in DCM
(25 mL). After cooling to 0 °C, the mixture was diluted with water,
made basic with 5% aqueous NH4OH, and extracted with DCM. The
organic solution was washed with water, dried with anhydrous
Na2SO4 and concentrated to give yellow crude dihydroisoquino-
lines. Sodium borohydride (1.04 g, 27.60 mmol) was added por-
tion-wise to a stirred solution of the crude dihydroisoquinoline
in methanol (20 mL) and the mixture was stirred at 0 °C for 3 h.
The reaction mixture was concentrated, and excess NaBH4 was de-
stroyed by adding water and glacial acetic acid. The mixture was
then extracted with DCM (3ꢁ 25 mL), dried over Na2SO4 and con-
centrated to give a crude oily product. This crude secondary amine
product and formaldehyde solution, 37% (2.59 mL, 2.55 mmol)
were mixed in anhydrous DCM (10 mL) and then treated with NaB-
H(OAc)3 (1.35 g, 6.38 mmol). The mixture was allowed to stir at rt
for 24 h. The reaction was quenched with 5% aq sodium bicarbon-
ate (25 mL), and extracted with ethyl acetate (2ꢁ 25 mL), dried
over Na2SO4 and concentrated to dryness. The residue was purified
via silica flash column chromatography (MeOH/DCM, 2:98) to pro-
vide 6a and 6b.
4.3.4. 1,2-Dimethoxy-6-ethyl-5,6,6a,7-tetrahydro-4H-benzo[de]
[1,3]benzodioxolo[5,6-g]quinoline (8b)
Compound 8a (0.30 g, 0.92 mmol) and acetaldehyde solution,
(5.4 mL, 1.84 mmol) were mixed in anhydrous DCM (20 mL) and
then treated with sodium triacetoxy-borohydride (0.98 g,
4.61 mmol). The mixture was allowed to stir at room temperature
overnight. The reaction was quenched with 5% aq sodium bicar-
bonate (25 mL), and extracted with dichloromethane (2ꢁ 25 mL),
dried over sodium sulfate and concentrated to dryness. The residue
was purified via flash chromatography (MeOH/DCM, 1:99) to pro-
vide 8b (0.23 g, 0.65 mmol, 71%) as a bright red oil: 1H NMR
(500 MHz, CDCl3): d 7.92 (s, 1H), 6.75 (s, 1H), 6.59 (s, 1H), 5.97
(s, 1H), 5.96 (s, 1H), 3.86 (s, 3H), 3.64 (s, 3H), 3.24 (dd, 1H,
J = 13.7, 3.1 Hz), 3.16 (dd, 1H, J = 11.3, 5.1 Hz), 3.12–3.04 (m, 2H),
2.97 (dd, 1H, J = 13.7, 3.8 Hz), 2.70–2.67 (dd, 1H, J = 13.4, 3.0 Hz),
2.62–2.43 (m, 3H), 1.14 (t, 3H, J = 7.1 Hz); 13C NMR (125 MHz,
CDCl3): d 151.8, 146.4, 146.3, 144.4, 131.0, 129.0, 127.9, 127.1,
125.6, 110.6, 108.9, 108.2, 100.8, 60.2, 59.2, 55.8, 48.3, 47.8, 35.0,
29.3, 10.8; HRESIMS: calcd for C21H24NO4 [M+H]+ 354.1627; found
354.1650.
4.3.5. 1,2-Dimethoxy-6-acetyl-5,6,6a,7-tetrahydro-4H-benzo-
[de][1,3]benzodioxolo[5,6-g]quinoline (8c)
4.3.1. 8-(Benzo[d][1,3]dioxol-5-yl)-6,7-dimethoxy-2-methyl-
1,2,3,4-tetrahydroisoquinoline (6a)
Prepared from 5a in 88% overall yield as bright yellow crystals:
mp 82–84 °C. 1H NMR (500 MHz, CDCl3): d 6.87 (d, 1H, J = 7.9 Hz),
6.70–6.65 (m, 3H), 6.01 (d, 2H, J = 8.4 Hz), 3.88 (s, 3H), 3.54 (s, 3H),
3.15 (br s, 2H), 2.94 (br s, 2H), 2.65 (br s, 2H), 2.35 (s, 3H); 13C NMR
Compound 8a (0.10 g, 0.31 mmol) and acetyl chloride (0.01 mL,
0.41 mmol) were mixed in anhydrous DCM (20 mL) and then trea-
ted with triethylamine (0.12 mL, 0.86 mmol). The mixture was al-
lowed to stir at 0 °C for 3 h under argon. The reaction was
quenched with saturated sodium bicarbonate (20 mL), extracted

5574
S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
with dichloromethane (3ꢁ 20 mL), dried over sodium sulfate and
concentrated to dryness. The residue was recrystallized from ethyl
acetate to obtain 8c (0.07 g, 0.19 mmol, 61%) as a white solid (mix-
ture of rotamers; NMR data for major rotamer provided); mp 190–
192 °C. 1H NMR (500 MHz, CDCl3): d 8.01 (s, 1H), 6.76 (s, 1H), 6.64
(s, 1H), 6.01 (s, 1H), 5.99 (s, 1H), 5.04 (dd, 1H, J = 13.8, 3.8 Hz), 4.00
(dd, 1H, J = 13.3, 2.3 Hz), 3.89 (s, 3H), 3.69 (s, 3H), 3.01–2.64 (m,
5H), 2.29 (s, 3H); 13C NMR (125 MHz, CDCl3): d 169.7, 169.1,
152.2, 151.9, 146.8, 146.7, 146.6, 145.1, 144.9, 131.3, 130.5,
128.7, 127.9, 125.8, 124.9, 110.9, 108.9, 108.8, 101.1, 60.0, 55.9,
53.0, 50.4, 41.9, 36.6, 34.0, 30.7, 29.8, 22.6, 21.6; HRMS: m/z (%)
[M+H]+ 404 (100).
metric optimization. To make the homology models, the programs
MODELLER (Discovery Studio 2.0 of Accelrys Inc.) and ICM Pro 3.6
were used. From several crystal structures available in PDB, as a
template, we selected bovine rhodopsin (PDB code: 1U19) since
in many previous reports it has been used as a good template for
the 5-HT2A receptor and also because its crystal structure is solved
at high resolution 2.20 Å. We also selected b2-adrenergic receptor
(PDB code: 2RH1) as a template, because this is presently the best
resolved structure (2.40 Å) of the available GPCR neurotransmitter
receptors. Twenty models were built for each of the templates
using MODELLER and one model for each template using ICM Pro
3.6. All homology models were evaluated using several different
model evaluation tools such as PROCHECK,37 Verify3D,36 ERRAT,35
WHAT_CHECK,51 and PROVE37 from SAVES33 metaserver. After
evaluating each model using the above methods, the final models
were selected—one from each template, which fits best by criteria
of selection in each method. The best docking solution was energy
minimized with Charmm as implemented in Discovery Studio 2.0
of Accerlys Inc., by applying 500 cycles of Smart Minimizer Algo-
rithm, followed by gradient minimization until RMS gradient was
lower than 0.01 kcal/mol Å. The models were renumbered, accord-
ing to their original sequence. The four selected homology models
were than superimposed with their templates using the protocol in
Discovery Studio 2.0: structure superimposing by sequence align-
ment, and RMSD determined for each model.
4.3.6. 1,2-Dimethoxy-6-methanesulfonyl-5,6,6a,7-tetrahydro-
4H-benzo[de][1,3]benzodioxolo[5,6-g]quinoline (8d)
Compound 8a (0.10 g, 0.31 mmol) and methanesulfonyl chlo-
ride (0.04 mL, 0.52 mmol) were mixed in anhydrous DCM
(20 mL) and then treated with triethylamine (0.12 mL, 0.86 mmol).
The mixture was allowed to stir at 0 °C to rt overnight. The reaction
was quenched with saturated sodium bicarbonate (25 mL), and ex-
tracted with dichloromethane (2ꢁ 25 mL), dried over sodium sul-
fate and concentrated to dryness. The residue was recrystallized
in diethyl ether to obtain 8d (0.07 g, 0.17 mmol, 55%) as a white so-
lid; mp 197–199 °C. 1H NMR (500 MHz, CDCl3): d 7.98 (s, 1H), 6.76
(s, 1H), 6.63 (s, 1H), 6.00 (s, 1H), 5.98 (s, 1H), 4.10 (br d, 1H,
J = 11.3 Hz), 3.90 (s, 3H), 3.66 (s, 3H), 3.25–3.15 (m, 4H), 2.96–
2.2.94 (m, 2H), 2.88 (s, 3H); 13C NMR (125 MHz, CDCl3): d 152.4,
146.8, 146.7, 145.2, 130.8, 128.5, 128.0, 124.8, 124.5, 110.8,
108.9, 108.8, 101.0, 60.06, 55.9, 53.0, 46.1, 40.4, 37.4, 29.4; HRE-
SIMS: calcd for C20H22NO6S [M+H]+ 404.1090; found 404.1160.
4.5.2. Preparation of the analogs and receptors, grid generation
and docking experiments
Nantenine and all analogs were drawn as 2D structures with
ChemDraw Ultra version 9.0 with a formal positive charge cen-
tered on the nitrogen, and then energy minimized through
Chem3D Ultra version 9.0/MOPAC, Job Type: Minimum RMS Gradi-
ent of 0.010 kcal/mol and RMS distance of 0.1 Å, and saved as MDL
MolFiles (ꢂ.mol) for purpose of docking with ICM Pro, or as SYBYL2
files (ꢂ.mol2) for the purpose of docking with the GLIDE and the
GOLD software. Before docking with the GLIDE and the GOLD each
analog was prepared using LigPrep, an application that is available
through Maestro 7.5 (a Linux graphical interface for Schröding-
er06). After employing the energy minimization through Macro-
Model application, each 3D structure was saved as an SD file
(ꢂ.sdf), and combined into a single analogs library SD file, to be
used for docking experiments.
4.4. 5-HT2A Ke determination in FLIPR assay
The Ke data were obtained by monitoring the ability of test com-
pounds to inhibit serotonin-mediated stimulation of the human 5-
HT2A receptor heterologously expressed in Chinese hamster ovary
(CHO) cells. Agonist dose–response curves were run in the pres-
ence or absence of a single concentration of test compound. The
Ke values are a measure of antagonist affinity determined in a func-
tional assay and these values were calculated using the formula:
Ke = [L]/(DR ꢀ 1), where [L] is the concentration of test compound
and DR is the ratio of agonist EC50 in the presence or absence of test
compound, respectively. At least two different concentrations of
test compound were used to calculate the Ke, and their concentra-
tions were chosen such that the agonist EC50 exhibited at least a
fourfold shift to the right.
4.5.2.1. ICM docking. First the binding site of homology receptors
was identified. The binding site was reviewed and adjusted: ICM
made a box around the ligand binding site based on the informa-
tion entered in the receptor setup section. The position of the
box encompassed the residues expected to be involved in ligand
binding. Then the receptor maps were made: energy maps of the
environment within the docking box were constructed. Flexibility
of the receptor residues was set to 4.0. Interactive docking was
used to dock nantenine and the other analogs. The thoroughness
level was set to the maximum value of 10. ICM scores were ob-
tained after this procedure.
4.5. Molecular modeling and docking
4.5.1. Sequence alignment, disulfide bond assignment, model
building, evaluation/selection of the best model and energy
minimization
Amino acid sequence of the human 5-HT2A receptor was re-
trieved from NCBI protein database.49 BLASTP was used to search
for a suitable template from the Protein Data Bank (PDB) for
homology modeling. Sequence alignment was carried out with
the ClustalX50 software (using the Gonnet series matrix with the
‘gap open’ and ‘gap elongation’ penalties of 10 and 0.2, respec-
tively) and ICM Pro 3.6 (based on ZEGA sequence alignment—Nee-
dleman and Wunsch algorithm with zero gap and penalties). The
alignment was then manually refined to ensure a perfect align-
ment of the highly conserved residues of the GPCR superfamily,
according to Baldwin et al. The conserved disulfide bond between
residue C148 at the beginning of TM3 and the cysteine C228 in the
middle of extracellular loop 2 (a feature common to many GPCR
receptors) was also created and was kept as a constraint in the geo-
4.5.2.2. GLIDE docking. Each homology receptor was prepared by
the Protein Preparation mode of GLIDE, and then the receptor grid
was generated by specifying Asp155 as a central residue and
0
selecting Extra Precision docking within 20 ÅA of Asp155. After this
step the G-scores were determined and the docking poses of each
analog were visually inspected using the GLIDE Pose Viewer.
4.5.2.3. GOLD docking. As input file for the GOLD docking, both
homology models were used as a PDB file. In the GOLD Wizard, set-
up hydrogens were added and the binding site was defined as the
0
residues that are falling within 15 ÅA of Asp155. The GOLD Score

S. Pecic et al. / Bioorg. Med. Chem. 18 (2010) 5562–5575
5575
15. Schmidhammer, H.; Jennewein, H. K.; Krassnig, R.; Traynor, J. R.; Patel, D.; Bell,
K.; Froschauer, G.; Mattersberger, K.; Jachs-Ewinger, C.; Jura, P.; Fraser, G. L.;
Kalinin, V. N. J. Med. Chem. 1995, 38, 3071.
16. Jerman, J. C.; Brough, S. J.; Gager, T.; Wood, M.; Coldwell, M. C.; Smart, D.;
Middlemiss, D. N. Eur. J. Pharmacol. 2001, 414, 23.
was chosen as fitness function. After docking was finished the top-
scoring receptor–analog complexes were visually inspected. High-
scoring complexes that did not meet H-bond Asp155-NHþ3 require-
ment were discarded.
17. Indra, B.; Matsunaga, K.; Hoshino, O.; Suzuki, M.; Ogasawara, H.; Ishiguro, M.;
Ohizumi, Y. Can. J. Physiol. Pharmacol. 2002, 80, 198.
18. Altschul, S. F.; Madden, T. L.; Schaffer, A. A.; Zhang, J.; Zhang, Z.; Miller, W.;
Lipman, D. J. Nucleic Acids Res. 1997, 25, 3389.
19. Warne, T.; Serrano-Vega, M. J.; Baker, J. G.; Moukhametzianov, R.; Edwards,
P. C.; Henderson, R.; Leslie, A. G.; Tate, C. G.; Schertler, G. F. Nature 2008,
454, 486.
20. Jaakola, V. P.; Griffith, M. T.; Hanson, M. A.; Cherezov, V.; Chien, E. Y.; Lane, J. R.;
Ijzerman, A. P.; Stevens, R. C. Science 2008, 322, 1211.
21. Cherezov, V.; Rosenbaum, D. M.; Hanson, M. A.; Rasmussen, S. G.; Thian, F. S.;
Kobilka, T. S.; Choi, H. J.; Kuhn, P.; Weis, W. I.; Kobilka, B. K.; Stevens, R. C.
Science 2007, 318, 1258.
4.5.3. Visualization of selected docking posses
All final receptor–analog complexes, obtained from three differ-
ent programs were visualized using 3D Window of Discovery Stu-
dio 2.0. H-bonds, hydrophobic interactions and distances for each
3D structure were calculated and plotted by LigPlot v4.4.2.
H-bonds are indicated by dashed lines between the atoms in-
volved, while hydrophobic contacts are represented by an arc with
spokes radiating towards the ligand atoms they contact.
22. Okada, T.; Sugihara, M.; Bondar, A. N.; Elstner, M.; Entel, P.; Buss, V. J. Mol. Biol.
2004, 342, 571.
23. Mobarec, J. C.; Sanchez, R.; Filizola, M. J. Med. Chem. 2009, 52, 5207.
24. Rasmussen, S. G.; Choi, H. J.; Rosenbaum, D. M.; Kobilka, T. S.; Thian, F. S.;
Edwards, P. C.; Burghammer, M.; Ratnala, V. R.; Sanishvili, R.; Fischetti, R. F.;
Schertler, G. F.; Weis, W. I.; Kobilka, B. K. Nature 2007, 450, 383.
25. Westkaemper, R. B.; Glennon, R. A. Curr. Top. Med. Chem. 2002, 2, 575.
26. Evers, A.; Hessler, G.; Matter, H.; Klabunde, T. J. Med. Chem. 2005, 48, 5448.
27. Sousa, S. F.; Fernandes, P. A.; Ramos, M. J. Proteins 2006, 65, 15.
28. Higgins, D. G.; Sharp, P. M. Gene 1988, 73, 237.
29. Abagyan, R.; Totrov, M.; Kuznetsov, D. J. Comput. Chem. 1994, 15, 488.
30. Abagyan, R. A.; Batalov, S. J. Mol. Biol. 1997, 273, 355.
31. Baldwin, J. M.; Schertler, G. F.; Unger, V. M. J. Mol. Biol. 1997, 272, 144.
32. Sali, A.; Blundell, T. L. J. Mol. Biol. 1993, 234, 779.
Acknowledgments
This publication was made possible by Grant Nos. RR003037
and R03DA025910 from the National Center for Research Re-
sources (NCRR) and National Institute of Drug Abuse (NIDA),
respectively, components of the National Institutes of Health. Its
contents are solely the responsibility of the authors and do not
necessarily represent the official views of the NIH or its divisions.
33. Li, M.; Wang, B. J. Mol. Model. 2007, 13, 1237.
34. Morris, A. L.; MacArthur, M. W.; Hutchinson, E. G.; Thornton, J. M. Proteins
1992, 12, 345.
Supplementary data
35. Colovos, C.; Yeates, T. O. Protein Sci. 1993, 2, 1511.
Supplementary data associated with this article can be found, in
the online version, at doi:10.1016/j.bmc.2010.06.043.
36. Eisenberg, D.; Luthy, R.; Bowie, J. U. Methods Enzymol. 1997, 277, 396.
37. Pontius, J.; Richelle, J.; Wodak, S. J. J. Mol. Biol. 1996, 264, 121.
38. Friesner, R. A.; Banks, J. L.; Murphy, R. B.; Halgren, T. A.; Klicic, J. J.; Mainz, D. T.;
Repasky, M. P.; Knoll, E. H.; Shelley, M.; Perry, J. K.; Shaw, D. E.; Francis, P.;
Shenkin, P. S. J. Med. Chem. 2004, 47, 1739.
References and notes
39. Halgren, T. A.; Murphy, R. B.; Friesner, R. A.; Beard, H. S.; Frye, L. L.; Pollard, W.
T.; Banks, J. L. J. Med. Chem. 2004, 47, 1750.
40. Jones, G.; Willett, P.; Glen, R. C. J. Mol. Biol. 1995, 245, 43.
41. Stortz, C. A. J. Comput. Chem. 2005, 26, 471.
42. Wallace, A. C.; Laskowski, R. A.; Thornton, J. M. Protein Eng. 1995, 8, 127.
43. Salom, D.; Lodowski, D. T.; Stenkamp, R. E.; Le Trong, I.; Golczak, M.;
Jastrzebska, B.; Harris, T.; Ballesteros, J. A.; Palczewski, K. Proc. Natl. Acad. Sci.
U.S.A. 2006, 103, 16123.
44. Dezi, C.; Brea, J.; Alvarado, M.; Ravina, E.; Masaguer, C. F.; Loza, M. I.; Sanz, F.;
Pastor, M. J. Med. Chem. 2007, 50, 3242.
1. Kroeze, W. K.; Kristiansen, K.; Roth, B. L. Curr. Top. Med. Chem. 2002, 2, 507.
2. Bojarski, A. J. Curr. Top. Med. Chem. 2006, 6, 2005.
3. Runyon, S. P.; Mosier, P. D.; Roth, B. L.; Glennon, R. A.; Westkaemper, R. B. J.
Med. Chem. 2008, 51, 6808.
4. Sanger, D. J.; Soubrane, C.; Scatton, B. Ann. Pharm. Fr. 2007, 65, 268.
5. Shelton, R. C.; Papakostas, G. I. Acta Psychiatr. Scand. 2008, 117, 253.
6. Meltzer, H. Y.; Li, Z.; Kaneda, Y.; Ichikawa, J. Prog. Neuropsychopharmacol. Biol.
Psychiatry 2003, 27, 1159.
7. Levin, E. D.; Slade, S.; Johnson, M.; Petro, A.; Horton, K.; Williams, P.; Rezvani, A.
H.; Rose, J. E. Eur. J. Pharmacol. 2008, 600, 93.
45. Bruno, A.; Guadix, A. E.; Costantino, G. J. Chem. Inf. Model. 2009, 49, 1602.
46. Shah, J. R.; Mosier, P. D.; Roth, B. L.; Kellogg, G. E.; Westkaemper, R. B. Bioorg.
Med. Chem. 2009, 17, 6496.
8. Nic Dhonnchadha, B. A.; Fox, R. G.; Stutz, S. J.; Rice, K. C.; Cunningham, K. A.
Behav. Neurosci. 2009, 123, 382.
9. Fantegrossi, W. E.; Kiessel, C. L.; Leach, P. T.; Van Martin, C.; Karabenick, R. L.;
Chen, X.; Ohizumi, Y.; Ullrich, T.; Rice, K. C.; Woods, J. H. Psychopharmacology
(Berl) 2004, 173, 270.
47. Selent, J.; Lopez, L.; Sanz, F.; Pastor, M. ChemMedChem 2008, 3, 1194.
48. Kanagarajadurai, K.; Malini, M.; Bhattacharya, A.; Panicker, M. M.;
Sowdhamini, R. Mol. Biosyst. 2009, 5, 1877.
10. Legendre, O.; Pecic, S.; Chaudhary, S.; Zimmerman, S. M.; Fantegrossi, W. E.;
Harding, W. W. Bioorg. Med. Chem. Lett. 2010, 20, 628.
11. Chaudhary, S.; Pecic, S.; Legendre, O.; Navarro, H. A.; Harding, W. W. Bioorg.
Med. Chem. Lett. 2009, 19, 2530.
12. Aranda, R.; Villalba, K.; Ravina, E.; Masaguer, C. F.; Brea, J.; Areias, F.;
Dominguez, E.; Selent, J.; Lopez, L.; Sanz, F.; Pastor, M.; Loza, M. I. J. Med.
Chem. 2008, 51, 6085.
49. Wheeler, D. L.; Barrett, T.; Benson, D. A.; Bryant, S. H.; Canese, K.; Chetvernin,
V.; Church, D. M.; Dicuccio, M.; Edgar, R.; Federhen, S.; Feolo, M.; Geer, L. Y.;
Helmberg, W.; Kapustin, Y.; Khovayko, O.; Landsman, D.; Lipman, D. J.;
Madden, T. L.; Maglott, D. R.; Miller, V.; Ostell, J.; Pruitt, K. D.; Schuler, G. D.;
Shumway, M.; Sequeira, E.; Sherry, S. T.; Sirotkin, K.; Souvorov, A.; Starchenko,
G.; Tatusov, R. L.; Tatusova, T. A.; Wagner, L.; Yaschenko, E. Nucleic Acids Res.
2008, 36, D13.
13. Chambers, J. J.; Nichols, D. E. J. Comput. Aided Mol. Des. 2002, 16, 511.
14. Lafrance, M.; Blaquiere, N.; Fagnou, K. Eur. J. Org. Chem. 2007, 811.
50. Thompson, J. D.; Plewniak, F.; Poch, O. Nucleic Acids Res. 1999, 27, 2682.
51. Feldman, H. J.; Hogue, C. W. Proteins 2000, 39, 112.