CoMFA studies and in vitro evaluation of some 3-substituted benzylthio quinolinium salts as anticryptococcal agents

Article abstract of DOI:10.1016/j.bmc.2013.08.043

The 3-dimensional quantitative structure-activity relationship (3D-QSAR) molecular modeling technique or comparative molecular field analysis (CoMFA) has been used to design analogs of the natural product cryptolepine (1). Twenty-three compounds with thei

Full text of DOI:10.1016/j.bmc.2013.08.043

Bioorganic & Medicinal Chemistry 21 (2013) 7194–7201
Contents lists available at ScienceDirect
Bioorganic & Medicinal Chemistry
journal homepage: www.elsevier.com/locate/bmc
CoMFA studies and in vitro evaluation of some 3-substituted
benzylthio quinolinium salts as anticryptococcal agents
Sidney Bolden a, Comfort A. Boateng a, Xue Y. Zhu a, Jagan R. Etukala a, Suresh K. Eyunni a,
Melissa R. Jacob b, Shabana I. Khan b, Seth Y. Ablordeppey a,
⇑
a College of Pharmacy and Pharmaceutical Sciences, Florida A&M University, Tallahassee, FL 32307, USA
b The National Center for the Development of Natural Products, Research Institute of Pharmaceutical Sciences, University of Mississippi, University, MS 38677, USA
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 1 July 2013
Revised 14 August 2013
Accepted 23 August 2013
Available online 3 September 2013
The 3-dimensional quantitative structure–activity relationship (3D-QSAR) molecular modeling technique
or comparative molecular field analysis (CoMFA) has been used to design analogs of the natural product
cryptolepine (1). Twenty-three compounds with their in vitro biological activities (IC50 values) against
Crytococcus neoformans were used to generate the training set database of compounds for the CoMFA
studies. The cross-validated q2, noncross-validated r2, and partial least squares (PLS) analysis results were
used to predict the biological activity of 11 newly designed test set compounds. The best CoMFA model
produced a q2 of 0.815 and an r2 of 0.976 indicating high statistical significance as a predictive model. The
steric and electrostatic contributions from the contour map were interpreted from the color-coded con-
tour plots generated from the PLS model and the active structural components for potency against C. neo-
formans were determined and validated in the test set compounds. The 3-substituted benzylthio
quinolinium salts (4) that make up the test set were synthesized and evaluated based on the predicted
activity from the CoMFA model and the results produced a good correlation between the predicted
and experimental activity (R = 0.82). Thus, CoMFA has served as an effective tool to aid the design of
new analogs and in this case, it has aided the identification of compounds equipotent with amphotericin
B, the gold standard in antifungal drug design.
Keywords:
CoMFA
Antifungal agents
Cryptolepine
Mycoses
Opportunistic infection
Substituted benzylthioquinolinium salts
Published by Elsevier Ltd.
1. Introduction
The natural product cryptolepine (CLP, 1, Fig. 1), obtained from
the African climbing shrub Cryptolepis sanguinolenta, was previ-
The incidence of opportunistic infections (OIs) has moderated
lately due to the declining incidence of HIV AIDS in especially
the developed countries.1 However, OIs continue to be of public
health concern. OIs occur when microorganisms that are well con-
trolled in healthy individuals become unchecked in patients with
compromised immune systems weakened by disease or medica-
tion. Consequently, as the number of people contracting HIV/AIDS,
or undergoing chemotherapy, or receiving organ transplants in-
creases, so does the risk of being infected by a pathogenic fungi.2
The most common OIs include Candida albicans, Aspergillus
fumigatus and Cryptococcus neoformans (Cn).3 While there are
several drugs against these OIs, many opportunistic fungi have
developed resistance to drugs that have been on the market for
an extended period of time such as fluconazole and nonliposomal
amphotericin B.4 In addition, the supply of new antifungal drugs
with unique targets against OIs is behind the demand for new
drugs that address the problem of resistance and side-effects
among pathogenic fungi.4
ously shown to have interesting biological activities against a
broad array of fungal and bacterial species, and operates through
a unique mechanism of action.5,6 During optimization of cryptole-
pine to improve its anti-infective properties, several resulting ana-
logs have demonstrated increased potency and lower cytotoxicity
than CLP.7–11 These analogs span six different scaffolds and have
generated important structure–activity relationship (SAR) data.
The encouraging progress made during the optimization process
spurred a need to develop a CoMFA model that would enable the
prediction of subsequently designed analogs prior to their synthe-
sis and thus, aid in the prioritization of the synthesis of designed
analogs. The observation of a strong correlation, having used differ-
ent chemotypes, would also provide the first indications that the
compounds may be acting through a similar mechanism in inhib-
iting or killing the microorganisms. Thus, in this study, we report
a CoMFA model that is able to predict the biological activity of
new analogs based on their steric and electrostatic properties using
a training set of 23 compounds. In addition, 11 new compounds
designed to probe the electronic and hydrophobic space around
the phenyl ring A, were synthesized and their inhibitory potencies
⇑
Corresponding author. Tel.: +1 850 599 3834; fax: +1 850 599 3934.
E-mail address: seth.ablordeppey@famu.edu (S.Y. Ablordeppey).
0968-0896/$ - see front matter Published by Elsevier Ltd.
http://dx.doi.org/10.1016/j.bmc.2013.08.043

S. Bolden et al. / Bioorg. Med. Chem. 21 (2013) 7194–7201
7195
CH3
N
CH3
N
R
N
C
I
I
I
(CH2)5
R =
C
A
D
B
S
D
A
C
A
D
B
S
N
H
3-(phenylthio)-1-(5-cyclohexylpentyl)
quinolinium Iodide, 3a
5-Methyl-benzothieno[3,2-b]
-quinoli-5-ium iodide, 2
5-methyl-10H-indolo[3,2-b]
quinolin-5-ium iodide, 1
Figure 1. Cryptolepine hydroiodide, sulfur bioisostere and ring-opened analogs.
Table 1
Training set compounds, experimental activities, and CoMFA predicted activities
R2
N
R
N
(CH2)5
R
N
R =
R2=
I
I
I
R1
R1
(CH2)5
S
O
S
S
R1
M) (Cn)
5a-d
M) (Cn)
3a-m
4a-f
aCompound
R1
Expt IC50
(
l
Expt.b pIC50
Pred.c IC50
(l
Pred.c pIC50
Cytotoxicity (lg/mL [lM])
3a
3b
3c
3d
3e
3f
3g
3h
3i
3j
3k
3l
3m
4a
4b
4c
H
0.966
3.74
0.683
0.512
1.88
2.34
1.31
0.565
0.375
0.375
13.2
6.015
5.427
6.165
6.290
5.727
5.631
5.882
6.248
6.425
6.425
4.879
4.734
6.136
6.521
5.870
7.054
6.114
6.339
6.380
4.561
4.962
5.034
5.042
—
0.986
3.672
0.646
0.579
1.905
2.118
1.196
0.417
0.417
0.417
16.106
19.952
0.857
0.307
1.588
0.139
0.804
0.440
0.428
32.137
10.046
7.079
13.520
—
6.006
5.435
6.190
6.237
5.720
5.674
5.922
6.379
6.379
6.379
4.793
4.700
6.067
6.512
5.799
6.857
6.095
6.356
6.368
4.493
4.998
5.150
4.869
—
4.60 [8.89]
NC
NC
NC
9.28 [17.4]
NC
o-CF3
m-CF3
p-CF3
o-OH
m-OH
p-OH
o-CH3
m-CH3
p-CH3
m-F
m-OCH3
p-OCH3
H
o-Cl
p-Cl
m-CH3
p-CH3
p-CF3
p-F
m-CF3
o-CF3
o-Br
NC
4.00 [7.53]
3.70 [6.96]
2.80 [5.27]
0.66 [1.23]
4.50 [8.22]
4.20 [7.67]
NC
18.5
0.731
0.301
1.35
0.088
0.769
0.458
0.416
27.5
10.9
9.25
9.08
14.9
NC
1.30 [2.30]
3.70 [4.95]
2.70 [6.78]
4.76 [7.94]
NC
NC
NC
NC
NC
4d
4e
4f
5a
5b
5c
5d
5e*
p-Br
p-CF3
5f*
10.0
43.3
—
4.364
—
—
—
—
10 [21.4]
3.20 [8.88]
Cryptolepine*
Amphotericin B*
0.422
6.375
—
—
6.50 [7.03]
a
b
c
Compounds 3a–m were previously reported in Refs. 10,11,13.
Experimental pIC50
Predicted IC50 and pIC50 from the CoMFA model; NC = not cytotoxic at 10
.
lg/mL.
*
These were not included in the training set.
fungal pathogens and an inherent resistance to the Candida
genus.11,12 The original lead compound (1), reportedly operates
through a unique antifungal mechanism of action which differs
from current drugs on the market by intercalating into DNA and
inhibiting topoisomerase II.13 The analogs in this paper are thought
to operate through a similar mechanism of action but with a lower
degree of intercalation into DNA due to the loss of the flat topogra-
phy when the B-ring of the tetracyclic structure is opened. This
hypothesis may explain the resulting lower cytotoxicity compared
to CLP.
The design of 4a analogs was based on the hypothesis that the
distance between the quinolinium and the 3-substituted phenyl
moieties in the 3-substituted benzylthio-1-(5-cyclohexylpen-
tyl)quinolin-1-ium iodide (4a) scaffold can be exploited to improve
potency and decrease toxicity. The introduction of a methylene
group was found to produce an optimum chain length since further
increase in chain length led to a decrease in anti-cryptococcal
activity.14 In addition, variations in the electronic and hydrophobic
Table 2
Summary of the CoMFA analysis
Statistical parameter
CoMFA model
Cross-validated regression co-efficient, q2
# Of components
0.815
4
0.976
0.112
Non cross-validated regression co-efficient, r2
Standard error of estimate (SEE)
Contribution of key parameters
Steric
Electrostatic
0.766
0.234
against C. neoformans were correctly predicted as shown in Table 3
and Figure 4.
A library of 3-(substituted) phenylthio quinolinium iodides (3)
has shown potential as a new antifungal chemotype demonstrating
low cytotoxicity and high potency against a broad spectrum of

7196
S. Bolden et al. / Bioorg. Med. Chem. 21 (2013) 7194–7201
Table 3
Compounds in the test set, their IC50 and pIC50 values against C. neoformans used in the validation of the CoMFA model
R
I
N
(CH2)5
R =
S
R1
4g-q
aCompound
R1
Exp IC50
(l
M) (Cn)
pIC50 Exp
Pred IC50
(lM) (Cn)
pIC50 Pred
D
(Exp ꢀ Pred) IC50
Cytotoxicity IC50 (nM)
4g
4h
4i
4j
4k
4l
4m
4n
4o
4p
p-OH
p-t-Bu
o-F
m-F
p-F
o-OCH3
m-OCH3
p-OCH3
o-Br
9.036
0.883
0.948
0.711
0.677
0.623
0.606
2.153
1.132
0.360
5.044
6.054
6.023
6.148
6.169
6.205
6.217
5.667
5.946
6.443
4.027
0.887
1.258
1.741
0.622
1.757
0.568
2.173
0.997
0.273
5.395
6.052
5.900
5.759
6.206
5.755
6.245
5.663
6.001
6.564
0.351
0.002
0.123
0.389
0.037
0.450
0.028
0.004
0.055
0.121
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
m-Br
4q
p-Br
0.369
6.432
0.267
6.573
0.141
NC
a
Detailed synthesis of compounds in this table are being published elsewhere. NC = not cytotoxic at 10 lg/mL.
properties of substituents on the A-ring would result in changes in
biological activity which can also be exploited to improve drug-like
properties. The synthesis and evaluation of the resulting com-
pounds against C. neoformans is reported (Table 3) and has pro-
vided the basis of the validation of the model.
cyclohexylpentyl group was attached to the nitrogen atom and a
benzyl group was introduced onto the sulfur atom for compounds
in the 3-(substituted) benzylthio quinolinium iodide series (4a–q)
and the carbon atom types in the quinolinium ring were manually
set to aromatic atom types with a +1 charge on the nitrogen. Once
built, charges for the compounds were assigned with MMFF94 and
minimized by Powell’s method and the Tripos force field as imple-
mented in SYBYL X (1.3), terminating with a maximum gradient of
0.05 kcal molꢀ1 Å.15,16 As expected, this approach resulted in the
minimized compounds adopting the correct geometry of the core
structure, that is, the quinolinium ring remained flat during the
minimization process. After obtaining the common core, the rest
of the training set substituted compounds were built from the
common core structure.
The minimized compounds were added to a molecular database
and aligned using a rigid fit of the common substructure in the
training set molecules.17 Compounds that were out of alignment
were adjusted using torsions about the single bond between the
sulfur atom and the benzylic carbon. After torsion adjustments
were made, the resulting compounds were aligned with the data-
base replacing previous poses (Fig. 3). The quality of the alignment
of the training set along with activity diversity are among the most
important factors in creating a statistically sound CoMFA model
with predictive capabilities.18,19
2. Methods
2.1. Dataset
A training set of 23 compounds was used to generate the CoM-
FA model. The training set includes compounds from three scaf-
folds: the phenylthioether (3), benzylthioether (4), sulfoxide (5)
ring-opened analogs of cryptolepine and consists of the most po-
tent pharmacophore groups found during the optimization of the
lead compound (Fig. 2). The pIC50 activity data, originally reported
in l lM for compounds that inhibited C.
g/mL11,12 and converted to
neoformans, had a range of at least 3 log units that provided a start-
ing point in the development of an alignment hypothesis.
2.2. Building aromatic quaternary compounds and structure
alignment in SybylÒ
At the beginning of this study, it was discovered that there was
no representative atom type for a quaternary aromatic nitrogen
atom in the Sybyl software [SYBYL X (1.3)] and thus, it was impos-
sible to build the structure of the salt form of cryptolepine and its
derivatives in Sybyl. All attempts to find suitable representations of
the quaternary aromatic nitrogen atoms were unsuccessful. Thus,
building the structures in the training set was accomplished by
extracting cryptolepine (1) from the crystal structure of DNA inter-
calated by cryptolepine (PDB code: 1K9G) to provide the most real-
istic nitrogen atom representation.4 The nitrogen atom at position
10 of CLP was replaced with sulfur and ring B was opened. The qua-
ternary aromatic nitrogen atom at position 5 of CLP structure was
represented as an sp2 hybridized nitrogen. Subsequently, the
2.3. CoMFA descriptor
The CoMFA steric and electrostatic fields were generated from
an active set of compounds that were placed in a 3D grid. At each
grid point, the steric and electrostatic energy was calculated for
each compound using a probe atom (C.3 with a +1 charge). The cut-
off value of 30 kcal/mol eliminated dominant steric and electro-
static energies. The CoMFA method used the partial-least squares
(PLS) method to predict activity from the energy values at the grid
points and the PLS method correlates the CoMFA fields with the
activity values.10,16 The models with cross-validated q2 >0.5 are
R2
N
R
N
(CH2)5
R
N
R =
R2=
I
I
I
R1
R1
(CH2)5
S
O
S
S
R1
5
3
4
Figure 2. 3-Substituted quinolinium salt scaffolds that make up the compounds used in the CoMFA model.

S. Bolden et al. / Bioorg. Med. Chem. 21 (2013) 7194–7201
7197
2.4. Test set
A test set of 11 compounds was generated from poses of the
corresponding training set compounds, minimized and aligned
using a rigid fit of the common substructure. The test set com-
pounds were synthesized and their biological activities are shown
in Table 3. To determine the validity of the CoMFA model obtained,
the experimental activity values were plotted against the predicted
activity values (Fig. 4) and the correlation coefficient was calcu-
lated using a Prism software.20
2.5. Chemistry
The syntheses of compounds 3a–m in the training set were pre-
viously reported.11,12 To obtain the rest of the compounds in the
training and test set (4a–f), 3-iodoquinoline (6) was required as
the starting material and was obtained by refluxing 3-bromoquin-
oline in the presence of CuI, NaI and N,N0-dimethylethylamine in
1,4-dioxane under N2. A mixture of 3-iodoquinoline, substituted
phenyl-methanethiol, CuI and ethylene glycol, in 2-propanol was
stirred under microwave irradiation to give substituted 3-(benzyl-
thio)quinolines. Green chemistry was employed as the resulting 3-
(substituted benzylthio) quinolines were each alkylated with (5-
iodopentyl) cyclohexane in H2O under microwave irradiation to
give substituted 3-(benzylthio)-1-(5-cyclohexylpentyl)quinolin-1-
ium iodides (4a–f). The synthesis of the sulfoxides, 5a–d and the
compounds in the test set (4g–q) are being reported elsewhere
(Scheme 1).
Figure 3. Alignment of structures in the training set.
Predicted vs Experimental pIC50 , Cn
Test Set Compounds
7.0
6.5
6.0
5.5
5.0
4.5
5.0
5.5
6.5
7.0
Expt pI6C.050
3. Results
Figure 4. Plot of CoMFA predicted pIC50 versus experimental pIC50 against Cn for
the test set.
3.1. CoMFA analysis
The results from the LOO CoMFA analysis are given in Tables 1–
3. The cv q2 was found to be 0.815 with four components, the non-
cv r2 was 0.976, and the SEE was 0.112. The steric contribution was
76.6% of the variance while the electrostatic contribution explains
23.4%. The predicted and experimental biological activities of the
training set compounds (pIC50) are also recorded in Table 1.
indicative of a good predictive model. Cross-validation analysis
was completed with SAMPLES turned-off and column filtering set
to 2.0 kcal molꢀ1 to speed up the analysis. The generation of statis-
tically sound CoMFA models included, at least 3 log units of biolog-
ical activity, a good alignment, and a common substructure that
has the same conformation in all compounds. In addition, torsional
angles of the side chains were free to be adjusted to allow for
superimposition as much as possible.
3.2. Synthesis of compounds 4a–f
The CoMFA descriptor, a 3D descriptor that uses PLS to avoid
over-prediction, combines the many variables including steric
and electrostatic energies at the grid points from the training set
compounds into bins that are represented by a few compo-
nents.18,19 It is desirable that, the number of components should
be limited to at most four for a data set. The leave-one out (LOO)
cross-validation (cv) method pulls out one of the training set com-
pounds, generates a new model, and then predicts the activity of
each of the compounds pulled out to ensure that the results of
the COMFA model are predictive for compounds that are not in
the training set. After several different alignments, the CoMFA
model that generated the best statistics was determined by the
highest q2, the lowest standard error of estimate (SEE) and the few-
est number of components which was then used to produce the fi-
nal model. The best model yielded a cv q2 of 0.815, a SEE of 0.113,
and four components (Table 2). The CoMFA calculation for the cv q2
is found in Eq. 1, where Ypredicted, Yactual, Yobserved and Ymean are the
The identification of substituted 3-(benzylthio)-1-cyclohexyl-
pentylquinolin-1-ium salts as a target for synthesis derived from
the observation that opening the B ring of 5-methylbenzo[4,5]thi-
eno[3,2-b]quinolin-5-ium iodide (2) and replacing the methyl
group with a 5-cyclohexylpentyl group resulted in compounds
with increased potency and reduced toxicity compared to the title
compound.11,12 The selection of 5-cyclohexylpentyl moiety as an
optimal group was based on our previous work that investigated
a homologous series of alkyl groups.9 Other than the use of new
synthetic strategies, that is, microwave synthesis and alkylation
in water, the synthesis of the compounds reported here was
uneventful.
3.3. Validation of the CoMFA model
3D-QSAR approach has been used as an aid in the design of po-
tent anti-cryptococcal agents based on the structure of the lead
compound, 3-phenylthioquinolinium scaffold. Such studies are
based on the general principle that semi-superimposable com-
pounds may have similar but different biological activities.15–18
Several CoMFA models have been generated on a set of compounds
with biological activities spread over 3 log units. In the correlation
graph Figure 4, the predicted and actual pIC50 values are provided,
predicted, actual, observed, and mean values of the pIC50 activity
P
data. The
ðYpredicted ꢀ YactualÞ is the predictive sum of squares
(PRESS). The COMFA model with the fewest number of components
provided the lowest PRESS value.
P
2
ðYpredicted ꢀ Yactual
Þ
q2 ¼ 1 ꢀ
ð1Þ
P
2
ðYobserved ꢀ Ymean
Þ

7198
S. Bolden et al. / Bioorg. Med. Chem. 21 (2013) 7194–7201
R1
S
R1
Br
I
S
c
a
b
N
I
N
N
N
(CH2)4
7
4
5
6
Scheme 1. Synthesis of 3-(substituted benzylthio)quinoline (7). Reagents and conditions: (a) CuI, NaI, dioxane, CH3NHCH2CH2NHCH3, reflux under N2, 110 °C, 48 h; (b)
substituted phenylmethanethiol, CuI, Cs2CO3, HOCH2CH2OH, i-PrOH, N2, MWAS, 170 °C, 15 min; (c) C6H11(CH2)4CH2–I, H2O, MWAS, 170 °C, 15 min.
Figure 5. Contour maps with aligned training set compounds.
each point on the graph representing a compound, and points in
the upper right area being the most active. Compounds with the
highest and lowest pIC50 activities were examined in the steric
and electrostatic contour maps and the effect of changing func-
tional groups and positions around the phenyl ring A were ex-
plored to provide insight into how the various structural entities
contribute to activity.
Figure 7. Contour map with least active compound.
contour that favors steric bulk and represents the most potent mol-
ecule in the training set.
Also upon inspection of the electrostatic contours, there is a
large red area surrounding the electronegative chloro substituent
in the para position of the phenyl ring. This is consistent with
the fact that substitution in the p-position enhances activity and
4. Discussion
electron withdrawing groups (+
r
) increase activity as compared
to electron donating groups (ꢀ
r
). Thus, together the steric and
4.1. CoMFA contour map analysis
electrostatic contour maps provide information about the position
and type of functional groups that are required for potency and by
exploring these 3D spaces with new compounds in silico can lead
to new discoveries of more potent inhibitors.
CoMFA analysis generates a color-coded contour map that de-
picts regions in 3D space where changes in the steric and electro-
static fields of a compound correlate strongly with changes in its
biological activity (Figs. 5 and 6). The contours of the steric map
(Fig. 5) are shown in yellow and green where greater values of bio-
logical activity are correlated with more bulk near green and less
bulk near yellow. In addition, the electrostatic map (Fig. 5) is
shown in red and blue where more positive charge near blue and
more negative charge near red are favorable for increased biologi-
cal activity. In Figure 6, the contours include a large green and
small yellow colored contours in the plane of the benzylthio side
chain. The p-chloro substituent 4c, is surrounded by a green
The least active compounds are from the sulfoxide series (5).
Compound 5a with a para fluoro substituent on the phenyl ring
is embedded in the CoMFA contour map shown in Figure 7. The
map displays a large green contour slightly out of plane with the
small 4-fluoro group on the phenylthio moiety. Inspection of the
electrostatic contour map shows that there are large and small
red contours and a small blue contour near the phenylthio moiety
but little else to explain the observed SAR. There are no clear indi-
cations in this pose as to why the sulfoxides are inactive and any
suggestions here would be considered as pure speculation.
4.2. Structure–activity relationship
The results of the biological evaluation of the compounds sug-
gest that 3-(benzylthio)-1-(5-cyclohexylpentyl)quinolin-1-ium
group constitutes the pharmacophore for the 4a–q series since
the 1-(5-cyclohexylpentyl)quinolin-1-ium moiety by itself does
not produce activity.9 In this manuscript, the electronic and hydro-
phobic space around the phenyl ring of the benzylthio moiety was
explored and indicates that functional groups with positive sigma
and increasing pi values increase potency and especially when
placed at the p-position. Oxidation of the sulfur directly attached
to the quinolinium ring (3a–m) to a sulfoxide (5a–f), such as might
occur during metabolism in vivo, attenuates activity.
It is unclear whether the attenuation of activity observed with
the sulfoxide has any relation to the electronic effect on the
Figure 6. Contour maps with the most active compound.

S. Bolden et al. / Bioorg. Med. Chem. 21 (2013) 7194–7201
7199
(CH2)5
(CH2)5
N
F3C
F3C
N
tPSA: 3.01
CLogP: 4.2343
tPSA: 20.08
CLogP: 2.28575
S
S
O
Figure 8. Estimate of the physicochemical characteristics of a thioether versus a sulfoxide.
quinolinium scaffold. However, estimates of Clog P and tPSA for a
typical sulfide and its corresponding sulfoxide (Fig. 8), suggest sig-
nificant decrease in Clog P (4.2–2.3) and an increase in tPSA (3.01–
20.1). Given that both parameters correlate well with passive
molecular transport through membranes and, hence allow the pre-
diction of transport properties of drugs across bio-membranes,21 it
is tempting to suggest that the decrease in activity from the thio-
ether to sulfoxide may be related to the ability of the latter to cross
biological membranes.
This study has led to the confirmation of substituted 1-(5-cyclo-
hexylpentyl)-3-{[(substituted)benzyl]-thio}quinolin-1-ium iodide
as a viable scaffold for the design and synthesis of novel anticryp-
tococcal agents. An approach to obtaining an atom type for quater-
nary aromatic nitrogen has been demonstrated and used in
building appropriate structures for this CoMFA study. A predictive
CoMFA model was obtained with a cross-validated q2 of 0.81 and r2
of 0.98. The model was subsequently validated by predicting 11
designed analogs which were synthesized, screened and the result-
ing anticryptococcal activities were shown to have a significant
correlation with that predicted by the model (R = 0.82). Substitu-
tion on the benzyl group and especially at the para position with
(0.049 g, 0.259 mmol), Cs2CO3 (1.69 g, 5.17 mmol), ethylene glycol
(0.321 g, 5.17 mmol) in 2-propanol (5 mL) and heated using micro-
wave irradiation at 170 °C for 15 min under N2. After cooling, aque-
ous NH4Cl (10 mL) was added to quench the reaction, followed by
extraction with EtOAc and water then washed with brine (10 mL),
and dried over anhydrous Na2SO4. The solvent from the combined
organic fractions was removed in vacuo and the residue was puri-
fied by Flash chromatography (12 g silica column) using a 10%
EtOAc:Hexane mobile phase, which provided the pure 3-(substi-
tuted benzylthio) quinoline as oils.
5.1.2.1. 3-(Benzylthio)quinoline, 7a.
Yield 77.1%; 1H NMR
(CDCl3): d 8.78 (s, 1H), 8.04 (d, 1H, J = 8.7 Hz), 7.98 (s, 1H), 7.70–
7.66 (m, 3H), 7.52 (t, 1H, J = 6.0 Hz), 7.29–7.26 (m, 4H), 4.19 (s, 2H).
5.1.2.2. 3-((2-Chlorobenzyl)thio)quinoline, 7b.
Yield 70.0%;
1H NMR (CDCl3): d 8.78 (s, 1H), 8.06 (d, 1H, J = 9.0 Hz), 7.98 (s,
1H), 7.72–7.69 (m, 2H), 7.53 (t, 1H, J = 8.4 Hz), 7.26–7.17 (m, 4H),
4.14 (s, 2H).
5.1.2.3. 3-((4-Chlorobenzyl)thio)quinoline, 7c.
Yield 50.5%;
increasing pi and positive
r
values enhance potency and combined
1H NMR (CDCl3): d 8.78 (s, 1H), 8.05 (d, 1H, J = 8.7 Hz), 7.98 (s,
1H), 7.72–7.70 (m, 1H), 7.69–7.66 (m, 1H), 7.45 (t, 1H, J = 9.0 Hz),
7.26–7.25 (m, 2H), 7.23–7.18 (m, 2H), 4.14 (s, 2H).
with their low cytotoxicity, hints at 3-(benzylthio)-1-(5-cyclo-
hexylpentyl)quinolin-1-ium scaffold constituting a new chemo-
type which can further be exploited to obtain analogs with
higher potency, low cytotoxicity and overall better therapeutic
anti-cryptococcal profile.
5.1.2.4. 3-((3-Methylbenzyl)thio)quinoline, 7d.
Yield 73.5%;
1H NMR (CDCl3): d 8.79 (s, 1H), 8.06 (d, 1H, J = 8.7 Hz), 7.95 (s,
1H), 7.66–7.61 (m, 2H), 7.52–7.46 (m, 1H), 7.18–7.13 (m, 1H),
7.04–7.08 (m, 3H,), 4.13 (s, 2H), 2.15 (s, 3H).
5. Experimental section
5.1. Chemistry
5.1.2.5. 3-((4-Methylbenzyl)thio)quinoline, 7e.
Yield 71.6%;
1H NMR (CDCl3): d 8.78 (s, 1H), 8.05 (d, 1H, J = 8.4 Hz), 7.99 (s,
1H), 7.68–7.63 (m, 2H), 7.54–7.49 (m, 1H), 7.17 (s, 2H,), 7.08 (d,
2H, J = 7.8 Hz), 4.16 (s, 2H), 2.30 (s, 3H).
The melting points were determined in °C on an Electrothermal
MEL-TEMP 3.0 device without correction. 1H NMR spectra of inter-
mediates and final products in CDCl3, DMSO-d6, or CD3OD were re-
5.1.2.6.
7f.
3-((4-(Trifluoromethyl)benzyl)thio)quinoline,
corded on
a Varian 300 MHz Mercury NMR Spectrometer.
Yield 55.7%; 1H NMR (CDCl3): d 8.79 (s, 1H), 8.06 (d, 1H,
Chemical shifts relative to TMS and the internal standard are given
in d (ppm) and J-values are recorded in Hertz. Elemental analyses
were carried out by Atlantic Microlab, Inc., Norcross, GA, and were
within 0.4% of the theory unless otherwise noted. All reagents and
solvents were purchased from Sigma–Aldrich, Fisher Scientific or
Alfa Aesar and were used without further purification. Reactions
were monitored by analytical thin layer chromatography (TLC) car-
ried out on Sigma–Aldrich TLC plates coated with F254 silica gel.
Purified intermediates and final products showed one spot.
J = 8.4 Hz), 7.98 (s, 1H), 7.73–7.67 (m, 2H), 7.57–7.52 (m, 1H),
7.37 (d, 2H, J = 8.1 Hz), 7.04–6.98 (m, 2H), 4.21 (s, 2H).
5.1.3. General procedure for the synthesis of 3-[(substituted)
benzylthio]-1-(5-cyclohexyl-pentyl) quinolin-1-ium iodide, 4a–
f
5-Iodopentyl cyclohexane (0.16 g, 0.572 mmol) was added to a
well-stirred solution of 3-(substituted benzylthio)quinoline, 7a–f
(0.381 mmol) in H2O (5 mL) and subjected to microwave irradia-
tion at 170 °C for 15 min. After cooling to room temperature, EtOAc
(10 mL) was added to the microwave reaction vial and the top or-
ganic fraction was collected. The organic layer was then sonicated
until a yellow salt crystallized out of solution, the resulting crude
product was then vacuum filtered using the solvents EtOAc, fol-
lowed by Et2O giving the product 3-(substituted benzylthio)-1-
(5-cyclohexypentyl)quinolin-1-ium iodide, 4a–f.
5.1.1. Procedure for the synthesis of 3-iodoquinoline, 6
The key intermediate, 3-iodoquinoline was obtained from the
commercially 3-bromoquinoline using a literature method previ-
ously utilized in our lab.7 1H NMR (CDCl3): d 9.03 (d, 1H, J =
2.4 Hz), 8.54–8.53 (m, 1H), 8.08–8.04 (m, 1H), 7.76–7.69 (m, 2H),
7.59–7.53 (m, 1H).
5.1.2. General procedure for the synthesis of 3-[(substituted)
benzylthio]quinoline, 7a–f
Substituted phenylmethanethiol (2.59 mmol) was added to a
stirred solution of 3-iodoquinoline (0.794 g, 3.11 Hzmmol), CuI
5.1.3.1.
iodide, 4a.
3-(Benzylthio)-1-(5-cyclohexylpentyl)quinolin-1-ium
Yield 58%, mp 108–110 °C; 1H NMR (DMSO-d6):
d 9.59 (s, 1H), 9.22 (s, 1H), 8.52 (d, 1H, J = 9.0 Hz), 8.31 (d, 1H,

7200
S. Bolden et al. / Bioorg. Med. Chem. 21 (2013) 7194–7201
J = 5.1 Hz), 8.18–8.12 (m, 1H), 8.01–7.96 (m, 1H), 7.41 (d, 2H,
J = 7.35 Hz), 7.34–7.21 (m, 3H), 4.96 (t, 2H, J = 7.5 Hz), 4.55 (s,
2H), 2.01–1.81 (m, 2H), 1.71–1.53 (m, 5H), 1.51–1.25 (m, 4H),
1.21–1.01 (m, 6H), 0.92–0.70 (m, 2H). Anal. Calcd for C27H34INS:
C, 61.01; H, 6.45; N, 2.64. Found: C, 60.94; H, 6.62; N, 2.61.
to 96-well microplates. Microbial suspensions were diluted in Sab-
ouraud Dextrose broth to afford desired colony forming units/mL.
After adding microbial cultures to the samples affording a final vol-
ume of 200 lL and final test concentration starting with 20 lg/mL,
plates were read at 530 nm prior to and after incubation using the
Biotek Powerwave XS plate reader (Bio-Tek Instruments, Vermont).
Growth (saline only), solvent, and blank (media only) controls
were included on each test plate. The drug control amphotericin
B (ICN Biomedicals, Ohio) was included in each assay. IC50s (con-
centrations that afford 50% inhibition relative to controls) were cal-
culated using XLfit 4.2 software (IDBS, Alameda, CA) using fit
model 201.
5.1.3.2. 3-((2-Chlorobenzyl)thio)-1-(5-cyclohexylpentyl)quino-
lin-1-ium iodide, 4b.
Yield 17.2%; mp 110–112 °C; 1H NMR
(DMSO-d6) d 9.64 (s, 1H), 9.27 (s, 1H), 8.54 (d, 1H, J = 8.92 Hz),
8.32 (dd, 1H, J = 1.45, 8.28 Hz), 8.19 (ddd, 1H, J = 1.51, 6.99,
8.80 Hz), 8.04–7.97 (m, 1H), 7.47 (ddd, 2H, J = 1.74, 6.16,
7.54 Hz), 7.36–7.20 (m, 2H), 4.98 (t, 2H, J = 8.78 Hz), 4.59 (s, 2H),
1.95–1.82 (m, 2H), 1.70–1.53 (m, 6H), 1.43–1.19 (m, 3H), 1.13
(m, 6H), 0.90–0.69 (m, 2H). Anal. Calcd for C27H33INSCl: C, 57.30;
H, 5.88; N, 2.47. Found: C, 57.17; H, 5.77; N, 2.49.
6.2. Cytotoxicity assay
In vitro cytotoxicity was determined against mammalian kid-
ney fibroblast (VERO) cells. The assay was performed in 96-well
tissue culture-treated microplates and compounds were tested
up to a highest concentration of 10 mg/mL as described earlier.23
In brief, cells (25,000 cells/well) were seeded to the wells of the
plate and incubated for 24 h. Samples were added and plates were
again incubated for 48 h. The number of viable cells was deter-
mined by the Neutral Red dye assay. IC50 values were determined
from dose curves of growth inhibition versus concentration. Doxo-
rubicin was used as a positive control, while DMSO was used as the
negative (vehicle) control.
5.1.3.3. 3-((4-Chlorobenzyl)thio)-1-(5-cyclohexylpentyl)quino-
lin-1-ium iodide, 4c.
Yield 59.0%, mp 102–104 °C; 1H NMR
(DMSO-d6): d 9.57 (s, 1H), 9.24 (s, 1H), 8.52 (d, 1H, J = 9.0 Hz),
8.35–8.29 (dd, 1H, J = 1.2, 8.4 Hz), 8.19–8.14 (m, 1H), 8.02–7.97
(m, 1H), 7.44–7.40 (m, 2H), 7.41–7.35 (m, 2H), 4.98 (t, 2H,
J = 9.0 Hz), 4.54 (s, 1H), 1.99–1.79 (m, 2H), 1.69–1.48 (m, 6H),
1.45–1.21 (m, 4H), 1.20–1.00 (m, 6H), 0.90–0.70 (m, 2H). Anal.
Calcd for C27H33ClINS: C, 57.30; H, 5.88; N, 2.47. Found: C, 57.35;
H, 5.81; N, 2.58.
5.1.3.4. 1-(5-Cyclohexylpentyl)-3-((3-methylbenzyl)thio)quino-
lin-1-ium iodide, 4d.
Yield 5.4%; mp 100.4–102.3 °C; 1H
Acknowledgments
NMR (DMSO-d6): d 9.60 (s, 1H), 9.23 (s, 1H), 8.52 (d, 1H,
J = 9.3 Hz), 8.31 (d, 1H, J = 7.2 Hz), 8.19–8.14 (m, 1H), 7.99 (t, 1H,
J = 7.5 Hz), 7.23–7.15 (m, 3H), 7.06–7.04 (m, 1H), 4.99 (t, 2H,
J = 7.5 Hz), 4.52 (s, 2H), 2.23 (s, 3H), 1.93–1.93 (m, 2H), 1.69–1.66
(m, 5H), 1.31–1.28 (m, 4H), 1.14–1.15 (m, 6H), 0.87–0.76 (m,
2H). Anal. Calcd for C28H36INS: C, 61.64; H, 6.65; N, 2.57. Found:
C, 61.76; H, 6.81; N, 2.63.
We acknowledge research support from the National Institutes
of Health, National Institute of Allergy and Infectious Diseases, Re-
search Centers at Minority Institutions (RCMI) Grant number G12
RR 03020, and Title III Grant to Florida A&M University. This re-
search was also supported in part by the Pharmaceutical Research
Center NIH/NCRR 1C06-RR12512-01 Grant. One of us, S.B. is grate-
ful for financial support from the AFPE. We thank Dr. Wang Zhang,
NMR facility manager responsible for instrumentation for the gen-
eration of NMR spectra of compounds in this paper, Mrs Barbara
Bricker, for proof reading the manuscript and Ms. Marsha Wright
for antifungal testing. Antifungal testing was supported by the
NIH, NIAID, Division of AIDS, Grant No. AI 27094.
5.1.3.5. 1-(5-Cyclohexylpentyl)-3-((4-methylbenzyl)thio)quino-
lin-1-ium iodide, 4e.
Yield 56.0%, mp 100–102 °C; 1H NMR
(DMSO-d6): d 9.57 (s, 1H), 9.21 (s, 1H), 8.51 (d, 1H, J = 9.0 Hz),
8.30 (d, 1H, J = 8.4 Hz), 8.18–8.12 (m, 1H), 8.01–7.96 (m, 1H),
7.31–7.26 (m, 2H), 7.12–7.08 (m, 2H), 4.98 (t, 2H, J = 8.7 Hz), 4.50
(s, 2H), 2.22 (s, 3H), 2.01–1.83 (m, 2H), 1.75–1.55 (m, 6H), 1.48–
1.22 (m, 4H), 1.20–1.05 (m, 5H), 0.91–0.70 (m, 2H). Anal. Calcd
for C28H36INS: C, 61.64; H, 6.65; N, 2.57. Found: C, 61.72; H,
6.76; N, 2.66.
References and notes
1. Kaplan, J. E.; Benson, C.; Holmes, K. H.; Brooks, J. T.; Pau, A.; Masur, H. MMWR
Recomm. Rep. 2009, 58, 1.
2. Sarmiento, G. P.; Vitale, R. G.; Afeltra, J.; Moltrasio, G. Y.; Moglioni, A. G. Eur. J.
Med. Chem. 2011, 46, 101.
3. Barrett, A. G. M.; Doubleday, W. W.; Hamprecht, D.; Kasdorf, K.; Tustin, G. J.;
White, A. J. P.; Williams, D. J. Chem. Commun. (Camb) 1997, 1693.
4. Kathiravan, M. K.; Salake, A. B.; Chothe, A. S.; Dudhe, P. B.; Watode, R. P.; Mukta,
M. S.; Gadhwe, S. Bioorg. Med. Chem. 2012, 20, 5678.
5. (a) Kumar, E. V.; Etukala, J. R.; Ablordeppey, S. Y. Mini-Rev. Med. Chem. 2008, 8,
538; (b) Ablordeppey, S. Y.; Hufford, C. D.; Borne, R. F.; Dwuma-Badu, D. Planta
Med. 1990, 56, 416; (c) Mardenborough, L. G.; Fan, P. C.; Ablordeppey, S. Y.;
Nimrod, A.; Clark, A. M. Med. Chem. Res. 1999, 9, 118; (d) Ablordeppey, S. Y.;
Fan, P.; Li, S.; Clark, A. M.; Hufford, C. D. Bioorg. Med. Chem. 2002, 10, 1337.
6. Lisgarten, J. N.; Coll, M.; Portugal, J.; Wright, C. W.; Aymami, J. Nat. Struct. Biol.
2002, 9, 57.
5.1.3.6.
1-(5-Cyclohexylpentyl)-3-((4-(trifluoro-
Yield 18.9%,
methyl)benzyl)thio)quinolin-1-ium iodide, 4f.
mp 126–128 °C; 1H NMR (DMSO-d6): d 9.59 (s, 1H), 9.26 (s, 1H),
8.53 (d, 1H, J = 8.4 Hz), 8.30 (d, 1H, J = 8.4 Hz), 8.17 (t, 1H,
J = 7.5 Hz), 8.03–7.97 (m, 1H), 7.66 (d, 2H, J = 8.7 Hz), 7.63 (d, 2H,
J = 8.7 Hz), 4.96 (t, 2H, J = 7.2 Hz), 4.64 (s, 2H), 1.96–1.80 (m, 2H),
1.70–1.50 (m, 5H), 1.4–1.25 (m, 4H), 1.2–1.0 (m, 6H), 0.90–0.70
(m, 2H). Anal. Calcd for C28H33F3INS: C, 56.09; H, 5.55; N, 2.34.
Found: C, 56.34; H, 5.56; N, 2.40.
7. Zhu, X. Y.; Mardenborough, L. G.; Li, S.; Khan, A.; Zhang, W.; Fan, P.; Jacob, M.;
Khan, S.; Walker, L.; Ablordeppey, S. Y. Bioorg. Med. Chem. 2007, 15, 686.
8. Mazu, T. K.; Etukala, J. R.; Zhu, X. Y.; Jacob, M. R.; Khan, S. I.; Walker, L. A.;
Ablordeppey, S. Y. Bioorg. Med. Chem. 2011, 19, 524.
9. (a) Ablordeppey, S. Y.; Fan, P.; Clark, A. M.; Nimrod, A. Bioorg. Med. Chem. 1999,
7, 343; (b) Mardenborough, L. G.; Zhu, X. Y.; Fan, P.; Jacob, M. R.; Khan, S. I.;
Walker, L. A.; Ablordeppey, S. Y. Bioorg. Med. Chem. 2005, 13, 3955.
10. Mazu, T. K.; Etukala, J. R.; Jacob, M. R.; Khan, S. I.; Walker, L. A.; Ablordeppey, S.
Y. Eur. J. Med. Chem. 2011, 46, 2378.
6. Biological activity
6.1. Antifungal testing
C. neoformans ATCC 90113 was obtained from the American
Type Culture Collection (Manassas, VA). Susceptibility testing
was performed using a modified version of the CLSI methods as
described by Samoylenko et al.22 Briefly, DMSO solutions of
samples were serially diluted in saline and transferred in duplicate
11. Boateng, C. A.; Eyunni, S. V.; Zhu, X. Y.; Etukala, J. R.; Bricker, B. A.; Ashfaq, M.
K.; Jacob, M. R.; Khan, S. I.; Walker, L. A.; Ablordeppey, S. Y. Bioorg. Med. Chem.
2011, 19, 458.

S. Bolden et al. / Bioorg. Med. Chem. 21 (2013) 7194–7201
12. Boateng, C. A.; Zhu, X. Y.; Jacob, M. R.; Khan, S. I.; Walker, L. A.; Ablordeppey, S. 18. Lu, P.; Wei, X.; Zhang, R. Eur. J. Med. Chem. 2010, 45, 3413.
7201
Y. Eur. J. Med. Chem. 2011, 46, 1789.
19. Clark, M.; Cramer, R. D.; Vanopdenbosch, N. J. Comput. Chem. 1989, 10, 982.
13. Dassonneville, L.; Bonjean, K.; De Pauw-Gillet, M. C.; Colson, P.; Houssier, C.;
Quetin-Leclercq, J.; Angenot, L.; Bailly, C. Biochemistry 1999, 38, 7719.
14. Bolden, S.; Zhu, X. Y.; Etukala, J. R.; Boateng, C.; Mazu, T.; Flores-Rozas, H.;
Jacob, M. R.; Khan, S. I.; Ablordeppey, S. Y. Eur. J. Med. Chem. 2013. under
review.
15. (a) Cramer, R. D.; Patterson, D. E.; Bunce, J. D. J. Am. Chem. Soc. 1988, 110, 5959;
(b) SYBYL-X 1.2, T. I., 1699 South Hanley Rd., St. Louis, Missouri, 63144, USA.
16. Murugesan, V.; Prabhakar, Y. S.; Katti, S. B. J. Mol. Graph. Model. 2009, 27, 735.
17. Carrieri, A.; Muraglia, M.; Corbo, F.; Pacifico, C. Eur. J. Med. Chem. 2009, 44,
1477.
20. GraphPad. Correlation Analysis, was Performed Using GraphPad Prism Version
5
for Mac OSX, Graphpad Software, San Diego California USA, http://
www.graphpad.com.
21. Ertl, P.; Rohde, B.; Selzer, P. J. Med. Chem. 2000, 43, 3714.
22. Samoylenko, V.; Jacob, M. R.; Khan, S. I.; Zhao, J.; Tekwani, B. L.; Midiwo, J. O.;
Walker, L. A.; Muhammad, I. Nat. Prod. Commun. 2009, 4, 791.
23. Mustafa, J.; Khan, S. I.; Ma, G.; Walker, L. A.; Khan, I. A. Lipids 2005, 40, 375.