A Computer-Driven Scaffold-Hopping Approach Generating New PTP1B Inhibitors from the Pyrrolo[1,2-a]quinoxaline Core

Article abstract of DOI:10.1002/cmdc.202100338

Protein tyrosine phosphatase 1B (PTP1B) is a very promising target for the treatment of metabolic disorders such as type II diabetes mellitus. Although it was validated as a promising target for this disease more than 30 years ago, as yet there is no drug in advanced clinical trials, and its biochemical mechanism and functions are still being studied. In the present study, based on our experience generating PTP1B inhibitors, we have developed and implemented a scaffold-hopping approach to vary the pyrrole ring of the pyrrolo[1,2-a]quinoxaline core, supported by extensive computational techniques aimed to explain the molecular interaction with PTP1B. Using a combination of docking, molecular dynamics and end-point free-energy calculations, we have rationally designed a hypothesis for new PTP1B inhibitors, supporting their recognition mechanism at a molecular level. After the design phase, we were able to easily synthesize proposed candidates and their evaluation against PTP1B was found to be in good concordance with our predictions. Moreover, the best candidates exhibited glucose uptake increments in cellulo model, thus confirming their utility for PTP1B inhibition and validating this approach for inhibitors design and molecules thus obtained.

Full text of DOI:10.1002/cmdc.202100338

Accepted Article
Title: A computer-driven scaffold-hopping approach generating new
PTP1B inhibitors from the pyrrolo[1,2-a]quinoxaline core
Authors: Javier García-Marín, Mercedes Griera, Ramón Alajarín,
Manuel Rodríguez-Puyol, Diego Rodríguez-Puyol, and Juan
J. Vaquero
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content of this Accepted Article.
To be cited as: ChemMedChem 10.1002/cmdc.202100338
Link to VoR: https://doi.org/10.1002/cmdc.202100338
01/2020

10.1002/cmdc.202100338
ChemMedChem
FULL PAPER
A computer-driven scaffold-hopping approach generating new
PTP1B inhibitors from the pyrrolo[1,2-a]quinoxaline core
c, e
b, e
Javier García-Marín,a, b, f, g, * Mercedes Griera,
Ramón Alajarín, a, b, f, Manuel Rodríguez-Puyol,
Diego Rodríguez-Puyol, b, d Juan J. Vaquero a, b, f,
*
[a]
[b]
Dr. J. García-Marín, Dr. R. Alajarín, Prof. J. J. Vaquero
Departamento de Química Orgánica y Química Inorgánica
Universidad de Alcalá
28805 Alcalá de Henares (Spain)
E-mail: javier.garciamarin@uah.es, ramon.alajarin@uah.es, juanjose.vaquero@uah.es
Dr. J. García-Marín, Prof. M. Rodríguez-Puyol, Dr. R. Alajarín, Prof. J. J. Vaquero, Dr. D. Rodríguez-Puyol
Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS)
Ctra. Colmenar Viejo, km. 9100
28034 Madrid (Spain)
[c]
[d]
M. Griera, Graphenano Medical Care, S.L.
Dr. D. Rodríguez-Puyol
Fundación de Investigación Biomédica, Unidad de Nefrología del Hospital Príncipe de Asturias y Departamento de Medicina y Especialidades Médicas
Universidad de Alcalá, 28805 Alcalá de Henares (Spain)
E-mail: diego.rodriguez@uah.es
[e]
Prof. M. Rodríguez-Puyol, M. Griera
Departamento de Biología de Sistemas
Universidad de Alcalá
E-mail: manuel.rodriguez@uah.es
28805 Alcalá de Henares (Spain)
[f]
Dr. J. García-Marín, Dr. R. Alajarín, Prof. J. J. Vaquero
Instituto de Investigación Química Andrés Manuel del Río (IQAR),
Universidad de Alcalá, Alcalá de Henares (Spain)
Dr. J. García-Marín
[g]
Departamento de Química Biológica y Estructural
Centro de Investigaciones Biológicas Margarita Salas (CIB-CSIC)
Calle Ramiro de Maeztu, 9, 28040 Madrid (Spain)
proteins are linked to abnormalities such as cancer or
immunological disorders, which is why some of them are
considered very important therapeutic targets for drug
development [1]. As an example, a considerable number of
clinically approved inhibitory drugs, especially in oncology are
molecules target kinases [2]. However, despite their potential to
treat some diseases, protein phosphatases currently remain
“undruggable”, therefore research in the field of phosphatase
inhibition and mechanistic studies is of great interest for the
scientific community [3-5]. I this regard, a phosphatase described
by Tonks et al in 1988 has attracted the interest and attention of
the scientific community for decades, especially in the drug
discovery field [6-9].
Abstract: Protein tyrosine phosphatase 1B (PTP1B) is a very
promising target for the treatment of metabolic disorders such as
type II diabetes mellitus. Although it was validated as a promising
target for this disease more than 30 years ago, as yet there is no
drug in advanced clinical trials, and its biochemical mechanism
and functions are still being studied. In the present study, based
on our experience generating PTP1B inhibitors, we have
developed and implemented a scaffold-hopping approach to vary
the pyrrole ring of the pyrrolo[1,2-a]quinoxaline core, supported
by extensive computational techniques aimed to explain the
molecular interaction with PTP1B. Using a combination of docking,
molecular dynamics and end-point free-energy calculations, we
have rationally designed a hypothesis for new PTP1B inhibitors,
supporting their recognition mechanism at a molecular level. After
the design phase, we were able to easily synthesize proposed
candidates and their evaluation against PTP1B was found to be
in good concordance with our predictions. Moreover, the best
candidates exhibited glucose uptake increments in cellulo model,
thus confirming their utility for PTP1B inhibition and validating this
approach for inhibitors design and molecules thus obtained.
Protein tyrosine phosphatase 1B (PTP1B), an enzyme which
catalyzes dephosphorylation of phosphotyrosine (pTyr) residues
insulin receptor, and related substrates, via
a two-step
mechanism that is shared among protein phosphatases, is an
archetypical phosphatase [10]. PTP1B is a negative regulator of
insulin signal transduction and it regulates leptin signaling [11].
Additionally, this enzyme has been validated as a promising target
for the treatment of type 2 diabetes mellitus [12]. Furthermore,
PTP1B has been linked to other important diseases such as
breast cancer, metabolic syndrome, immunological alterations, or
hepatic disorders [13]. Indeed, this enzyme has been recently
related with neurological disorders like Alzheimer’s disease
[14,15]. A large number of PTP1B inhibitor-based anti-diabetes
molecules have been reported in the literature to date [16-18].
However, only non-competitive inhibitors have entered clinical
trials viz. trodusquemine (NCT00509132), Ertiprotabib or JTT-551
(Fig. 1) [19,20].
Introduction
Reversible protein phosphorylation is a key step in cellular and
biochemical homeostasis, controlling signaling propagation inside
the cell. All intracellular signaling cascades are tuned by a fine
balance in the degree of protein phosphorylation, which is carried
out by protein kinases. In this regard, protein phosphate groups
are removed by the action of protein phosphatases. As such,
alterations or aberrant changes in the activity of both types of
1
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10.1002/cmdc.202100338
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H
O
O
better properties by means of a scaffold-hopping strategy
involving replacing the pyrrole ring with different azoles. Azoles
with extra nitrogen atoms bearing an sp2 lone pair are especially
interesting given their ability, for instance, to form hydrogen bonds.
Furthermore, incorporation of relatively electronegative nitrogen
atoms in aromatic heterocycle may decrease its susceptibility to
oxidative metabolism [37]. Thus, compounds 2, 3 and 4, which
contain imidazole, 1,2,4-triazole and tetrazole rings, respectively
(Fig. 2), were considered as representative candidates for our
O
O
N
N
S
S
O
N
H
OH
S
Br
Br
N
HN
NH
O
N
S
N
O
S
H
O
I IC50 = 0.12 µM
II IC50 = 8 µM
O
CH3
starting hypothesis. To that end, we have designed
a
computational protocol that combines docking, MD and end-point
free-energy calculations to estimate the behavior at a molecular
level and generate possible PTP1B inhibitors.
S
N
O
CH3
N
O
N
N
1
JTT-551 IC50 = 8 µM
OH
N
S
IC50 = 1 µM
Fig. 1. Representative examples of PTP1B inhibitors and their IC50 values: pTyr
mimetic (top left), allosteric inhibitors at the α3/α6/α7 site (top right) and a non-
competitive inhibitor which entered Phase I clinical trials (bottom) [20-22].
N
N
N
N
N
N
CH3
CH3
CH3
N
N
N
In this context, the research on PTP1B inhibition is an active field
that aims to provide new insights into its function and therapeutic
approaches with a plethora of inhibitors reported [23-27].
Scaffold-hopping strategies, which aim to identify iso-functional
molecules with different main cores, form part of the current
medicinal chemistry toolbox. This term, which was first used by
Schneider in 1991 [28], has become a common medicinal
chemistry and chemical biology technique that is widely employed
in pharma and academia nowadays [29]. The objectives
underlying these approaches are quite diverse, depending on the
aims of the ongoing research and objectives. For example,
scaffold-hopping is applied to improve activity, pharmacokinetic
parameters or explore novel chemical and patentable space.
However, its application depends on the target under
investigation and the synthetic accessibility of the molecular
designs. Nevertheless, although human intuition influences the
scaffold-hopping process and the synthetic chemist takes part in
the final decision, scaffold-hopping has essentially always been
related to computational approaches like virtual screening,
pharmacophore generation and similarity analysis [30]. As such,
pharmacophores have been used to generate new PTP1B
inhibitors by means of scaffold-hopping [31,32], or even
experience-driven scaffold-hopping, to yield compounds with IC50
values in the low micromolar range [33]. In a work reported by
Saxena, authors identify through scaffold hopping approaches
interesting compounds from the point of view of their in vivo
activities [32]. Nonetheless, despite the success of these works,
in a great number of them, reported PTP1B inhibition activities in
medium ranges. Besides, only one work by Shinde et al performs
virtual screening in the allosteric site of the enzyme with moderate
results [34]. Another weakness of these approaches is that
molecular docking, and pharmacophores do not provide a
dynamic and so, a more realistic representation of the protein to
account for effects such as induced fit and molecular recognition.
In this regard, molecular dynamics (MD) simulations have
become widespread in the field of drug design, and thank to the
advances in GPU development and code improvements its
incorporation into drug design work-flows has become very
efficient, thus accelerating the drug-discovery process [35].
N
N
N
2
3
4
Fig. 2. Hypothesis for scaffold-hopping derivatization modification of 4-
methylpyrrolo[1,2-a]quinoxaline.
Results and Discussion
Computational design
Our scaffold-hopping approach was based on the replacement of
the pyrrole ring by azoles. Transformation of the pyrrole ring into
other azoles containing more nitrogen atoms leads to a significant
variation in the physicochemical properties of the resulting
azolo[1,2-a]quinoxaline scaffold. Thus, a decrease in cLogP
values is expected, as reflected in Table 1.
Table 1. Predicted chemoinformatic properties of compounds 1-4.
ESOL
Tanimoto
similarity
to 1
TPSA
A2
Lipinski
Compd.
cLogP
Solubility
violations
mg/mL[a]
1
2
3
4
2.79
2.19
1.58
0.98
17.30
30.19
43.08
55.97
0.036
0.103
0.24
0
0
0
0
1
0.60
0.54
0.46
0.84
[a] Predicted using SwissADME software (http://www.swissadme.ch/).
As a consequence, these proposed azoloquinoxalines would
present a higher polarity, which would, in turn, increase their
solubility in aqueous media given the increase in hydrogen
bonding. This change is accompanied by a marked increase in
TPSA (close to 60), while maintaining good values to promote cell
Previous studies by our group have allowed us to identify hit 1 as
a PTP1B inhibitor with good in vitro activity and putative binding
to the allosteric cavity of this protein (see supporting info F1) [36].
This site comprised a tunnel delimited by α-helixes 3, 6 and 7 in
the C-terminal region of the soluble PTP1B enzyme [21]. However, permeability. Additionally, all proposed designs fulfil the Lipinsky
1 presents a high cLogP and highly aromatic carbon atoms, thus
rules for oral absorption, thus making them interesting hit
limiting its solubility and promoting undesired aggregate formation. molecules with no functional groups and low molecular weights,
As such, we propose the design of new candidates with, a priori,
thus allowing further complex derivatizations to generate lead
2
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compounds. To assess the impact of the azole moiety on the
topology of the whole structure, a simple similarity analysis was
carried out based on Morgan fingerprints. Interestingly, the
similarity of the target compounds to 1 is dramatically decreased,
especially for 4. As shown in Table 1, the greater the number of
sp2 nitrogen atoms with a sp2 lone pair, the lower the Tanimoto
similarity index, thus a significant change in biological activity
might be expected comparing with hit 1. Even in the case of a
considerably lower similarity to the starting compound 1, the
substitution of an sp2 carbon by nitrogen atoms may act as a
strategy to block metabolically labile positions in the five-
membered ring, thus maintaining the desired activity. A similar
bioisosteric replacement, has proved to be more useful, even for
multiparameter optimization, especially in ADMET properties [38].
All in all, these data suggest that these new compounds present
better drug-like properties, especially as regards their increased
solubility without impairing permeability. The predicted
pharmacokinetic profile and drug-like properties for these hits
were also evaluated by means of in silico tools to support this
hypothesis (see supporting info). All the proposed structures
showed low molecular weight (<500) and suitable surface area
values (Table 1). There were not any PAINS alert for these
molecules and regarding drug-like properties, there were no
violation in terms of ‘Rule of Five’ by Lipinski and related. Finally,
the predicted gastrointestinal absorption was predicted to be high
(see supporting info S2-S5).
to establish a first approach, other computational techniques may
also provide valuable and extensive information.
Considering aforementioned data, which support the interest of
these candidates, we modelled the target azoles 2-4 as well as 1
on PTP1B by means of docking and conventional molecular
dynamics approaches to gain a deeper insight into the molecular-
recognition process at an atomic level.
Fig. 3. Docking poses obtained for compounds 1-4 in the homology model
generated for PTP1B. The hydrogen bonds found between the ligands and
Asn193 in PTP1B are depicted as dashed yellow lines.
In previous studies on the pyrrolo[1,2-a]quinoxaline system,
experimental and extensive computational modelling let us
propose that these molecules would bind to the allosteric cavity of
PTP1B [36]. In consequence, for the present work, we modelled
these compounds into the same pocket. The shape and aromatic
properties of these scaffolds fit quite well into the allosteric cavity
of PTP1B, and as such, they tend to establish the same
interactions as the benzbromarone core of PTP1B inhibitors
described by Wiesmann et al (see supporting info F1) [21].
Thus, molecular dynamics (MD) simulations allow the study of a
target protein over a pre-defined time. Consequently, MD can be
used as a refinement protocol for docking poses to study which
binding mode is more plausible and the likelihood that it is stable
in physiological media. Moreover, MD studies have been
extensively incorporated into drug-design workflows and free-
energy calculations for hit-to-lead optimizations [39,40].
Docking experiments revealed two different binding modes. As
illustrated for 1, the imidazoquinoxaline
2
and the
In this context, we decided to perform MD simulations to gain an
in-depth insight into the molecular-recognition phenomena
between our molecular designs and PTP1B in order to evaluate
potential effects on the target and to support our hypothesis.
triazoloquinoxaline 3 shared the same binding mode (Fig. 3). This
is stabilized by several π-π stacking interactions mediated by the
scaffold with Phe196 (α3 helix) and Phe280 (α6 helix). In addition,
a parallel-displaced interaction with Trp291 (α7 helix) could be
observed, as well as a CH-π interaction between the hydrogens
of the methyl group and the pyrrole ring of Trp291. Finally, as a
directional leading force, the nitrogen lone pair of the quinoxaline
moiety is hydrogen bonded to the Asn193 side chain (α3 helix). In
contrast, a different scenario was observed for the tetrazolo
derivative 4. In this case, π-π interactions are established with the
aromatic residues of the allosteric site, and a hydrogen bond is
formed with one of the nitrogen atoms of the tetrazole ring (Fig.
2). This different binding mode can be partially explained by a
better geometry of the interaction (2 Å long and a θ angle of 177°,
see supporting information). On the other hand, a second binding
mode, which orients the methyl group towards a small gap in a
similar fashion as the ethyl substituent in benzbromarone
derivatives (PDB: 1T48, 1T4J, 1T49), in order to gain van der
Waals interactions was observed for 4.
Since the crystal structure of PTP1B bound to an allosteric ligand
has not been completely solved, homology model techniques
were employed to generate a complete α7 helix PTP1B for our
purposes. This fact is in part due to the destabilizing effect of
ligands on the α7 helix that triggers and propagates the allosteric
signaling over the protein, which leads to a blocking of the WPD
loop in its open form.
Initially, in order to lay the groundwork for our subsequent
simulations, a control simulation of the PTP1B in its apo form
(without any ligand) was carried out starting from the open WPD
loop conformation to study the system behavior in solution.
Monitoring of the root-mean-square deviation (RMSD) values
allowed us to conclude that the protein readily reached an
equilibrium state after approximately 50 ns, with a mean value of
around 1.8
Å (Fig. 4). Furthermore, a root-mean-square
Overall, it seems that the proposed analogues are able to
maintain the same key binding patterns as cognate ligands
previously described in the literature.
fluctuation (RMSF) plot for Cα did not show significantly high
values, except for those residues located in the α7 helix, as
previously observed in the literature ([3,41]).
Although molecular docking may provide a useful description for
the interaction between a protein and a ligand at a molecular level
3
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corresponded mainly to loops, while the rest of the secondary
structural elements remained more rigid. As far as the WPD loop
is concerned, the RMSF values for the simulations were similar.
As a consequence, we concluded that our models are able to
capture a stabile form of the catalytic loop in its open inactive
conformation, as described previously [41,42].
A different picture was found when ligands 1-4 were studied in
detail. In general, the designed molecules remained inside the
allosteric cavity during the 100 ns, thus supporting the hypothesis
of the binding site, and all of them maintained the hydrogen bond
with Asn193 during most of the simulations. Our results show that
the proposed binding modes, which are stable over 100 ns of
conventional MD simulation, are dominated by van der Waals and
hydrophobic interactions. Despite this, small fluctuations, which
eventually led to shifts of the ligands in the pocket, as reflected in
the RMSD values, were detected (Fig. 4), but no unbinding event
was observed. The π-π interactions are also well maintained
during the simulations, especially for Phe192 and Phe280. Indeed,
this latter has been claimed to be a key anchoring residue for
PTP1B allosteric inhibitor binding and stabilization [21,41,43].
However, the interactions involving Trp291 (α7 helix) change
during the dynamics, mainly due to the high mobility of this part of
the protein. An unexpected finding emanating from the present
simulations was obtained in the case of 4. In this case, after just
4 ns from the beginning, this compound suffered a change in its
binding mode. This event led to a new reorientation of 4 in the
binding site to the same binding mode observed for ligands 1-3
(Fig 5A and 5B). Thus, the nitrogen of the quinoxaline core
establishes a hydrogen bond with the Asn193 side chain until the
end of the simulation. These findings support the hypothesis
about the binding mode of these compounds, which was
dilucidated by docking for ligands 1-3. Moreover, the Ala189 and
Ile281 side chains contribute to binding via van der Waals
interactions during the MD simulation.
Fig. 4. Cα backbone RMSD (top) and Cα RMSF (bottom) plots for the PTP1B
MD simulation at 100 ns.
After checking that our protocol worked with apo PTP1B, we
performed four more simulations for complexes PTP1B-1 to
PTP1B-4, starting from the molecular docking coordinates. These
simulations showed that PTP1B remained stable, with RMSD
plots similar to those for the apo form (see supporting information,
F6) that remained relatively unchanged along the trajectory. The
overall Cα RMSDs for the protein structures relative to the
respective starting coordinates during these simulations are 2.35,
2.7, 2.02 and 1.5 Å for complexes PTP1B-1 to PTP1B-4,
respectively. According to these values, a more mobile structure
arises upon complexation of PTP1B to ligands 1, 2 and 3
compared with 4, as deduced from the higher RMSD mean values.
These data suggest that complexation of PTP1B with 4 does not
produce an extensive structural rearrangement in the whole
protein. As a consequence, compound 4 might exert a lower
impact on allosteric mechanism propagation along the PTP1B
backbone and in the final inhibition compared with 1-3.
These simulations were useful for evaluating the potential of our
designs to remain bound to the PTP1B and to refine the poses
obtained during docking experiments. However, a detailed
analysis of the geometry of the allosteric tunnel may support the
allosteric mechanism of inhibition.
Similarly, the RMSFs also tended to be very similar to that for apo
the form, thus corroborating the stability of the system (see
supporting information, F7). The mobile parts of the enzyme
Fig. 5. Snapshot of ligand 4 taken from 2 ns (A) and 10 ns (B) of conventional MD simulations. RMSD heatmap plot of ligands 1-4 across 100 ns of simulation time.
4
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Fig. 6. A) PTP1B cartoon representation of PTP1B bound to ligand 3. B) Mean RMSD bar plot calculated for the α7 helix across the simulation. Results are the
mean ± SD. *** P ≤ 0.001, ns = not statistically significant. Statistical significance was carried out by performing t-test between Apo RMSD and each of the PTP1B-
ligand simulations.
The allosteric cavity is delimited by the three alpha helixes α3, α6
and α7 (Fig. 6A). The presence of a ligand leads to a partial
displacement and destabilization of the α7 helix in order to
accommodate the ligand. This fact has been extensively studied
previously using computational approaches and is supported by
the lack of fully solved PTP1B-inhibitor crystal structures. In fact,
α7 helix movement and destabilization has previously been
considered to be a marker for the allosteric signaling effect in
PTP1B [36,44,45]. As such, we measured the mean RMSD
values for the α7 helix to compare its stability among simulations
(Fig. 6B). Thus, while apo PTP1B presented a mean value of 4.29
Å, 1, 2, and 3 gave considerably higher RMSDs, as shown in Fig
6. However, this effect was not observed for 4 (mean RMSD =
4.28 Å) in our simulation. Although the analysis of these findings
Finally, we also calculated the binding free energy of our
candidates to PTP1B to assess their potential as a tight, medium
or weak binder. To this end, we selected the ultra-fast method
MM-ISMSA, which has been developed to estimate the free
binding energy between protein-protein or protein-ligand partners
in a similar fashion as other, more computationally demanding
methods such as MMGSA and MMPBSA or the perturbation and
thermodynamics integration procedures. The predicted binding
energies for all complexes are dominated by van der Waals and
hydrophobic interactions, as depicted in Table 2. This is in good
agreement with previous studies that reported estimated values
for the binding free energy between allosteric ligands and PTP1B
[43]. Remarkably, the values obtained for all four complexes are
quite similar. This fact highlights the potential of our designs 2-4
should not be considered statistically significant, during simulation, to bind PTP1B with good affinity, thus suggesting inhibitory
ligand 4 exhibited the highest fluctuation inside the cavity (Fig. 5),
therefore its weaker binding might exert a lower destabilizing
effect on the PTP1B α7 helix.
activity. According to this, all ligands should present similar
affinities to 1, except imidazoquinoxaline 2, which should exert a
better value.
In summary, all the MD results also suggest a good scenario for
the candidates and their putative binding to PTP1B.
Table 2. Per-term MM-ISMSA energy decomposition calculated for ligands 1-4 over the last 50 ns of MD simulation (kcal/mol).
Compd.
desolvation
PTP1B
desolvation
Compd.
Total energy
Van der Waals
Coulombic
Apolar
1
2
3
4
-30.69 ± 2.34
-32.73 ± 3.35
-30.70 ± 2.81
-30.69 ± 3.27
-29.42 ± 0.51
-31.72 ± 0.62
-29.29 ± 0.48
-30.92 ± 0.66
-2.00 ± 0.28
-1.51 ± 0.22
-1.37 ± 0.24
-0.77 ± 0.07
1.83 ± 0.12
1.71 ± 0.13
2.21 ± 0.21
1.42 ± 0.17
1.05 ± 0.33
0.95 ± 0.7
-2.14 ± 0.073
-2.17 ± 0.09
-2.10 ± 0.11
-2.20 ± 0.084
-0.13 ± 0.58
1.78 ± 0.78
5
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Inspection of the per-residue energy decompositions highlighted
the importance of the ligand environment for binding (Fig. 7). Thus,
residue Asn193 makes a marked contribution to the binding free
energy in all complexes, as expected for a hydrogen-bond
interaction, followed by aromatic residues such as Phe196,
Trp291 and hydrophobic residues Leu192 and Ala189.
Interestingly, this method was able to highlight the importance of
the Phe280 residue, which has also been described previously,
thereby supporting and validating these simulations [41,43].
proposed candidates 2-4 by setting up a multistep synthetic
procedure based on previously described protocols.
The synthesis of 4–methylimidazo[1,2–a]quinoxaline (2) was
carried out by nucleophilic substitution of 2–nitrofluorobenzene
with 2–acetylimidazole in basic media to give 5, and following
reduction of the nitro group by iron and in situ cyclisation,
obtaining the final product with good yield (Scheme 1a).
To prepare 3 and 4, we adapted protocols previously described in
the literature, using commercially available 2-chloro-3-
methylquinoxaline as the starting material for triazole ring
construction and cyclisation [46,47], thus 6 was first obtained by
treatment with hydrazine and subsequent cyclisation in the
presence of trimethyl orthoformate at 130 °C via the iminium
cation (Scheme 1b). Further experiments showed that hydrazine
intermediate
6 need not be isolated, thus avoiding one
chromatography step and obtaining the desired final product in
reasonable yield.
For the synthesis of tetrazole 4, we explored a different synthetic
pathway. In this case, we prepared 2-chloroquinoxaline 8 by
condensation of commercially available o-phenylendiamine with
pyruvic aldehyde at room temperature. After treatment of 7 with
phosphorous oxychloride,
intermediate was subsequently
8
was easily obtained. This
converted into
Fig. 7. Calculated energy contributions of individual complexes residues to the
overall binding free energy.
tetrazoloquinoxaline 9 by treatment with NaN3 in DMF. The
product thus obtained was then methylated with methyllithium at
low temperature to afford 4-methyl-4,5-dihydrotetrazolo[1,5-
a]quinoxaline (10). Finally, 4 was easily obtained in excellent yield
by oxidation of 10 with activated MnO2 (Scheme 1c).
Chemistry
Based on the aforementioned computational workflow and its
conclusions, we established that application of the scaffold
hopping strategy to the pyrrole ring may provide interesting
candidates for PTP1B inhibition. As such, we prepared the three
N
H3C
F
a)
H
N
N
N
K2CO3 , 18-
Crown-6
N
O
NO2
Fe
O
NO2
DMSO
100 ºC
AcOH
reflux
N
CH3
N
CH3
5
2
(71%)
(60%)
N
N
b)
H
N
N
Cl
N
N
N
N
N
NH2NH2
CH(OEt)3
NH2
130 ºC
EtOH
50 ºC
CH3
CH3
CH3
3
(54%)
6 (99%)
c)
NH2
NH2
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
NaN3
CH3Li
MnO2
O
CH2Cl2
reflux
Cl
EtOH
rt
N
H
O
POCl3
reflux
DMF
120 °C
THF
-78 °C
N
CH3
N
H
CH3
N
O
HO
7
8
9
10
4
(90%)
(97%)
(66%)
(78%)
(89%)
Scheme 1. A) . Synthesis of 4–Methylimidazo[1,2–a]quinoxaline. B) Synthesis of 4-methyl-[1,2,4]triazolo[4,3-a]quinoxaline. C) Synthetic route to generate
tetrazolo[1,5–a]quinoxaline derivatives.
6
This article is protected by copyright. All rights reserved.

10.1002/cmdc.202100338
ChemMedChem
FULL PAPER
the closest homologue to PTP1B with a 72% of shared sequence
identity [48]. Inhibition of this enzyme should be take into account
as a check point during PTP1B development, as it is responsible
of very dangerous effects observed in murine models such as
blood abnormalities, inflammation and subsequent death [49].
Biological evaluation
Once we prepared the desired compounds, we assessed their
PTP1B inhibitory effects in vitro using the commercially available
soluble 322 amino acids enzyme. Since our synthetic approach
led to the isolation of two extra azolo derivatives (9 and 10), we
included them in these experiments (Table 3). Compound 1 had
already been evaluated against PTP1B with an IC50 of 1.00 μM
[36]. The remaining compounds showed a good inhibitory activity
within a relatively narrow low- and sub-micromolar IC50 range. Of
all the compounds proposed, 2 showed the highest potency (pIC50
= 6.33), in all the series (minimum pIC50 of 5.66 for compound 10).
This is in good agreement with the free energy predicted using
the MM-ISMSA method, which indicated that this compound
stands out from the others in terms of total binding free energy
(Table 2). In addition, 3 also showed a marked ability to inhibit the
enzyme. In contrast, the worst inhibitory effect was obtained for
tetrazolo derivative 4 (IC50 = 1.48 μM). However, these findings
are also valuable from the point of view of our computational
model, which predicted a worse behavior during MD experiments.
It should be noted that compound 9 showed a very good IC50,
whereas the dihydro derivative of 4 (compound 10) showed the
worst value for all the compounds synthesized herein. As a
consequence, compound 10 is the least interesting from the point
of view of optimization and hit-to-lead because of its low potency
(pIC50 = 5.66).
In our in vitro experiments, all molecules inhibited this enzyme, as
shown in Table 3. However, for compounds 2, 3 and 9, higher
inhibition for PTP1B rather than TCPTP was observed at the
same concentration (SI > 1). Only 2 displayed approximately two
times selectivity for PTP1B over TCPTP, whilst 4 and 10 turned
out to be non-selective (SI ≤ 1). This behavior is, in part, expected
since these derivatives lack of functional groups and present a
relatively simple structure, similar to hit 1 which was non-selective
(SI = 0.94). Given these results, future optimization of these hits
should also consider addressing the selectivity issue over TCPTP
to avoid undesired side effects in this related off-target.
Finally, to provide an added value to our breakthroughs we
decided to explore the phenotypic efficacy of some relevant
compounds in ex vivo assays. Although IC50 is a good marker for
evaluating the potency of compounds against an enzymatic target,
cellular assays can be used to establish the utility and efficacy as
regards the mechanism of action and desired effects. With this in
mind, we investigated whether our compounds are able to modify
glucose uptake in cellular models. Our most promising candidates
in terms of pIC50 (derivatives 2 and 3) were selected for this more
sophisticated experiment.
We also carried out an initial selectivity evaluation of these
compounds against T cell protein-tyrosine phosphatase (TCPTP),
Table 3. In vitro data obtained for compounds 1-4, 9 and 10.
% Inh PTP1B
(1 µM) [b]
% Inh TCPTP
(1 µM)[b]
Compd.
Structure
IC50 ± SD (µM)
pIC50
SI [c]
0.94
1
1[a]
6
51
87
70
54
44
55
2
3
0.46 ± 0.04
0.79 ± 0.01
6.33
6.1
1.97
1.27
4
9
1.48 ± 0.07
0.62 ± 0.2
2.17 ± 0.08
5.82
6.2
46
80
37
50
68
35
0.92
1.17
1
10
5.66
[a] From reference 34. [b] Percentage of enzyme inhibition at 1 μM. [c] SI = selectivity index, is defined here as percentage inhibition ratio
PTP1B/TCPTP at 1 μM.
7
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10.1002/cmdc.202100338
ChemMedChem
FULL PAPER
applied to
a
scaffold-hopping strategy to obtain good
concordance with in vitro results. Furthermore, the cheap
computational requirements of this algorithm to calculate binding
free energy, it become in a very attractive tool for drug discovery
purposes. Moreover compounds 2 and 3 are very interesting for
hit optimization because they are selective for PTP1B rather than
TCPTP. Finally, these two derivatives have been shown to
increase glucose uptake in phenotypic models, thus validating
this approach and, confirming the relevance of these fragments
for further optimization and development. As such, scaffold
hopping strategies aimed to exchange the pyrrole ring in the
nucleus of pyrrolo[1,2-a]quinoxaline core by the studied azoles
may be of interest to obtain novel chemotypes with similar
activities and different physicochemical properties. These results
also bring an opportunity to select the most suitable scaffold,
according to the synthetic accessibility purposes, while preserving
its inhibitory properties towards PTP1B.
Fig. 8. Effect of inhibitors 2 and 3 on glucose uptake in C2C12 –based myotubes.
Cells were incubated with vehicle (CT), insulin (INS, 10 nM, 30 min) compounds
2 or 3 (2 μM, 90 min), and the fluorescent oxyglucose analog 2-NBDG (0.1 mM)
was added for an additional 30 min period. Changes in intracellular fluorescence
reflect glucose uptake, and they were referred to glucose uptake by their
respective controls (CT). Date are the mean ± S.E.M of 5 independent
experiments. *p˂0.05 vs CT. **p<0.05 vs CT and INS.
Experimental Section
Computational methods
Ligand preparation and analysis. All ligands were generated
using the corresponding smiles codes generated with
MarvinSketch 21.3, ChemAxon (https://www.chemaxon.com).
Thereafter, RDKit, was used to add hydrogens and generate
minimized 3D coordinates for all compounds using our in-house
scripts. For similarity analysis with RDKit (http://www.rdkit.org),
Morgan fingerprints of radius 2 and 1240 bytes (MFP2) were
selected, then the Tanimoto similarity was calculated. Statistical
analysis was carried out using the Python SciPy library [50].
ADME and physicochemical properties were calculated using
web server SWISS-ADME (http://www.swissadme.ch/).
The insulin mimetic activity was evaluated by using insulin as
positive control. This latter was included in the assays to compare
to basal conditions the ability of cells to increase glucose uptake.
This experiment showed that both compounds induced a slight
but statistically significantly increased glucose uptake by cultured
myotubes that are cells particularly sensible to insulin actions on
glucose metabolism (Figure 8). Interestingly, the effects on
glucose uptake from both compounds did not reflect their ability
to inhibit PTP1B activity. Whilst compound 2, with the best pIC50,
only increased glucose by 15 % with respect to control cells,
compound 3 exhibited about a 30% of increment. Given these
data, both compounds, may be of therapeutical interest for further
development, based in its phenotypic effects which confirm they
ability to produce an ex vivo response aimed to decrease glucose
content outside the cell.
Ligand docking. Docking was performed using the GOLD engine
program as implemented in Hermes. For docking purposes, a
homology model of PTP1B with a whole α7 helix in the allosteric
site was generated, as described previously [36,41]. Briefly, a
homology model was constructed with the sequence of whole
PTP1B (UniProt ID: P18031) using as template PDB: 1T48 in
SWISS-MODEL
(https://swissmodel.expasy.org/),
then
Conclusion
protonation states were investigated with H++ webserver
(http://biophysics.cs.vt.edu/hppdetails.php). The binding site was
defined as being 6 Å away from the coordinates of the ligand BB3
(PDB:1T48). The genetic algorithm search option was set to slow
(more accurate) and early termination was allowed if the number
of GA runs in the top 5 solutions were within 1 Å. The remaining
parameters were set as default.
PTP1B is considered to be a promising target for the treatment of
type
2 diabetes mellitus, metabolic syndrome and other
conditions. Studies carried out into this target and its biochemical
roles are still of interest for the scientific community, as is the
synthesis of new chemical probes and drugs for its inhibition and
subsequent study. Despite not being particularly novel
approaches, scaffold-hopping strategies are of particular interest
for this purpose due to their ability to provide new chemotypes
with tailored physicochemical properties for different objectives.
In this work, we have designed a computational workflow that
includes a simple chemoinformatic analysis of the pyrrolo[1,2-
a]quinoxaline scaffold and further validation by means of docking
and MD approaches. Molecular docking suggested a similar
pattern of molecular recognition compared to previously
described and characterized cognate inhibitors. Additionally, MD
simulation allowed us to study the molecular determinants of the
interactions and predict the suitability of our designs. We have
also used the MM-ISMSA algorithm to predict binding free energy,
obtaining similar results to others described previously and
documented in the literature, thereby validating its utility for the
study of PTP1B. This whole implementation has allowed us to find
new derivatives bearing imidazole, 1,2-4-triazole and tetrazole
rings fused to the side (a) in the quinoxaline core, which maintain
and even improve its PTP1B inhibitory activity and are in very
good agreement with our simulations. Additionally, to the best of
our knowledge, this is the first time that MM-ISMSA has been
Molecular dynamics. Protein topology was described using
Amber ff14SB [51], while the GAFF forcefield was chosen for
ligands [52]. To parameterize small molecules, an AM1-BCC
model of RESP charges [53] was generated using sqm in
antechamber [54]. The, tleap module implemented in
Ambertools16 [55], was used to solvate the systems with a TIP3P
cubic water box extending 10 Å away from the solute. After this,
five sodium ions were added to the system in order to achieve a
neutral charge. The topology and coordinates files were
submitted to
a multi-step minimization, thermalization and
equilibration using the Sander engine, following previously
described protocols [41]. All-atom classical molecular dynamics
simulation were then carried out with the OpenMM software [56].
All simulations used a Langevin integrator with a temperature of
310 K and a friction coefficient of 1 ps-1. Long-range electrostatic
interactions were treated with the particle mesh Ewald method,
with constraints for all bonds involving hydrogen. Production
dynamics was carried out in the NPT ensemble using a
Montecarlo Barostat (1 atm) and a 2-fs time step. The OpenCl
platform in single precision mode was selected as engine for MD.
8
This article is protected by copyright. All rights reserved.

10.1002/cmdc.202100338
ChemMedChem
FULL PAPER
Simulations were performed on a Windows Workstation with a
Nvidia® Gigabyte GeForce RTX 2060 GPU, yielding a max
performance of 122 ns/day.
H4), 7.38 (dd, J = 8.0, 1.6 Hz, 1H, Ar-H3), 7.35 (s, J = 1.2 Hz, 1H,
HetAr-H5), 7.15 (d, J = 1.1 Hz, 1H, HetAr-H5), 2.63 (s, 3H, CH3);
13C-NMR (125 MHz, CDCl3): δ 204.17 (CO), 149.54 (Ar-C2),
138.30 (Ar-C2), 134.44 (ArC), 133.02 (ArC), 133.00 (ArC), 130.89
(Ar-C1), 130.47 (ArC), 129.55 (Ar-C1’), 126.49 (C-Ar5’’), 126.04
(Ar-C4’’), 27.31 (CH3); HRMS (ESI-TOF) m/z calculated for
C11H10N3O3 [M+H]+: 232.0717. Found [M+H]+: 232.0718.
Binding energy calculations were performed using the ultrafast
software MM-ISMSA compiled for Windows 64-bit systems [57].
To this end, 500 snapshots were taken from the last 50 ns of MD
trajectories for each system, corresponding to equilibrated
structures. This software allows the solvent-corrected binding
energies to be estimated for the same sets of coordinates, as well
as their per-residue free energy decompositions into van der
Waals, coulombic, apolar, and desolvation terms.
4-Methylimidazo[1,2-a]quinoxaline (2). Fe powder (52 mg, 0.92
mmol, 4 equiv) was added to a solution of 5 (55 mg, 0.23 mmol,
1 equiv) in AcOH (3 mL). The system was then purged with argon
and the reaction mixture refluxed for 3 h until end of the reaction
(TLC monitoring). The reaction mixture was subsequently cooled
to room temperature and the solution neutralized with satd.
NaHCO3 (5 mL). The aqueous phase was extracted with CH2Cl2
(3 x 10 mL) and the organic extracts were pooled and dried
(MgSO4). The desiccant was filtered off and the solvent was
removed under reduced pressure to give a residue that was
chromatographed on silica gel (CH2Cl2/methanol 9.5:0.5) as
eluent to afford 2 as a cream colored solid. Yield: 30 mg, 71%;
M.P.: 81-83 °C; 1H-NMR (500 MHz, CDCl3): δ 8.09 (d, J = 1.1 Hz,
1H, H1), 8.03 (td, J = 5.4, 1.3 Hz, 1H, H2), 7.85 (dd, J = 7.7, 1.8
Hz, 1H, H6), 7.76 (d, J = 1.1 Hz, 1H, H9), 7.64 – 7.53 (m, 2H, H7
and H8), 2.98 (s, 3H, CH3); 13C-NMR (125 MHz, CDCl3): δ 146.37
(C4), 139.4 (C3a), 135.7 (C5a), 129.61 (C6), 128.63 (C8), 127.03
(C9a), 126.81 (C7), 114.69 (C9), 112.73 (C1), 29.74 (CH3).
HRMS (ESI-TOF) m/z calculated for C11H10N3 [M+H]+: 184.0869.
Found [M+H]+: 184.0867.
MD analysis was performed using MDtraj [58], MDAnalysis [59]
and Pandas python libraries [60]. Protein Cα atoms were aligned
to the starting conformation of the simulation to calculate RMSD
and RMSF values. Graphics were generated with Matplotlib [61]
and Seaborn [62]. Simulation and image rendering were carried
out with VMD [63], Chimera X [64] and Pymol (The PyMOL
Molecular Graphics System, Version 2.1 Schrödinger, LLC.).
Chemistry
All reagents were acquired from the following commercial sources
and used without further purifications: Merck, ACROS,
Novabiochem and Fluorochem. Solvents were purchased from
Scharlab and EtOAc, Hexane and CH2Cl2 were distilled prior to
use. Dry solvents were obtained using an MBRAUN MB-SPS-800
device. For those reactions which were performed under inert
atmosphere, argon or nitrogen were used with oven-dried
glassware, magnetic stirring and dry solvents.
4-Methyl-[1,2,4]triazolo[4,3-a]quinoxaline (3). Compound 6 (110
mg, 0.559 mmol) was dissolved in triethyl orthoformate (4 mL) and
the reaction mixture stirred at 130 oC overnight before being
cooled to room temperature. The reaction mixture was
concentrated under reduced pressure and the residue thus
obtained was purified by column chromatography on silica gel
(CH2Cl2/MeOH, 9:1) to give 3 as an orange solid. Yield: 55 mg,
54%; M.P.: 129-131 °C; 1H-NMR (500 MHz, CDCl3): δ 9.28 (s, 1H,
H1), 8.09 (dd, J = 7.1, 2.4 Hz, 1H, Ar-H6), 7.97 – 7.85 (dd, J = 7.2,
2.2 Hz, 1H, H9), 7.75 – 7.60 (m, 2H, H7 and H8), 3.06 (s, 3H,
CH3); 13C-NMR (125 MHz, CDCl3): δ 148.31 (C4), 145.86 (C3a),
139.26 (C1), 131.58 (C5a), 130.32 (C7), 130.25 (C8), 129.17 (C6),
128.17 (C9a), 115.29 (C9), 21.42 (CH3). Spectroscopic data and
melting point agree with those reported in the literature [46].
Reactions were followed by thin layer chromatography (TLC) on
Merck Kieselgel 60 F254 0.25 mm precoated aluminum plates.
TLC plates were visualized using UV light (λ = 254 nm or 365 nm)
and/or staining with Ninhydrin (1 M, EtOH), 1% aq. KMnO4 or
phosphomolybdic acid (0.05 M, EtOH). Purification was carried
out by normal-phase silica gel flash chromatography, using gel
grade 60 (70-230 mesh, Merck). High-resolution analyses
(HRMS) were performed on an Agilent 6210 time of flight LC/MS
using electrospray (ESI) as ion source and a mobile phase of
ACN/H2O 75:25 with 0.1% TFA as additive. The HPLC column
(50 mm ×4.6 mm) contained a C18 stationary phase with a
particle size of 3.5 μm. Compounds were >95% pure High-
resolution mass spectra were recorded on an Agilent 6210 LC/MS
TOF mass spectrometer. Data are expressed as mass units (z/e).
1H and 13C NMR spectra were recorded on a either a Varian
Mercury VX-300, Varian Unity 300 or Varian Unity 500 MHz
spectrometer at room spectrometer in the deuterated solvent
stated. Chemical shifts (δ) are quoted in parts per million (ppm)
and using the residual non-deuterated solvent signal as an
internal reference. Multiplicities are denoted as singlet (s), doublet
(d), triplet (t), quartet (q) and multiplets as (m). Coupling constants
(J) are given in Hertz (Hz).
4-Methyltetrazolo[1,5-a]quinoxaline (4). Activated MnO2 (116 mg,
1.535 mmol) was added to a solution of 10 (50 mg, 0.267 mmol)
in CH2Cl2 (11 mL/mmol) and the suspension stirred for 2.5 h. After
this time, the reaction mixture was filtered through a pad of
Celite® and the solvent eliminated under reduced pressure to
afford 4 as an amorphous yellowish solid. Yield: 44 mg, 90%;
M.P.: 146-148 °C; 1H-NMR (500 MHz, CDCl3): δ 8.55 (dd, J = 6.3,
3.2 Hz, 1H, H6), 8.18 (dd, J = 6.1, 3.3 Hz, 1H, H9), 7.92 – 7.68
(m, 2H, H7 and H8), 3.12 (s, 3H, CH3); 13C-NMR (125 MHz,
CDCl3): δ 151.27 (C4), 145.87(C3a), 136.37 (C5a), 132.25 (C6),
130.52 (C9a), 130.00 (C8), 129.88 (C7), 116.48 (C9), 22.26 (CH3).
Spectroscopic data and melting point agree with those reported
in the literature [46].
2-Acetyl-1H-1-(2-nitrophenyl)imidazole
(5).
2-Acetyl-1H-
imidazole (100 mg, 0.9 mmol, 1 equiv), anhydrous K2CO3 (139
mg, 0.99 mmol, 1.1 equiv), and 18-crown-6 (523 mg, 1.98 mmol,
2.2 equiv) were added to an oven-dried Schlenk flask provided
with a stir bar. The air was then evacuated under vacuum and the
Schlenk flask purged with argon. Anhydrous DMSO (5 mL) was
added, followed by 1-fluoro-2-nitrobenzene (139 mg, 0.99 mmol,
1 equiv). The resulting mixture was heated to 100 oC and stirred
for 3 h. The reaction mixture was then cooled to room temperature,
diluted with H2O (27 mL) and extracted with CH2Cl2 (3 x 10 mL).
The organic layer was dried over anhydrous Na2SO4, the solvent
was removed under vacuum, and the product was purified by
flash column chromatography on silica gel (CH2Cl2/acetone 9:1)
to give 5 as a yellowish solid. Yield: 126 mg, 0.54 mmol, 60%; 1H-
NMR (500 MHz, CDCl3): δ 8.19 (dd, J = 8.0, 1.7 Hz, 1H, Ar-H6),
7.73 (td, J = 7.6, 1.7 Hz, 1H, Ar-5), 7.65 (td, J = 7.6 Hz, 1H, Ar-
Tetrazolo[1,5-a]quinoxaline (9). Sodium azide (2 equiv) was
added to a suspension of 8 (300 mg, 1.62 mmol) in DMF (1.85
ml/mmol). The flask was then purged with argon and heated to
120 °C for 24 hours. After cooling to room temperature, the
mixture was poured into an ice/water (61 mL/mmol) bath and the
aqueous layer extracted with EtOAc (3 x 10 ml) and washed with
water (3 x 10 mL), followed by brine (10 mL). The organic layer
was dried over anhydrous Na2SO4, and the solvent was
evaporated under reduced pressure. The residue was purified by
flash chromatography over silica gel (EtOAc/hexane, 1:1) to
afford 9 as an orange solid. Yield: 50 mg, 78%; M.P.: 126-128 °C;
1H-NMR (300 MHz, CDCl3): δ 9.58 (s, 1H, H4), 8.67 (d, J = 7.8
Hz, 1H, Ar-H6), 8.34 (d, J = 7.9 Hz, 1H, H9), 8.01 – 7.78 (m, 2H,
9
This article is protected by copyright. All rights reserved.

10.1002/cmdc.202100338
ChemMedChem
FULL PAPER
H7 and H8). Spectroscopic data and melting point agree with
those reported in the literature [47].
Cell culture and differentiation induction
Mouse skeletal muscle cell lines, C2C12 myoblasts (from ATCCH
CRL-1772TM) were cultivated un Dulbecco´s modified Eagles
medium supplemented with 10% heat-inactivated fetal bovine
serum (FBS), 100 U/ml penicillin, 100 U/ml streptomycin at 37°C
in humidified air containing 5% CO2. Differentiation was induced
by switching the growth medium to DMEM supplemented with 2%
horse serum (HS; differentiation medium). The differentiation
medium was changed every 48h [67].
4-Methyl-4,5-dihydrotetrazolo[1,5-a]quinoxaline
(10).
Methyllithium (1.6 M in hexane, 9.6 mg, 0.438 mmol) was added
to a solution of 9 (50 mg, 0.292 mmol, 1 equiv) in anhydrous THF
(4.5 mL/mmol) at -78 °C under argon. After 30 min, the reaction
was quenched with satd. NH4Cl (34 mL/mmol). The aqueous layer
was then extracted with ethyl acetate (3 x 7 mL) and washed with
water (3 x 10 mL), followed by brine (2 x 10 mL). The organic layer
was dried over Na2SO4, and evaporated to give 10 as an orange
solid. Yield: 54 mg, 94%; M.P.: 119-121 °C; 1H-NMR (500 MHz,
CDCl3): δ 7.93 (dd, J = 8.0, 1.5 Hz, 1H, H9), 7.25 (td, J = 7.8, 1.4
Hz, 1H, H7), 6.93 (td, J = 7.9, 1.2 Hz, 1H, H8), 6.83 (d, J = 8.0 Hz,
1H, H6), 5.18 (qd, J = 6.5, 3.0 Hz, 1H, CH), 4.23 (s, 1H, NH), 1.75
(dd, J = 6.5, 3.0 Hz, 3H, CH3); 13C-NMR (125 MHz, CDCl3): δ
150.50 (C3a), 135.20 (C9a), 129.96 (C8), 120.23 (5a), 120.19
(C7), 119.70 (C8), 117.18 (C9), 115.28 (C6), 46.50 (CH), 20.63
(CH3). Spectroscopic data and melting point agree with those
reported in the literature [47].
Glucose uptake
Glucose uptake was performed as described previously [36].
Briefly, C2C12 cells cultured in DMEM were treated with
compounds 2 and 3 (2 μM, 90 min) or insulin (10 nM, 30 min)
before adding 0.1 mM of the fluorescent D-glucose analog 2-[N(7
nitrobenz-2-oxa-1,3-diazol-4)amino]-2-deoxy-glucose (2-NBDG,
Sigma-Aldrich). After 30 min incubation, free 2-NBDG was
washed out 3 times with cold PBS. Rates of glucose uptake were
determined as the intracellular fluorescence (VICTORX4,
2-Hydrazino-3-methylquinoxaline
(6).
2-Chloro-4-methyl
PerkinElmer),
and
calculated
after
substraction
of
quinoxaline (170 mg, 0.957 mmol) and hydrazine monohydrate
(238 mg, 4.75 mmol) were dissolved in EtOH (5.2 mL). The
reaction mixture was stirred at 50 °C until the starting material
could not be detected by TLC (6 h). The solvent was then
eliminated under reduced pressure and the residue thus obtained
was purified by silica gel column chromatography on silica gel
(CH2Cl2/CH3OH, 9:1) to give 6 as a red solid. Yield: 164 mg, 99%;
1H-NMR (300 MHz, CDCl3): δ 7.86 (d, J = 8.1 Hz, 1H, H5), 7.75
(d, J = 8.1 Hz, 1H, H8), 7.57 (td, J = 8.1, 1.4 Hz, 1H, H7), 7.43 (td,
J = 7.6, 0.8 Hz, 1H, H6), 6.97 (s, 2H, NH2), 6.14 (s, 1H, NH), 2.55
(s, 3H, CH3). Spectroscopic data agree with those reported in the
literature [47].
autofluorescence from negative control without 2-NBDG. Cells
were then lysed, the protein content was determined in each
experiment with a BCA protein assay kit, and fluorescence values
corrected for protein content.
Acknowledgements
We are grateful for funding from the Spanish Ministerio de
Economía
y Competitividad (CTQ2017-85263-R MINECO/
FEDER UE to J.J.V.); Instituto de Salud Carlos III and FEDER
funds (RD16/0009/0015, RD16/0009/18, PI17/01513 and
PI17/00625 to J.J.V., D.R.-P. and M.R.-P.). J. G-M was the
recipient of an FPU fellowship (FPU16/01647) Spanish Ministerio
de Educación y Cultura. We would like to thank anonymous
reviewers for their kind and valuable comments during the peer
review process.
1H-Quinoxalin-2-one (7). A solution of o-phenylenediamine (2.75
g 25 mmol, 1 equiv) and glyoxylic acid (2.2 g, 25 mmol, 1 equiv,
50% wt in water) was refluxed for 2 h. The resulting precipitate
was filtered and washed with cold methanol and dried in vacuum
1
to give 7 as a white solid. Yield: 5 g, 97%; H-NMR (300 MHz,
CDCl3): δ 11.79 (s, 1H, -NH), 8.41 (s, 1H, H3), 7.79 (dd, J = 8.1,
1.3 Hz, 1H, H5), 7.51 (td, 1H, H7), 7.42 – 7.25 (m, 2H, H6 and
H8), 2.53 (s, 3H, CH3). Spectroscopic data agree with those
reported in the literature [65].
Keywords: PTP1B, phosphatase, scaffold hopping, molecular
modelling, molecular dynamics, MM-ISMSA, pyrrolo[1,2-
a]quinoxaline, glucose uptake.
2-Chloroquinoxaline (8). A suspension of 7 (1g, 6.84 mmol) in
POCl3 (1.17 ml/mmol) was refluxed at 120 °C for 5 h. The resulting
mixture was then cooled to room temperature and poured into a
DMF-ice bath. The solid was filtered off, washed with DMF and
recrystallized from DMF to yield 8 as a colorless crystalline solid.
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Yield; 750 mg, 66%; H-NMR (300 MHz, CDCl3): δ 8.75 (s, 1H,
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Enzyme inhibition
For IC50 and inhibition percentage determination, previously
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Recombinant 322 amino acids PTP1B was purchased from Enzo
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