Synthesis and Quantitative Structure-activity Relationships Study for Arylpropenamide Derivatives as Inhibitors of Hepatitis B Virus Replication

Article abstract of DOI:10.1111/cbdd.12774

A series of new arylpropenamide derivatives containing different aryl groups were synthesized, characterized, and evaluated for their anti-hepatitis B virus (HBV) activities. A new high accuracy QSAR model of arylpropenamide was constructed based on a more completely activities data and calculation parameter. The 2D-QSAR equations, by using DFT and multiple linear regression analysis methods, revealed that higher value of thermal energy (TE) and lower entropy (S^?) increase the anti-HBV activities of the arylpropenamide molecules. Predictive 3D-QSAR models were established by SYBYL multifit molecular alignment rule. The optimum models were all statistically significant with cross-validated and conventional coefficients, indicating that they were reliable enough for activity prediction.

Full text of DOI:10.1111/cbdd.12774

Chem Biol Drug Des 2016
Research Article
Synthesis and Quantitative Structure-activity
Relationships Study for Arylpropenamide Derivatives
as Inhibitors of Hepatitis B Virus Replication
Ma Min1, Jiang Xingjun1, Wang Xueding1,
are nucleoside analogues lamivudine, telbivudine, ente-
cavir, adefovir, and tenofovir (Figure 1) (7–10).
Zou Hao1, Yang Weiqing1, Zhang Yuanyuan1,2
Peng Changrong1,2, Li Zicheng2, Yang Jing1,
Du Quan1 and Ma Menglin1,*
,
Phenylpropenamides, such as AT-61 and AT-130 (Fig-
ure 2) (11–16), were reported as a non-nucleoside class of
inhibitors of HBV replication in cell culture. A series of
phenylpropenamide derivatives (1a–r and 2a–r) with anti-
hepatitis B virus activities were reported by our research
group recently (Figure 2) (17). Their quantitative structure-
activity relationships (QSAR) of phenylpropenamide com-
pound had been studied, parameters for constructing the
QSAR models were showed in Tables S1–S3 and QSAR
equations were listed in Scheme 1.
1Key Lab of Advanced Scientific Computation of Sichuan
Province, School of Science, Xihua University, Chengdu
610039, China
2College of Chemical Engineering, Sichuan University,
Chengdu, 610065, China
*Corresponding author: Ma Menglin, mmlchem@163.com
A series of new arylpropenamide derivatives containing
different aryl groups were synthesized, characterized,
and evaluated for their anti-hepatitis B virus (HBV)
The versatility of QSAR equations I and II, whether they
could be applied to different structural units is a question.
activities.
A new high accuracy QSAR model of
arylpropenamide was constructed based on a more
completely activities data and calculation parameter.
The 2D-QSAR equations, by using DFT and multiple lin-
ear regression analysis methods, revealed that higher
value of thermal energy (TE) and lower entropy (Sө)
increase the anti-HBV activities of the arylpropenamide
molecules. Predictive 3D-QSAR models were estab-
lished by SYBYL multifit molecular alignment rule. The
optimum models were all statistically significant with
cross-validated and conventional coefficients, indicat-
ing that they were reliable enough for activity prediction.
A
series of new arylpropenamide derivatives were
designed with a modified arylpropenamide B ring com-
pared with series 1 and 2 (Figure 2). The activities of new
arylpropenamides were predicted by QSAR equation I and
II, and then they were synthesized, characterized and
evaluated for anti-hepatitis B virus activities. The feasibility
of QSAR equations was verified by comparison with tested
and predicted values. More abundant biological activity
data and quantum chemical calculation parameters could
be gotten via the changement of substituted aromatic
groups and positions, which provided good foundation for
building a more accurate QSAR model based on more
data sources and greater data quantity.
Key words: 2D-QSAR, 3D-QSAR, arylpropenamide, hepatitis
B virus, SYBYL
Received 4 December 2015, revised 16 March 2016 and
accepted for publication 29 March 2016
Experimental
Chemistry
Hepatitis B is a serious disease that do seriously to harm
human health. The asymptomatic hepatitis B virus carriers
are approaching three hundred million people in the world
(1–3). Hepatitis B is a major cause of liver disease world-
wide, ranking as a substantial cause of cirrhosis and hepa-
tocellular carcinoma. In addition to hepatitis B vaccine for
immunization, two main anti-HBV drugs have been
approved for clinical use, namely interferon and nucleoside
drugs (4,5). However, interferon has the higher cost of
treatment and the greater adverse effects (6). The other
current agents approved for the treatment of HBV infection
Thin layer chromatography was performed with Qingdao
Ocean silica gel GF254. Nuclear magnetic resonance (NMR)
spectra were recorded on a Bruker DPX-300 FT NMR spec-
trometer (School of chemical engineering, Sichuan Univer-
1
sity, Sichuan Province, China) at 300 MHz for H and were
referenced to tetramethylsilane (d values are given in ppm
and J-values in Hz). Mass spectra were measured on a Var-
ian CH-5 apparatus. IR spectra were measured acquired on
a Nicolet 380 and obtained by using KBr plates pellet. The
X-ray diffraction data were collected on X’Pert Pro MPD
diffract meter. The synthetic route was shown in Scheme 2.
ª 2016 John Wiley & Sons A/S. doi: 10.1111/cbdd.12774
1

Min et al.
NH2
N
N
N
NH2
N
NH2
N
NH2
N
N
N
N
N
O
O
O
N
O
P
O
N
O
O
O
O
O
N
NH
NH2
OH
O
N
O
O
HO
O
P
OH
N
OH
OH
S
OH
Telbivudine
HO
O
Lamivudine
Entecavir
Adefovir
Tenofovir
Figure 1: Agents for the treatment of hepatitis B infection.
R
A
Ar
O
O
F
O
O
B
X
N
O
Ar: a
: Ph
b
c
: o-CN-Ph
: o-NO2-Ph
Cl
N
O
Br
N
O
X
N
O
HN
d: p-Cl-Ph
g: o-OCH3-Ph h: p-OCH3-Ph i: o-Br-Ph
l:
e: o-CH3-Ph
f: p-CH3-Ph
HN
HN
HN
j
k
: m-Br-Ph
: p-Br-Ph
o-F-Ph
o:3-pyridine
p:3-quinoline q:4-isoquinoline r 2-furan
m:p-F-Ph
n: o-Cl-Ph
R
NO2
1a-r
: X=Br
General structure
AT-61
AT-130
2a-r: X=Cl
Figure 2: Structure of AT-61, AT-130, and our research group reported phenylpropenamide.
General procedure for the preparation of the aryl
carboxamide acetic acid (4a–q)
Series 1:n=18, R2=0.80692, F=31.34498, P<0.0001
According to literature (18), the mixture of substituted ben-
zoic acid or nicotinic acid (33 mmol) and thionyl chloride
(5 mL, 69 mmol) was stirred at 80 °C for 4 h. The reaction
mixture was concentrated in vacuo to give benzoyl or nicoti-
noyl chloride hydrochloride, which was used in following
reaction without purification. Benzoyl or nicotinoyl chloride
hydrochloride was added to the glycine (1.4 g, 19 mmol) in
Series 2: n=18, R2=0.68535, F=16.33582, P< 0.00017
Scheme 1: Our research group reported QSAR equations.
R2
R2
O
O
N
O
O
ii
COOH
iii
N
H
i
OH
O
HN
Y
O
N
CHO
Y
Y
R1
R1
R1
Y
R2
5a-q
R1
3a-q
4a-q
6a-q
7a-q
R2
a: Y=C, R1=m-CH3,
R2=H
j: Y=C, R1=p-NO2, R2=o-F
k: Y=C, R1=p-NO2, R2=o-Cl
b: Y=C, R1=3,5-dimethoxy, R2=H
iv or v
O
c: Y=C, R1=o-NO2,
R2=H
R2=H
R2=H
R2=H
l: Y=N, R1=H,
m: Y=N, R1=H,
n: Y=N, R1=H,
o: Y=N, R1=H,
p: Y=N, R1=H,
q: Y=N, R1=H,
R2=p-OCH3
d: Y=C, R1= -NO ,
R2=H
N
O
X
p
e: Y=C, R1=o-Cl, 2
f: Y=C, R1=p-CH3,
g: Y=C, R1=o-NO2,
h: Y=C, R1=o-NO2,
R2=o-F
R2=o-CH3
R2=o-Cl
R2=p-Br
HN
Y
R2=p-F
Scheme 2: Synthesis of arylpropenamide
derivatives: (i): SOCl2, glycine; (ii): aromatic
aldehydes, AcOK, Ac2O, reflux; (iii):
piperidine, 0 °C; (iv): Br2, 0 °C; (v): SO2Cl2,
0 °C.
R1
R2=o-CH3
i: Y=C, R1=3,5-dimethoxy, R2= -F
p
8a-q: X=Br
9a-q: X=Cl
2
Chem Biol Drug Des 2016

Synthesis and QSAR Study for Arylpropenamide Derivatives
14 mL of a 10% sodium hydroxide solution and stirred for
30 min at 0 °C. After the solution was acidified by adding
1 mol/L HC1, the precipitated solid was filtered and the
solid was recrystallized from water to afford 4a–q.
General procedure for the preparation of (Z)-N-[1-
chloro-3-oxo-1-aryl-3-(piperidin-1-yl)pr-op- 1-en-2-
yl]arylamide (9l–q)
Sulfuryl dichloride (2.55 g, 19 mmol) in dichloromethane
solution (29 mL) was slowly added to a dichloromethane
solution of 7a–q (15 mmol) at ice temperature. The result-
ing solution was stirred for 3 h, filtered and evaporated to
afford the yellow oil. The yellow oil was crystallized to give
9a–q by using ethanol as solution. The structures of 9a–q
were characterized by FTIR, 1H NMR, and HRMS and
data were showed in supporting information.
General procedure for the preparation of
4-arylidene-2-aryloxazol-5(4H)-one (6a–q)
The aryl carboxamide acetic acid (4a–q) (28 mmol), aro-
matic aldehydes (20 mmol), potassium acetate (2.11 g,
22 mmol), and acetic anhydride (7 mL, 9 mmol) were
added to a 50 mL three-necked flask and heated at reflux
for 1 h. The reaction mixture was treated with ethanol
(10 mL) and cooled to room temperature. The product
was precipitated out of the solution, and the solid was col-
lected, washed with ethanol (2 9 10 mL) and then dried
to obtain 6a–q as yellow crystals.
Crystal data for 9c
The crystal data of the rearranged product are as fol-
lows. Crystal Data for C21H20ClN3O4 (M = 413.85 g/mol):
monoclinic, space group P21/c (no. 14), a = 9.9358(4)
ꢀ
ꢀ
ꢀ3
ꢀ
A, b = 12.4259(6) A, c = 16.0874(6) A, b = 94.990(4)°,
V = 1978.65(14) A , Z = 4, T = 293.15 K, l (MoKa) =
General procedure for the preparation of N-[3-
oxo-1-aryl-3-(piperidin-1-yl)prop-1-en-2-yl]
arylamide (7a–q)
Dichloromethane (25 mL) and piperidine (1.5 g, 18 mmol)
were added a solution of 6a–q (18 mmol) in dichloro-
methane (40 mL) at 0 °C, and then were stirred for 1 h at
this temperature to obtain CH2Cl2 solution of 7a–q, which
were used for the next reaction without further purification.
0.227 mmꢀ1
,
Dcalc = 1.389 g/cm3, 8421 reflections
measured (6° 2Θ 52.74°), 4045 unique (Rint = 0.0213,
Rsigma = 0.0377) which were used in all calculations.
The final R1 was 0.0421 (>2r(I)) and wR2 was 0.1011.
The full crystallographic details of the rearranged product
have been deposited at the Cambridge Crystallographic
Data Center and were allocated the deposition number
CCDC 1434735. The crystal structure was shown in
Figure 3.
General procedure for the preparation of (Z)-N-[1-
bromo-3-oxo-1-aryl-3-(piperidin-1-yl)prop- 1-en-2-
yl]arylamide (8a–q)
Computational calculations for QSAR
Solid calcium carbonate (2.08 g, 21 mmol) was added to
a dichloromethane solution of 7a–q (17 mmol) at 0 °C,
and bromine liquid (2.66 g, 17 mmol) in CH2Cl2 (30 mL)
was slowly added to the reaction system. The resulting
solution was stirred for 5 h, filtered and evaporated to
afford the yellow oil. The yellow oil was crystallized use
ethanol to give 8a–q. The structures of 8a–q were charac-
terized by FTIR, 1H NMR, and HRMS and data were
shown in supporting information.
The optimized molecular geometry of compound
All computations were carried out on the GAUSSIAN 09a
computer software package. The electronic descriptors
were obtained from
a single-point calculation at the
B3LYP/6-311 + g (d) level.
The optimized molecular geometry of compound was
computed first and the optimized geometrical parameters,
such as bond length and total charge of aromatic ring (∑Q
Figure 3: Crystal structure of compound
9c.
Chem Biol Drug Des 2016
3

Min et al.
of Ar), benzene ring (∑Q of Ph) and a piperidine ring (∑Q
of Cy) were given in Table S4.
molecular alignment strategy. To derive the CoMFA
descriptor fields, the aligned training set molecules were
ꢀ
placed in a 3D cubic lattice with grid spacing of 2 A in x,
y, and z directions such that the entire set was included in
it. The CoMFA steric and electrostatic field energies were
calculated using a sp3 carbon probe atom with a van der-
The parameters for constructing the 2D-QSAR
models
ꢀ
Structural parameters include: energy of highest occupied
molecular orbital (EHOMO), energy of lowest unoccupied
molecular orbital (ELUMO), energy difference between
LUMO and HOMO (Egap),the most positive H atom charge
(qH+), Molecular dipole moment (l) and heat of formation
(Dhf) for the structure at 298.15 K and 1 atm (HF). Ther-
modynamic parameters include: total energy (TE), zero
point energy (ZPE), enthalpy (Hө), free energy (Gө), correc-
tion value of thermal energy (Eth), molar heat capacity at
constant volume (CVө) and entropy (Sө). Some of the
quantum chemical parameters were listed in Table 1,
Tables S5 and S6.
Waals radius of 1.52 A and a charge of +1.0. Cut-off val-
ues for both steric and electrostatic fields were set to
30.0 kcal/mol.
Regression analysis by PLS method
The partial least squares (PLS) methodology analysis with
the leave-one-out (LOO) cross-validation procedure was
carried out to determine the optimal number of compo-
nents using the SAMPLS (21). The cross-validated coeffi-
cient q2, as an internal statistical index of predictive
power, was subsequently obtained. The quality of the
external prediction was documented using the standard
deviation of error prediction (R2).
Molecular modeling and alignment of 3D-QSAR
The 3D-QSAR studies of the arylpropenamide compounds
using the CoMFA performed on the SYBYL 8.0 (Tripos
company in School of chemical engineering, Sichuan Uni-
versity, Sichuan Province, China) package running on the
Linux operating system. Partial atomic charges of all com-
pounds were calculated by the Gasteigere-Marsili method,
and then were optimized for their geometry using Tripos
field (19) with a distance-dependent dielectric function and
Biological assay
It was reported that this series has been found to be gener-
ally non-toxic in the HepAD38 cell line even at the highest
concentrations tested. So in this article, the EC50 of com-
pounds were tested and used in QSAR study only (11). The
anti-HBV activities were evaluated in the HepAD38 cellular
assay according to literature (22). The DNA replication of
HBV in the cell was detected by dot blot hybridization and
the results were listed in Table 2 as observed Data. The
EC50 is the concentration of the compound (in lM) which
inhibits the synthesis of viral DNA by 50%.
ꢀ
energy convergence criterion of 0.21 kcal/mol A using the
maximum iterations set to 1000 (20).
CoMFA analysis
The improvement of QSARs may originate from the choice
of DFT-optimized template and the usage of RMSD-based
Used computational calculation obtained thermal energy
(TE) and lower entropy (Sө) as the parameters (Table 1),
Table 1: The parameters for constructing the 2D-QSAR models
TE
Sө
TE
Sө
Compound
Hartree
Cal/Mol-Kel.
Compound
Hartree
Cal/Mol-Kel.
8a
8b
8c
8d
8e
8f
ꢀ3686.148875
ꢀ3875.877676
ꢀ3850.712991
ꢀ3851.404744
ꢀ4106.465680
ꢀ3686.023247
ꢀ3950.680092
ꢀ3890.681923
ꢀ3975.154327
ꢀ3950.680481
ꢀ4311.024169
ꢀ1737.341213
ꢀ3662.903578
ꢀ3762.174503
ꢀ3702.197370
ꢀ4122.533282
ꢀ6236.458110
180.038
195.550
187.426
186.295
173.943
177.103
189.636
190.652
204.014
190.555
192.897
183.892
170.519
176.253
177.440
176.201
179.337
9a
9b
9c
9d
9e
9f
ꢀ1572.218341
ꢀ1761.957429
ꢀ1737.341213
ꢀ1737.485987
ꢀ1992.546581
ꢀ1572.216583
ꢀ1776.762636
ꢀ1836.745624
ꢀ1861.233973
ꢀ1836.754037
ꢀ2197.104802
ꢀ1663.499419
ꢀ1548.983133
ꢀ1648.258941
ꢀ1588.277024
ꢀ2008.612706
ꢀ4122.530828
178.959
194.876
183.892
183.506
173.272
175.184
185.954
183.465
200.355
189.000
189.523
182.265
167.328
172.464
174.332
173.825
179.527
8g
8h
8i
9h
9g
9i
8j
9j
8k
8l
9k
9l
8m
8n
8o
8p
8q
9m
9n
9o
9p
9q
4
Chem Biol Drug Des 2016

Synthesis and QSAR Study for Arylpropenamide Derivatives
Table 2: The predicted and measured data of anti-HBV activities of compound 8a–q and 9a–q
Predicted data Observed data Predicted data
EC50
ꢀlog(1/EC50
9.2
Observed data
EC50
ꢀlog(1/EC50
13.6
Compound
EC50
ꢀlog(1/EC50
)
EC50
ꢀlog(1/EC50
)
Compound
)
)
8a
8b
8c
8d
8e
8f
2.9
15.6
6.9
6.2
2.5
2.2
9.5
9.9
39.2
10.4
19.0
0.5
1.1
2.1
2.3
3.1
38.6
0.456182160
1.193165637
0.840923392
0.793792429
0.391582597
0.333001797
0.979080235
0.994424888
1.593363886
1.017632462
1.279699891
ꢀ0.268115326
0.046292263
0.331964409
0.354492075
0.493610398
1.586204445
12.3
56.0
1.4
1.8
1.0
2.1
6.5
2.0
82.0
21.0
35.0
1.0
1.8
3.9
7.0
18.8
77.0
1.08990511
1.74818803
0.14612804
0.25527251
0.00000000
0.32221929
0.81291336
0.30103000
1.91381385
1.32221929
1.54406804
0.00000000
0.25527251
0.59106461
0.84509804
1.27415785
1.88649073
9a
9b
9c
9d
9e
9f
0.961778866
2.367959724
1.449888866
1.418122811
0.699505672
0.650416001
1.463574292
1.639356941
2.868709123
1.920105231
2.140525478
1.279365663
ꢀ0.008977132
0.463481264
0.588044361
0.753021227
2.263314942
1.13353891
2.00000000
ꢀ0.04575749
0.25527250
0.07918125
0.30103000
1.82607480
0.30103000
2.00000000
1.74818803
1.99122608
1.74818803
0.25527251
0.65321251
0.74818803
0.85733250
1.96848295
233.3
28.2
26.2
5.0
>100.0
0.9
1.8
1.2
2.0
67.0
2.0
>100.0
56.0
98.0
56.0
1.8
4.5
8g
8h
8i
9g
9h
9i
29.1
43.6
739.1
83.2
138.2
19.0
1.0
2.9
3.9
5.7
183.4
8j
9j
8k
8l
9k
9l
8m
8n
8o
8p
8q
9m
9n
9o
9p
9q
4.5
5.6
7.2
93.0
the predicted activities were get based on the QSAR
equations I and II (Scheme 1) and the results were listed in
Table 2 as predicted Data.
Serise 8
Serise 9
Serise 8: n = 17, R = 0.73720, SD = 0.36563, p < 7.33949*10–4
Serise 9: n = 17, R = 0.70132, SD = 0.39287, p < 0.00171
3.0
2.5
2.0
Results and Discussion
1.5
SAR investigation
1.0
SAR investigation of arylpropenamide was done firstly. The
pyridine substituted propenamide compounds 1o and 2o
reported by our group had good biological activities (17),
so the B ring of some new propenamide derivatives were
designed with pyridine group. The biological assay results
shown that the vinyl bromides compounds 8l and 8m,
where phenyl was replaced by pyridine, have good biologi-
cal activities with EC50 of 0.5 and 1.1 lM respectively. The
vinyl chlorides pyridine substituted compounds 9m and 9n
also showed good results.
0.5
0.0
–0.5
0.0
0.5
1.0
1.5
2.0
Observed –log(1/EC50
)
Figure 4: The Relationships between the ꢀlog(1/EC50) values
from experiment and prediction based on QSAR equations I and
II.
2D-QSAR
data of more comprehensive structural modification
arylpropenamide.
The ꢀlog(1/EC50) values from observed and prediction cal-
culated by QSAR equations I and II (Scheme 1) have cer-
tain linear relationship (Figure 4). The series 8 possess
relatively high correlation coefficient with R = 0.73720, and
for series 9 the R value is equal to 0.70132 lower than ser-
ies 8. The QSAR equations of I and II (Scheme 1) were
constructed based on the thermodynamic parameters and
activities data of series 1 and 2, in which only A ring of
phenylpropenamide compounds have different structure
(Figure 2), so the QSAR equations have limitations. In the
series 8 and 9, the B ring of arylpropenamide with different
electronic and steric effects substituents have been inves-
tigated. It is necessary to establish a new QSAR equa-
tion based on quantum mechanics and biological activity
Same as equations I and II, thermal energy (TE) and
entropy (Sө) were more correlated with ꢀlog(1/EC50), so
they were used in the construction of the new model. A
new and more accurate QSAR equations were con-
structed by using the parameters of thermal energy (TE)
and entropy (Sө) of the arylpropenamides of vinyl bro-
mides compounds 1a–r and 8a–q and chloro-substituted
compounds 2a–r and 9a–q, and the QSAR equations can
be written as Scheme 3.
In the QSAR equations, n is the number of data points, R2
is square of the correlation coefficient and represents the
Chem Biol Drug Des 2016
5

Min et al.
and II. The reason was that the parameters of equations I
and II derived from the compounds that only A ring have
different substitutes, but the data of equations III and IV
were from a larger research objects which A and B rings
were modified. Because of the new equations based on
more comprehensive substrates, so they have stronger
biological activity prediction ability and more extensive
application capabilities.
Bromides Series : n=35, R2=0.6610, F= 31.19704, P<0.0001
Chlorides Series : n=35, R2= 0.57827, F= 21.93873, P<0.0001
Scheme 3: The new QSAR equations based on the ꢀlog(1/EC50
)
values and thermodynamic parameters of vinyl bromides (1a–r
and 8a–q) and vinyl chlorides (2a–r and 9a–q).
The correlation plots between experimental and calculated
activities values presented in Figure 5 indicated that the
selected parameters can predict the anti-HBV activities of
the set arylpropenamide molecules with greater pre-
dictability. Thus, designing new arylpropenamide mole-
cules with high thermal energy (TE) and low entropy (Sө)
may increase the anti-HBV activities. The 9c and 9h, for
example, were some of outlier in this 2D-QSAR model.
There were ortho-nitro-substitution on the B ring of prope-
namides in 9c and 9h, so this model will not work in cer-
tain special substituents, such as ortho nitro compounds.
goodness of fit, F is the overall F-statistics for the addition
of each successive term, and p is the p values using the F
statistics.
The arylpropenamides of vinyl bromides compounds, the
QSAR equations possess relatively high correlation coeffi-
cient with R2 = 0.6610 and better 31.19704 F-statistics,
and least number of variables. For some of the values of
EC50 of chloro-substituted propenamides compounds
greater than 100 lM, the 100 been used to calculated
ꢀlog (1/EC50) and participated the linear regression, so
the R2 value of the series is equal to 0.57827 lower than
above, but still meet the statistical requirements. The R2 of
QSAR equation III and IV are much lower than equations I
3D-QSAR
Same as the 2D-QSAR, the 3D-QSAR reported by our
research group has some limitations too. In this study, a
new and more representatively 3D-QSAR were con-
structed using the CoMFA performed based on the data
of arylpropenamides of vinyl bromides compounds 1a–r
and 8a–q and chloro-substituted propenamides com-
pounds 2a–r and 9a–q.
Bromo
Chloro
2.5
2.0
Bromo: n = 35, R = 0.81302, SD = 0.30008, p < 0.0001
Chloro: n = 35, R = 0.76044, SD = 0.39823, p < 0.0001
1.5
All the data-based fitting procedure was finally adopted
through careful comparison and each analog was super-
imposed to the template based on the common substruc-
ture of propenamide moiety. The aligned molecules were
illustrated in Figure 6 and the statistical parameters were
listed in Table 3.
1.0
0.5
0.0
For arylpropenamide molecules, as shown in Table 3, the
better predictions are obtained by the 3D-QSAR/CoMFA
for anti-HBV activities. The model has a high R2 (0.931
and 0.923) respectively for series 1 and 8, and 2 and 9,
showed in Table 3 with a low standard deviation (SE,
0.177 and 0.238, respectively) and a high Fischer ratio
(F, 78.414 and 69.721, respectively); while a QSAR model
–0.5
–0.5
0.0
0.5
1.0
1.5
2.0
Observed –log(1/EC50
)
Figure 5: The relationships between the ꢀlog(1/EC50
) values
from experiment and prediction based on QSAR equations III and
IV.
A
B
Figure 6: 3D-views of all aligned
phenylpropenamide molecules (A for series 1
and 8, B for series 2 and 9) congeners by
RMSD-based fitting.
6
Chem Biol Drug Des 2016

Synthesis and QSAR Study for Arylpropenamide Derivatives
Table 3: The statistical parameters for the
best 3D-QSAR CoMFA models
Statistical results
Methods R2
Filed contribution
Steric Electrostatic
Series
F
SE
q2
1a–r and 8a–q CoMFA
2a–r and 9a–q
0.931 78.414 0.177 0.604 62.34% 37.66%
0.923 69.721 0.238 0.563 4.61% 95.39%
For the vinyl bromides series, the steric field is the domi-
nating factor for the anti-HBV activities and the electro-
static field gave the least contribution (Table 3). In
contrast, for the vinyl chlorides series, the electrostatic field
is the dominating factor for the anti-HBV activities and the
steric field effect is relatively small (Table 3).
2.5
2
Sreise of vinyl bromides R = 0.9665
2
Sreise of vinyl chlorides R = 0.95844
2.0
1.5
1.0
To view the field effect on the target property, CoMFA
contour maps were generated and shown in Figure 8. For
steric fields, the green is means bulky group favorable and
yellow is bulky group unfavorable. Similarly, the blue is
means electropositive charge favorable and red is elec-
tronegative charge favorable.
0.5
0.0
–0.5
–0.5
0.0
0.5
1.0
1.5
2.0
For the compounds 1 and 8, the steric field of vinyl bro-
mides of arylpropenamide molecules has green contours
(64.20%) refer to sterically favored regions for anti-HBV
activities and yellow contours (35.80%) highlight the steri-
cally unfavorable regions. The electrostatic field has blue
contours (21.61%) represent electropositively preferred
regions to activities and red contours (78.39%) indicate
regions where more electronegative substituents are
favored (Figure 8). For the compounds 2 and 9, the steric
field of vinyl chlorides of arylpropenamide molecules has
green contours (57.72%) refer to sterically favored regions
for anti-HBV activities and yellow contours (42.28%) high-
light the sterically unfavorable regions. The electrostatic
field has blue contours (7.01%) represent electropositively
preferred regions to activities and red contours (92.99%)
indicate regions where more electronegative substituents
are favored (Figure 8).
Observed activity
Figure 7: Plots
of
experimental activities
corresponding predicted activities by QSAR/CoMFA models.
versus
the
is generally acceptable if R2 is approximately 0.9 or higher
(23). Specially, the cross-validation related coefficient q2 is
0.604 and 0.563, respectively (>0.5), suggesting a good
prediction ability of this model (24).
The plots of the predicted versus actual ꢀlog(1/EC50) for
the QSAR/CoMFA models were displayed in Figure 7. It
could be noted that the data points were uniformly dis-
tributed along the regression line; additionally, as shown in
Table 3, all the prediction errors were smaller than 0.5,
suggesting the satisfactorily predictive capability, high relia-
bility and accuracy of the models.
A
B
C
D
Figure 8: Stereoview of CoMFA steric filed (A) and electrostatic filed (B) of vinyl bromides of phenylpropenamide molecules 1 and 8 and
steric filed (C) and electrostatic filed (D) of vinyl chlorides of phenylpropenamide molecules 2 and 9.
Chem Biol Drug Des 2016
7

Min et al.
Judging from 3D-QSAR models, the anti-HBV activities
are mainly affected by the steric and electrostatic proper-
ties of substitutents. The compounds 8b and 8i have poor
biological activity than others for their strong electroposi-
tively substitution at red regions. Especially, in the vinyl
chlorides series, the electrostatic field is the dominating
factor for the anti-HBV activities, electropositively substitu-
tion resulted the 9b and 9i mostly inactive for HBV. So
from the perspective of pharmacophore, electron-donating
is not recommended for introducing to the B ring of new
designed arylpropenamide. Thus, complementary results
can be obtained with 3D-QSAR and CoMFA models,
which can provide theoretical guide to the application of
QSAR in the environmental chemical field.
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This work was supported by the NSF of Sichuan
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Conflict of Interest
The authors have no potential conflict of interest.
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