Combined target-based and ligand-based drug design approach as a tool to define a novel 3D-pharmacophore model of human A3 adenosine receptor antagonists: Pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine derivatives as a key study

Article abstract of DOI:10.1021/jm049662f

A combined target-based and ligand-based drug design approach has been carried out to define a novel pharmacophore model of the human A₃ receptor antagonists. High throughput molecular docking and comparative molecular field analysis (CoMFA) ha

Full text of DOI:10.1021/jm049662f

152
J. Med. Chem. 2005, 48, 152-162
Combined Target-Based and Ligand-Based Drug Design Approach as a Tool To
Define a Novel 3D-Pharmacophore Model of Human A3 Adenosine Receptor
Antagonists: Pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine Derivatives as a Key
Study
Stefano Moro,*,† Paolo Braiuca,‡ Francesca Deflorian,† Cristina Ferrari,† Giorgia Pastorin,‡ Barbara Cacciari,§
Pier Giovanni Baraldi,§ Katia Varani,| Pier Andrea Borea,| and Giampiero Spalluto*,‡
Molecular Modeling Section, Dipartimento di Scienze Farmaceutiche, Universita` di Padova, Via Marzolo 5,
I-35131 Padova, Italy, Dipartimento di Scienze Farmaceutiche, Universita` degli Studi di Trieste, Piazzale Europa 1,
I-34127 Trieste, Italy, Dipartimento di Scienze Farmaceutiche, Universita` degli Studi di Ferrara, Via Fossato di Mortara
17-19, I-44100 Ferrara, Italy, and Dipartimento di Medicina Clinica e Sperimentale-Sezione di Farmacologia,
Universita` degli Studi di Ferrara, Via Fossato di Mortara 17-19, I-44100 Ferrara, Italy
Received May 5, 2004
A combined target-based and ligand-based drug design approach has been carried out to define
a novel pharmacophore model of the human A3 receptor antagonists. High throughput molecular
docking and comparative molecular field analysis (CoMFA) have been used in tandem to
assemble a new target based pharmacophore model. In parallel, to provide more accurate
information about the putative binding site of these A3 inhibitors, a rhodopsin-based model of
the human A3 receptor was built and a novel Y-shape binding motif has been proposed. Docking-
based structure superimposition has been used to perform a quantitative study of the structure-
activity relationships for binding of these pyrazolo-triazolo-pyrimidines to adenosine A3
receptor using CoMFA. Both steric and the electrostatic contour plots obtained from the CoMFA
analysis nicely fit on the hypothetical binding site obtained by molecular docking. On the basis
of the combined hypothesis, we have designed, synthesized, and tested 17 new derivatives.
Consistently, the predicted Ki values were very close to the experimental values.
Introduction
peutic applications. In particular, antagonists for A3
receptors seem to be useful for the treatment of inflam-
mation and regulation of cell growth.2,13 However,
concerning specifically the potential treatment of in-
flammation, the role of both A3 agonists and antagonists
is still ambiguous.3
In the last five years, many efforts have been con-
ducted searching potent and selective human A3 ad-
enosine antagonists. In this field several different
classes of compounds, possessing good affinity (nM
range) and with a broad range of selectivity, have been
proposed.10,14,15
Many physiological functions may be regulated by
interaction of adenosine with a set of specific receptors,
classified as A1, A2A, A2B, and A3.1 For this reason,
adenosine receptors could be considered in the treat-
ment of different pathophysiologic conditions.2-6 Ad-
enosine receptor subtypes belong to the family of seven
transmembrane domain receptor coupled G proteins,
and they exert their physiological role by activation or
inhibition of different second messenger systems.2-6
A3 adenosine receptors are associated with cerebro-
protection7,8 and cardioprotection9 effects of adenosine
agonists and effects on the immune and inflammatory
systems.3,10 The A3 adenosine receptor subtype, recently
cloned from different species (e.g. rat, human, dog,
sheep),11,12 is coupled to the modulation of at least two
second messenger systems: inhibition of adenylate
cyclase and stimulation of phospholipase C and D.11,12
In human, A3 receptors have been found in several
organs, such as lung, liver, kidney, and heart, and with
a lower density in brain.9,11,12 This receptor subtype is
under examination in relation to its potential thera-
Recently, our group has synthesized a new series of
pyrazolo-triazolo-pyrimidines bearing different sub-
stitutions at the N5
and N8 positions which have been
described as highly potent and selective human A3
adenosine receptor antagonists. Table 1 summarizes all
the compounds (1-106) previously synthesized as hu-
man A3 adenosine receptor antagonists.15-20
A combined target-based and ligand-based drug de-
sign approach has been carried out to define a novel
pharmacophore model of the human A3 receptor an-
tagonists. High throughput molecular docking and
comparative molecular field analysis (CoMFA) have
been used in tandem to assemble a novel target-based
pharmacophore model. In parallel, to provide more
accurate information about the putative binding site of
these A3 inhibitors, a rhodopsin-based model of the
human A3 receptor was built, and more than 100
pyrazolotriazolopyrimidine ligands were docked into the
putative ligand binding site. A novel Y-shaped binding
* Author to whom correspondence should be addressed. Mailing
address: Molecular Modeling Section, Department of Pharmaceutical
Sciences, University of Padova, Via Marzolo 5, I-35131 Padova, Italy.
Tel: +39 049 8275704. Fax: +39 049 827 5366. E-mail: stefano.moro@
unipd.it.
† Universita` di Padova.
‡ Universita` degli Studi di Trieste.
§ Dipartimento di Scienze Farmaceutiche, Universita` degli Studi di
Ferrara.
| Dipartimento di Medicina Clinica e Sperimentale-Sezione di Far-
macologia, Universita` degli Studi di Ferrara.
10.1021/jm049662f CCC: $30.25 © 2005 American Chemical Society
Published on Web 12/17/2004

Pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidines
Journal of Medicinal Chemistry, 2005, Vol. 48, No. 1 153
Table 1. Structures and Human A3 Binding Affinities for All Analyzed Compounds
no.
R
R1
hA3 Ki (nM)
no.
R
R1
hA3 Ki (nM)
1
2
3
4
5
6
7
8
9
H
H
H
CH3
CH3
CH3
C2H5
C2H5
C2H5
H
348 (267-453)
56
57
58
59
60
61
62
63
64
65
66
67
C2H5
C2H5
C2H5
C2H5
C2H5
C2H5
C2H5
C2H5
4-NO2-Ph-NHCO 0.65 (0.56-0.75)
4-CH3-Ph-NHCO 0.14 (0.11-0.18)
4-MeO-Ph-NHCO 0.14 (0.08-0.27)
3-Cl-Ph-NHCO
H
4-MeO-Ph-NHCO 0.20 (0.17-0.24)
3-Cl-Ph-NHCO
H
4-MeO-Ph-NHCO 0.60 (0.51-0.70)
3-Cl-Ph-NHCO
H
0.50 (0.34-0.73)
300 (265-339)
4-Br-Ph-NHCO
4-F-Ph-NHCO
4-CF3-Ph-NHCO
0.37 (0.29-0.47)
0.86 (0.77-0.97)
0.97 (0.86-1.09)
0.40 (0.24-0.64)
331 (285-385)
2-OMe-Ph-NHCO 0.56 (0.49-0.64)
3-OMe-Ph-NHCO 0.86 (0.77-0.96)
2-Cl-Ph-NHCO
4-Cl-Ph-NHCO
Ph-NHCO
0.30 (0.23-0.40)
0.20 (0.15-0.28)
0.15 (0.10-0.18)
1.60 (1.42-1.79)
408 (364-460)
C2H5
a
10 n-C3H7
11 n-C3H7
12 n-C3H7
n-C3H7
n-C3H7
n-C3H7
4-MeO-Ph-NHCO 0.80 (0.63-0.1.00)
3-Cl-Ph-NHCO 0.91 (0.85-0.98)
4-MeO-Ph-NHCO 0.48 (0.32-0.74)
600 (525-691)
3,4-Cl2-Ph-NHCO 2.5 (2.0-3.1)
3,4-O-CH2O- -Ph- 0.30 (0.22-0.40)
NHCO
4-NO2-Ph-NHCO 0.81 (0.63-1.04)
4-CH3-Ph-NHCO 0.40 (0.31-0.50)
13 CH2CHdCH2
14 n-C4H9
H
68
69
70
71
72
73
74
75
76
77
78
79
n-C3H7
n-C3H7
n-C3H7
n-C3H7
n-C3H7
n-C3H7
n-C3H7
n-C3H7
n-C3H7
n-C4H9
n-C4H9
n-C4H9
15 n-C4H9
4-MeO-Ph-NHCO 0.32 (0.27-0.34)
16 n-C4H9
3-Cl-Ph-NHCO
H
4-MeO-Ph-NHCO 0.80 (0.63-1.00)
3-Cl-Ph-NHCO
H
4-MeO-Ph-NHCO 30 (23-40)
3-Cl-Ph-NHCO
H
4-MeO-Ph-NHCO 40 (35-47)
3-Cl-Ph-NHCO
H
4-MeO-Ph-NHCO 0.98 (1.22-1.78)
3-Cl-Ph-NHCO
H
4-MeO-Ph-NHCO 40 (33-48)
3-Cl-Ph-NHCO
H
0.60 (0.52-0.68)
1149 (1061-1245)
4-Br-Ph-NHCO
4-F-Ph-NHCO
4-CF3-Ph-NHCO
0.45 (0.37-0.56)
0.29 (0.21-0.40)
0.51 (0.42-0.62)
17 t-C4H9
18 t-C4H9
19 t-C4H9
2.78 (2.13-3.62)
700 (664-738)
2-OMe-Ph-NHCO 0.34 (0.27-0.43)
3-OMe-Ph-NHCO 0.40 (0.32-0.50)
20 (CH3)2CHCH2CH2
21 (CH3)2CHCH2CH2
22 (CH3)2CHCH2CH2
23 (CH3)2CdCHCH2
24 (CH3)2CdCHCH2
25 (CH3)2CdCHCH2
26 PhCH2CH2
2-Cl-Ph-NHCO
4-Cl-Ph-NHCO
Ph-NHCO
0.71 (0.61-0.83)
0.34 (0.24-0.48)
0.21 (0.12-0.37)
40 (33-48)
811 (691-952)
a
3,4-Cl2-Ph-NHCO 3.7 (3.2-4.3)
3,4-O-CH2O- -Ph- 0.50 (0.40-0.62)
NHCO
4-NO2-Ph-NHCO 0.55 (0.46-0.64)
4-CH3-Ph-NHCO 0.21 (0.16-0.28)
55 (50-61)
280 (347-317)
27 PhCH2CH2
28 PhCH2CH2
29 PhCH2CH2CH2
30 PhCH2CH2CH2
31 PhCH2CH2CH2
32 2,4,5-Br3-Ph-CH2CH2
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
n-C4H9
n-C4H9
n-C4H9
n-C4H9
n-C4H9
n-C4H9
n-C4H9
n-C4H9
n-C4H9
CH3
8.0 (7.2-8.9)
430 (378-488)
4-Br-Ph-NHCO
4-F-Ph-NHCO
4-CF3-Ph-NHCO
0.91 (0.82-1.02)
0.80 (0.70-0.92)
0.72 (0.61-0.84)
60 (51-70)
4481 (3650-5501)
2-OMe-Ph-NHCO 0.57 (0.46-0.70)
3-OMe-Ph-NHCO 0.60 (0.53-0.68)
33 2,4,5-Br3-Ph-CH2CH2 4-MeO-Ph-NHCO 25 (17-36)
34 2,4,5-Br3-Ph-CH2CH2 3-Cl-Ph-NHCO
71 (65-78)
3416 (3228-3614)
2-Cl-Ph-NHCO
4-Cl-Ph-NHCO
Ph-CH2CO
Ph-CH2CO
Ph-CH2CO
Ph-CH2CO
CONHCH(CH3)2
CONHC(CH3)3
0.86 (0.76-0.98)
0.43 (0.37-0.50)
0.81 (0.69-0.97)
1.03 (0.79-1.34)
1.01 (0.65-1.58)
1.11 (0.74-1.67)
(7.3-11) 9.0
35 2-(R-naphthyl)ethyl
H
36 2-(R-naphthyl)ethyl
4-MeO-Ph-NHCO 16 (14-19)
3-Cl-Ph-NHCO
H
4-MeO-Ph-NHCO 0.14 (0.08-0.24)
3-Cl-Ph-NHCO
Ph-NHCO
3,4-Cl2-Ph-NHCO 3.40 (3.05-3.78)
3,4-O-CH2O- -Ph- 0.24 (0.21-0.28)
NHCO
4-NO2-Ph-NHCO 0.43 (0.38-0.48)
4-CH3-Ph-NHCO 0.31 (0.25-0.38)
4-Br-Ph-NHCO
4-F-Ph-NHCO
4-CF3-Ph-NHCO 0.74 (0.64-0.86)
2-OMe-Ph-NHCO 0.70 (0.59-0.83)
3-OMe-Ph-NHCO 0.80 (0.71-0.91)
37 2-(R-naphthyl)ethyl
51 (34-76)
85 (76-95)
C2H5
n-C3H7
n-C4H9
38a
39
40
0.19 (0.13-0.27)
0.16 (0.13-0.20)
PhCH2CH2
PhCH2CH2
(CH3)2CHCH2CH2 CONHCH(CH3)2
(CH3)2CHCH2CH2 CONHC(CH3)3
CH3CH2CH2
CH3CH2CH2
PhCH2CH2 CH2
41 CH3
42 CH3
43 CH3
4.9 (3.4-7.2)
65 (56-75)
39 (24-63)
CONHCH(CH3)2
CONHC(CH3)3
CONHCH(CH3)2
CONHC(CH3)3
21 (15-28)
44 CH3
45 CH3
46 CH3
47 CH3
48 CH3
49 CH3
50 CH3
51 CH3
52 CH3
53 C2H5
54 C2H5
55 C2H5
15 (10-21)
55 (46-65)
0.46 (0.39-0.54)
0.34 (0.28-0.41)
100 PhCH2CH2 CH2
101 PhCH2CH2
102 PhCH2CH2
65 (56-75)
CO(CH2)3NH3+ Cl 65 (42-103)
CO(CH2)3NH-
COOC(CH3)3
1480 (1019-2149)
103 (CH3)2CHCH2CH2 CO(CH2)3-
90 (73-110)
2-Cl-Ph-NHCO
4-Cl-Ph-NHCO
Ph-NHCO
3,4-Cl2-Ph-NHCO 3.0 (2.7-3.4)
3,4-O-CH2O --Ph- 0.27 (0.22-0.34)
NHCO
0.91 (0.82-1.01)
0.29 (0.23-0.36)
0.18 (0.13-0.23)
NH3+ Cl-
104 (CH3)2CHCH2CH2 CO(CH2)3NH-
COOC(CH3)3
105 PhCH2CH2
106 PhCH2CH2
2488 (1993-3108)
163 (137-193)
COCH2NH3+ Cl
CO(CH2)2NH3+ Cl 80 (63-100)
a CGS15943.

154 Journal of Medicinal Chemistry, 2005, Vol. 48, No. 1
Moro et al.
Molecular Modeling. 1. Building a Y-Shape An-
tagonist-Bound Model of Human A3 Receptor. As
already mentioned pyrazolo-triazolo-pyrimidines bear-
ing different substitutions at the N5 and N8 positions
have been described as highly potent and selective
human A3 adenosine receptor antagonists. To perform
our combined target-based and ligand-based approach,
we decided to theoretically depict the putative TM
binding motif of pyrazolo-triazolo-pyrimidines on hu-
man A3 receptor. Following our recently reported mod-
eling approaches,15,20,25,26 we built an improved model
of the human A3 receptor, using the bovine rhodopsin
crystal structure as template,27 which can be considered
a further refinement in building the hypothetical bind-
ing site of the A3 receptor antagonists already proposed.
Special care had to be given to the second extracellular
(E2) loop which in bovine rhodopsin folds back over
transmembrane helices limiting the size of the active
site.27 As Jacobson and coauthors have already demon-
strated, amino acids of this loop could be involved in
direct interactions with the ligands.28,29 Details of the
building model are given in the Experimental Section.
As already reported, the recognition of classic A3
antagonists seems to occur in the upper region of the
TM helical bundle. TMs 3, 5, 6, and 7 seem to be crucial
for the recognition of both agonists and antagonists. As
Figure 1. Flowchart describing our combined target-based
and ligand-based drug design approach.
motif has been proposed for this class of A3 inhibitors.
Docking-based structure superimposition has been used
to perform a quantitative study of structure-activity
relationships using CoMFA. A remarkable correlation
coefficient (cross-validated r2cv) of 0.840 was obtained.
Both steric and electrostatic contour plots, obtained from
the CoMFA analysis, nicely fit on the hypothetical
binding site achieved by molecular docking. Following
our computational approach, we have designed, syn-
thesized, and tested 17 new derivatives. Consistently,
the predicted Kivalues were very close to the experi-
mental values.
recently reported by Jacobson and collaborators,30
a
number of amino acid residues in the transmembrane
domains 3, 5, and the second extracellular loop (EL2)
were individually replaced with Ala and other amino
acids. These residues are homologous to those that have
been predicted in previous molecular modeling studies
of adenosine receptor to be involved in the ligand
recognition, including His95, Trp243, Ser247, Asn250,
and Lys152. To recognize the hypothetical binding motif
of this class of human A3 inhibitors, a molecular docking
study has been carried out on all 106 pyrazolotriazolo-
pyrimidine derivatives reported in Table 1. A multi-
docking protocol implemented by MOE has been utilized
in this computational step (see the Experimental Section
for details). Unfortunately, but as logically expected, we
did not found any robust quantitative correlation be-
tween the experimental binding affinity and the theo-
retical interaction energies based on the scoring function
of our docking protocol. However, our goal was to explore
if a multidocking protocol could be used to define a
target-based pharmacophore model. The first very in-
teresting result obtained from our molecular docking
studies is that all pyrazolotriazolopyrimidine derivatives
share a common binding motif inside the TM region of
human A3 receptor. Just for simplifying the description
of our results, we have selected derivative 5, as reference
ligand. Indeed, the most energetically stable docked
conformation is very similar for all the analyzed com-
pounds. As shown in Figure 2, we identified the hypo-
thetical binding site of the pyrazolotriazolopyrimidine
moiety surrounded by TMs 3, 5, 6, and 7 with the furan
ring and the N8-substituents pointing toward the EL2,
and the carbamoyl moiety in the 5-position oriented
toward the intracellular environment.
Results and Discussion
Our computational strategy has been summarized in
Figure 1. We decided to combine a target-based ap-
proach (high throughput docking) and a quantitative
ligand-based methodology like CoMFA to improve our
capability to design new potent and selective human A3
antagonists.
Starting from our recent rhodopsin-based model of the
“resting state” of human A3 receptor, we decide to per-
form high throughput docking to analyze the hypotheti-
cal binding conformation of more than 100 pyrazolo-
triazolopyrimidines recently synthesized and tested in
our laboratory. Nowadays, the robustness of the differ-
ent scoring functions to correctly predict the binding
affinity of different ligands versus the corresponding
target is very feeble, and this is particularly true in the
case of ligand-GPCRs recognition.21-24 In this study,
we decided to use CoMFA as an “alternative” strategy
to quantitatively address the binding properties of our
pyrazolotriazolopyrimidine derivatives. In fact, after
analyzing docking results, we utilized the superposition
of all low energy docked conformations as structural
input (supermolecule) for a conventional CoMFA. Both
field analysis and quantitative regression model have
been used to intrinsically validate the model. As already
mentioned above, a remarkable correlation coefficient
(cross-validated r2cv) of 0.840 was obtained. On the basis
of our combined approach, we have designed, synthe-
sized, and tested 17 new derivatives. To severely test
the quality of our model, we voluntarily designed antag-
onists with estimated activities from the micromolar to
the sub-nanomolar range. Impressively, all predicted Ki
values were very close to the experimental values. This
is nice evidence that this combined approach is a good
integration between a very consolidated target-based
approach, such as molecular docking, and a solid
quantitative ligand-based methodology such as CoMFA.
Moreover, the furan ring is positioned between TM5
and TM3 whereas the N8-substituents are surrounded
by TM2 and TM7. We have defined this peculiar and
highly conserved binding motif as the Y-shape binding

Pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidines
Journal of Medicinal Chemistry, 2005, Vol. 48, No. 1 155
Figure 2. Left: General topology of the human A3 receptor model. Reference compound 5 (colored in magenta) is docking inside
the trans-membrane recognition site (see Experimental Section for details). Side chains of some amino acids important for ligand
recognition are highlighted. Right: Side view of the human A3 receptor TM recognition region. We selected some of our 106
docked antagonists, and we superimposed them to define a new Y-shaped pharmacophore model.
motif. Interestingly, this new target-based pharmaco-
phore model is nicely coherent with all structure-
activity relationships already collected on these
pyrazolo-triazolo-pyrimidine analogues. Analyzing in
detail our model, all pyrazolotriazolopyrimidine deriva-
tives present the carbamoyl moiety in the 5-position
surrounded by two polar amino acids: His95 (TM3) and
Ser247 (TM6). This region seems to be very critical for
the recognition of the antagonist structures. In fact, a
major structural difference between the hypothetical
binding sites in these receptor subtypes is that the A3
receptor does not contain the histidine residue in TM6
common to all A1 (His251 in hA1) and A2 (His250 in
hA2A) receptors. This histidine has been shown to
participate in both agonist and antagonist binding to
phenyl ring induce a decrease of affinity at the human
A3 adenosine receptors of about 2-5-fold with respect
to the unsubstituted derivatives.15,26 The same steric
control takes place when substituents larger than
hydrogen are present at the meta position of the phenyl
ring. In this case a strong steric repulsion among
substituents, at the meta position, and amino acid side
chains of TM6 and TM7 could significantly reduce the
affinity at the hA3 receptor. On the contrary, substitu-
ents at the ortho position seem to occupy an empty
region of the binding cavity. As previously described,
in the chloro substituted series the change of the
position (2- or 4-substitution) seems not to influence
affinity at the hA1, hA2A, and hA2B receptors compared
to the 3-chloro substituted compounds, maintaining it
in the high nanomolar range (100-500 nM), while
significant differences appeared in binding affinity to
the hA3 adenosine receptors (see Table 1).15
Another important and highly conserved interaction,
probably a π-π interaction, is predicted among the
furan ring of the pyrazolotriazolopyrimidine analogues
and the two phenylalanine residues, Phe168 (EL2) and
Phe182 (TM5), respectively. This interaction seems to
be another important pharmacophore feature of our
binding motif. Interestingly, the amino acids corre-
sponding to Leu90 and Phe182 in the human A2A
receptor were found to be essential for the binding of
both agonists and antagonists.31,32
A
2A receptors.31 In the A3 receptor this histidine in TM6
is replaced with a serine residue (Ser247 in hA3). The
stabilizing interactions among the carbamoyl moiety
and these polar amino acids orient the carbamoyl phenyl
ring in the middle of the TM bundle as clearly shown
in Figure 2. In particular, the N-H of His95 (TM3) and
the oxygen atom of the carbamoyl group are separated
by 2.6 Å and appropriately oriented to form an H-
bonding interaction. The side chain of Ser247 (TM6) is
within hydrogen-bonding distance of NH of the carbam-
oyl group at 2.9 Å. According to the recently published
mutagenesis results, His95 is crucial for ligand recogni-
tion, whereas Ser247 slightly affects the binding of both
agonists and antagonists.30 The receptor region around
the phenyl ring of the carbamoyl moiety is mostly
hydrophobic and characterized by three nonpolar amino
acids: Ile98 (TM3), Ile186 (TM5), Leu244 (TM6). This
environment could justify why polar substituents at the
para position are not very well tolerated, as in the case
of sulfonic acid group.15 Evaluation of the ligand binding
pocket of the receptor reveals that very limited empty
space is present between TM5 and TM6 and, conse-
quently, a steric control seems to take place around the
para position of the phenyl ring. As already demon-
strated, substituents at the para position of the N5-
Moreover, another important and peculiar hydro-
phobic pocket delimited by nonpolar amino acids,
Leu90 (TM3), Leu246 (TM6), and Ile268 (TM7), is also
addressable in our binding site model. According to our
docking studies, all the substituents at the N8 position
are located within this region of the receptor according
to our binding hypothesis. However, two hydrophilic
amino acids, such as Ser175 (EL2) and His272 (TM7),
are present on the border of this hydrophobic pocked,
and they can interact through hydrogen bonding in the
presence of appropriate substituents. We have already

156 Journal of Medicinal Chemistry, 2005, Vol. 48, No. 1
Table 2. Statistics of the Calibration Human A3 CoMFA Model
Moro et al.
Figure 3. Side view of the 5-A3 complex model. The side
chains of some crucial important residues in proximity (e5
Å) to the docked pyrazolo-triazolo-pyrimidine molecule are
highlighted and labeled: Leu90 (TM3), His 95 (TM3); Phe182
(TM5), Ile186 (TM5); Trp243 (TM6); Ser247 (TM6), Asn250
(TM6), Ser271 (TM7), His272 (TM7), Ser275 (TM7). The steric
and the electrostatic contour plots, obtained from the CoMFA
analysis, are included into ligand binding cavity. The yellow
and the blue polyhedra correspond to regions of the field that
are predicted to decrease the A3 receptor affinity, while the
green and the red regions are predicted to increase binding
affinity.
no. of compounds
106
principal componentsa
6
b
r2
0.840
0.922
141.67
<0.001
0.802
0.571
0.429
0.185
0.022
cv
r2
F-testc
p
d
r2
bs
steric contribution
electrostatic contribution
SEPe
std devf
analysis based on a least-squares fit gave a correlation
with a cross-validated r2cv of 0.840, with the maximum
number of components set equal to 6 (maximum number
of components set equal to 4, 5, or 7 gave lower cross-
validated r2cv) and the cross-validation groups set equal
to the number of observations. The non-cross-validated
PLS analysis was repeated with the optimum number
of components, as determined by the cross-validated
analysis, to give an r2 of 0.922. To obtain statistical
confidence limits, the non-cross-validated analysis was
repeated with 10 bootstrap groups, which yielded an r2
of 0.802 (optimum number of components was 6), SEP
) 0.185, standard deviation ) 0.022, steric contribution
) 0.571, and electrostatic contributions ) 0.429. The
CoMFA-derived QSAR of pyrazolotriazolopyrimidine
derivatives exhibited a good cross-validated correlation,
indicating that it was highly predictive. Cross-validation
provides information concerning the predictive ability
of the QSAR data set by minimizing the occurrence of
chance correlations in the QSAR model. The high
bootstrapped r2 value and a small standard deviation
suggest a high degree of confidence in the analysis.
Fitted vs measured pKi values for the CoMFA analysis
of the human A3 training set are shown in Table 2.
The coefficients corresponding to each sampled field
point in the resulting correlation equation were graphi-
cally contoured. Contours corresponding to the steric
(green and yellow) and electrostatic (blue and red) fields
are plotted together with compound 5 docked inside the
human A3 binding cavity as shown in Figure 3.
a Minimum s ) 2.0. b Standard error of prediction (cross-
validated) ) (PRESS/(n - c - l))1/2, n ) number of rows, c )
number of components. c Ratio of r2 explained to unexplained )
r2/(l - r2). d r2bs ) r2 after bootstrapping. e Cross-validated r2 after
leave-one-out procedure: r2 ) (SD - PRESS)/SD, SD ) (Yactual
cv
2
- Ymean
)
and PRESS ) ∑(Ypredicted - Yactual). For further expla-
nationof these mathematical formulas, see ref 40. f The std dev
row belongs with the bootstrapping r2.
published and rationalized that hydrophobic substitu-
ents are very well tolerated at the N8 position.18
Finally, a strong hydrogen bonding interaction is
possible between Asn250 (TM6) and the triazolo ring
of the pyrazolotriazolopyrimidine moiety. In particular,
the N-H of Asp250 and the N4 of the triazolo ring group
are separated by 2.5 Å and appropriately oriented to
form an H-bonding interaction. Also this asparagine
residue, conserved among all adenosine receptor sub-
types, was found to be important for ligand binding.31,32
No direct interactions are predicted between the
antagonist structure and the two polar amino acids
Thr94 (TM3) and Ser97 (TM3). As previously reported,
the corresponding two amino acids in the A1 and A2A
receptors, respectively, are important for the coordina-
tion of agonists, but not for antagonists.31,32
Molecular Modeling. 2. CoMFA as “Alternative”
Scoring Function. In tandem with our molecular
docking studies, a CoMFA methodology was applied to
the data from the A3 binding assay as a means of
identifying the structural features of pyrazolotriazolo-
pyrimidine derivatives responsible for affinity. Our
approach consists of utilizing CoMFA as a quantitative
tool to predict the receptor binding affinity using the
pharmacophore model based on the multidocking ap-
proach described above. PLS was used in conjunction
with cross-validation to obtain the optimal number of
components to be used in the subsequent analyses. PLS
The polyhedra describe the regions of space where the
steric and the electrostatic fields are predicted by the
CoMFA model to have the greatest effect on binding
affinity. The yellow and the blue polyhedra correspond
to regions of the field that are predicted to decrease the
A3 receptor affinity, while the green and the red regions
are predicted to increase binding affinity. As shown in

Pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidines
Journal of Medicinal Chemistry, 2005, Vol. 48, No. 1 157
Table 3. Structures, Physicochemical Parameters, and Human A3 (Predicted and Calculated) Binding Affinities of New Synthesized
Compounds (107-123)
hA3 Ki (nM)
no.
R
R1
mp (°C)
MW
obsd
calcd
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
n-C8H17
CH2-c-C6H11
CH3
CH3
CH3
H
H
135
353.20
337.17
380.17
368.17
461.17
436.23
424.23
516.22
440.20
478.28
466.28
558.27
486.25
462.25
450.25
542.24
470.22
2050 (1570-2680)
1720 (1320-2240)
1.01 (0.89-1.16)
1.95 (1.39-2.72)
0.82 (0.59-1.15)
20.53 (17.65-28.76)
8.09 (7.46-8.78)
11.89 (8.72-16.20)
7.41 (5.56-9.86)
16.29 (13.74-19.30)
7.83 (4.89-12.53)
9.97 (8.29-11.98)
4.48 (3.65-5.50)
6.70 (5.30-8.46)
3.98 (3.16-5.01)
6.95 (5.34-9.06)
5.94 (4.36-8.10)
3288
1380
0.93
0.33
0.45
20.70
7.39
9.95
7.28
17.06
6.10
8.20
3.09
7.21
2.58
3.48
2.54
195
CONH-c-C6H11
208-210
185-188
222-224
165
178-180
163
223-228
123-125
125
150-154
226-228
130
170
185
206-210
CONH-n-C5H11
CONH-Ph-4-CH2CO2Et
CONH-c-C6H11
CH2CH2CH(CH3)2
CH2CH2CH(CH3)2
CH2CH2CH(CH3)2
CH2CH2CH(CH3)2
n-C8H17
CONH-n-C5H11
CONH-Ph-4-CH2CO2Et
CONH-Ph-4-CH3
CONH-c-C6H11
n-C8H17
CONH-n-C5H11
n-C8H17
CONH-Ph-4-CH2CO2Et
CONH-Ph-4-CH3
CONH-c-C6H11
n-C8H17
CH2-c-C6H11
CH2-c-C6H11
CH2-c-C6H11
CH2-c-C6H11
CONH-n-C5H11
CONH-Ph-4-CH2CO2Et
CONH-Ph-4-CH3
Figure 3, the proposed pharmacophore model fits very
nicely within the transmembrane binding cleft. All steric
and electrostatic features are coherent with the struc-
ture-activity relationship already described during the
molecular docking analysis above. In particular, a green
polyhedron, with a mean steric bulk favorable region,
is found near the N5-carbamoyl moiety. As already
described, this green polyhedron nicely fits with the
receptor region around the phenyl ring of the carbamoyl
moiety and characterized by three nonpolar amino
acids: Ile98 (TM3), Ile186 (TM5), Leu244 (TM6). More-
over, from an electrostatic point of view the two red
polyhedra around to N8-substituents and to the N5-
carbamoyl moiety are complementary respectively to
Ser175 (EL2), His95 (TM3), Ser247 (TM6), and His272
(TM7). On the other hand, the blue polyhedron close to
the N5-phenyl ring is surrounded by four nonpolar
amino acids [Ile98 (TM3), Ile186 (TM5), Phe239 (TM6),
and Leu244 (TM6)] and the most important electrostatic
interactions are mediated by the corresponding CO-
NH peptide bonds.
Molecular Modeling. 3. Validation Set. On the
basis of both the target-based pharmacophore model and
the CoMFA model as alternative scoring function, we
have designed, synthesized, and tested 17 (107-123)
new derivatives with a different spectrum of affinity at
the human A3 receptor. Compounds 107-123 (test set,
shown in Table 2) were used to evaluate the predic-
tive power of this CoMFA model. As in the calibration
step, a good predictive ability with an r2pred ) 0.873 for
the compounds in the test set was obtained. Table 3
shows that the affinities of all the examined compounds
were predicted within 0.25 log unit across a range of
2.00 log units. Impressively, the predicted Ki values
were very close to the experimental values. In particu-
lar, derivative 111 (4-[3-(2-furan-2-yl-8-methyl-8H-
pyrazolo[4,3-e][1,2,4]triazolo[1,5-c]pyrimidin-5-yl)ureido]-
phenylacetic acid ethyl ester) is active in a sub-nano-
molar range (0.82 nM) as correctly predicted by our
regression model. Again, this is clear evidence that this
combined approach is a nice integration between a very
consolidated target-based approach, such as molecular
docking, and a solid quantitative ligand-based method-
ology such as CoMFA.
Synthesis of the Validation Set. Compounds 107-
123 were prepared following the general synthetic
strategy summarized in Scheme 1. Compounds 107-
123 were synthesized according to a well-known proce-
dure for the synthesis of the pyrazolo[4,3-e]-1,2,4-
triazolo[1,5-c]pyrimidines, previously reported.14-18
Alkylation of 5-amino-4-cyanopyrazole 124 with the
appropriate alkyl halide in dry dimethylformamide led
to an approximately 1:4 mixture of the N1 and N2
regioisomers (125, 126) as an inseparable mixture, used
for the following steps without any further purification.
Pyrazoles (125 and 126) were reacted with 2-furoic
acid hydrazide in diphenyl ether at 260 °C to yield the
aminotriazoles 127 and 128 , which were in turn
converted into the 5-amino-8-(substituted)-2-(2-furyl)-
pyrazolo[4,3-e]-1,2,4-triazolo[1,5-c]pyrimidine deriva-
tives by reaction with cyanamide in the presence of
p-toluenesulfonic acid. After separation of N7 (minor
product) and N8 (major product) regioisomers by flash
chromatography, the dried compounds 107 and 108
were obtained in good overall yield. Final compounds
109-123 were obtained by reaction of amino compounds
5, 20, 107, and 108, with the appropriate isocyanate
(129-132) in dioxane at reflux.
Final Remarks. Fundamental understanding of the
molecular details of ligand/GPCR interactions remains

158 Journal of Medicinal Chemistry, 2005, Vol. 48, No. 1
Moro et al.
Scheme 1a
a
Reagents: (i) NaH, DMF, RX; (ii) 2-furoic hydrazide, Ph2O, 260 °C; (iii) NH2CN, 1-methyl-2-pyrrolidone, pTsOH, 140 °C, then flash
chromatography; (iv) dioxane reflux, 18 h. For compounds 8 and 9 see ref 18.
Homology modeling, energy calculation, and docking studies
have been done using Molecular Operating Environment
(MOE, version 2003.03) suite.34
very rudimentary. How agonist binding transforms a
resting GPCR into its active form and the microscopic
basis of binding site blockade by an antagonist are
generally still unclear. We decided to utilize in tandem
structure-based and ligand-based drug design strategies
to improve our knowledge about the human A3 recep-
tor-antagonist recognition process. In particular, using
this combined strategy we have identified common
subtle structural features of pyrazolo-triazolo-pyrim-
idines which lead to enhanced potency or selectivity at
A3 receptors. To specifically address the hypothetical
binding motif of pyrazolotriazolopyrimidine derivatives
we have used a multiple docking strategy to identify a
novel target-based pharmacophore model. Superimposi-
tion of all low energy docked conformations has been
used to characterize the more conserved chemical
features crucial to the recognition process (target-based
pharmacophore) and their fit in the putative binding
site of the receptor. On the basis of the proposed
pharmacophore map, we can state that the receptor
binding properties of different A3 antagonist derivatives
are due to recognition at a common region inside the
receptor binding site and, consequently, a common
electrostatic potential profile. Due to the poor predic-
tivity of the current scoring functions, we have decided
to use CoMFA as an alternative tool to quantitatively
predict the ligand-receptor binding affinity. Consist-
ently with this new combined pharmacophore hypoth-
esis, we have designed, synthesized, and tested 17 new
pyrazolotriazolopyrimidine derivatives with a different
spectrum of affinity at the human A3 receptor. As
already underlined, the predicted pKi values were very
close to the experimental values.
CoMFA is a three-dimensional QSAR method that operates
on a set of ligands that have been superimposed to reflect their
anticipated common receptor binding orientation. CoMFA
models describe the extent to which the change in magnitude
of the electrostatic and steric fields as a function of compound,
sampled as a function of spatial position around the compound
set, accounts for the variance in measured biological activity.
CoMFA studies were performed on a Silicon Graphics Power
Indigo2 R8000 workstation running SYBYL 6.5.35 Quantum
calculations used throughout this study were performed using
MOPAC (version 7.0).36
Homology Model of the Resting State of Human A3
Receptor. On the basis of the assumption that GPCRs share
similar TM boundaries and overall topology,37 a homology
model of the human A3 receptor was constructed. First, the
amino acid sequences of TM helices of the resting state A3
receptor were aligned with those of bovine rhodopsin, guided
by the highly conserved amino acid residues, including the
DRY motif (D3.49, R3.50, and Y3.51) and three Pro residues
(P4.60, P6.50, and P7.50) in the TM segments of GPCRs. The
same boundaries were applied for the TM helices of the A3
receptor as were identified from the X-ray crystal structure
for the corresponding sequences of bovine rhodopsin,27 the CR
coordinates which were used to construct the seven TM helices
for the human A3 receptor. The loop domains of the human A3
receptor were constructed by the loop search method imple-
mented in MOE. In particular, loops are modeled first, in
random order. For each loop, a contact energy function
analyzes the list of candidates collected in the segment
searching stage, taking into account all atoms already modeled
and any atom specified by the user as belonging to the model
environment. These energies are then used to make a Boltz-
mann-weighted choice from the candidates, the coordinates of
which are then copied to the model. Any missing side chain
atoms are modeled using the same procedure. Side chains
belonging to residues whose backbone coordinates were copied
from a template are modeled first, followed by side chains of
modeled loops. Outgaps and their side chains are modeled last.
Special caution had to be given to the second extracellular (E2)
loop, which has been described in bovine rhodopsin to fold back
over transmembrane helices,27 and, therefore, it limits the size
of the active site. Hence, amino acids of this loop could be
involved in direct interactions with the ligands. The presence
of a disulfide bridge between cysteines in TM3 and E2 might
be the driving force to this peculiar fold of the E2 loop. Since
this covalent link is conserved in all receptors modeled in the
current study, the E2 loop was modeled using a rhodopsin-
like constrained geometry around the E2-TM3 disulfide
bridge. After the heavy atoms were modeled, all hydrogen
atoms were added, and the protein coordinates were then
In conclusion, using our combined approach pyra-
zolo-triazolo-pyrimidine derivatives have served as
structural scaffolds for enhancement of selectivity at
human A3 receptors and as important modeling probes
for the study of the human A3 receptor binding site.
Moreover, we are deeply analyzing whether or not
structurally unrelated antagonists would fit into the
novel defined pharmacophore model.
Experimental Section
Computational Methodologies. All molecular modeling
studies were carried out on a 6 CPU (PIV 2.0-3.0 GHZ) Linux
cluster running under openMosix architecture.33

Pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidines
Journal of Medicinal Chemistry, 2005, Vol. 48, No. 1 159
minimized with MOE using the AMBER94 force field.38 The
minimizations were carried out by 1000 steps of steepest
descent followed by conjugate gradient minimization until the
rms gradient of the potential energy was less than 0.1 kcal
Partial least squared (PLS) regression analysis43 was per-
formed on the human A3 antagonist dataset using a subset of
CoMFA field sample points falling with a standard deviation
e1.0 kcal/mol. The steric and the electrostatic fields were
scaled to equalize their weighting in the CoMFA models
(SYBYL command “scaling CoMFA_std”). PLS was performed
using cross-validation to evaluate the predictive ability of the
CoMFA models.44 The optimal number of latent variables came
from the cross-validation equation having the lowest standard
error, and a significance level g99.5% was estimated using
the stepwise F-test. Bootstrap analysis of the dataset was used
mol-1 Å-1
.
Molecular Docking (Multidocking) of the Human A3
Receptor Antagonists. All 106 antagonist structures were
docked into the hypothetical TM binding site by using the
MULTIDOCK docking program, which is part of the MOE
suite. Conformational samplings were conducted within a user-
specified 3D docking box, using the Tabu Search protocol39 and
MMFF94 force field.40 MOE-Dock performs a user-specified
number of independent docking runs (20 in our specific case)
and wrote the resulting conformations and their energies in a
molecular database file. The resulting docked complexes were
subjected to MMFF94 energy minimization until the rms of
the conjugate gradient was <0.1 kcal mol-1 Å-1. Charges for
the ligands were imported directly from the MMFF94 force
field.
The interaction energy values were calculated as follows:
∆Ebinding ) Ecomplex - (Eligand + Ereceptor). These energies are not
rigorous thermodynamic quantities, but can only be used to
compare the relative stabilities of the complexes. Therefore,
these interaction energy values cannot be used to calculate
binding affinities since changes in entropy and solvation effects
are not taken into account.
to evaluate the statistical confidence limits of the results.44
A
σ value of 2.0 was adopted for both the cross-validated and
non-cross-validated analysis. σ values of 1.0 or 0.5 did not
significantly change the calculated r2.
Initial PLS analyses were performed in conjunction with the
cross-validation option (leave-one-out method) to obtain the
optimal number of components to be used in the subsequent
analyses of the dataset. The PLS analysis was repeated with
the number of cross-validation groups set to zero. The optimal
number of components was designated as that which yielded
the highest cross-validated r2 values in the non-cross-validated
(conventional) analyses. The final PLS analysis with 10
bootstrap groups and the optimal number of components was
performed on the complete dataset.
The corresponding calibration equation (resulting from the
simultaneous contribution of all the observations) was derived
after the optimal dimensionality of each receptor model was
established, by PLS analysis and cross-validation. The calibra-
tion equation with latent variables was then converted to the
original parametric space represented by probe-ligand inter-
action energies. A 3D-QSAR whose coefficients were associated
with statistically significant lattice locations was therefore
derived. CoMFA coefficient contour maps were generated by
interpolation of the pairwise products between the 3D-QSAR
coefficients and the standard deviations of the associated
energy variables.
CoMFA: Data Sets and Binding Studies. A total of 106
pyrazolo-triazolo-pyrimidine derivatives were included in the
training set used to generate the CoMFA model for human A3
receptors (see Table 1).
The synthesis of all pyrazolo-triazolo-pyrimidine deriva-
tives was reported in detail previously.15-20 Binding of
[3H]MRE3008-F20 to CHO cells transfected with the human
recombinant A3 adenosine receptors was performed according
to Varani et al.41 Competition experiments were carried out
in duplicate in a final volume of 250 µL in test tubes containing
1 nM [3H] MRE3008-F20, 50 mM Tris HCl buffer, 10 mM
MgCl2, pH 7.4, 100 µL of diluted membranes (50 µg protein/
assay), and at least 6-8 different concentrations of examined
ligands. Incubation time was 120 min at 4 °C, according to
the results of previous time-course experiments.41 Nonspecific
binding was defined as binding in the presence of 1 µM
MRE3008-F20 and was about 25% of total binding. Bound and
free radioactivity were separated by filtering the assay mixture
through Whatman GF/B glass-fiber filters using a Micro-Mate
196 cell harvester (Packard Instrument Company). The filter
bound radioactivity was counted on Top Count (efficiency 57%)
with Micro-Scint 20. The protein concentration was determined
according to the Bio-Rad method with bovine albumin as
reference standard.42
CoMFA: Test Sets. The test sets consisted of 17 new
synthesized molecules for the considered training set 107-
123 (Table 2). These structures were chosen to maximize a
uniform sampling of biological activity. All predicted activities
for the test set molecules were calculated using the optimized
CoMFA model. The results of the non-cross-validated calibra-
tion model on the test sets are summarized in Table 2.
CoMFA: “Predictive” r2 Values. The “predictive” r2
pred
was based only on molecules not included in the training set
and is defined as explained by Marshall and co-workers.45
Chemistry. General. Reactions were routinely monitored
by thin-layer chromatography (TLC) on silica gel (precoated
F254 Merck plates) and products visualized with iodine or
potassium permanganate solution. Infrared spectra (IR) were
CoMFA: Molecular Superposition. The pyrazolo-
triazolo-pyrimidine moiety is believed to be a determinant
key for binding interactions of described derivatives. The
energetically more stable docking conformation has been used
for all compounds, as input for the CoMFA field calculations.
1
measured on a Jasco FT-IR 200 spectrophotometer. H NMR
were determined in CDCl3 or DMSO-d6 solutions with a Varian
Gemini 200 spectrometer, peaks positions are given in parts
per million (δ) downfield from tetramethylsilane as internal
standard, and J values are given in hertz. Light petroleum
ether refers to the fractions boiling at 40-60 °C. Melting points
were determined on a Buchi-Tottoli instrument and are
uncorrected. Chromatographies were performed using Merck
60-200 mesh silica gel. All products reported showed IR and
1H NMR spectra in agreement with the assigned structures.
Organic solutions were dried over anhydrous magnesium
sulfate. Elemental analyses were performed by the micro-
analytical laboratory of Dipartimento di Chimica, University
of Trieste, and were within (0.4% of the theoretical values
for C, H, and N.
CoMFA: Field Calculations and Regression Tech-
niques. The electrostatic and steric fields were sampled along
a three-dimensional lattice encompassing all molecules in each
receptor data set. The lattice consisted of 720 sample points
based on a 2.0 Å lattice spacing with boundaries extending
4.0 Å beyond the largest structure in all directions. Lattice
spacings of 0.75 and 1.5 Å were also used without improve-
ments of the CoMFA results. The lattice points within the
union volume of the superimposed structures were dropped.
The probe used to calculate the CoMFA fields consisted of an
sp3 carbon atom with a +1 charge and a van der Waals radius
of 1.52 Å. The steric and electrostatic fields were calculated
separately for each molecule using respectively a Lennard-
Jones 6-12 potential and a Coulombic potential with a 1/r
distance-dependent dielectric. The steric and electrostatic
energies were truncated at 30 kcal/mol. The field values
corresponding to the 720 sample points for each molecule,
together with binding affinity data, were stored in a SYBYL
Molecular Spreadsheet to facilitate statistical analysis.
General Procedures for the Preparation of 8-(Ar)alkyl-
2-(2-furyl)pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine
(107, 108). A solution of 124 (10 mmol) in 40 mL of DMF cooled
to 0 °C was treated with NaH (60% in oil, 12 mmol) in several
portions over 10 min. After 45 min, the appropriate alkyl
halide (12 mmol) was added and the reaction mixture was
allowed to warm to 25 °C and stirred for 3-5 h (TLC:EtOAc
1:1). The reaction was quenched by addition of H2O (80 mL),

160 Journal of Medicinal Chemistry, 2005, Vol. 48, No. 1
Moro et al.
and the aqueous layer was extracted with EtOAc (5 × 25 mL).
The organic layers were recombined, dried (Na2SO4), filtered,
and concentrated at reduced pressure, to afford the alkylated
pyrazole (125, 126) as an inseparable mixture of N1 and N2
isomers (ratio approximately 1:4). This mixture of N1- and N2-
substituted-4-cyano-5-amino pyrazoles (125, 126) was then
dissolved in diphenyl ether (50 mL), and 2-furoic acid hy-
drazide (13 mmol) was added. The mixture was heated at 260
°C using a Dean-Stark trap for the azeotropic elimination of
water produced in the reaction. After 2.5 h, the mixture was
poured onto hexane (300 mL) and cooled. The precipitate of
crude pyrazole-triazole derivatives (127, 128) was filtered off
and utilized for the next step without further purifications.
The crude residue was dissolved in N-methylpyrrolidone (40
mL), cyanamide (60 mmol) and p-toluenesulfonic acid (15
mmol) were added, and the mixture was heated at 160 °C for
4 h. Cyanamide (60 mmol) was added again, and the solution
was heated overnight. Then the solution was diluted with
EtOAc (80 mL) and the precipitate (excess of cyanamide) was
filtered off; the filtrate was concentrated under reduced
pressure and washed with water (3 × 30 mL). The organic
layer was dried (Na2SO4) and evaporated under vacuum. The
residue was purified by flash chromatography (EtOAc/light
petroleum 3:7) for obtaining the major product (N8 alkylated)
(107, 108), which was obtained in a good overall yield.
5-Amino-8-n-octyl-2-(2-furyl)-pyrazolo[4,3-e]1,2, 4-tri-
azolo[1,5-c]pyrimidine (107). Yield: 45%; pale brown solid.
IR (KBr): 3430-2950, 1680, 1655, 1620, 1550, 1450 cm-1. 1H
NMR (DMSO-d6) δ: 0.78 (t, 2H, J ) 7); 1.01-1.25 (m, 10H);
1.62-1.99 (m, 2H); 4.22 (t, 2H, J ) 7); 6.67 (dd, 1H, J ) 2, J
) 4); 7.14 (d, 1H, J ) 4); 7.57 (bs, 2H); 7.88 (d, 1H, J ) 2);
8.58 (s, 1H). Anal. (C18H23N7O) C, H, N.
Yield: 87%; white solid. IR (KBr): 3250-2970, 1673, 1610,
1600, 1515 cm-1. 1H NMR (CDCl3) δ: 0.88 (d, 6H, J ) 6); 1.15-
1.99 (m, 13H); 3.61-3.63 (m, 1H); 4.21 (t, 2H, J ) 7); 6.65
(dd, 1H, J ) 2, J ) 4); 7.23 (d, 1H, J ) 4); 7.97 (d, 1H, J ) 2);
8.64 (bs, 1H); 8.81 (s, 1H); 9.00 (bs, 1H). Anal. (C22H28N8O2)
C, H, N.
5-[[(n-Pentyl)amino]carbonyl]amino-8-isopentyl-2-(2-
furyl)pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine (113).
Yield: 87%; white solid. IR (KBr): 3245-2955, 1675, 1625,
1600, 1510 cm-1. 1H NMR (CDCl3) δ: 0.79-0.99 (m, 9H); 1.11-
1.59 (m, 11H); 1.64-1.81(m, 2H); 4.35 (t, 2H, J ) 7); 6.68 (dd,
1H, J ) 2, J ) 4); 7.25 (d, 1H, J ) 4); 7.94 (d, 1H, J ) 2); 8.63
(bs, 1H); 8.81 (s, 1H); 9.02 (bs, 1H). Anal. (C21H28N8O2) C, H,
N.
4-[3-(2-Furan-2-yl-8-isopentyl-8H-pyrazolo[4,3-e][1,2,4]-
triazolo[1,5-c]pyrimidin-5-yl)ureido]phenylacetic Acid
Ethyl Ester (114). Yield: 68%; pale brown solid. IR (KBr):
3230-2950, 1723, 1670, 1625, 1600, 1500 cm-1 1H NMR
.
(CDCl3) δ: 0.96 (d, 6H, J ) 6); 1.23 (t, 3H, J ) 7); 1.25-1.28
(m, 1H); 3.59 (s, 1H); 4.19 (t, 2H, J ) 7); 4.39 (q, 2H, J ) 7);
6.61 (dd, 1H, J ) 2, J ) 4); 7.17 (d, 2H, J ) 9); 7.30 (d, 1H, J
) 4); 7.61 (d, 2H, J ) 7); 7.65 (d, 1H, J ) 2); 8.21 (s, 1H); 8.57
(bs, 1H); 11.12 (bs, 1H). Anal. (C26H28N8O4) C, H, N.
5-[[(4-Tolyl)amino]carbonyl]amino-8-isopentyl-2-(2-
furyl)pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine (115).
Yield: 81%; pale yellow solid. IR (KBr): 3235-2945, 1672,
1
1620, 1600, 1505 cm-1. H NMR (CDCl3) δ: 0.96 (d, 6H, J )
6); 1.16-1.22 (m, 1H); 1.89-1.92 (m, 2H); 2.32 (s, 3H); 4.39 (t,
2H, J ) 7); 6.59 (dd, 1H, J ) 2, J ) 4); 7.14 (d, 2H, J ) 9);
7.25 (d, 1H, J ) 4); 7.54 (d, 2H, J ) 9); 7.64 (d, 1H, J ) 2);
8.21 (s, 1H); 8.56 (bs, 1H); 11.01 (bs, 1H). Anal. (C23H24N8O2)
C, H, N.
5-Amino-8-cyclohexylmethyl-2(2-furyl)pyrazolo[4,3-
e]1,2,4-triazolo[1,5-c]pyrimidine (108). Yield: 38%; pale
brown solid. IR (KBr): 3445-2960, 1675, 1650, 1615, 1555,
5-[[(Cyclohexyl)amino]carbonyl]amino-8-n-octyl-2-(2-
furyl)pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine (116).
Yield: 80%; white solid. IR (KBr): 3235-2945, 1665, 1615,
1560 cm-1. 1H NMR (CDCl3) δ: 0.80 (t, 3H, J ) 7); 1.01-2.00
(m, 22H); 3.59-3.62 (m, 1H); 4.32 (t, 2H, J ) 7); 6.72 (dd, 1H,
J ) 2, J ) 4); 7.25 (d, 1H, J ) 4); 7.95 (d, 1H, J ) 2); 8.68 (bs,
1H); 8.78 (s, 1H); 8.99 (bs, 1H). Anal. (C25H34N8O2) C, H, N.
5-[[(n-Pentyl)amino]carbonyl]amino-8-n-octyl-2-(2-
furyl)pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine (117).
Yield: 78%; white solid. IR (KBr): 3250-2970, 1663, 1610,
1545 cm-1. 1H NMR (CDCl3) δ: 0.78-0.84 (m, 6H); 1.04-1.32
(m, 16H); 1.42-1.50 (m, 2H); 1.79-1.98 (m, 2H); 4.38 (t, 2H,
J ) 7); 6.69 (dd, 1H, J ) 2, J ) 4); 7.22 (d, 1H, J ) 4); 7.93 (d,
1H, J ) 2); 8.65 (bs, 1H); 8.77 (s, 1H); 9.01 (bs, 1H). Anal.
(C24H34N8O2) C, H, N.
4-[3-(2-Furan-2-yl-8-n-octyl-8H-pyrazolo[4,3-e][1,2,4]-
triazolo[1,5-c]pyrimidin-5-yl)ureido]phenylacetic Acid
Ethyl Ester (118). Yield: 87%; white solid. IR (KBr): 3240-
2950, 1730, 1665, 1615, 1600, 1530 cm-1. 1H NMR (CDCl3) δ:
0.86 (t, 3H, J ) 7); 1.09-1.31 (m, 13H); 1.97-2.11 (m, 2H);
3.56 (s, 1H); 4.15 (q, 2H, J ) 7); 4.36 (t, 2H, J ) 7); 6.62 (dd,
1H, J ) 2, J ) 4); 7.19 (d, 2H, J ) 9); 7.23 (d, 1H, J ) 4); 7.62
(d, 2H, J ) 7); 7.64 (d, 1H, J ) 2); 8.21 (s, 1H); 8.57 (bs, 1H);
11.13 (bs, 1H). Anal. (C29H34N8O4) C, H, N.
1
1450 cm-1. H NMR (DMSO-d6) δ: 0.89-1.08 (m, 4H); 1.43-
1.49 (m, 4H); 1.71-1.89 (m, 1H); 4.08 (d, 2H, J ) 6); 6.68 (dd,
1H, J ) 2, J ) 4); 7.14 (d, 1H, J ) 4); 7.58 (bs, 2H); 7.89 (d,
1H, J ) 2); 8.54 (s, 1H). Anal. (C17H19N7O) C, H, N.
General Procedure for the Preparation of 5-[[(Sub-
stituted)amino]carbonyl]amino-8-alkyl-2-(2-furyl)pyra-
zolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine (109-123). Amino
compound (5, 20, 107, 108) (10 mmol) was dissolved in freshly
distilled dioxane (15 mL), and the appropriate isocyanate
(129-132) (13 mmol) was added. The mixture was refluxed
under argon for 18 h. Then the solvent was removed under
reduced pressure, and the residue was purified by flash
chromatography (EtOAc-light petroleum 7:3) to afford the
desired compounds 109-123.
5-[[(Cyclohexyl)amino]carbonyl]amino-8-methyl-2-(2-
furyl)pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine (109).
Yield: 90%; white solid. IR (KBr): 3245-2950, 1675, 1615,
1600, 1520 cm-1 1H NMR (CDCl3) δ: 1.01-1.95 (m, 10H);
.
3.26-3.29 (m, 1H); 4.06 (s, 3H); 6.68 (dd, 1H, J ) 2, J ) 4);
7.25 (d, 1H, J ) 4); 7.94 (d, 1H, J ) 2); 8.72 (s, 1H); 8.73 (bs,
1H); 9.01 (bs, 1H). Anal. (C18H20N8O2) C, H, N.
5-[[(n-Pentyl)amino]carbonyl]amino-8-methyl-2-
(2-furyl) pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine
(110). Yield: 82%; white solid. IR (KBr): 3240-2970, 1670,
5-[[(4-Tolyl)amino]carbonyl]amino-8-n-octyl-2-(2-furyl)-
pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine
(119).
Yield: 77%; white solid. IR (KBr): 3230-2940, 1675, 1615,
1580 cm-1. 1H NMR (CDCl3) δ: 0.84 (t, 3H, J ) 7); 1.09-1.21
(m, 10H); 1.95-2.05 (m, 2H); 2.31 (s, 3H); 4.36 (t, 2H, J ) 7);
6.60 (dd, 1H, J ) 2, J ) 4); 7.15 (d, 2H, J ) 9); 7.23 (d, 1H, J
) 4); 7.55 (d, 2H, J ) 9); 7.64 (d, 1H, J ) 2); 8.20 (s, 1H); 8.56
(bs, 1H); 11.02 (bs, 1H). Anal. (C26H30N8O2) C, H, N.
1
1620, 1600, 1510 cm-1. H NMR (CDCl3) δ: 0.88 (t, 3H, J )
7); 1.10-1.51 (m, 6H); 3.26-3.29 (m, 1H); 4.09 (s, 3H); 6.72
(dd, 1H, J ) 2, J ) 4); 7.26 (d, 1H, J ) 4); 7.96 (d, 1H, J ) 2);
8.72 (s, 1H); 8.73 (bs, 1H); 8.98 (bs, 1H). Anal. (C17H20N8O2)
C, H, N.
4-[3-(2-Furan-2-yl-8-methyl-8H-pyrazolo[4,3-e][1,2,4]-
triazolo[1,5-c]pyrimidin-5-yl)-ureido]phenylacetic Acid
Ethyl Ester(111). Yield: 82%; pale gray solid. IR (KBr):
5-[[(Cyclohexyl)amino]carbonyl]amino-8-cyclohexyl-
methyl-2-(2-furyl)pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrim-
idine (120). Yield: 74%; white solid. IR (KBr): 3245-2935,
3250-2960, 1725, 1675, 1615, 1600, 1510 cm-1 1H NMR
.
1672, 1610, 1560 cm-1 1H NMR (CDCl3) δ: 0.93-2.01 (m,
.
(CDCl3) δ: 1.23 (t, 3H, J ) 7); 3.62 (s, 2H); 4.16 (q, 2H, J ) 7);
6.72 (dd, 1H, J ) 2, J ) 4); 7.17 (d, 2H, J ) 9); 7.26 (d, 1H, J
) 4); 7.71 (d, 2H, J ) 7); 7.76 (d, 1H, J ) 2); 8.15 (s, 1H); 8.56
(bs, 1H); 11.13 (bs, 1H). Anal. (C22H21N8O4) C, H, N.
5-[[(Cyclohexyl)amino]carbonyl]amino-8-isopentyl-2-
(2-furyl)pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine(112).
21H); 3.48-3.56 (m, 1H); 4.19 (d, 2H, J ) 6); 6.78 (dd, 1H, J
) 2, J ) 4); 7.22 (d, 1H, J ) 4); 7.98 (d, 1H, J ) 2); 8.63 (bs,
1H); 8.76 (s, 1H); 8.98 (bs, 1H). Anal. (C24H30N8O2) C, H, N.
5-[[(n-Pentyl)amino]carbonyl]amino-8-n-octyl-2-(2-
furyl)pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine (121).
Yield: 83%; white solid. IR (KBr): 3245-2965, 1665, 1615,

Pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidines
Journal of Medicinal Chemistry, 2005, Vol. 48, No. 1 161
1
1550 cm-1. H NMR (CDCl3) δ: 0.82-1.97 (m, 22H); 4.11 (d,
References
2H, J ) 6); 6.72 (dd, 1H, J ) 2, J ) 4); 7.25 (d, 1H, J ) 4);
7.94 (d, 1H, J ) 2); 8.73 (bs, 1H); 8.75 (s, 1H); 8.97 (bs, 1H).
Anal. (C23H30N8O2) C, H, N.
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4-[3-(2-Furan-2-yl-8-cyclohexylmethyl-8H-pyrazolo-
[4,3-e][1,2,4]triazolo[1,5-c]pyrimidin-5-yl)ureido]phenyl-
acetic Acid Ethyl Ester (122). Yield: 69%; white solid. IR
(KBr): 3255-2966, 1725, 1670, 1625, 1600, 1510 cm-1 1H
.
NMR (CDCl3) δ: 1.20 (t, 3H, J ) 7); 1.41-1.92 (m, 11H); 3.59
(s, 1H); 4.12 (d, 2H, J ) 6); 4.16 (q, 2H, J ) 7); 6.61 (dd, 1H,
J ) 2, J ) 4); 7.21 (d, 2H, J ) 9); 7.24 (d, 1H, J ) 4); 7.61 (d,
2H, J ) 7); 7.63 (d, 1H, J ) 2); 8.17 (s, 1H); 8.59 (bs, 1H);
11.15 (bs, 1H). Anal. (C28H30N8O4) C, H, N.
5-[[(4-Tolyl)amino]carbonyl]amino-8-cyclohexylmethyl-
2-(2-furyl)pyrazolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine
(123). Yield: 87%; white solid. IR (KBr): 3250-2955, 1673,
1620, 1570 cm-1. 1H NMR (CDCl3) δ: 0.93-1.21(m, 6H); 1.42-
1.78 (m, 4H); 1.97-2.12 (m, 1H); 2.29 (s, 3H); 4.15 (d, 2H, J )
6); 6.59 (dd, 1H, J ) 2, J ) 4); 7.18 (d, 2H, J ) 9); 7.24 (d, 1H,
J ) 4); 7.51 (d, 2H, J ) 9); 7.64 (d, 1H, J ) 2); 8.16 (s, 1H);
8.56 (bs, 1H); 11.00 (bs, 1H). Anal. (C25H26N8O2) C, H, N.
Appendix
Abbreviations. CGS15943, 5-amino-9-chloro-2-(2-
furyl)[1,2,4]triazolo[1,5-c]quinazoline; MRS1220, 9-chloro-
2-(2-furanyl)-[1,2,4]triazolo[1,5-c]quinazoline; CHA, N6-
cyclohexyladenosine; DPCPX, 1,3-dipropyl-8-cytclo-
pentylxanthine; DMSO, dimethyl sulfoxide; THF, tetra-
hydrofuran; CHO cells, chinese Hamstery ovary cells;
EDTA, ethylenediaminotetraacetate; SCH58261, 5-
amino-2-(2-furyl)-7-(2-phenylethyl)pyrazolo[4,3-e][1,2,4]-
triazolo[1,5-c]pyrimidine; IB-MECA, 3-iodobenzyl-5′-(N-
ethylcarbamoyl)adenosine; NECA, 5′-(N-ethylcarbamoyl)-
adenosine; HEK cells, human embryonic kidney cells;
MRE3008-F20, 5-[[(4-methoxyphenyl)amino]carbonyl]-
amino-8-propyl-2-(2-furyl)pyrazolo[4,3-e]1,2,4-triazolo-
[1,5-c]pyrimidine; GTP, guanosine 5′-triphosphate; cAMP,
cyclic adenosine 5′-monophosphate; ATP, adenosine 5′-
triphosphate; TLC, thin-layer chromatography; HCl,
hydrochloric acid; mp, melting point; EtOAc, ethyl
acetate; HPLC, high performance liquid chromatogra-
phy; IR, infrared spectra; NMR, nuclear magnetic
resonance; CDCl3, deuterated chloroform; 3D-QSAR,
three-dimensional quantitative structure-activity re-
lationship; CoMFA, comparative molecular field analy-
sis; PLS, partial least squares; QSAR, quantitative
structure-activity relationship; r2bs, correlation coef-
ficient from bootstrap analysis; r2cv, correlation coef-
ficient from cross-validation equation; rms, root mean
square; GPCR, G protein-coupled receptor.
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Acknowledgment. The molecular modeling work
coordinated by S.M. has been carried out with financial
support of Associazione Italiana per la Ricerca sul
Cancro (AIRC), Milan, and the Italian Ministry for
University and Research (MIUR), Rome, Italy. S.M. is
strongly grateful to Christian Montopoli and Andrea
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to Chemical Computing Group for the scientific and
technical partnership.
Supporting Information Available: Tables listing actual
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