On the: In silico and in vitro anticancer activity of sulfonamide chalcones: Potential JNKK3 inhibitors

Article abstract of DOI:10.1039/c9nj05612b

Science is constantly looking for new strategies to combat tumor progression and improve patient care due to increasing cancer incidence and high mortality. Although many chalcone analogues have been synthesized and studied because of their activity against tumor cell growth, the use of hybrid compounds containing both sulfonamides and chalcone moieties for this purpose is still scarce. Hereby, this work proposes a series of sulfonamide chalcones presenting biological potential against this disease. After being experimentally tested, these compounds showed cytotoxicity against tumor cell lines SF-295 and PC-3, which motivated us to investigate the possible structural bases for this action. Topological analyses were carried out through Hirshfeld analysis to assign intermolecular interaction sites important for protein-ligand analysis. To identify potential targets, the synthesized compounds were submitted to a structure-based pharmacophoric screening, which suggest strong potential activity as mitogen-Activated protein kinase 10 (JKN3) inhibitors. Considering these results, these compounds were docked within the JKN3 active site. Our hypothesis that these compounds achieve their biological potential by inhibiting the JKN3 protein is reinforced when their energies of ligand-protein interaction were compared to co-crystallized ligands: They showed similar or even lower binding energies. Finally, the energy of the different conformations (solid phase, aqueous phase and within the protein active site) of these sulfonamide chalcones was investigated using theoretical calculations. Our findings enable further studies on more sulfonamide chalcone analogues toward the development of new anticancer drugs.

Full text of DOI:10.1039/c9nj05612b

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On the In Silico and In Vitro Anticancer Activity of Sulfonam
D
i
O
d
e
Chalcones: Potential JNKK3 Inhibitors
a,b
c,d
c
b
Jean M. F. Custodio *, Andrea F. Moura , Manoel O. de Moraes , Caridad N. Perez and
Hamilton B. Napolitanoe
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aDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN, 46556,
United States
bInstituto de Química, Universidade Federal de Goias, Goiania, Goias, 74690-900, Brazil
cNúcleo de Pesquisas e Desenvolvimento de Medicamentos, Universidade Federal do Ceará,
Fortaleza, Ceará, 60430-275, Brazil
dNúcleo de Pesquisa em Biotecnologia e Biodiversidade - BIOTEC, Universidade Federal do Piauí,
Parnaíba, Piauí, 64200500, Brazil
eCiências Exatas e Tecnológicas, Universidade Estadual de Goiás, Anapolis, Goias, 75132-903, Brazil
Correspondence email: jeanmfcustodio@gmail.com
Abstract Science is constantly looking for new strategies to combat tumor progression and
improve patient care due to increasing cancer incidence and high mortality. Although many
chalcones analogues have been synthesized and studied because of their activity against
tumor cell growth, the use of hybrid compounds containing both sulfonamides and chalcone
moieties for this purpose is still scarce. Hereby, this work proposes a series of sulfonamide
chalcones presenting biological potential against this disease. After experimentally tested,
these compounds showed cytotoxicity against tumor cell lines, SF-295 and PC-3, which
motivated us to investigate the possible structural bases for this action. Topological analyses
were carried out through Hirshfeld analysis to assign intermolecular interactions sites
important for protein-ligand analysis. To identify potential targets, the synthesized compounds
were submitted to a structure-based pharmacophoric screening, which suggest strong potential activity
as Mitogen-activated protein kinase 10 (JKN3) inhibitors. Considering these results, these compounds
were docked within the JKN3 active site. Our hypothesis that these compounds achieve their
biological potential by inhibiting JKN3 protein is reinforced when their energies of ligand-protein
interaction were compared to co-crystallized ligands: they showed similar or even lower binding
energies. Finally, the energy of the different conformations (solid phase, aqueous phase and
within the protein active site) of these sulfonamide chalcones was investigated from

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theoretical calculations. Our findings enable further studies on more sulfonamide chalcone
analogues toward the development of new anticancer drugs.
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1
. Introduction
Science is constantly looking for new strategies to combat tumor progression and
improve patient care due to increasing cancer incidence and high mortality. However, the
results are not always satisfactory, with high rates of tumor recurrence and metastasis, as well
as induction of many side effects. Therefore, research based on targeted target therapy has
grown significantly. Studying the different characteristics of cancer cells has resulted in the
1
development of targeted target drugs , especially those involving protein kinases, enzymes
encoded by the human genome.
Among these protein kinases, the mitogen-activated protein kinases (MAP kinases)
are a family of kinases that respond to oncogenic mutational events and regulate proliferation
and apoptosis as well as the metabolic reprogramming of tumor cells. In mammalians, three
subfamilies of MAPKs are well-characterized: ERKs (extracellular signal-regulated kinases),
2
p38 kinases and JNKs (c-Jun N-terminal kinase)) . The oncogenesis related with JNKs
involves cell proliferation, survival, transformation, inflammation, migration and suppression
of cell death disorders. Thereby, pharmaceutical industry has been developed new
3
compounds that act as selective inhibitors of the JNKs . The development of new molecules
based on knowledge of the pathophysiology of diseases, the study of biochemical pathways
and the selection of molecular targets in order to identify novel compounds with optimized
and targeted biological activity, low toxicity and favorable therapeutic index has been
4
,5
encouraged .
Although many compound classes have been studied as JNK inhibitors, we are
interested in using chalcones for this purpose due their chemistry, which provides many
biological applicability for them6–10. Having a double bond in conjugation with carbonyl
1
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group, these α-β-unsaturated ketones are known by their potential as anti-cancer , anti-
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malarial , antimicrobial , anti-protozoal and anti-HIV agents. In order to search for new
molecules more effective, new chalcones have been developed from the addition of organic
groups, as substituents of aromatic rings, with known biological properties. Several
substituents at different positions in the chemical structure of these molecules may determine
different biological activities as well as specific mechanisms of action16 .Sulfonamide
2

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addition has been described, in which compounds, called sulfonamide chalcones, demonstrate
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18,19
several biological activities already reported, like antifilaria , antimalarial
and
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anticancer , as well as α-glucosidase inhibitor , beta-secretase and acetylcholinesterase ,
carbonic anhydrase23,24 and ecto-5'-nucleotidase and intestinal alkaline phosphatase25.
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Herein, we describe some previously synthesized sulfonamide chalcones (I-IX),
discussing some structural aspects obtained from single crystal X-ray Diffraction (SCXRD).
Their topological analysis was presented from Hirshfeld surfaces (HS), which shows
potential intermolecular interaction sites important to protein ligand analysis. The biological
potential against tumor cell lines, like glioblastoma (SF-295) and prostate adenocarcinoma
(
PC-3) was confirmed by cytotoxic assay. To identify their possible potential targets, these
compounds were submitted to a structure-based pharmacophoric screening. Once identified
the target, they were docked into the active site of the result target and their binding modes
and energies were compared to the standard cocrystalized ligand. Finally, we investigated the
energy of the different conformations (solid phase, aqueous phase and within the protein
active site) from theoretical calculations.
2. Methodology
2
.1. Crystallographic Model
The compound 2′N-(phenylsulfonyl)acetophenone (a) was synthesized from reaction
between benzenesulfonyl chloride and 2-aminoacetophenone in dichloromethane medium
Scheme 1a). Then, sulfonamide chalcones I-IX were obtained from Claisen-Schmidt
(
condensation between a and their respective benzaldehydes, following Scheme 1b. They
were crystallized from saturated dichloromethane solutions. Suitable crystals of I-IX were
mounted and collected using a Bruker APEX-II CCD diffractometer equipped with MoKα
radiation, and were found to be crystallized under centrosymmetric space groups triclinic P1
(IV and V); monoclinic P2 /c (I, VI, IX and VIII); P2 /n (VII and III); and C2/c (II).
1
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Compounds I-IV and VI-IX have one molecule per asymmetric unit (AU), while V presents
two molecules per AU. All hydrogen atoms were refined following the ridding model, with
fixed U at 1.2 times U (C) (for aromatic and CH groups) and 1.5 times U (C) (for methyl
iso
eq
2
eq
groups). Crystallographic data for compounds I-IX were deposited at Cambridge
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Crystallographic Data Centre (CCDC) under codes 1868826, 1868827, 1850083, 1949070,
1949072, 1868828, 1904244, 1904245 and 1949073, respectively.
O
O
NH2
O
S
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TEA:DCM
ºC, 37h
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basic solvent
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R = I: o-Cl; II: o-F; III: o-Br; IV: p-Cl; V: p-Br; VI: p-F; VII: o-Methoxy; VIII: m-Nitro; IX: p-Ethoxy
1
(b)
Scheme 1 Synthesis of intermediate a (a) and sulfonamide chalcones I-IX (b) with
numbering scheme used for them.
The intermolecular interactions observed stabilizing the crystal packing of I-IX were
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analyzed from their HS through Crystal Explorer program. Weak C–H⋯O interactions were
qualitatively analyzed from dnorm HS, which is based on the combination of d (distance from
e
an outer nucleus to the HS) and d (distance from an inner nucleus to the HS) in a color-based
i
27
scale ranging from blue (longest distances) to red (shortest distances) . Also, hydrophobic
interactions such as C–H⋯휋 and 휋⋯휋 were studied from shape index HS, which shows both
their acceptor and donor regions as red concave and blue convex shapes, respectively28–30
.
Finally, these interactions were quantitatively analyzed from the fingerprint plots, showing a
D representation of de and di of each contact type31.
2
2.2. Antitumor tests
The human tumor cells lines used in this work were SF-295 (glioblastom) and PC-3
(prostate adenocarcinoma), which were kindly provided by the National Cancer Institute
Bethesda, MD, USA). These cells were cultured in RPMI1640 medium and supplemented
(
-1
-1
with 10% fetal bovine serum (2 mM glutamine, 100 U.mL penicillin), and 100 μg.mL
streptomycin at 37 °C with 5% CO . All cell lines were cultured in humidified atmosphere of
2
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% CO at 37 °C. Stock solution of I-IX and doxorubicin (positive control) were solubilized
2
in DMSO for cytotoxic assay. Their cytotoxicity against above mentioned cell lines was
-1
tested using MTT assay. Cells were plated in 96-well plates and treated with 25 µg.mL of
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compounds I-IX to initial screening. At the end of 72 h of incubation, the plates were
centrifuged, and the supernatant was removed and replaced with fresh medium (150 μL)
containing MTT (0.5 mg/mL). Cells were incubated for 3 hours. Tumor cell growth was
quantified by the ability of living cells to reduce the yellow dye 3-(4,5-dimethyl-2-thiazolyl)-
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,5-diphenyl-2H-tetrazolium bromide (MTT) to a purple formazan product by metabolically
active cells (MOSMANN, 1983). The MTT formazan product was dissolved in 150 μL of
DMSO, and the absorbance was measured using a multiplate reader (Spectra Count, Packard,
Ontario, Canada) at 595 nm.
Cell growth inhibition percentage (GI%) was calculated. In sequence, they were
retested using MTT assay for determination of half-maximal inhibitory concentration (IC50
-1
value). For this, increasing concentrations of I-IX (0.19 - 25 µg.mL ) were used for test.
-1
DMSO was used as negative control and doxorubicin (0.04 - 5 µg.mL ) was used as a
positive control. The GI% was determined based on the negative control. The IC50 values
and their 95% confidence intervals (CI 95%) were obtained by non-linear regression using
GraphPad Prism 5.0 (Intuitive Software for Science, San Diego, CA).
2
.3. Structure-based pharmacophoric screening
The structure-based potential drug target identification was obtained from a reversed
3
2
pharmacophore matching approach using the online tool PharMapper . PharMapper results
are reliable because they are derived from more than 23 000 proteins covering 16 159
3
2
druggable pharmacophore models and 51 431 ligandable pharmacophore models present in
the databases TargetBank, DrugBank, BindingDB and PDTD. As input, the maximum
generated conformations for each compound was set to 300 and only human protein targets
were considerate.
2.4. Molecular Docking
Aiming an improved understanding on how compounds I-VIII interact with the found
target (Mitogen-activated protein kinase 10, JNK3), we propose a molecular modeling of
these synthetic molecules. The MarvinSketch v.6.3.1 program (ChemAxon, Budapest,
Hungary, http://www.chemaxon.com) was used to build the 3D structure of I-VIII at neutral
condition (pH = 7.4). In addition, OMEGA v.3.0.0.1 software33,34 was used to generate up to
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69 conformers, which AM1-BCC charges were calculated through QUACPAC v.1.7.0.2 .
The 3D structure of JNK3 enzyme was obtained from the Protein Data Bank (PDB) and was
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also prepared at pH = 7.4 and its protonation states were predicted by H++ server
.
DOI: 10.1039/C9NJ05612B
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Molecular docking procedures were carried out on AutoDock-Vina software .
.5. Theoretical Calculations
Chemical conformations of I-IX were calculated in the solid state (SS), aqueous-
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simulated medium (AS) and that observed from docking results (DS). The atomic coordinates
were taken from their respective crystallographic model. For SS, all hydrogen atoms were
optimized, for DS all atoms were totally optimized using dielectric constant ε=78.3553
(water) and for DS, the single point energy was calculated from docking results output. All
calculations were performed using the density functional theory (DFT) at exchange-
correlation functional M062X and basis set 6-311++G(d,p).
3
. Results and Discussion
3.1. Solid State Comments
Figure 1 presents the overlay of compounds I-IX, obtained by overlapping aromatic
ring B. These compounds have different conformations, and overall differences are regarding
both the planarity (dihedral angles and angle and formed between the rings A and B) and
conformation of ring C. Compounds I and III differ each other by an isomorphic substitution
of the chlorine by a bromine at ring A. Also, there is no noticeable difference on molecular
structures of IV and IX. The conformation of the sulfonyl ring is derived from a rotation of
the C15–N1 휎-bond, so that the dihedral angle C14–C15–N1–S1 was analyzed for I-IX (휔푰=
-
5.93; 휔 = 28.26; 휔 = -6.12; 휔 = -41.43; 휔 = -34.49; 휔 = -23.73; 휔 = -49.76; 휔푽푰푰푰=
푰푰 푰푰푰 푰푽 푽 푽푰 푽푰푰
4
.97; 휔 = -41.94). These values evidence the conformational variability of the ring C, which
푰푿
range from syn-periplanar (I-III, VI and VII) to syn-clinal (IV-V, VII and IX).
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Figure 1 Overlay of compounds I-IX in solid phase, showing the main difference of their
conformations.
Further information about intermolecular interactions observed for I-III are inferred
from their dnorm HS and respective 2D fingerprint plots in Figure 2a, Figure 2b and Figure 2c.
Figure 2a shows the C–H⋯O interactions that stabilizes the crystal packing of I, highlighting
them as red spots on both HS points of view where “a” and “d” mean their acceptor and
donor regions, respectively. The strongest interaction, C21–H21⋯O1, assembles I in dimers
involving the carbonyl group. For II, the strongest interaction involves the atoms O2, O3, H8
and H5 in a chain with similar d and d of I. Although with similar distances for their
e
i
strongest interaction (Figure 2b), the weaker interactions of I (C5–H5⋯O3 and C13–H13⋯
O2) are stronger than those observed for II (C18–H18⋯F1 and C3–H3⋯O2) and play an
important role in its crystal packing. Figure 2c confirms that the crystal packing of III is also
stabilized by a dimer through interaction C17–H17⋯O1, an interaction with medium distance
(
C5–H5⋯O2) and one weak interaction (C13–H13⋯O3). The ranges used for the dnorm HS
calculation and distances observed for each compound is presented in Table 1.
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Figure 2 dnorm HS and 2D fingerprint plots showing the C–H⋯O interactions of (a) I, (b) II and (c)
III. Acceptor and donor regions are represented by “a” and “d”, respectively.
Table 1 Ranges used for the dnorm HS calculation and distances observed for compounds I-IX.
Approximated Approximated
Range used for dnorm
Donor
Distances (Å)
Acceptor
Distances (Å)
Compound
Selected Contacts
HS (Å)
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de
I
-0.1504 – 1.3826
-0.1500 – 1.5279
C21–H21⋯O1
C8–H8⋯O3
C5–H5⋯O3
C17–H17⋯O1
C5–H5⋯O2
C13–H13⋯O3
C4–H4⋯O1
C8–H8⋯O2
C13–H13⋯O3
C5–H5⋯O2
C8–H8⋯O2
C4–H4⋯O1
C2*–H2*⋯C6
C17*–H17*⋯C13
C8*–H8*⋯O2*
1.0
1.0
1.0
0.9
1.2
1.3
1.0
1.0
1.2
0.9
1.1
1.2
1.1
1.1
1.0
1.3
1.3
1.3
1.2
1.4
1.5
1.3
1.4
1.5
1.3
1.4
1.5
1.8
1.6
1.3
1.3
1.3
1.3
1.2
1.4
1.5
1.3
1.4
1.5
1.3
1.4
1.5
1.8
1.6
1.3
1.0
1.0
1.0
0.9
1.2
1.3
1.0
1.0
1.2
0.9
1.1
1.2
1.1
1.1
1.0
II
III
IV
-0.1595 – 1.5010
-0.1823 – 1.4464
Vα
-0.2511 – 1.2786
-0.1778 – 1.3551
V
Vβ
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C19*–H19*⋯C6*
C19*–H19*⋯C1*
C4*–H4*⋯O1*
C12–H12⋯C20
C20–H20⋯O1
C5–H5⋯O2
C22–H22B⋯O2
C21–H21⋯O1
C22–H22B⋯O2
C9⋯C9
C5–H5⋯O2
C8–H8⋯O2
C11–H11⋯O2
C19–H19⋯O4
C7–H7⋯O3
1.2
1.1
1.2
1.1
1.4
1.1
1.2
1.1
1.1
1.6
1.0
1.0
1.0
1.4
1.2
0.9
1.0
0.9
1.0
1.7
1.7
1.5
1.6
1.6
1.5
1.5
1.3
1.4
1.6
1.1
1.1
1.1
1.6
1.4
1.1
1.1
1.0
1.1
1.7
1.7
1.5
1.6
1.6
1.5
1.5
1.3
1.4
1.6
1.1
1.1
1.1
1.6
1.4
1.1
1.1
1.0
1.1
1.2
1.1
1.2
1.1
1.4
1.1
1.2
1.1
1.1
1.6
1.0
1.0
1.0
1.4
1.2
0.9
1.0
0.9
1.0
VI
-0.1731 – 1.3684
-0.1445 – 1.2976
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
VII
VIII
IX
-0.2927 – 1.4930
-0.2045 – 1.4787
C20–H20⋯O3
C5–H5⋯O2
C8–H8⋯O2
C11–H11⋯O2
The crystal packing of compounds I-III are also stabilized by both C–H⋯휋 and 휋⋯휋
interactions, which play an important role in several fields, such as the packing of aromatic
4
0
molecules in crystals and complexation in many host-guest systems . On the shape index
HS, these interactions are represented as one red concave region and one blue convex region
over the aromatic ring and H atom, respectively (C–H⋯휋 interactions) and as two red and
blue triangular shapes over aromatic rings (휋⋯휋 interactions). On the other hand, C–H⋯휋
interactions are represented by C–H contacts in the 2D fingerprint plot, while 휋⋯휋
interactions are represented by C–C contacts. Two molecules of I are related by the
interaction 퐶푔 ⋯퐶푔 (Figure 3a). Also, there are two molecules of I related by the
1
2
interaction C3–H3⋯퐶푔 . For II, the 휋⋯휋 interactions involve 퐶푔 ⋯퐶푔 and 퐶푔 ⋯퐶푔 ,
3
1
1
2
2
while the C–H⋯휋 interaction occurs between C11 and 퐶푔 as shown in Figure 3b. Figure 3c
3
shows that, similarly to I, the crystal packing of III is also stabilized by one 퐶푔 ⋯퐶푔 and
1
2
one C3–H3⋯퐶푔3 interactions. Details on distances involved in C–H⋯휋 and 휋⋯휋
interactions observed for compounds I-IX are given on Table 2.
9

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0
1
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9
0
1
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3
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7
8
9
0
1
2
3
4
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9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
Figure 3 Representation of C–H⋯휋 and 휋⋯휋 interactions stabilizing the crystal packings of (a) I,
b) II and (c) III. Both shape index HS and 2D fingerprints plots are shown. Blue and red represent
(
donor and acceptor regions, while other colors represent intermediate states.
Table 2 Distance of C–H⋯휋 and 휋⋯휋 interactions observed for compounds I-IX. 퐶푔 , 퐶푔 and
1
2
퐶푔 are the center of gravity of aromatic rings A, B and C, respectively.
3
π⋯흅
C–H⋯ π
Compound
Selected Contacts
풅푪품⋯푪품 (Å)
Slippage (Å)
풅푯⋯푪품(Å)
풅
∠퐂ퟑ–퐇ퟑ⋯푪품 (º)
푪⋯푪품 (Å)
퐶푔 ⋯퐶푔2
3.9076
–
1.238
–
–
3.25
–
–
4.086
–
–
150
–
1
I
C3–H3⋯퐶푔3
퐶푔 ⋯퐶푔1
3.9034
4.0181
–
1.281
1.515
–
1
II
퐶푔 ⋯퐶푔2
2
–
–
–
C11–H11⋯퐶푔3
2.94
–
3.612
–
130
–
퐶푔 ⋯퐶푔2
3.8863
–
1.269
–
1
III
IV
C3–H3⋯퐶푔3
퐶푔1⋯퐶푔1
2.94
–
3.612
–
130
–
3.7773
1.200
1
0

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퐶푔 ⋯퐶푔2
3.9342
1.581
–
2.81
2.79
2.76
–
–
3.740
3.604
3.591
–
–
2
C3–H3⋯퐶푔3
–
–
–
174
C2*–H2*⋯퐶푔1
C17*–H17*⋯퐶푔2
퐶푔 *⋯퐶푔 *
–
154
149
–
Vα
Vβ
–
3.8339
–
–
V
1
1
1.495
–
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
C19*–H19*⋯퐶푔1*
C21–H21⋯퐶푔2 ∗
2.70
2.86
–
3.559
3.721
–
155
155
–
–
–
퐶푔 ⋯퐶푔1
4.4063
4.0974
3.8971
3.8178
–
2.311
1.861
1.513
1.329
–
1
VI
퐶푔 ⋯퐶푔2
–
–
–
2
VII
VIII
퐶푔1⋯퐶푔2
–
–
–
퐶푔 ⋯퐶푔2
–
–
–
1
C3–H3⋯퐶푔3
2.96
–
3.794
–
144
–
퐶푔 ⋯퐶푔2
3.8882
–
1.370
–
1
IX
C22–H22⋯퐶푔1
C21–H21⋯퐶푔2
2.903
2.839
3.763
3.707
148
156
–
–
For IV, there are two strongest interactions observed the dnorm HS: C4–H4⋯O1 and
C8–H8⋯O2 (Figure 4a). Its crystal packing is also stabilized by a different dimer regarding
compounds I-III. This dimer involves atoms C13 and O3 and, based on its intermolecular
distances, plays a secondary role on the crystal packing. Compound V has two conformers
per asymmetric unit, here named Vα and Vβ. Thus one dnorm HS was generated one dnorm HS
for each conformer, shown in Figure 4b (Vα) and Figure 4c (Vβ). For Vα, there are two
strongest interactions involving C5–H5⋯O2 and C8–H8⋯O2. Also, weaker interactions
stabilize the crystal packing of V relating two Vα conformers (C4–H4⋯O1) and one Vα with
one Vβ conformers (C2*–H2*⋯C6 and C17*–H17*⋯C13) conformers. There are one
stronger interaction (C8*–H8*⋯O2*) and three weaker interactions (C19*–H19*⋯C6*,
C19*–H19*⋯C1* and C4*–H4*⋯O1*) relating two Vβ molecules. The dnorm HS calculated
for VI (Figure 4d) shows that the strongest directional interaction involves two C atoms
(
C12–H12⋯C20), different from compounds I-V. There are also two C–H⋯O interactions
observed for VI, C20–H20⋯O1 and C5–H5⋯O2.
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1
2
3
4
5
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9
0
1
2
3
4
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8
9
0
Figure 4 dnorm HS and 2D fingerprint plots showing C–H⋯O and C–H⋯C interactions of (a) IV, (b)
Vα, (c) Vβ and (d) VI. Acceptor and donor regions are represented by “a” and “d”, respectively.
The shape index HS calculated for IV shows that these molecules are assembled
through both C–H⋯휋 and 휋⋯휋 interactions (Figure 5a). Molecules of IV are stacked by
means of the 퐶푔 ⋯퐶푔 interaction, while molecules of IV are stacked throughout 퐶푔 ⋯퐶푔
1
1
2
2
interaction. There is also one interaction involving C3–H3⋯퐶푔 , which forms a
3
centrosymmetric dimer. There are only C–H⋯휋 interactions involving Vα (Figure 5b).
Centroids 퐶푔 and 퐶푔 act as acceptors for the intermolecular interactions C2*–H2*⋯퐶푔
1
1
2
and C17*–H17*⋯퐶푔 . On the other hand, 퐶푔 * and 퐶푔 * are involved both in 휋⋯휋 and C–
2
1
2
H⋯휋 interactions (Figure 5c) for Vβ. For compound VI, only 휋⋯휋 interactions were
observed involving both 퐶푔 and 퐶푔 (Figure 5d).
1
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1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
Figure 5 Representation of C–H⋯휋 and 휋⋯휋 interactions stabilizing the crystal packing of (a) IV,
(b) Vα, (c) Vβ and (d) VI. Both shape index HS and 2D fingerprints plots are shown.
The dnorm HS calculated for VII evidences that there are three C–H⋯O (C22–H22B⋯
O2; C21–H21⋯O1 and C22–H22B⋯O2) interactions and one unusual C9⋯C9 contact
stabilizing the crystal packing (Figure 6a). For both VIII (Figure 6b) and IX (Figure 6c),
there is the same trifurcated interaction pattern involving C5–H5⋯O2, C8–H8⋯O2 and C11–
H11⋯O2, in which that involving C5 is dominant. There are three more C–H⋯O interactions
stabilizing the crystal packing of VIII: C19–H19⋯O4.
1
3

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0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
Figure 6 dnorm HS and 2D fingerprint plots showing the C–H⋯O interactions of (a) VII, (b) VIII
and (c) IX. Acceptor and donor regions are represented by “a” and “d”, respectively.
The shape index HS was calculated for VII (Figure 7a), VIII (Figure 7b) and IX
(
Figure 7c) to analyze how these molecules pack and what kind of contacts stabilize their
crystal packing. The crystal packing of VII is stabilized by 휋-stacking interactions involving
both 퐶푔 and 퐶푔 . Figure 7b shows that the crystal packing of VIII is stabilized by one 퐶푔
1
2
1
⋯
퐶푔 stacking and one C–H⋯휋 interaction involving C3–H3⋯퐶푔 , similar to IV. Finally,
2
3
the crystal packing of compound IX was found to be stabilized by a 퐶푔 ⋯퐶푔 stacking. For
1
2
this compound, both 퐶푔 and 퐶푔 act also as acceptors for interactions C22–H22⋯퐶푔 and
1
2
1
C21–H21⋯퐶푔2.
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4

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1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
5
5
5
5
5
5
5
5
5
5
6
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
Figure 7 Representation of C–H⋯휋 and 휋⋯휋 interactions stabilizing the crystal packings of (a) VII,
(b) VIII and (c) IX. Both shape index HS and 2D fingerprints plots are shown.
3
.2. Cytotoxic Assay
The addition of chemical clusters to molecules with known biological activity through
chemical synthesis has been frequent in order to determine different biological activities as
well as specific mechanisms of action. In order to find new molecules more effective against
a specific therapeutic target, new chalcones have been developed from the addition of organic
1
6
groups, as substituents of aromatic rings, with known biological properties . The
cytotoxicity activity of sulfonamide chalcones previously synthesized by our group has been
reported in other studies already published41–43. In this study, nine sulfonamide chalcones
were tested against the human tumor cell lines SF-295 and PC-3 to verify in vitro cytotoxicity
activity, using MTT assay. Among the sulfonamide chalcones tested, I-VIII were cytotoxic,
with GI% greater than or equal to 75% against at least one tested tumor cell line. Only IX
showed no cytotoxicity against tested tumor cell lines (Table 3).
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1
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1
1
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
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Table 3 Cytotoxicity of Sulfonamide chalcones against two tumor cell lines. GI% values
-1
determined by MTT-assay using a concentration of 25 µg.mL after 72 h of incubation. Doxorubicin
was used as positive control using a concentration of 5 µg.mL . Values are the average from three
independent experiments shown with standard error.
-1
Compound
SF-295
PC-3
I
82.6 ± 1.9
83.2 ± 11.5
79.8 ± 11.8
85.8 ± 10.8
91.4 ± 0.6
73.8 ± 19.7
86.4 ± 10.5
63.5 ± 1.1
39.6 ± 0.2
79.3 ± 0.5
99.0 ± 0.7
74.6 ± 22.4
75.8 ± 22.9
77.5 ± 21.6
99.4 ± 0.4
73.9 ± 24.7
77.7 ± 20.9
77.9 ± 3.4
43.8 ± 3.7
89.4 ± 0.2
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
II
III
IV
V
VI
VII
VIII
IX
Doxorubicin
Sulfonamide chalcones I-VIII were tested again using serial concentrations ranged
-1
0
.19 to 25 µg.mL to determine IC values (Table 4). The tested compounds showed IC
50 50
-1
values ranging from 2.1 to 7.9 µg.mL against two tested tumor cell lines. Among these
-1
active compounds, compound IV had the lowest IC values (2.1 and 2.4 µg.mL against SF-
5
0
2
95 and PC-3, respectively). In a previous study, carried out by our group, cytotoxicity of
these molecules was evaluated against HCT-116, with IC50 values ranging from 2.4 to 7.5
-1 44
µg.mL . With this, all these compounds are promising new drug candidate with anticancer
activity.
Table 4 IC50 Values of compounds I-VIII against SF-295 and PC-3 tumor cell lines. IC50 Values
and their 95% confidence intervals (CI 95%) were determined by MTT-assay using serial
concentrations ranging to 0.19 to 25 µg.mL , after 72 h of incubation. IC50 Values are from three
independent experiments shown with 95% confidence intervals (CI 95%). Doxorubicin was used as
-1
-1
positive control using serial concentrations ranging from 0.04 to 5 µg.mL .
Compound
SF-295
PC-3
I
4.0 (3.1-5.1)
4.6 (4.0-5.3)
7.6 (6.5-8.9)
2.1 (1.7-2.7)
5.0 (4.2-6.0)
6.2 (4.3-8.9)
7.1 (5.8-8.7)
5.1 (4.8-5.4)
5.2 (4.8-5.6)
7.5 (6.8-8.3)
2.4 (2.1-2.6)
5.9 (5.2-6.9)
5.9 (5.2-6.7)
6.9 (6.2-7.7)
II
III
IV
V
VI
VII
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VIII
7.9 (6.5-9.7)
0.4 (0.3-0.5)
6.6 (5.7-7.5)
0.1 (0.1-0.2)
Doxorubicin
Recent studies have reported the chemical synthesis of new sulfonamide chalcones
and their antitumor potential. The in vitro antitumor effect of these molecules has been
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described in some tumor cell lines, such as HEPG2 (liver cancer) , MCF-7 (breast cancer) ,
46
SF-295 (glioblastoma), PC-3 (prostate cancer) and HCT-116 (colorectal cancer) . However,
the mechanism of action of this class of molecules has not yet been explored. Based on these
studies, molecules containing sulfonamide and chalcone moieties may lead to new hybrid
architectures with improved biological profiles.
3
.3. Molecular Docking
The wide range of biological activities of this compound class and the experimental
results for compounds I-VIII motivated us study how our compounds acts to give the
observed antitumor activity. First, we performed a structure-based potential drug target
identification from a reversed pharmacophore matching approach using the online tool
3
2
PharMapper . PharMapper results are reliable because they are derived from more than
3,000 proteins covering 16,159 druggable pharmacophore models and 51,431 ligatable
2
3
2
pharmacophore models present in the databases TargetBank, DrugBank, BindingDB and
PDTD. Also, seeking an improved accuracy, PharMapper also calculates a Fit Score for the
pharmacophore model’s ligands extracted from PDB and compares these Fit Scores to those
obtained from analysed molecules47,48
.
Compounds I-VIII were submitted to PharMapper and the top-7 (those with better Fit
Score) human proteins for each compound are presented in Table S1. The Mitogen-activated
protein kinase 10 (JNK3, PDB code: 1PMV) was found to be a potential target for all
analysed compounds, so that this protein was chosen for the binding mode analysis. Figure 8a
shows this protein crystallized with dihydroanthrapyrazole (ATRP), a small molecule
4
9
inhibitor .
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Figure 8 Mitogen-activated
protein
kinase
10
(JNK3)
protein
crystallized
with
dihydroanthrapyrazole (ATRP), one of its inhibitors (a). Binding model of ATRP into JNK3 obtained
from our docking model (b). The RMSD between our ATRP calculated model and the crystallized
compound is 1.063 Å, indicating a suitable theoretical method.
c-Jun N-terminal kinase (JNK) is a subfamily of mitogen-activated protein kinase
(MAPK) with three differently spliced genes, namely, JNK1 (MAPK8), JNK2 (MAPK9), and
JNK3 (MAPK10). Some diseases, such as cancer, inflammation, and neurodegenerative
diseases, show over activation of JNK. JNK1 and JNK2 are expressed in various tissues,
while JNK3 is restricted to testes, heart and brain. Expression of JNK3 is largely restricted to
the brain as a tumor suppressor, and most of brain tumor presents loss of expression of the
jnk3 gene2,50,51. Considering this, the JKN3 protein was chosen as potential target for
compounds I-VIII. Indeed, as will be shown in the experimental tests, this protein has
straight relationship with one cell line tested.
Docking studies started with the active site ligand-based selection, which is a box
with dimensions 14.5 Å x 20.5 Å x 18.1 Å centered at 20.29 Å x, 28.40 Å y and 20.57Å z.
This model was validated by docking ATRP into this active site, which resulted in a RMSD =
4
9
1
.063. In our model (and in the Scapin’s work ), ATRP was found to inhibit JNK3 by
interacting with both Glu147 (2.2 Å) and Met149 (3.2 Å) residues with binding affinity (BA)
-9.1 kcal/mol. Figure 9 shows the structures of compounds I-IX docked into this same active
site of JNK3, while their bindings modes are presented in Figure 9 and Table 3 presents the
estimated BA, number of interactions (N ) and protein residues involved.
HB
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Figure 9 Binding modes of compounds I (a), II (b), III (c), IV (d), V (e), VI (f), VII (g) and VIII
h) into the active site of JNK3. For each item are shown the molecular poses, intermolecular
(
interactions, residues and distances (in Å).
Table 5 Details on energy, quantity and residues of the binding modes of compounds I-VIII and
ATRP, the standard inhibitor, into JNK3
Compound
Estimated BA
NHB
2
2
Residues
Serine (SER) and Asparagine (ASN)
Serine (SER) and Asparagine (ASN)
-1
I
II
-9.1 Kcal.mol
-9.5 Kcal.mol
-1
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III
IV
V
-9.6 Kcal.mol
-10.0 Kcal.mol
2
2
2
2
1
2
2
Serine (SER) and Alanine (ASN)
-1
Glutamine (GLN)
Asparagine (ASN)
Serine (SER) and Asparagine (ASN)
Asparagine (ASN) and Lysine (LYS)
Glycine (GLY) and Alanine (ALA)
-
-
-
-
1
1
1
1
-8.8 Kcal.mol
-9.8 Kcal.mol
-9.2 Kcal.mol
-9.3 Kcal.mol
-9.1 Kcal.mol
VI
VII
VIII
ATRP
0
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-1
Glutamic acid (GLU) and Methionine (MET)
JNK3 is known to be inhibited through intermolecular interactions involving both
GLU-147 and MET-149 residues. Although the most recent JNK3 inhibitors are from
4
9
52
diarylimidazole family, ATP analogues and ATRP , some 3-substituted indoli-2-one ,
53
54
aminopyrazole and trisubstituted thiophene derivatives have been also studied for this
purpose. Hereby, we present some sulfonamid -chalcones hybrids which could inhibit JNK3
via alternative residues, as seen in Figure 9. Both compounds I and II (Figures 9a and 9b)
have similar binding modes, which involve two H Bonds (HB) between their sulfonyl group
and SER-72 and ASN-152 with distances 2.1 Ǻ and 2.5 Ǻ, respectively. Because of
differences on their poses, their BA are slightly different, both having similar or better values
than ATRP. Interacting with SER-193 and ALA-74 through HAMINO and OsULFONYL with
distances 2.7 Ǻ, compound III was found to have better BA to JNK3 than ATPR (Figure 9c).
Unlike I-III, the binding mode of IV is ruled by interactions between GLN-75 and the
-1
chlorine atom (2.7 Ǻ and 3.6 Ǻ; Figure 9d). With better BA to JNK3 (-10.0 Kcal.mol ) than
ATRP and compounds I-III and V-VIII, we suggest that this halogen in the para-position
plays key role on its biological potential. For V, it was observed one bifurcated interaction
with JNK3 in which OCARBONYL acts as acceptor for ASN-152 hydrogens (2.5 and 2.7 Ǻ, BA
-
1
=
-8.8 Kcal.mol ; Figure 9e). Besides also interacting with ASN-152, the sulfonyl group
from compound VI stablishes one H bonding with SER-72 (2.0 Ǻ and 2.5 Ǻ, providing a BA
-1
=
-8.8 Kcal.mol ; Figure 9f). Finally, compounds VII and VIII have different binding
modes, both involving the substituent of the chalcone backbone: VII is accommodated into
JNK3 active site through interactions involving OSULFONYL⋯ASN-152 (2.3 Ǻ) and OETHOXYL
⋯
LYS-93 (2.7 Ǻ) (Figure 9g), while the nitro group of VIII interacts with GLY-76 (2.2 Ǻ)
and ALA-74 (2.5 Ǻ) (Figure 9h). Both compounds VII and VIII showed better BA to JNK3
-1
-1
than ATRP, with values -9.2 Kcal.mol and -9.2 Kcal.mol , respectively.
Some studies demonstrate that activation of oncogenes such as Ras, c-fos, Met and
Bcr-Abl may be JNK dependent, contributing to cellular transformation that supports cancer
development. Whereas, JNK inhibitors are strong candidates for anticancer agent. Some JNK
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inhibitors were approved and have been used to treat cancer, and others are in different
phases of clinical study2,50,51. These compounds seem to affect the proliferation, adhesion and
migration of some tumor cell lines, inducing cell cycle arrest and apoptosis, as well as,
making these cells more sensitive to treatment with other chemotherapies55–58. In additions to
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cancer, some inhibitors are also used in inflammation and as antiviral agent .
6
1
Warmka and collabolators described the inhibitory effect of a chalcone analog on
cell viability and NF-kB, with activation of caspases, and activation of extracellular signal
regulated kinase 1/2 (ERK1/2) and c-Jun N-terminal kinase (JNK) in A549 lung cancer cells.
When associated with a pharmacological inhibitor of ERK1/2 or JNK, these cells were more
sensitive to chalcone-induced cytotoxicity without affecting NF-κB or caspase activity. Other
studies showed that sulfonamides and their derivatives can activate or inhibit JNK pathway.
The activation of this pathway can led to the induction of apoptosis of colorectal cancer
cells62,63, while the inhibition prevents neuronal cell death induced by growth factor and
64
serum deprivation . No studies have shown the effect of sulfonamide chalcones on the JNK
pathway. Studies on the action of chalcones and sulfonamides on this pathway are still
controversial. Thus, further investigation is required.
4
. Theoretical Calculations
Theoretical calculations were performed in order to study the influence of different
media on compounds I-VIII. Figure 10 shows overlays between the molecular conformations
of I-VIII in the solid state (SS), aqueous-simulated medium (AS) and docking results (DS),
adopting the aromatic ring A as fixed group. AS conformations (black) of all compounds
were found to be relatively similar to SS conformations, with main discrepancy observed for
benzenesulfonyl rings. In contrast, compounds I, II, III, V, VI and VIII adopt totally
different conformation in SS and DS. These differences motivated us to calculate the energy
of each conformation, energy gap between SS/AS (ΔE1) and energy gap between SS/DS
(
Table 3). For all compounds, the energy was found to increase following the sequence AS >
DS > SS. Considering the energy to convert the SS conformation into that observed for DS,
2
(ΔE2), compound V demands more energy (-7.620x10 kJ/mol) while the smallest energy
2
was observed for compound VI (-6.961x10 kJ/mol).
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Overlay between the molecular conformations of I (a), II (b), III (c), IV (d), V (e),
VI (f), VII (g) and VIII (h) in their solid state (SS), aqueous-simulated medium (black) and docking
simulation (white). The aromatic ring A was kept fixed.
Table 6 Energy of each conformation in solid state (SS), aqueous-simulated medium (AS), docking
results (DS), gap between SS/AS (ΔE1) and gap between SS/DS (ΔE2).
Energy (kJ/mol)
ΔE1
x10 )
ΔE2
SS (x106)
AS (x106)
DS (x106)
3
2
(
(x10 )
I
II
III
IV
V
VI
VII
VIII
-5.127
-4.178
-10.692
-5.126
-10.693
-4.178
-4.218
-4.455
-5.129
-4.181
-10.699
-5.129
-10.698
-4.181
-4.221
-4.458
-5.127
-4.179
-10.693
-5.127
-10.694
-4.179
-4.219
-4.456
-2.280
-2.313
-2.172
-2.376
-2.335
-2.346
-2.426
-2.442
-7.024
-7.410
-7.282
-7.330
-7.620
-6.961
-7.510
-7.209
5. Conclusion
After experimentally tested, our compounds were found to be cytotoxic against tumor
cell lines SF-295 and PC-3, which motivated us to investigate the possible structural bases for
this action. Topological analysis for our compounds was carried out through Hirshfeld
analysis to identify intermolecular interactions sites, important also for protein-ligand
analysis. Then, it was performed a structure-based pharmacophoric screening, which
indicated that all sulfonamide chalcones are potential mitogen-activated protein kinase 10
(
JNK3) inhibitors. Molecular docking simulations were used to investigate the binding model
of our compounds, and they were found to interact with JNK3 with same or better binding
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affinity than ATRP, one small molecule cocristallized with JNK3. Our findings allow further
studies to confirm the mechanism involved in the antitumor effect of sulfonamide chalcones
in order to develop new anti-cancer molecules. In addition, this work opens perspectives to
evaluate the effect of sulfonamide chalcones against other diseases which the JNK pathway is
also involved, such as inflammation and neurodegeneration.
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6. Acknowledgements
The authors thank to Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
(
CAPES) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for the
financial support. Research developed with support of the High Performance Computing Center at the
Universidade Estadual de Goiás (UEG).
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