Synthesis, antifungal activity and QSAR study of 2-arylhydroxynitroindoles

Article abstract of DOI:10.1016/j.ejmech.2011.07.008

A series of 2-arylhydroxynitroindoles were prepared and tested for antifungal activity in vitro. The preliminary bioassays indicated that some compounds are comparable to the commercial fungicide (triadimefon). To further explore the structure-activity re

Full text of DOI:10.1016/j.ejmech.2011.07.008

European Journal of Medicinal Chemistry 46 (2011) 4374e4382
Contents lists available at ScienceDirect
European Journal of Medicinal Chemistry
journal homepage: http://www.elsevier.com/locate/ejmech
Original article
Synthesis, antifungal activity and QSAR study of 2-arylhydroxynitroindoles
,
a
b
Galina V. Kokurkina a, Mikhail D. Dutov a , Svyatoslav A. Shevelev , Sergey V. Popkov ,
*
Alexey V. Zakharovc, Vladimir V. Poroikovc
a Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, 47 Leninsky prosp, 119991 Moscow, Russian Federation
b Mendeleev University of Chemical Technology of Russia, 125047 Moscow, Russian Federation
c Institute of Biomedical Chemistry of Russian Academy of Medical Sciences, 119121 Moscow, Russian Federation
a r t i c l e i n f o
a b s t r a c t
Article history:
A series of 2-arylhydroxynitroindoles were prepared and tested for antifungal activity in vitro. The
preliminary bioassays indicated that some compounds are comparable to the commercial fungicide
(triadimefon). To further explore the structureeactivity relationships, the data set of the seventeen
structures and their quantitative values of antifungal activities were used for QSAR modeling. Based on
the obtained QSAR models four new chemical compounds were designed, synthesized and tested in
fungicidal assays. Reasonable correspondence between the experimental and predicted values of anti-
fungal activity was observed.
Received 28 April 2011
Received in revised form
29 June 2011
Accepted 4 July 2011
Available online 28 July 2011
Keywords:
Ó 2011 Elsevier Masson SAS. All rights reserved.
2-Arylhydroxynitroindoles
Cyclization of ketoximes
Fungicidal activity
QSAR
1. Introduction
2. Results and discussion
Substituted 2-arylindoles are known to be biologically active
molecules. They inhibit aldose reductase(H), which is important for
diabetes treatment [1], combat against multidrug resistance strains
of Staphilococcus aureus [2], and in the form of 2-pyridylindoles
inhibit the micelial growth of some fungi [3].
Furthering our researches on the conversion of aromatic
explosives (TNT, TNB, etc.) and their transformation to multipur-
pose synthons for organic chemistry [4,5] we developed a method
for the synthesis a number of new 2-arylindoles with hydroxyl
and nitro groups in 4- and 6-positions, respectively [6]. As follows
from the results of the initial studies, some of them have high
fungicidal activity dramatically exceeding that of the conventional
commercial fungicideetriadimefon [7]. This research deals with
the synthesis of substituted 2-aryl-4-hydroxy-6-nitroindoles,
study of their fungicidal properties and elucidation of the struc-
2.1. Chemistry
For broadening a scope of 2-aryl-4-hydroxy-6-nitroindoles with
a view to investigate an impact of substituents in the aryl ring on
the fungicidal properties we used the synthetic method (Scheme 1
[6]) having been developed by us earlier.
At first sight, the generation of indoles 3 seems unexpected.
However it can be explained on the basis of the cyclization mech-
anism of O-arylketoximes to benzo[b]furans [8].
In case of O-(3-amino-5-nitrophenyl)ketoximes 2, the [3,3]-
sigmatropic rearrangement (2 / C) may equally probable occur
both to the ortho-position to NO2 (Scheme 2, a) and to the ortho-
position to NH2 (Scheme 2, b) with the generation of corresponding
intermediates C0 and C00 and, further on, intermediates D0 and D00.
For intermediates D0, cyclization proceeds in a common way to
produce 6-amino-4-nitrobenzo[b]furans 4 (D0 / E0 / F0, Scheme
2, a). As regards intermediates D00, intramolecular addition is
likely to be implemented to the C]NHþ2 bond of the NH2 group
rather than of the OH group (D00 / G) followed by the ammonium
ion split-off and generation of 4-hydroxy-6-nitroindoles 3 (G / H,
Scheme 2, b).The OH group here can not compete with the NH2
group (NH2 is much more nucleophilic than unionized OH),
otherwise 4-amino-6-nitrobenzofurans would be formed, what
actually does not happen.
tureefungicidal activity relations within
a series of such
compounds.
* Corresponding author. Tel.: þ7 499 1355339; fax: þ7 499 1355328.
E-mail address: dutov@ioc.ac.ru (M.D. Dutov).
0223-5234/$ e see front matter Ó 2011 Elsevier Masson SAS. All rights reserved.
doi:10.1016/j.ejmech.2011.07.008

G.V. Kokurkina et al. / European Journal of Medicinal Chemistry 46 (2011) 4374e4382
4375
NO2
NO2
procedure [9e11] with six phytopathogenic fungi from different
taxonomic classes: Sclerotinia sclerotiorum (S.s.), Fusarium oxy-
sporum (F.o.), Fusarium moniliforme (F.m.), Bipolaris sorokiniana
(B.s.), Rhizoctonia solani (R.s.), and Venturia inaequalis (V.i.) (Table 1).
The effect of the tested compounds on the mycelium radial growth
in the potato-saccharose agar with widely used fungicide tri-
adimefon as a reference compound was measured in a concentra-
NO2
R1
R1
N
N
O2N
NO2
O2N
O
H2N
O
R2
R2
2a-k
R2
1a-k
NO2
OH
tion 30
mg . The tests in the concentration range
mLꢀ1
R1
R1
R2
1e100
m
g mLꢀ1 let evaluate EC50 for the two most potent fungicidal
substances (Table 2).
O
N
H2N
O2N
H
The first members (3a and 3b) in the sequences of 2-aryl-4-
hydroxy-6-nitroindoles displayed the strongest fungicidal action.
Their potency exceeds those of the commercial fungicide (tri-
adimefon) with respect to all phytopathogens e they inhibit the
mycelium growth in the majority of fungi at concentration
4a-k
3a-k
R1=CH3, R2=H(a); R1=R2=H(b); R1=H, R2=2-Cl(c); R1=H, R2=2,4-Cl2(d);
H
C
N
R1=H, R2=4-OH(e); R1=
R2=4-F(f);
2
N
N
R1=H, R2=4-Br(g); R1=H, R2=4-CF3(h); R1=H, R2=4-F(i); R1=H, R2=4-OCH3(j);
R1=H, R2=2-OCH3(k).
30
a
m
g mLꢀ1. The introduction of halogen into the aryl ring led to
considerable activity decrease, for the exception of 2-
chlorophenyl-substituted indole 3c. This compound equivalent in
activity to its non-substituted analog 3b, whereas its impact on the
scab pathogen of apple tree V. inaequalis is twice lower than that of
3b. The modification of the structure of the most active 4-hydroxy-
6-nitro-2-phenylindole by alkylation showed that antifungal action
decreased to medium values in the transition to N-methylation
product 8b, mean while N-(4-chloro-benzyl) derivative 8d exerted
just moderate activity. The fungicidal properties disappear almost
completely in the transition to O-alkylation products 5a, 6a and 6b,
what allows assuming that 4-hydroxyl groups play an important
pharmacophoric role for fungicidal 2-aryl-6-nitroindoles 3 at large.
The introduction of the 1,2,4-triazolylethyl moiety to the indole 3rd
position should be admitted as a failing modification option e here
fungicidal activity declines to moderate. It is worth pinpointing that
only indole products of heterocyclization of ketoximes 2aej exhibit
fungicidal activity, whereas substituted benzofurans 4aej, e.g.,
benzofuran 4b, do not actually affect the mycelium growth in
pathogenic fungi.
Scheme 1.
To assess the molecular structure influence on fungicidal
activity we studied a possibility of synthesizing 2-aryl-4-hydroxy-
6-nitroindole derivatives alkylated by oxygen and nitrogen. As
found for compound 3a, O-alkylation of the 4-hydroxyl group runs
first, and only after that N-alkylation of the nitrogen indole atom
occurs. All further attempts to demethylate the methoxy group
using various reagents (HBr, AlCl3, HI, BBr3, PhSH) in order to afford
indole 7a did not yield positive results: either the reaction does not
run or it is accompanied by resinification (Scheme 3).
Indole 3b behaves in a similar manner. In this case, in a pure
form we managed to isolate merely a bismethylation product.
As an alternative, we looked at a possibility to synthesize
hydroxynitroindoles substituted by nitrogen from N-monoalkyl-
substituted derivatives of ketoximes 7bed through the Scheme 4.
It appeared that in this case reductive alkylation proceeded with
a good yield, and at the same time the C]N bond of the oxime
moiety was not impacted. Of note is that the alkylation conditions
for formaldehyde and for aromatic aldehydes differ significantly.
The rearrangement of oximes 7 proceeds by analogy with non-
substituted oximes 2aek, though indole yields are much lower.
2.3. Quantitative structureeactivity relationships (QSAR)
2.3.1. Data sets
The data set of the seventeen structures and their quantitative
values of antifungal activities were used for QSAR modeling with
the end-points similar to those published in the paper [12]. The
2.2. Fungicidal activity testing and discussion
The 2-aryl-4-hydroxy-6-nitroindoles were tested in vitro for the
fungicidal activity according to a very common conventional
end-points were presented in percent of inhibition at 30
m
g mLꢀ1
concentration for six different taxonomic classes of fungi: B.s., F.m.,
F.o., R.s., S.s., V.i. Thus, six different modeling sets were obtained.
Each sets correspondent to the appropriate end-point was
randomly divided onto the training and test sets in the ratio of 70%
and 30%, respectively. The training set was used for creation of
QSAR models and test set for the assessment of external predictive
accuracy. QSAR models were developed using GUSAR program,
which based on Multilevel and Quantitative Neighborhoods of
Atoms (MNA, QNA) descriptors [13,14] and self-consistent regres-
sion (SCR) algorithm [15].
NO2 R
R
NO2
NO2
NO2
R
R
Ar
Ar
Ar
+
(a)
Ar
+
-NH4
+
NH2
NH2
OH
D'
+
O
H2N
O
NH3
O
H2N
H+
H2N
H2N
C'
E'
F', 4
NH2
CH2R
N
O2N
O
Ar
H+
2
R=H,CH3
NH2 R
R
OH
OH
R
OH
R
Ar
Ar
Ar
+
Ar (b)
+
-NH4
+
NH2
NH2
NH2
D''
+
N
H
N
O
O2N
O2N
NH3
O2N
O2N
H
H, 3
2.3.2. QSAR modeling on the basis of QNA descriptors
C''
G
QNA descriptors are P and Q values calculated for each atom of
molecule. The calculation of P and Q values is based on the
Scheme 2.
OH
OCH3
OCH3
CH3
OH
CH3
CH3
CH3
N
H
N
N
CH3
N
CH3
O2N
O2N
O2N
O2N
H
3a
7a
5a
6a
Scheme 3.

4376
G.V. Kokurkina et al. / European Journal of Medicinal Chemistry 46 (2011) 4374e4382
NO2
NO2
NO2
H
N2H4*H2O, FeCl3*6H2O
1.RCHO
2.NaBH4
N
CH3
N
CH3
N
CH3
O2N
O
H2N
O
R
N
O
Cact.,MeOH
H
1b
2b
7b-d
OH
NO2
N
O
O2N
HN
R
R
8b-d
9b-d
R = H(b), Ph(c), 4-ClPh(d).
Scheme 4.
connectivity matrix (C) and the standard values of ionization
potential (IP) and electron affinity (EA) of atoms in a molecule [13].
The estimation of a target property of chemical compound is
calculated as the mean value of the function of P and Q values of the
atoms of a molecule in QNA descriptors’ space. We have proposed
to use two-dimensional Chebyshev polynomials for approximation
of the function of P and Q values. So, the independent regression
variables are calculated as average values of particular two-
dimensional Chebyshev polynomials of P and Q values for mole-
cule atoms.
QNA descriptors and their polynomial transformations do not
provide information on the shape and volume of a molecule
although this information may be important for determination of
the structureeactivity relationships. Therefore, these parameters
were added to the variables obtained from Chebyshev polynomials.
Topological length of a molecule is the maximal distance calculated
in the number of bonds between any two atoms (including
hydrogen). The volume of a molecule is the sum of each atom’s
volume.
parameters of Chebyshev polynomials. The final QSAR model is the
consensus of built in this way different QNA based models.
2.3.3. QSAR modeling on the basis of biological activity profiles
prediction using MNA descriptors
GUSAR allows creating QSAR models based on biological activity
profiles of chemical compounds. Each chemical compound repre-
sented as a list of MNA descriptors, which are used as input
parameters [14] for obtaining the prediction of biological activity
profiles. PASS algorithm is used for calculation of this profile
[15e17]. The results of PASS prediction are given as a list of bio-
logical activities, for which the difference between probabilities to
be active (Pa) and to be inactive (Pi) was calculated. The activities
from the list of predicted biological activities are randomly selected
as the input independent variables for regression analysis to obtain
different QSAR models. The latest version of PASS (10.1) predicts
4130 kinds of biological activity with the mean prediction accuracy
about 95%. The list of predictable biological activities currently
includes 501 pharmacotherapeutic effects (e.g., Antihypertensive,
Hepatoprotectant, Nootropic, etc.), 3295 mechanisms of action
(e.g., 5 Hydroxytryptamine antagonist, Acetylcholine M1 receptor
agonist, Cyclooxygenase inhibitor, etc.), 57 adverse and toxic effects
(e.g., Carcinogenic, Mutagenic, Hematotoxic, etc.), 199 metabolic
terms (e.g., CYP1A inducer, CYP1A1 inhibitor, CYP3A4 substrate,
etc.) 49 transporter proteins (e.g., P-glycoprotein 3 inhibitor,
Nucleoside transporters inhibitors) and 29 activities related to gene
expression (e.g., TH expression enhancer, TNF expression inhibitor,
VEGF expression inhibitor).
GUSAR algorithm uses three randomly chosen procedures for
generation of different QSAR models based on QNA descriptors: (a)
calculation of QNA descriptors for all atoms or for those molecule
atoms, which have two or more immediate neighbors; (b) changing
of the coefficient before the connectivity matrix (c) changing of
Table 1
Fungicidal activity of some synthesized compounds.
g mLꢀ1
)
ꢁ
N
Mycelium growth inhibition, % (C ¼ 30
m
2.3.4. Self-consistent regression
V.i.
R.s.
F.o.
F.m.
B.s.
S.s.
GUSAR uses self-consistent regression for building of (Q)SAR
models. Self-consistent regression (SCR) is based on the regularized
least-squares method [13,18]. Unlike the stepwise regression and
other methods of combinatorial search, the initial SCR model
includes all regressors. The basic result of application of SCR
method is a removal of variables, which are worse for the
description of an appropriate value [18]. The number of the final
variables in QSAR equation selected after the self-consistent
regression procedure is significantly less comparing to the
number of the initial variables. However, as was shown in [13] the
3a
3b
3c
3d
3e
3f
3g
3h
3i
3k
4b
5a
6a
6b
8b
8d
93
89
44
26
20
2
15
53
60
26
16
2
12
21
46
12
41
48
70
65
42
100
100
100
36
38
31
11
82
96
8
87
88
88
25
27
28
12
71
58
15
9
11
8
7
56
27
34
63
73
91
60
100
100
100
54
39
30
21
84
73
36
5
89
100
100
22
18
52
5
74
35
20
3
7
12
7
77
11
83
95
83
87
71
100
100
100
29
19
17
14
70
48
20
7
5
0
8
23
2
3
13
4
7
8
7
23
51
18
54
71
84
88
79
77
34
91
89
100
100
66
Table 2
Fungicidal activity (EC50) of 2-phenyl-4-hydroxy-6-nitroindoles 3a and 3b.
10a
10b
10c
10d
51
94
51
54
47
Compound
EC50
,
m
g mLꢀ1
V.i.
R.s.
F.o.
F.m.
B.s.
S.s.
8.65
17.2
6.18
Triadimefon
3a
3b
15.4
16.9
20.0
5.86
11.2
20.6
18.0
21.5
3.25
3.48
6.84
2.41
13.0
26.6
11.0
V.i. e Venturia inaequalis, R.s. e Rhizoctonia solani, F.o. e Fusarium oxysporum, F.m. e
Fusarium moniliforme, B.s. e Bipolaris sorokiniana, S.s. e Sclerotinia sclerotiorum.
Triadimefon

G.V. Kokurkina et al. / European Journal of Medicinal Chemistry 46 (2011) 4374e4382
4377
compounds fell in AD of the model. In this study we used the
threshold for AD equal to 0.7.
2.3.7. Consensus modeling
The final predicted value is estimated by taking into account
a weighted average of the predicted values from each obtained
QSAR model (QSAR models provide the predictions that are within
the respective applicability domains). The predicted value obtained
from each developed model is weighted on similarity value calcu-
lated during the evaluation of applicability domain. General
scheme of the algorithm combined the result of QSAR modeling on
the basis of QNA descriptors and PASS predicted biological activity
profiles, is represented in Fig. 1.
Fig. 1. QSAR modeling workflow.
2.3.8. Interpretation of the obtained QSAR models
final model contains a set of variables, correctly representing the
Simultaneously with the estimation of activity value for the
entire structure, GUSAR calculates the contribution of each partic-
ular functional group into the activity. At the user’s display these
contributions are reflected by different colors: “green” e no
significant contribution; “red” e increase in the activity; “blue” e
decrease in the activity. This provides the hints to medicinal
chemist concerning the further modification of the structure. If she/
he wants to increase the activity, it is necessary to modify the
groups reducing the activity. If she/he wants to decrease the activity
(e.g., for toxicity), it is necessary to modify the groups elevating the
activity. In Fig. 2 we present an example of structure, where “[”
marks the groups elevating the activity; and “Y” marks the groups
reducing the activity.
existing relationship.
2.3.5. Nearest neighbor’s correction
It is well known that the combining global and local models for
non-congeneric sets one can improve the quality of QSAR models
[19]. We used the experimental data of the nearest neighbors (NN)
for the correction of prediction values obtained from the regression
model. The correction value was estimated by taking an average of
the 3 chemicals values in the training set that are the most similar
to the chemical under prediction. The similarity of any chemical
compounds’ pairs is estimated as Pirson’s coefficient calculated in
the space of independent variables obtained after SCR. The average
value of the nearest neighbors was averaged with the predicted
value for the test compound calculated by the regression model.
2.3.9. QSAR modeling and validation of antifungal end-points
For each training set of antifungal end-point one hundred QSAR
models were generated. Models that satisfied the following criteria
were considered as acceptable for prediction: I) R2 > 0.6, II)
Q2 > 0.5. Selected models were used for consensus prediction of
appropriate test sets taking into account of applicability domain.
Prediction results and characteristics of models are presented in the
Table 3.
2.3.6. Applicability domain
Three nearest neighbors from the training set are calculated for
each tested chemical compound using a similarity value. Similarity
of two chemical compounds is estimated as Pirson’s coefficient
calculated in the space of independent variables obtained after SCR.
The average similarity of three nearest neighbors is used for
assessment of the applicability domain (AD) of the model. If the
average similarity exceeds a certain threshold then the chemical
compound under prediction falls in AD of the model and vice-versa.
The higher value of the threshold was selected the more similar
R2 values for three antifungal activities exceed 0.80, for two e
0.60 and for one 0.50. For all antifungal activities average error of
prediction is 27%; it means that the obtained models successfully
identify active and inactive compounds in the test sets. All
compounds from the test sets fall in applicability domain of models
for five antifungal end-points. Only BS antifungal end-point was
predicted with coverage 80%.
The obtained QSAR models were used for analysis of atoms’
contribution of chemical compounds from the training set into the
antifungal activity and for selection of fragments with significant
contribution to the activity. It was found that hydroxyl and methyl
groups increase the activity against all six fungi. Nitro group in the
meta-position has a negative influence to antifungal activity
(Fig. 2). According to the analysis it was considered to consider 2-
phenylindole derivates with nitro and hydroxyl groups placed in
Fig. 2. Atom contribution into the antifungal activity.
Table 3
QSAR modeling of antifungal activities results.
Activity name
Number of compounds training set/test set
Number of models
R
2 Training set
Q
2 Training set
R
2 Test set
Coverage, %
RMSE test
B.s.
F.m.
F.o.
R.s.
S.s.
V.i.
12/5
12/5
12/5
12/5
12/5
12/5
4
21
3
20
11
2
0.89
0.89
0.85
0.91
0.89
0.83
0.72
0.77
0.68
0.79
0.79
0.61
0.57
0.80
0.66
0.72
0.81
0.82
80
100
100
100
100
100
35.74
28.01
17
27.58
37.29
20.37
R2 e determination coefficient.
Q2 e determination coefficient calculated for leave-one-out cross validation procedure.
RMSE e root mean square error.

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G.V. Kokurkina et al. / European Journal of Medicinal Chemistry 46 (2011) 4374e4382
4. Experiment
4.1. General remarks
All reagents and solvents were used without further purification
or drying. All reagents were purchased from Acros Organics. The 1H
NMR spectra were recorded by Bruker AM-300. The chemical shifts
were given relative to Me4Si in DMSO-d6, d, ppm, J, Hz. Melting
points of the synthesized compounds were measured on a Boetius
hot stage according to Koffler (heating rate 4 ꢁC minꢀ1).
4.2. General procedure for the synthesis of O-(3,5-dinitrophenyl)
ketoximes 1
Trinitrobenzene (TNB), 0.1 mol (21.3 g), is added to a mixture of
0.1 mol of acetophenoneoxime substituted in an appropriate
manner1and 0.1 mol (13.8 g) of K2CO3 in 1-methyl-2-pyrrolidone
(120 mL). The reaction mixture is heated to 50 ꢁC and stirred at
this temperature until the TNB full conversion (3e8 h). The reaction
mass is poured into 600 mL of water. The precipitate is filtered off,
water-washed and dried. The residue is recrystallized from EtOH.
Reaction time, yields, melting points and 1H NMR spectra of the
synthesized compounds:
4.2.1. 1-(2,4-Dichlorophenyl)ethanone O-(3,5-dinitrophenyl)oxime
Fig. 3. Comparison of the experimental (black line) and predicted (gray line) anti-
fungal activities for compounds 10a (1e6), 10b (7e12), 10c (13e18), 10d (19e24). 1e6,
7e12, 13e18 and 19e24 are activities against B.s., F.m., F.o., R.s., S.s. and V.i., respectively.
Average RMSE values calculated for each activity vary from 12 to 25; for each
(1d)
4 h, yield 84%, m.p. ¼ 170e171 ꢁC.
1H NMR:
d
7.58e7.70 (m, 2H), 7.82 (d, 1H,J ¼ 1.8 Hz), 8.42 (d, 2H,
compound e from 12 to 28. All values are given in percent of inhibition at 30 m
g mLꢀ1
J ¼ 1.9 Hz), 8.55 (t, 1H, J ¼ 2.0 Hz). Anal. Found %: C, 45.12; H, 2.11; N,
concentration of the compound.
11.70. Calcd. for C14H9Cl2N3O5 %: C, 45.43; H, 2.45; N, 11.35.
4.2.2. 1-(4-Hydroxyphenyl)ethanone O-(3,5-dinitrophenyl)oxime
the ortho- and para-position. Several dozen structures were
designed by chemists in silico, and based on the GUSAR estimation
four structures 10aed (Fig. 3) were selected for synthesis [20] and
tested on their antifungal activity against B.s., F.m., F.o., R.s., S.s., V.i.
The observed values of antifungal activity for compounds 10aed
reasonably corresponds to those calculated on the basis of QSAR
models (Fig. 3). All four compounds match to the applicability
domain of the obtained QSAR models.
(1e)
6 h, yield 49%,m.p. ¼ 179e180 ꢁC.
1H NMR:
d
6.90 (d, 2H, J ¼ 8.7 Hz), 7.73 (d, 2H, J ¼ 8.7 Hz), 8.43 (d,
2H, J ¼ 1.9 Hz), 8.50 (t, 1H, J ¼ 2.0 Hz), 10.03 (s, 1H). Anal. Found %: C,
53.26; H, 3.76; N, 13.09. Calcd. for C14H11N3O6 %: C, 53.00; H, 3.49;
N, 13.24.
4.2.3. 1-(4-Fluorophenyl)-4-(1H-1,2,4-triazol-1-yl)butan-1-one O-
(3,5-dinitrophenyl)oxime (1f)
Compounds 10c and 10d were found to be the most active
against all six fungi. All compounds shown high inhibition activity
5 h, yield 58%, m.p. ¼ 152e154 ꢁC.
at 30 m
g mLꢀ1 concentration for R.s. The best predicted results were
1H NMR:
d 2.09e2.14 (m, 2H), 2.98e3.04 (m, 2H), 4.29e4.34 (m,
obtained for compound 10c (RMSE ¼ 12). This compound shows
the potent inhibition activity against B.s., F.m. and R.s. Three anti-
fungal activities F.m., R.s. and V.i. were predicted better than B.s. and
S.s. These results correspond to accuracy of test sets prediction in
terms of RMSE obtained during validation of QSAR models (see
Fig. 3). Thus, application of validated QSAR models allowed finding
new chemical compounds with high antifungal activity.
2H), 7.34e7.40 (m, 2H); 7.86e7.91(m, 2H), 7.98 (s, 1H), 8.40e8.41
(m, 2H), 8.52e8.53 (m, 2H). Anal. Found %: C, 52.32; H, 3.38; N,
20.63. Calcd. for C18H15FN6O5 %: C, 52.18; H, 3.65; N, 20.28.
4.2.4. 1-(4-Bromophenyl)ethanone O-(3,5-dinitrophenyl)oxime
(1g)
3 h, yield 95%,m.p. ¼ 175e176ꢁ C.
1H NMR:
d
7.74 (d, 2H, J ¼ 8.5 Hz), 7.83 (d, 2H, J ¼ 8.6 Hz), 8.47 (d,
2H, J ¼ 2.1 Hz), 8.54 (t, 1H, J ¼ 2.0 Hz). Anal. Found %: C, 44.57; H,
3. Conclusions
2.31; N, 10.78. Calcd. for C14H10BrN3O5 %: C, 44.23; H, 2.65; N, 11.05.
A series of hydroxynitroindoles possessing fungicidal activity
were prepared by acid-catalyzed cyclization of ketoximes 2 and 7.
Among them, indoles 3aec and 3h,i have the highest fungi toxicity
and surpass the commercial fungicide (triadimefon) with respect to
4.2.5. 1-[4-(Trifluoromethyl)phenyl]ethanone O-(3,5-dinitrophenyl)
oxime (1h)
4 h, yield 48%, m.p. ¼ 149e151 ꢁC.
1H NMR:
d
2.50 (s, 3H), 7.89 (d, 2H, J ¼ 8.3 Hz), 8.07 (d, 2H,
all phytopathogens e at concentration 30 m
g mLꢀ1 they substan-
J ¼ 8.2 Hz), 8.47(d, 2H, J ¼ 1.9 Hz), 8.52 (t, 1H, J ¼ 2.0 Hz). Anal.
Found %: C, 48.63; H, 2.51; F, 15.18; N, 11.42. Calcd. for C15H10F3N3O5
%: C, 48.79; H, 2.73; F, 15.44; N, 11.38.
tially inhibit the mycelium growth in all fungi. 4-hydroxyl groups
play an important pharmacophoric role for fungi toxic 2-aryl-6-
nitroindoles 3. Based on the QSAR estimates, from several dozen
designed structures we selected and synthesized four chemical
compounds. Two compounds 10c and 10d appeared to be the most
active against all six fungi in comparison with triadimefon.
1
For compound 1f, corresponding 4-azobutyrophenone was prepared by the
known procedure [21].

G.V. Kokurkina et al. / European Journal of Medicinal Chemistry 46 (2011) 4374e4382
4379
4.2.6. 1-(4-Fluorophenyl)ethanone O-(3,5-dinitrophenyl)oxime (1i)
4 h, yield 76%, m.p. ¼ 163e164 ꢁC.
1H NMR:
d
5.98 (s, 2H), 6.89 (t, 1H, J ¼ 2.0 Hz), 7.13 (t, 1H,
J ¼ 2.1 Hz), 7.16 (t,1H, J ¼ 2.0 Hz), 7.86 (d, 2H, J ¼ 8.2 Hz), 8.02 (d, 2H,
J ¼ 8.1 Hz). Anal. Found %: C, 53.46; H, 3.32; N, 12.54. Calcd. for
C15H12F3N3O3 %: C, 53.10; H, 3.57; N, 12.39.
1H NMR:
d 2.50 (s, 3H), 7.33e7.40 (m, 2H), 7.91e7.96 (m, 2H),
8.45 (d, 2H, J ¼ 2.0 Hz), 8.52 (t, 1H, J ¼ 2.0 Hz). Anal. Found %: C,
52.43; H, 3.31; N, 13.29. Calcd. for C14H10FN3O5 %: C, 52.67; H, 3.16;
N, 13.16.
4.3.6. 1-(4-Fluorophenyl)ethanone O-(3-amino-5-nitrophenyl)
oxime (2i)
4.2.7. 1-(4-Methoxyphenyl)ethanone O-(3,5-dinitrophenyl)oxime
Yield 87%, m.p. ¼ 136e137 ꢁC.
(1j)
1H NMR:
d
2.44 (s, 3H), 5.95 (s, 2H), 6.90 (t, 1H, J ¼ 1.9 Hz), 7.12(t,
8 h, Yield 71%, m.p. ¼ 179e180 ꢁC.
1H, J ¼ 1.9 Hz), 7.15 (t, 1H, J ¼ 1.9 Hz), 7.30e7.38 (m, 2H), 7.85e7.90
(m, 2H). Anal. Found %: C, 58.38; H, 4.52; N, 14.80. Calcd. for
C14H12FN3O3 %: C, 58.13; H, 4.18; N, 14.53.
1H NMR:
d
3.83 (s, 3H), 7.06 (d, 2H, J ¼ 8.8 Hz), 7.82 (d, 2H,
J ¼ 8.7 Hz), 8.42 (d, 2H J ¼ 2.0 Hz), 8.49 (t, 1H, J ¼ 2.0 Hz). Anal.
Found %: C, 54.06; H, 4.29; N, 12.53. Calcd. for C15H13N3O6 %: C,
54.38; H, 3.96; N, 12.68.
4.3.7. 1-(4-Methoxyphenyl)ethanone O-(3-amino-5-nitrophenyl)
oxime (2j)
Yield 70%, m.p. ¼ 122e123 ꢁC.
4.3. General procedure for the synthesis of O-(3-amino-5-
1H NMR:
d 2.40 (s, 3H), 3.81 (s, 3H), 5.93 (s, 2H), 6.88 (t, 1H,
nitrophenyl)-ketoximes (2)
J ¼ 2.0 Hz), 7.03 (d, 2H, J ¼ 8.8 Hz), 7.10 (t, 1H, J ¼ 1.9 Hz), 7.13 (t, 1H,
J ¼ 1.9 Hz), 7.76 (d, 2H, J ¼ 8.8 Hz). Anal. Found %: C, 59.36; H, 4.78;
N, 13.81. Calcd. for C15H15N3O4 %: C, 59.79; H, 5.02; N, 13.95.
Hydrazine hydrate 10 mL (0.2 mol) was added to a mixture of an
appropriate O-(3,5-dinitrophenyl)ketoxime 1 (0.1 mol), FeCl3$6H2O
(0.13 g, 0.5 mmol), and activated carbon (6 g) in methanol (700 mL).
The reaction mixture was refluxed until the starting dinitro
compound was completely consumed (monitoring by TLC with
CHCl3 as an eluent) and filtered hot. The carbon was washed with
hot methanol (2 ꢂ 50 mL), the filtrate was cooled to 4 ꢁC, and the
precipitate that formed was filtered off.
4.4. General procedure for the synthesis of 4-hydroxy-6-
nitroindoles (3) and 4-amino-6-nitrobenzofurans (4)
An appropriate O-(3-amino-5-nitrophenyl)oxime 2(0.01 mol)
was added to a mixture of ethanol (10 mL) and 36% HCl (10 mL). The
reaction mixture was refluxed 2 h. On cooling to w20 ꢁC, the
precipitate was filtered off and neutralized in water (50 mL) with
aqueous ammonia to weakly basic reaction. The precipitate of 6-
amino-4-nitrobenzofuran 4 was filtered off and dried in vacuo.
The filtrate was evaporated to dryness and the residue was
neutralized in water (50 mL) with aqueous ammonia to weakly
basic reaction. The precipitate of 4-hydroxy-6-nitroindole 3 was
filtered off, recrystallized from a minimum amount of ethanol, and
dried in vacuo.
Yields, melting points and 1H NMR spectra of the synthesized
compounds:
4.3.1. 1-(2,4-Dichlorophenyl)ethanone O-(3-amino-5-nitrophenyl)
oxime (2d)
Yield 65%, m.p. ¼ 151e152 ꢁC.
1H NMR:
d
2.40 (s, 3H), 5.95 (s, 2H), 6.83 (t, 1H, J ¼ 2.0), 7.10e7.12
(m, 2H,), 7.58e7.59 (m, 2H), 7.80 (d,1H, J ¼ 1.8 Hz). Anal. Found %: C,
49.19; H, 3.69; N, 12.09. Calcd. for C14H11Cl2N3O3 %: C, 49.43; H,
3.26; N, 12.35.
Yields, melting points and 1H NMR spectra of the synthesized
compounds:
4.3.2. 1-(4-Hydroxyphenyl)ethanone O-(3-amino-5-nitrophenyl)
oxime (2e)
4.4.1. 2-(2,4-Dichlorophenyl)-6-nitro-1H-indol-4-ol (3d)
Yield 28%, m.p. ¼ 279e281 ꢁC.
Yield 51%, m.p. ¼ 159e162 ꢁC.
1H NMR:
d
7.10 (d, 1H, J ¼ 1.5 Hz), 7.27 (d, 1H, J ¼ 1.5 Hz),
1H NMR:
d
2.39 (s, 3H), 5.91 (s, 2H), 6.85 (t, 1H, J ¼ 1.9 Hz), 6.88
7.58e7.64 (m,1H), 7.76e7.82 (m, 2H), 7.87 (s,1H),10.55 (s,1H),12.16
(s, 1H). Anal. Found %: C, 51.78; H, 2.27; Cl, 22.83; N, 8.32. Calcd. for
C14H8Cl2N2O3 %: C, 52.04; H, 2.50; Cl, 21.94; N, 8.67.
(d, 2H, J ¼ 8.7 Hz), 7.10 (t, 1H, J ¼ 2.0 Hz), 7.14 (t, 1H, J ¼ 2.0 Hz), 7.67
(d, 2H, J ¼ 8.6 Hz), 9.91 (s, 1H). Anal. Found %: C, 58.17; H, 4.79; N,
14.55. Calcd. for C14H13N3O4 %: C, 58.53; H, 4.56; N, 14.63.
4.4.2. 2-(2,4-Dichlorophenyl)-4-nitro-1-benzofuran-6-amine (4d)
Yield 30%, m.p. ¼ 252e253 ꢁC.
4.3.3. 1-(4-Fluorophenyl)-4-(1H-1,2,4-triazol-1-yl)butan-1-one O-
(3-amino-5-nitrophenyl)oxime (2f)
1H NMR:
d
6.04 (s, 2H), 7.16 (d,1H, J ¼ 1.4 Hz), 7.55 (d, 1H,
Yield 38%, m.p. ¼ 97e99 ꢁC.
J ¼ 1.5 Hz), 7.78e7.83 (m, 3H), 7.97e8.00 (m, 1H). Anal. Found %: C,
52.39; H, 2.13; N, 8.49. Calcd. for C14H8Cl2N2O3 %: C, 52.04; H, 2.50;
N, 8.67.
1H NMR:
d 2.03e2.08 (m, 2H), 2.90(m, 2H), 4.29 (m, 2H), 5.98 (s,
2H), 6.85(t, 1H, J ¼ 1.9 Hz), 7.10e7.11 (m, 2H), 7.34 (m, 2H),
7.80e7.85 (m, 2H), 8.0 (s, 1H), 8.52 (s, 1H). Anal. Found %: C, 56.39;
H, 4.24; N, 21.63. Calcd. for C18H17FN6O3 %: C, 56.25; H, 4.46; N,
21.86.
4.4.3. 2-(4-Hydroxyphenyl)-6-nitro-1H-indol-4-ol (3e)
Yield 21%, m.p. ¼ 262e263 ꢁC.
1H NMR:
d
6.92 (d, 2H, J ¼ 8.6 Hz), 7.69 (s, 1H), 7.91 (d, 2H,
4.3.4. 1-(4-Bromophenyl)ethanone O-(3-amino-5-nitrophenyl)
oxime (2g)
J ¼ 8.6 Hz), 8.37 (d, 1H, J ¼ 1.5 Hz), 8.54 (d, 1H, J ¼ 1.6 Hz), 10.16 (s,
1H),11.76 (s,1H). Anal. Found %: C, 62.48; H, 3.36; N,10.21. Calcd. for
C14H10N2O4 %: C, 62.22; H, 3.73; N, 10.37.
Yield 59%, m.p. ¼ 156e158 ꢁC.
1H NMR:
d
2.44 (s, 3H), 5.94 (s, 2H), 6.90 (t, 1H, J ¼ 1.9 Hz),
7.12e7.15 (m, 2H), 7.68e7.79 (m, 4H). Anal. Found %: C, 48.36; H,
4.4.4. 4-(6-Amino-4-nitro-1-benzofuran-2-yl)phenol (4e)
Yield 26%, m.p. ¼ 231e233 ꢁC.
3.60; N, 12.33. Calcd. for C14H12BrN3O3 %: C, 48.02; H, 3.45; N, 12.00.
1H NMR:
d
6.00 (s, 2H), 6.90 (d, 2H, J ¼ 8.3 Hz), 7.32 (d, 1H,
4.3.5. 1-[4-(Trifluoromethyl)phenyl]ethanone O-(3-amino-5-
nitrophenyl)oxime (2h)
J ¼ 1.4 Hz), 7.52 (d,1H, J ¼ 1.6 Hz), 7.60(s,1H), 7.80 (d, 2H, J ¼ 8.4 Hz).
Anal. Found %: C, 62.03; H, 3.56; N,10.48. Calcd. for C14H10N2O4 %: C,
62.22; H, 3.73; N, 10.37.
Yield 59%, m.p. ¼ 151e154 ꢁC.

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4.4.5. 2-(4-Fluorophenyl)-6-nitro-3-[2-(1H-1,2,4-triazol-1-yl)
ethyl]-1H-indol-4-ol (3f)
4.4.14. 2-(4-Methoxyphenyl)-4-nitro-1-benzofuran-6-amine (4j)
Yield 43%, m.p. ¼ 209e210 ꢁC.
Yield 23%, m.p. ¼ 145e147 ꢁC.
1H NMR:
d
3.83 (s, 3H), 5.86 (s, 2H), 7.06 (d, 2H, J ¼ 8.7 Hz), 7.17
1H NMR:
d
4.52e4.53 (m, 2H), 7.31e7.44 (m, 5H), 7.78e7.85 (m,
(d, 1H, J ¼ 1.3 Hz), 7.49 (d, 1H, J ¼ 1.3 Hz), 7.55 (s, 1H), 7.88 (d, 2H,
J ¼ 8.7 Hz). Anal. Found %: C, 63.02; H, 4.48; N, 9.69. Calcd. for
C15H12N2O4 %: C, 63.38; H, 4.25; N, 9.85.
2H), 8.23 (s, 1H), 10.63 (s, 1H), 11.89 (s, 1H).Anal. Found %: C, 58.36;
H, 3.56; F, 5.39; N, 19.23. Calcd. for C18H14FN5O3 %: C, 58.85; H, 3.84;
F, 5.17; N, 19.07.
4.5. Procedure for the synthesis of (5a), (6a,b)
4.4.6. 2-(4-Fluorophenyl)-4-nitro-3-[2-(1H-1,2,4-triazol-1-yl)
ethyl]-1-benzofuran-6-amine (4f)
Dimethylsulfate (0.01 mol or 0.03 mol for the synthesis of 6) was
added to a mixture of an appropriate indole 3 (0.01 mol) and
potassium carbonate (0.03 mol) in dry DMF (10 mL). The mixture
was stirred for 2 h at ambient temperature and next, poured in
water. The precipitate was collected, washed with water, and dried
in vacuo.
Yield 30%, m.p. ¼ 220e222 ꢁC.
1H NMR:
d 3.37e3.40 (m, 2H), 4.29e4.36 (m, 2H), 5.90 (s, 2H),
7.10 (d, 1H, J ¼ 1.5 Hz), 7.28e7.36 (m, 2H), 7.44 (d, 1H, J ¼ 1.6 Hz),
7.53e7.55 (m, 2H), 7.77 (s, 1H), 8.19 (s, 1H). Anal. Found %: C, 58.32;
H, 3.69; N, 19.11. Calcd. for C18H14FN5O3 %: C, 58.85; H, 3.84;
N, 19.07.
Yields, melting points and 1H NMR spectra of the synthesized
compounds:
4.4.7. 2-(4-Bromophenyl)-6-nitro-1H-indol-4-ol (3g)
Yield 21%, m.p. ¼ 298e300 ꢁC.
4.5.1. 4-Methoxy-3-methyl-6-nitro-2-phenyl-1H-indole (5a)
Yield 78%, m.p. ¼ 234e235 ꢁC.
1H NMR:
d
7.72 (d, 2H, J ¼ 8.3 Hz), 7.97(d, 2H, J ¼ 8.2 Hz), 8.01 (d,
1H, J ¼ 1.5 Hz), 8.41 (d, 1H, J ¼ 1.4 Hz), 8.56 (s, 1H), 10.52 (s, 1H),
11.79 (s, 1H). Anal. Found %: C, 50.61; H, 2.78; N, 8.39. Calcd. for
C14H9BrN2O3 %: C, 50.47; H, 2.72; N, 8.41.
1H NMR:
d 2.57 (s, 3H), 3.99 (s, 3H), 7.19e7.25(m, 3H), 7.29 (d,1H,
J ¼ 1.7 Hz), 7.56e7.69 (m, 2H), 7.95(d, 1H, J ¼ 1.9 Hz). Anal. Found %:
C, 68.43; H, 5.33; N, 9.87. Calcd. for C16H14N2O3 %: C, 68.07; H, 5.00;
N, 9.92.
4.4.8. 2-(4-Bromophenyl)-4-nitro-1-benzofuran-6-amine (4g)
Yield 27%, m.p. ¼ 276e277 ꢁC.
4.5.2. 4-Methoxy-1,3-dimethyl-6-nitro-2-phenyl-1H-indole (6a)
Yield 86%, m.p. ¼ 132e133 ꢁC.
1H NMR:
d
5.94 (s, 2H), 7.17 (d, 1H, J ¼ 1.3 Hz), 7.52 (d, 1H,
J ¼ 1.3 Hz), 7.68 (d, 2H, J ¼ 8.4 Hz), 7.74 (s, 1H), 7.89 (d, 2H,
J ¼ 8.3 Hz). Anal. Found %: C, 50.62; H, 2.93; N, 8.69. Calcd. for
C14H9BrN2O3 %: C, 50.47; H, 2.72; N, 8.41.
1H NMR:
d 2.34(s, 3H), 3.66(s, 3H), 3.98(s, 3H), 7.16e7.27 (m, 3H),
7.34 (d, 1H, J ¼ 1.3 Hz), 7.46e7.58 (m, 2H), 8.13 (d,1H, J ¼ 1.6 Hz).
Anal. Found %: C, 68.46; H, 5.27; N, 9.79. Calcd. for C17H16N2O3 %: C,
68.91; H, 5.44; N, 9.45.
4.4.9. 6-Nitro-2-[4-(trifluoromethyl)phenyl]-1H-indol-4-ol (3h)
Yield 16%, m.p. ¼ 224e226 ꢁC.
4.5.3. 4-Methoxy-1-methyl-6-nitro-2-phenyl-1H-indole (6b)
Yield 83%, m.p. ¼ 106e108 ꢁC.
1H NMR:
d 7.26e7.27 (m, 2H), 7.85e7.88 (m, 3H); 8.10e8.13 (m,
2H), 12.36 (s, 1H). Anal. Found %: C, 55.59; H, 2.46; N, 8.81. Calcd. for
C15H9F3N2O3 %: C, 55.91; H, 2.82; N, 8.69.
1H NMR:
d 3.86 (s, 3H), 4.01 (s, 3H), 6.74 (s, 1H), 7.41(d, 1H,
J ¼ 1.5 Hz), 7.48e7.59 (m, 3H), 7.64e7.66 (m, 2H), 8.22(d,1H,
J ¼ 1.4 Hz). Anal. Found %: C, 68.31; H, 4.73; N, 9.46. Calcd. for
C16H14N2O3 %: C, 68.07; H, 5.00; N, 9.92.
4.4.10. 4-Nitro-2-[4-(trifluoromethyl)phenyl]-1-benzofuran-6-
amine (4h)
Yield 37%, m.p. ¼ 218e221 ꢁC.
4.6. Synthesis of 1-phenylethanone O-[3-(methylamino)-5-
nitrophenyl]oxime (7b)
1H NMR:
d
6.06 (s, 2H), 7.19(d, 1H, J ¼ 1.4 Hz), 7.54 (d, 1H,
J ¼ 1.3 Hz) 7.66 (s, 1H), 7.82 (d, 2H, J ¼ 8.3 Hz), 7.90 (s, 1H), 8.12(d,
2H, J ¼ 8.2 Hz). Anal. Found %: C, 55.66; H, 2.68; N, 8.86. Calcd. for
C15H9F3N2O3 %: C, 55.91; H, 2.82; N, 8.69.
O-(3-Amino-5-nitrophenyl)methylphenylketoxime
(2b)
(0.013 mol) was added to a freshly prepared solution of sodium
methylate (0.064 mol) in methanol (30 mL) containing para form
(0.018 mol). The mixture was stirred for 5 h at ambient tempera-
ture. Next, sodium borohydride (0.013 mmol) was added at inten-
sive stirring and the mixture was refluxed until gas evolving is over.
The reaction was cooled to 20 ꢁC, then 1 M NaOH was added until
pH ¼ 9e10. The precipitate was collected, washed with water, and
dried, and recrystallized from methanol.
4.4.11. 2-(4-Fluorophenyl)-6-nitro-1H-indol-4-ol (3i)
Yield 21%, m.p. ¼ 283e284 ꢁC.
1H NMR:
d
7.07 (d, 1H, J ¼ 1.5 Hz); 7.26 (d, 1H, J ¼ 1.4 Hz),
7.33e7.40 (m, 2H), 7.83 (s, 1H), 7.94e7.96 (m, 2H), 10.40 (s, 1H),
12.15 (s, 1H). Anal. Found %: C, 61.62; H, 3.59; N, 10.52. Calcd. for
C14H9FN2O3 %: C, 61.77; H, 3.33; N, 10.29.
Yield 91%, m.p. ¼ 142e144 ꢁC.
4.4.12. 2-(4-Fluorophenyl)-4-nitro-1-benzofuran-6-amine (4i)
Yield 30%, m.p. ¼ 203e204 ꢁC.
1H NMR:
d
2.45 (s, 3H); 2.75(d, 3H, J ¼ 4.9 Hz), 6.50e6.55 (m,
1H), 6.81 (t, 1H, J ¼ 1.9 Hz), 7.05 (t, 1H, J ¼ 1.9 Hz), 7.21 (t, 1H,
J ¼ 2.0 Hz), 7.49e7.50 (m, 3H), 7.79e7.82 (m, 2H). Anal. Found %: C,
63.41; H, 5.63; N,14.69. Calcd. for C15H15N3O3 %: C, 63.15; H, 5.30; N,
14.73.
1H NMR:
d
5.92 (s, 2H), 7.18 (d, 1H, J ¼ 1.7 Hz), 7.30e7.37 (m, 2H),
7.52 (d, 1H, J ¼ 1.8 Hz), 7.68 (s, 1H), 7.96e8.04 (m, 2H). Anal. Found
%: C, 61.42; H, 3.17; N, 10.27. Calcd. for C14H9FN2O3 %: C, 61.77; H,
3.33; N, 10.29.
4.7. General procedure for the synthesis of (7c,d)
4.4.13. 2-(4-Methoxyphenyl)-6-nitro-1H-indol-4-ol (3j)
Yield 30%, m.p. ¼ 256e257ꢁC.
A mixture of P-(3-amino-5-nitrophenyl)methylphenylketoxime
(0.013 mol) and an appropriate benzaldehyde (0.018 mol) in acetic
acid (11 mL) was stirred at ambient temperature for 30 min. To this
sodium boronhydride (0.013 mol) was added slowly. The mixture
was stirred at ambient temperate for 2 h. Next,1 M NaOH was added
1H NMR:
d
3.82 (s, 3H), 6.97 (d, 1H, J ¼ 1.5 Hz), 7.08(d, 1H,
J ¼ 8.7 Hz), 7.24 (d, 1H, J ¼ 1.7 Hz), 7.81e7.85 (m, 3H), 10.36 (s, 1H),
12.06 (s, 1H). Anal. Found %: C, 63.62; H, 4.02; N, 9.31. Calcd. for
C15H12N2O4 %: C, 63.38; H, 4.25; N, 9.85.

G.V. Kokurkina et al. / European Journal of Medicinal Chemistry 46 (2011) 4374e4382
4381
until pH ¼ 9e10. The precipitate was collected, washed with water,
and dried on the filter, and recrystallized from methanol.
Yields, melting points and 1H NMR spectra of the synthesized
compounds:
1H NMR:
d
4.43 (d, 2H, J ¼ 5.8 Hz), 7.13e7.18 (m, 2H), 7.23e7.28
(m, 1H), 7.33e7.51 (m, 6H), 7.59 (d, 1H, J ¼ 1.5 Hz), 7.69 (s, 1H),
7.90e7.93 (m, 2H). Anal. Found %: C, 66.39; H, 3.53; Cl, 9.23; N, 7.52.
Calcd. for C21H15ClN2O3 %: C, 66.58; H, 3.99; Cl, 9.36; N, 7.40.
4.7.1. 1-Phenylethanone O-[3-(benzylamino)-5-nitrophenyl]oxime
4.8. Bioassays of fungicidal activites
(7c)
Yield 69%, m.p. ¼ 150e151 ꢁC.
The antifungal activities were tested according to the conven-
tional procedure [9e11] with six phytopathogenic fungi from
different taxonomic classes: S. sclerotiorum (S.s.), F. oxysporum (F.o.),
F. moniliforme (F.m.), B. sorokiniana (B.s.), R. solani (R.s.), and V.
inaequalis (V.i.). The effect of the chemicals on mycelial radial
growth was determined by dissolving them at various concentra-
tion in acetone and suspending aliquots in potato-saccharose agar
at 50 ꢁC to give the required series of concentration
1H NMR:
d
2.42 (s, 3H), 4.37 (d, 2H, J ¼ 5.8 Hz), 6.88 (t, 1H,
J ¼ 2.0 Hz), 7.12e7.14 (m, 2H), 7.18(t, 1H, J ¼ 2.0 Hz), 7.23e7.28 (m,
1H), 7.35 (t, 1H, J ¼ 1.9 Hz), 7.37e7.40 (m, 2H), 7.48e7.50 (m, 3H),
7.75e7.78 (m, 2H). Anal. Found %: C, 69.35; H, 5.11; N, 11.19. Calcd.
for C21H19N3O3 %: C, 69.79; H, 5.30; N, 11.63.
4.7.2. 1-Phenylethanone O-{3-[(4-chlorobenzyl)amino]-5-
nitrophenyl}oxime (7d)
(1e100
mg
mLꢀ1). The final acetone concentration of both
Yield 74%, m.p. ¼ 132e134 ꢁC.
fungicide-containing and control samples was 10 mL Lꢀ1. Petri
dishes containing 15 mL of the agar medium were inoculated by
placing 3-mm fungus-coated discs upside down on the agar
surface. Plates were incubated at 25 ꢁC and radial growth was
measured after 72 h. The mixed medium without sample was used
as the blank control. Three replicates of each test were carried out.
The mycelium elongation diameter (mm) of fungi settlements was
measured after 72 h of culture. The growth inhibition rates were
calculated with the following equation: I ¼ [(DC ꢀ DT)/DC]x100%.
Here I is the growth inhibition rates (%), DC is the control settlement
diameter (mm), and DT is the treatment group fungi settlement
diameter (mm). The results are summarized in Tables 1 and 2.
1H NMR:
d
2.42 (s, 3H), 4.38 (d, 2H, J ¼ 5.8 Hz), 6.86 (t, 1H,
J ¼ 1.9 Hz), 7.12 (t, 1H, J ¼ 1.9 Hz), 7.17e7.20 (m, 2H), 7.38e7.43(m,
4H), 7.47e7.51(m, 3H), 7.75e7.77(m, 2H). Anal. Found %: C, 63.46; H,
4.14; Cl, 9.03; N, 10.38. Calcd. for C21H18ClN3O3 %: C, 63.72; H, 4.58;
Cl, 8.96; N, 10.62.
Compounds 8bed, 9bed were prepared by the same procedure
as for 3, 4.
Yields, melting points and 1H NMR spectra of the synthesized
compounds:
4.7.3. 1-Methyl-6-nitro-2-phenyl-1H-indol-4-ol (8b)
Yield 9%, m.p. ¼ 188e190 ꢁC.
1H NMR:
d
3.82 (s, 3H), 6.75 (s, 1H), 7.31 (d,1H, J ¼ 1.6 Hz),
Acknowledgments
7.49e7.58 (m,3H), 7.62e7.65 (m, 2H), 8.04 (d, 1H, J ¼ 1.5 Hz), 10.47
(s,1H).Anal. Found %: C, 67.32; H, 4.58; N, 10.12. Calcd. for
C15H12N2O3 %: C, 67.16; H, 4.51; N, 10.44.
The authors thank the Russian Foundation for Basic Research
(Grant No 10-03-00623) for financial support.
4.7.4. N-Methyl-4-nitro-2-phenyl-1-benzofuran-6-amine (9b)
Yield 77%, m.p. ¼ 97e99 ꢁC.
References
1H NMR:
d
2.81 (s, 3H), 5.54 (s, 1H), 7.22 (d, 1H, J ¼ 1.6 Hz),
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7.41e7.43 (m,1H), 7.47e7.51 (m,3H), 7.70 (s,1H), 7.92e7.95 (m,2H).
Anal. Found %: C, 67.48; H, 4.93; N, 10.21. Calcd. for C15H12N2O3 %: C,
67.16; H, 4.51; N, 10.44.
4.7.5. 1-Benzyl-6-nitro-2-phenyl-1H-indol-4-ol (8c)
Yield 0.5%, m.p. ¼ 161e163 ꢁC.
1H NMR:
d 5.58 (s, 2H), 6.84 (s, 1H), 6.88e6.90 (m, 2H), 7.19e7.27
(m, 3H), 7.32 (d, 1H, J ¼ 1.6 Hz), 7.45e7.55 (m,5H), 7.90 (d, 1H,
J ¼ 1.5 Hz), 10.58 (s,1H).Anal. Found %: C, 73.61; H, 4.36; N, 8.29.
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4.7.6. 2-N-Benzyl-4-nitro-2-phenyl-1-benzofuran-6-amine (9c)
Yield 79%, m.p. ¼ 183e185 ꢁC.
1H NMR:
d
4.42 (d, 2H, J ¼ 5.8 Hz), 7.13e7.18(m, 2H), 7.23e7.51
(m, 8H), 7.59 (t, 1H, J ¼ 1.5 Hz), 7.69 (s,1H), 7.90e7.92 (m,2H).Anal.
Found %: C, 73.70; H, 4.77; N, 8.32. Calcd. for C21H16N2O3%: C, 73.24;
H, 4.68; N, 8.13.
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4382
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