Synthesis and quantitative structure-activity relationship (QSAR) study of novel N-arylsulfonyl-3-acylindole arylcarbonyl hydrazone derivatives as nematicidal agents

Article abstract of DOI:10.1021/jf400536q

In continuation of our program aimed at the discovery and development of natural-product-based pesticidal agents, 54 novel N-arylsulfonyl-3-acylindole arylcarbonyl hydrazone derivatives were prepared, and their structures were well characterized by ¹

Full text of DOI:10.1021/jf400536q

Subscriber access provided by Georgetown University | Lauinger and Blommer Libraries
Article
Synthesis and Quantitative Structure-Activity Relationship
(QSAR) Study of Novel N-Arylsulfonyl-3-Acylindole
Arylcarbonyl Hydrazone Derivatives as Nematicidal Agents
Zhiping Che, shaoyong zhang, yonghua shao, Lingling Fan,
Hui Xu, Xiang Yu, Xiaoyan Zhi, Xiaojun Yao, and Rui Zhang
J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/jf400536q • Publication Date (Web): 20 May 2013
Downloaded from http://pubs.acs.org on May 22, 2013
Just Accepted
“Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted
online prior to technical editing, formatting for publication and author proofing. The American Chemical
Society provides “Just Accepted” as a free service to the research community to expedite the
dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts
appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been
fully peer reviewed, but should not be considered the official version of record. They are accessible to all
readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered
to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published
in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just
Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor
changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers
and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors
or consequences arising from the use of information contained in these “Just Accepted” manuscripts.
Journal of Agricultural and Food Chemistry is published by the American Chemical
Society. 1155 Sixteenth Street N.W., Washington, DC 20036
Published by American Chemical Society. Copyright © American Chemical Society.
However, no copyright claim is made to original U.S. Government works, or works
produced by employees of any Commonwealth realm Crown government in the course
of their duties.

Page 1 of 42
Journal of Agricultural and Food Chemistry
1
Synthesis and Quantitative Structure-Activity Relationship (QSAR) Study
of Novel N-Arylsulfonyl-3-Acylindole Arylcarbonyl Hydrazone
Derivatives as Nematicidal Agents
2
3
4
5
6
7
8
9
Zhiping Che,† Shaoyong Zhang,‡ Yonghua Shao,# Lingling Fan,† Hui Xu,*,† Xiang Yu,†
Xiaoyan Zhi,† Xiaojun Yao,# and Rui Zhang †
†Laboratory of Pharmaceutical Design & Synthesis, College of Sciences, Northwest A&F
University, Yangling 712100, Shaanxi Province, People′s Republic of China
‡Provincial Engineering Laboratory of Biopesticide Preparation, Zhejiang A&F
University, Lin′an 311300, Zhejiang Province, People′s Republic of China
#Department of Chemistry, Lanzhou University, Lanzhou 730000, Gansu Province, People′s
Republic of China
10
11
12
13
14
15
16
17
18
19
20
21
1
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 2 of 42
22
Abstract
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
In continuation of our program aimed at the discovery and development of
naturalꢀproductꢀbased pesticidal agents, fiftyꢀfour novel Nꢀarylsulfonylꢀ3ꢀacylindole
arylcarbonyl hydrazone derivatives were prepared, and their structures were well
1
characterized by H NMR, 13C NMR, HRMS, ESIꢀMS, and mp. Their nematicidal activity
was evaluated against the pine wood nematode, Bursaphelenchus xylophilus in vivo. Among
all the derivatives, especially V-12 and V-39 displayed the best promising nematicidal activity
with the LC50 values of 1.0969 and 1.2632 mg/L, respectively. It suggested that introduction
of R1 and R2 together as the electronꢀwithdrawing substituents, R3 as the methyl group, and
R4 as the phenyl with the electronꢀdonating substituents could be taken into account for
further preparation of this kind of compounds as nematicidal agents. Six selected descriptors
are a WHIM descriptor (E1m), two GETAWAY descriptors (R1m+ and R3m+), a Burden
eigenvalues descriptor (BEHm8), and two edge adjacency indices descriptors (EEig05x and
EEig13d). Quantitative structureꢀactivity relationship (QSAR) studies demonstrated that the
structural factors, such as molecular masses (a negative correlation with the bioactivity) and
molecular polarity (a positive correlation with bioactivity), are likely to govern the
nematicidal activities of these compounds. For this model, the correlation coefficient (R2
training
2
set), the leaveꢀoneꢀout crossꢀvalidation correlation coefficient (Q LOO) and the sevenꢀfold
crossꢀvalidation correlation coefficient (Q27ꢀfold) were 0.791, 0.701 and 0.715, respectively.
And the external crossꢀvalidation correlation coefficient (Q2ext) and the root mean square
error for the test set (RMSEtest set) were 0.774 and 3.412, respectively. It will pave the way for
future design, structural modification and development of indole derivatives as nematicidal
2
ACS Paragon Plus Environment

Page 3 of 42
Journal of Agricultural and Food Chemistry
44
agents.
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
KEYWORDS: Indole, hydrazone, structural modification, botanical pesticide, nematicidal
activity, QSAR, Bursaphelenchus xylophilus
3
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 4 of 42
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
INTRODUCTION
Pine wood nematode, Bursaphelenchus xylophilus, has caused pine wilt disease which has
been devastating forests worldwide.1 Moreover, at present there are only few commercial
nematicides left in use, and their repeated applications over the years have led to the
enhancement of biodegradation mechanisms in soil and the development of pest resistance.2ꢀ4
To prevent the pine wilt disease and overcome the problems about resistance development
and environment pollution, therefore, the research and development of efficacy nematicidal
agents has received much attention internationally in recent years.5ꢀ11 In the meantime, during
the long period of evolution, plants must resist attackers over their lifetime by producing and
exuding secondary metabolites, and pesticides produced from plant secondary metabolites
may result in less or slower resistance development and lower pollution.12,13 Hence, the
discovery of new pesticidal compounds directly from plant secondary metabolites, or by
using them as the lead compounds for further structural modifications has recently been one
of the important procedures for research and development of new pesticides.14ꢀ17 Some
botanical pesticides such as nicotine, pyrethrum and neem extracts are the characteristic
examples made from plants as defenses against pests.18
Indole (I-1, Scheme 1), an aromatic heterocyclic compound, is a constituent of many
natural plants, such as Robinia pseudacacia, jasmines, certain citrus plants and orange
blossoms. Due to its crucial heterocyclic skeleton, extensive efforts by using I-1 as a lead
compound have been made for the preparation of potent antiꢀhuman immunodeficiency
virus type 1 (
HIVꢀ1) inhibitors (e.g., delavirdine),19,20 hepatitis C virus (HCV) inhibitors,21
antimicrobial agents,22 glutamate carboxypeptidase II (GCPII) inhibitors,23 antifungal
agents,24 and so on. In contrast, to the best of our knowledge, little work has been conducted
4
ACS Paragon Plus Environment

Page 5 of 42
Journal of Agricultural and Food Chemistry
90
on the structural modifications of indoles as nematicidal agents against the pine wood
91
92
nematode, B. xylophilus. Recently, we have found that some fraxinelloneꢀbased hydrazone
derivatives
exhibited
the
pronounced
insecticidal
activity,25
and
some
93
Nꢀarylsulfonylꢀ3ꢀacetylindoles showed the potent antiꢀHIVꢀ1 activity.26 In continuation of
our program aimed at the discovery and development of novel naturalꢀproductꢀbased
pesticidal agents,24ꢀ28 consequently, we herein synthesized fiftyꢀfour novel
94
95
96
Nꢀarylsulfonylꢀ3ꢀacylindole arylcarbonyl hydrazone derivatives (V-1~V-54, Scheme 3) by
97
introduction of the hydrazone fragments on the Nꢀarylsulfonylꢀ3ꢀacylindolyl skeleton. Their
nematicidal activity was evaluated against B. xylophilus. In addition, the quantitative
98
99
structureꢀactivity relationship (QSAR) studies of V-1~V-54 were also investigated.
100
101
102
103
104
105
106
107
108
109
110
111
112
MATERIALS AND METHODS
General: All reagents and solvents were of reagent grade or purified according to the
standard methods before use. Analytical thinꢀlayer chromatography (TLC) and preparative
thinꢀlayer chromatography (PTLC) were performed with silica gel plates using silica gel 60
GF254 (Qingdao Haiyang Chemical Co., Ltd.). Melting points were determined on a XTꢀ4
digital meltingꢀpoint apparatus (Beijing Tech Instrument Co., Ltd.) and were uncorrected.
Infrared spectra (IR) were recorded on a Bruker TENSOR 27 spectrometer. Nuclear magnetic
resonance spectra (NMR) were recorded on a Bruker Avance DMX 300, 400 or 500 MHz
instrument in CDCl3 or DMSOꢀd6 (1H at 300, 400 or 500 MHz and 13C at 125 MHz) using
TMS (tetramethylsilane) as the internal standard. Electrospray iontrap mass spectrometry
(ESIꢀTRAPꢀMS) and electron ionization mass spectra (EIꢀMS) were carried out with Bruker
ESIꢀTRAP Esquire 6000 plus mass spectrometry instrument, and HP 5988 instrument,
respectively. Highꢀresolution mass spectra (HRꢀMS) were carried out with IonSpec 4.7 Tesla
5
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 6 of 42
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
FTMS instrument.
Synthesis of 3ꢀFormylindoles (II-1
~
II-4): A mixture of N,Nꢀdimethylformamide (DMF, 5 mL)
o
and phosphorus oxychloride (POCl3, 0.5 mL) was stirred at 0 C for 20 min. Then a solution
of indoles (I-1~I-4, 5 mmol) in DMF (2 mL) was added dropwise to the above mixture. After
adding, the mixture was stirred at 35 oC for 1 h, and water was added, followed by adding
30% aqueous sodium hydroxide (NaOH) to adjust pH value to 8ꢀ9. The mixture was then
refluxed for 1 h. On cooling, the mixture was poured into ice water, and the precipitated
product was collected, washed by water, and recrystallized from absolute methanol to afford
II-1~II-4 in 84ꢀ95% yields.
Data for II-1: Yield = 91%, pink solid. mp = 190ꢀ192 oC [literature, 195ꢀ198 °C].29 1H NMR
(400 MHz, DMSOꢀd6) δ: 9.93 (s, 1H), 8.29 (s, 1H), 8.08 (d, J = 8.0 Hz, 1H), 7.50 (d, J = 8.0
Hz, 1H), 7.20–7.28 (m, 2H). EIꢀMS, m/z (%): 145 (M+, 96).
Data for II-2: Yield = 95%, brown solid. mp =187ꢀ189 C [literature, 186ꢀ188 °C].29 1
H
o
NMR (400 MHz, DMSOꢀd6) δ: 9.89 (d, J = 2.0 Hz, 1H), 8.21 (s, 1H), 7.95 (d, J = 8.4 Hz,
1H), 7.30 (s, 1H), 7.04 (d, J = 8.0 Hz, 1H), 2.41 (s, 3H). EIꢀMS, m/z (%): 159 (M+, 68).
Data for II-3: Yield = 88%, yellow solid. mp = 241ꢀ243 C [literature, 244ꢀ245 °C].29 1
H
o
NMR (400 MHz, DMSOꢀd6) δ: 10.01 (s, 1H), 8.52 (s, 1H), 8.47 (s, 1H), 7.71 (d, J = 8.4 Hz,
1H); 7.65 (d, J = 8.0 Hz, 1H). EIꢀMS, m/z (%): 170 (M+, 70).
Data for II-4: Yield = 84%, yellow solid. mp > 300 C [literature, 312ꢀ313.3 °C].30 1H
o
NMR (400 MHz, DMSOꢀd6) δ: 10.03 (s, 1H), 8.94 (d, J = 2.0 Hz, 1H), 8.58 (s, 1H), 8.15 (dd,
J = 2.4, 9.2 Hz, 1H), 7.71 (d, J = 9.2 Hz, 1H). EIꢀMS, m/z (%): 190 (M+, 100).
Synthesis of NꢀArylsulfonylindoles (III-1~III-17): A mixture of I-1~I-4 (1 mmol),
benzyltriethylammonium chloride (TEBA, 0.1 mmol), NaOH (1.8 mmol), and arylsulfonyl
6
ACS Paragon Plus Environment

Page 7 of 42
Journal of Agricultural and Food Chemistry
136
chlorides (1.2 mmol) in dry CH2Cl2 (5 mL) was stirred at room temperature. After stirring for
1ꢀ2 h, the reaction was complete according to TLC analysis, and water (10 mL) was added to
the mixture, which was extracted with CH2Cl2 (30 mL × 3). Subsequently, the combined
organic phase was washed by brine (30 mL), dried over anhydrous Na2SO4, and concentrated
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
under the reduced pressure to give III-1~III-17 in 73ꢀ99% yields. The example data of III-1
and III-2 are shown as follows, whereas data of III-3~III-17 can be found in the Supporting
Information.
Data for III-1: Yield = 97%, white solid. mp = 78ꢀ79 °C [literature, 78ꢀ79 °C].31 1H NMR
(400 MHz, CDCl3) δ: 7.99 (dd, J = 8.4, 4.0 Hz, 1H), 7.87 (d, J = 8.0 Hz, 2H), 7.56 (d, J = 3.6
Hz, 1H), 7.50 (d, J = 8.0 Hz, 2H), 7.40 (d, J = 7.6 Hz, 2H), 7.29 (d, J = 8.4 Hz, 1H), 7.21 (d,
J = 7.6 Hz, 1H), 6.66 (d, J = 2.8 Hz, 1H). EIꢀMS, m/z (%): 257 (M+, 85).
o
Data for III-2: Yield = 96%, white solid. mp = 83ꢀ84 C [literature, 87ꢀ88 °C].32 1H NMR
(400 MHz, CDCl3) δ: 7.97 (d, J = 10.8 Hz, 1H), 7.75 (d, J = 10.8 Hz, 2H), 7.56 (d, J = 4.4 Hz,
1H), 7.97 (d, J = 10.0 Hz, 1H), 7.20 (m, 4H), 6.65 (d, J = 4.8 Hz, 1H), 2.33 (s, 3H). EIꢀMS,
m/z (%): 271 (M+, 100).
Synthesis of 3ꢀFormylꢀNꢀArylsulfonylindoles (IV-1~IV-13): A mixture of II-1~II-4 (2 mmol),
arylsulfonyl chlorides (4 mmol), and K2CO3 (6 mmol) in dry CH2Cl2 (10 mL) was refluxed
for 12ꢀ20 h. Then the reaction mixture was filtered. The corresponding filtrate was collected,
concentrated under the reduced pressure, and purified by PTLC to produce IV-1-IV-13 in
64ꢀ99% yields. The example data of IV-1 and IV-2 are shown as follows, whereas data of
IV-3~IV-13 can be found in the Supporting Information.
o
Data for IV-1: Yield = 71%, white solid. mp = 148ꢀ150 oC [literature, 149 C].33 1H NMR
(500 MHz, CDCl3) δ: 10.09 (s, 1H), 8.25 (d, J = 7.5 Hz, 1H), 8.22 (s, 1H), 7.95 (d, J = 8.0 Hz,
7
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 8 of 42
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
1H), 7.85 (d, J = 8.5 Hz, 2H), 7.34ꢀ7.42 (m, 2H), 7.29 (d, J = 8.0 Hz, 2H), 2.36 (s, 3H).
ESIꢀMS, m/z (%): 300 ([M+H]+, 100).
o
Data for IV-2: Yield = 75%, white solid. mp = 137ꢀ139 oC [literature, 137 C].33 1H NMR
(500 MHz, CDCl3) δ: 10.08 (s, 1H), 8.26 (d, J = 7.5 Hz, 1H), 8.22 (s, 1H), 7.95 (d, J = 8.5 Hz,
1H), 7.89ꢀ7.91 (m, 2H), 7.34ꢀ7.42 (m, 2H), 6.94 (d, J = 9.0 Hz, 2H), 3.81 (s, 3H). ESIꢀMS:
m/z (%): 316 ([M+H]+, 25).
Synthesis of 3ꢀAcylꢀNꢀArylsulfonylindoles (IV-14
mmol) and R3COCl (acetyl chloride, propionyl chloride or nꢀhexanoyl chloride, 1.5 mmol) in
dry CH2Cl2 (5 mL) at room temperature, a solution of III-1 III-17 (1 mmol) in dry CH2Cl2 (2
~IV-33): To a stirred mixture of AlCl3 (3
~
mL) was added dropwise. After adding, the mixture was stirred at room temperature for 1.5ꢀ2
h, and the reaction process was checked by TLC analysis. Then water (10 mL) was added to
the mixture, which was extracted with CH2Cl2 (30 mL × 3). Subsequently, the combined
organic phase was washed with saturated aqueous NaHCO3 (30 mL × 2) and brine (30 mL),
dried over anhydrous Na2SO4, concentrated in vacuo, and purified by PTLC to afford
IV-14
~IV-33 in 62ꢀ99% yields. The example data of IV-14 and IV-15 are shown as follows,
whereas data of IV-16
~
IV-33 can be found in the Supporting Information.
o
o
Data for IV-14: Yield = 72%, white solid. mp = 158–159 C [literature, 159–160 C].34 1
H
NMR (300 MHz, CDCl3) δ: 8.32ꢀ8.34 (m, 1H), 8.21 (s, 1H), 7.92ꢀ7.97 (m, 3H), 7.48ꢀ7.61 (m,
3H), 7.34ꢀ7.39 (m, 2H), 2.58 (s, 3H). EIꢀMS m/z (%): 299 (M+, 74).
o
o
Data for IV-15: Yield = 91%, white solid. mp = 142–144 C [literature, 145–146 C].35 1
H
NMR (300 MHz, CDCl3) δ: 8.31ꢀ8.34 (m, 1H), 8.21 (s, 1H), 7.90ꢀ7.94 (m, 1H), 7.82 (d, J =
8.4 Hz, 2H), 7.26ꢀ7.37 (m, 4H), 2.57 (s, 3H), 2.36 (s, 3H). EIꢀMS m/z (%): 313 (M+, 35).
Synthesis of NꢀArylsulfonylꢀ3ꢀAcylindole Arylcarbonyl Hydrazone Derivatives (V-1~V-54): A
8
ACS Paragon Plus Environment

Page 9 of 42
Journal of Agricultural and Food Chemistry
182
mixture of IV-1
~
IV-33 (0.5 mmol), the corresponding hydrazides (0.5 mmol) and HOAc (two
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
drops) in ethanol (5 mL) was refluxed for 2ꢀ6 h. When the reaction was complete according
to TLC analysis, the mixture was allowed to cool, and filtered to give the solid, which was
further recrystallized from absolute ethanol to produce target compounds V-1
74ꢀ97% yields. The example data of V-1 V-20 are shown as follows, whereas data of
V-21 V-54 can be found in the Supporting Information.
~V-54 in
~
~
Data for V-1: Yield = 90%, white solid. mp = 215ꢀ216 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.63 (s, 1H), 8.45 (d, J = 7.5 Hz, 1H), 8.36 (s, 1H), 7.92ꢀ7.98 (m, 5H), 7.61 (d, J = 6.5 Hz,
1H), 7.56 (d, J = 7.0 Hz, 2H), 7.40ꢀ7.44 (m, 4H), 2.31 (s, 3H). 13C NMR (125 MHz,
DMSOꢀd6) δ: 163.4, 146.3, 142.6, 135.2, 134.2, 133.9, 132.1, 130.8, 130.3, 128.9, 128.0,
127.4, 127.3, 126.3, 124.7, 123.8, 118.7, 113.5, 21.5. ESIꢀMS: m/z (%): 418 ([M+H]+, 100).
HRMS (ESI): calcd for C23H20N3O3S ([M+H])+, 418.1219; found, 418.1226.
Data for V-2: Yield = 83%, white solid. mp = 182ꢀ183 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.64 (s, 1H), 8.45 (d, J = 7.5 Hz, 1H), 8.36 (s, 1H), 7.97ꢀ8.00 (m, 3H), 7.95 (d, J = 7.5 Hz,
2H), 7.62 (t, J = 7.5 Hz, 1H), 7.56 (t, J = 7.5 Hz, 2H), 7.46 (t, J = 7.5 Hz, 1H), 7.41 (t, J = 7.5
Hz, 1H), 7.11 (d, J = 9.0 Hz, 2H), 3.79 (s, 3H). 13C NMR (125 MHz, DMSOꢀd6) δ: 164.4,
142.7, 135.2, 133.9, 132.1, 130.3, 129.8, 128.9, 128.4, 128.0, 127.4, 126.2, 124.6, 123.7,
118.5, 115.6, 113.5, 56.3. ESIꢀMS: m/z (%): 434 ([M+H]+, 100). HRMS (ESI): calcd for
C23H20N3O4S ([M+H])+, 434.1169; found, 434.1161.
Data for V-3: Yield = 79%, white solid. mp = 267ꢀ268 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.64 (s, 1H), 8.45 (d, J = 7.5 Hz, 1H), 8.33 (s, 1H), 7.93ꢀ8.00 (m, 5H), 7.79 (d, J = 8.0 Hz,
13
2H), 7.55ꢀ7.61 (m, 3H), 7.39ꢀ7.45 (m, 2H), 2.05 (s, 3H). C NMR (125 MHz, DMSOꢀd6) δ:
169.6, 163.4, 145.2 142.6, 135.2, 133.9, 132.1, 130.3, 130.1, 128.9, 128.8, 128.0, 127.4,
9
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 10 of 42
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
126.2, 124.6, 123.7, 119.3, 118.5, 113.5, 24.5. ESIꢀMS: m/z (%): 483 ([M+Na]+, 100). HRMS
(ESI): calcd for C24H21N4O4S ([M+H])+, 461.1278; found, 461.1284.
Data for V-4: Yield = 97%, white solid. mp = 208ꢀ209 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.63 (s, 1H), 8.47 (d, J = 7.5 Hz, 1H), 8.39 (s, 1H), 8.08 (d, J = 8.5 Hz, 2H), 7.94ꢀ7.99 (m,
3H), 7.70 (d, J = 7.0 Hz, 2H), 7.62 (t, J = 7.0 Hz, 1H), 7.56 (t, J = 7.5 Hz, 2H), 7.48 (t, J =
7.5 Hz, 1H), 7.43 (t, J = 7.5 Hz, 1H). 13C NMR (125 MHz, DMSOꢀd6) δ: 163.4, 142.4, 140.5,
135.8, 135.2, 133.8, 132.2, 130.6, 130.2, 129.2, 128.9, 128.1, 127.5, 126.5, 124.9, 123.9,
119.1, 113.5. ESIꢀMS: m/z (%): 460 ([M+Na]+, 100). HRMS (ESI): calcd for C22H17N3O3SCl
([M+H])+, 438.0673; found, 438.0681.
Data for V-5: Yield = 76%, yellow solid. mp = 155ꢀ156 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.70 (s, 1H), 8.62 (s, 1H), 8.50ꢀ8.53 (m, 3H), 8.46 (d, J = 8.0 Hz, 1H), 8.05 (d, J = 8.5 Hz,
1H), 7.90ꢀ7.93 (m, 3H), 7.62 (t, J = 7.0 Hz, 1H), 7.56 (t, J = 7.5 Hz, 2H), 7.51 (t, J = 8.0 Hz,
1H), 7.44 (t, J = 7.5 Hz, 1H). 13C NMR (125 MHz, DMSOꢀd6) δ: 163.4, 148.6, 142.3, 138.3,
135.2, 133.8, 133.0, 132.5, 132.2, 130.2, 129.9, 128.9, 128.0, 127.6, 126.7, 125.2, 124.0,
122.0, 119.6, 113.5. ESIꢀMS: m/z (%): 471 ([M+Na]+, 70). HRMS (ESI): calcd for
C22H17N4O5S ([M+H])+, 449.0914; found, 449.0917.
Data for V-6: Yield = 78%, yellow solid. mp = 217ꢀ218 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.81 (s, 1H), 8.63 (s, 1H), 8.48 (d, J = 7.5 Hz, 1H), 8.41 (s, 1H), 8.34ꢀ8.35 (m, 1H), 8.02ꢀ8.04
(m, 2H), 7.95 (d, J = 7.5 Hz, 2H), 7.63 (t, J = 7.0 Hz, 1H), 7.56 (t, J = 7.5 Hz, 2H), 7.51 (t, J
= 7.5 Hz, 1H), 7.46 (t, J = 7.5 Hz, 1H). 13C NMR (125 MHz, DMSOꢀd6) δ: 163.4, 148.3,
142.2, 136.8, 135.1, 134.2, 133.8, 132.4, 132.2, 131.7, 130.1, 128.9, 128.1, 127.6, 126.7,
125.2, 124.7, 124.0, 119.6, 113.6. ESIꢀMS: m/z (%): 483 ([M+H]+, 100). HRMS (ESI): calcd
for C22H16ClN4O5S ([M+H])+, 483.0524; found, 483.0531.
10
ACS Paragon Plus Environment

Page 11 of 42
Journal of Agricultural and Food Chemistry
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
Data for V-7: Yield = 89%, white solid. mp = 242ꢀ243 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.60 (s, 1H), 8.30 (d, J = 8.0 Hz, 1H), 8.27 (s, 1H), 7.92ꢀ7.93 (m, 4H), 7.78 (s, 1H), 7.62 (t, J
= 7.0 Hz, 1H), 7.55 (t, J = 7.0 Hz, 2H), 7.42 (d, J = 8.5 Hz, 2H), 7.23 (d, J = 8.0 Hz, 1H),
2.47 (s, 3H), 2.32 (s, 3H). 13C NMR (125 MHz, DMSOꢀd6) δ: 163.4, 146.2, 142.7, 136.0,
135.6, 134.3, 133.9, 132.1, 130.8, 129.8, 128.9, 128.0, 127.3, 126.1, 125.2, 123.4, 118.7,
113.5, 21.9, 21.5. ESIꢀMS: m/z (%): 454 ([M+Na]+, 100). HRMS (ESI): calcd for
C24H22N3O3S ([M+H])+, 432.1376; found, 432.1385.
Data for V-8: Yield = 82%, white solid. mp = 224ꢀ225 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.60 (s, 1H), 8.30 (d, J = 8.0 Hz, 1H), 8.26 (s, 1H), 8.00 (d, J = 9.0 Hz, 2H), 7.95 (d, J = 7.5
Hz, 2H), 7.79 (s, 1H), 7.61 (t, J = 7.5 Hz, 1H), 7.55 (t, J = 7.5 Hz, 2H), 7.23 (d, J = 8.5 Hz,
13
1H), 7.11 (d, J = 9.0 Hz, 2H), 3.79 (s, 3H), 2.48 (s, 3H). C NMR (125 MHz, DMSOꢀd6) δ:
164.4, 142.7, 136.0, 135.6, 134.0, 133.9, 132.1, 129.8, 129.7, 128.9, 128.5, 128.0, 126.0,
125.2, 123.4, 118.5, 115.5, 113.5, 56.3, 22.0. ESIꢀMS: m/z (%): 448 ([M+H]+, 100). HRMS
(ESI): calcd for C24H22N3O4S ([M+H])+, 448.1325; found, 448.1330.
Data for V-9: Yield = 84%, white solid. mp = 234ꢀ235 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.59 (s, 1H), 8.28ꢀ8.31 (m, 2H), 8.08 (d, J = 8.5 Hz, 2H), 7.94 (d, J = 7.5 Hz, 2H), 7.78 (s,
1H), 7.71 (d, J = 8.5 Hz, 2H), 7.62 (t, J = 7.0 Hz, 1H), 7.55 (t, J = 7.5 Hz, 2H), 7.25 (d, J =
8.0 Hz, 1H), 2.48 (s, 3H). 13C NMR (125 MHz, DMSOꢀd6) δ: 163.4, 142.5, 140.4, 136.3,
135.9, 135.6, 133.8, 132.2, 130.6, 129.6, 129.2, 128.9, 128.0, 126.3, 125.2, 123.5, 119.1,
113.4, 21.9. ESIꢀMS: m/z (%): 452 ([M+H]+, 100). HRMS (ESI): calcd for C23H19N3O3SCl
([M+H])+, 452.0830; found, 452.0832.
Data for V-10: Yield = 82%, yellow solid. mp = 189ꢀ190 oC. 1H NMR (500 MHz, DMSOꢀd6)
δ: 8.70 (s, 1H), 8.59 (s, 1H), 8.52 (dd, J = 8.0 Hz, 1.5 Hz, 2H), 8.40 (s, 1H), 8.32 (d, J = 8.0
11
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 12 of 42
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
Hz, 1H), 7.91ꢀ7.94 (m, 3H), 7.85 (s, 1H), 7.62 (d, J = 7.0 Hz, 1H), 7.55 (t, J = 7.5 Hz, 2H),
7.26 (d, J = 8.0 Hz, 1H), 2.49 (s, 3H). 13C NMR (125 MHz, DMSOꢀd6) δ: 163.4, 148.6, 142.4,
138.4, 136.6, 135.6, 133.8, 133.0, 132.5, 132.2, 129.8, 129.7, 128.9, 128.0, 126.5, 125.3,
123.6, 122.0, 119.6, 113.5, 21.9. ESIꢀMS: m/z (%): 463 ([M+H]+, 100). HRMS (ESI): calcd
for C23H19N4O5S ([M+H])+, 463.1070; found, 463.1078.
Data for V-11: Yield = 79%, white solid. mp = 219ꢀ220 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.83 (s, 1H), 8.64 (s, 1H), 8.59 (s, 1H), 8.17 (d, J = 8.5 Hz, 1H), 8.00 (d, J = 8.0 Hz, 2H),
7.96 (d, J = 7.0 Hz, 2H), 7.87 (d, J = 9.5 Hz, 1H), 7.63 (t, J = 7.5 Hz, 1H), 7.57 (t, J = 7.5 Hz,
2H), 7.46 (d, J = 8.0 Hz, 2H), 2.35 (s, 3H). 13C NMR (125 MHz, DMSOꢀd6) δ: 163.5, 146.9,
141.7, 137.0, 133.8, 133.6, 132.3, 132.1, 131.0, 129.3, 128.9, 128.5, 128.1, 127.5, 119.5,
118.1, 114.8, 107.4, 21.5. ESIꢀMS: m/z (%): 443 ([M+H]+, 100). HRMS (ESI): calcd for
C24H19N4O3S ([M+H])+, 443.1172; found, 443.1174.
Data for V-12: Yield = 93%, yellow solid. mp = 250ꢀ251 oC. 1H NMR (500 MHz, DMSOꢀd6)
δ: 8.82 (s, 1H), 8.75 (s, 1H), 8.70 (s, 1H), 8.62 (d, J = 2.5 Hz, 1H), 8.56 (t, J = 6.5 Hz, 2H),
8.23 (d, J = 8.5 Hz, 1H), 7.88ꢀ7.95 (m, 4H), 7.62 (d, J = 7.0 Hz, 1H), 7.56 (t, J = 7.5 Hz, 2H).
13C NMR (125 MHz, DMSOꢀd6) δ: 163.6, 148.7, 141.4, 138.0, 137.0, 133.6, 133.2, 132.7,
132.3, 132.0, 130.3, 129.7, 128.9, 128.5, 128.1, 127.7, 122.4, 119.4, 118.9, 114.9, 107.8.
ESIꢀMS: m/z (%): 474 ([M+H]+, 100). HRMS (ESI): Calcd for C23H16N5O5S ([M+H])+,
474.0866; found, 474.0878.
Data for V-13: Yield = 74%, yellow solid. mp = 157ꢀ158 oC. 1H NMR (500 MHz, DMSOꢀd6)
δ: 9.30 (s, 1H), 8.67 (s, 1H), 8.63 (s, 1H), 8.32 (dd, J = 9.5 Hz, 2.0 Hz, 1H), 8.21 (d, J = 9.0
Hz, 1H), 8.02 (d, J = 8.0 Hz, 2H), 7.96 (d, J = 7.5 Hz, 2H), 7.63 (t, J = 7.5 Hz, 1H), 7.96 (t, J
= 7.5 Hz, 2H), 7.47 (d, J = 8.5 Hz, 2H), 2.35 (s, 3H). 13C NMR (125 MHz, DMSOꢀd6) δ:
12
ACS Paragon Plus Environment

Page 13 of 42
Journal of Agricultural and Food Chemistry
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
162.9, 146.9, 146.5, 144.2, 142.1, 141.3, 137.5, 133.2, 133.1, 131.7, 130.5, 128.4, 128.0,
127.5, 127.0, 126.8, 121.1, 118.4, 21.0. ESIꢀMS: m/z (%): 463 ([M+H]+, 100). HRMS (ESI):
calcd for C23H19N4O5S ([M+H])+, 463.1070; found, 463.1081.
Data for V-14: Yield = 93%, white solid. mp = 205ꢀ206 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.74 (d, J = 4.0 Hz, 1H), 8.34 (s, 1H), 8.09 (d, J = 7.5 Hz, 2H), 7.92ꢀ7.97 (m, 3H), 7.72 (t, J =
7.0 Hz, 1H), 7.58ꢀ7.63 (m, 3H), 7.53ꢀ7.54 (m, 2H), 7.36ꢀ7.41 (m, 2H), 2.47 (s, 3H). 13C NMR
(125 MHz, DMSOꢀd6) δ: 163.9, 150.7, 136.6, 134.7, 133.9, 131.4, 129.8, 128.2, 127.8, 127.4,
126.7, 125.4, 124.6, 124.1, 121.7, 112.7, 14.7. ESIꢀMS: m/z (%): 418 ([M+H]+, 100). HRMS
(ESI): calcd for C23H20N3O3S ([M+H])+, 418.1219; found, 418.1228.
Data for V-15: Yield = 84%, white solid. mp = 201ꢀ202 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.72 (d, J = 5.5 Hz, 1H), 8.33 (s, 1H), 8.09 (d, J = 7.5 Hz, 2H), 7.98 (d, J = 7.0 Hz, 1H), 7.72
(t, J = 7.5 Hz, 3H), 7.63 (t, J = 7.5 Hz, 2H), 7.36ꢀ7.40 (m, 4H), 2.47 (s, 3H), 2.40 (s, 3H). 13C
NMR (125 MHz, DMSOꢀd6) δ: 163.9, 150.6, 140.3, 137.5, 136.6, 134.7, 133.8, 132.0, 129.8,
128.1, 127.8, 127.4, 126.7, 125.4, 125.0, 124.1, 121.7, 112.7, 20.8, 14.7. ESIꢀMS: m/z (%):
432 ([M+H]+, 100). HRMS (ESI): calcd for C24H22N3O3S ([M+H])+, 432.1376; found,
432.1382.
1
Data for V-16: Yield 90%, white solid. mp = 208ꢀ210 oC. H NMR (500 MHz, DMSOꢀd6) δ:
10.66 (s, 1H), 8.73 (s, 1H), 8.32 (s, 1H), 8.09 (d, J = 7.5 Hz, 2H), 7.97 (d, J = 8.5 Hz, 1H),
7.91 (s, 2H), 7.73 (t, J = 7.5 Hz, 1H), 7.64 (t, J = 7.5 Hz, 2H), 7.39ꢀ7.41 (m, 1H), 7.34 (s, 1H),
7.08 (d, J = 8.0 Hz, 2H), 3.85 (s, 3H), 2.47 (s, 3H). 13C NMR (125 MHz, DMSOꢀd6) δ: 162.3,
137.3, 135.3, 135.2, 130.3, 128.2, 128.0, 127.3, 126.6, 126.5, 125.9, 125.1, 124.5, 122.4,
114.0, 113.3, 55.9, 15.1. ESIꢀMS: m/z (%): 470 ([M+Na]+, 100). HRMS (ESI): calcd for
C24H22N3O4S ([M+H])+, 448.1325; found, 448.1320.
13
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 14 of 42
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
Data for V-17: Yield = 87%, white solid. mp = 196ꢀ198 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
10.93 (s, 1H), 8.72 (d, J = 7.5 Hz, 1H), 8.36 (s, 1H), 8.10 (d, J = 7.0 Hz, 2H), 7.97 (s, 2H),
7.89 (d, J = 7.0 Hz, 1H), 7.74 (t, J = 7.5 Hz, 1H), 7.68 (d, J = 7.5 Hz, 1H), 7.64 (t, J = 7.5 Hz,
13
2H), 7.59 (t, J = 7.5 Hz, 1H), 7.41ꢀ7.42 (m, 1H), 7.36ꢀ7.38 (m, 1H), 2.49 (s, 3H). C NMR
(125 MHz, DMSOꢀd6) δ: 163.1, 151.9, 137.2, 136.4, 135.3, 133.5, 131.8, 130.8, 130.4, 128.7,
128.1, 128.0, 127.3, 127.2, 126.0, 125.1, 124.7, 122.1, 113.3, 15.4. ESIꢀMS: m/z (%): 452
([M+H]+, 100). HRMS (ESI): calcd for C23H19N3O3SCl ([M+H])+, 452.0830; found,
452.0828.
Data for V-18: Yield = 92%, white solid. mp = 220ꢀ221 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.72 (d, J = 4.0 Hz, 1H), 8.30 (s, 1H), 7.92ꢀ7.95 (m, 5H), 7.59 (d, J = 7.0 Hz, 1H), 7.54 (d, J
= 7.0 Hz, 2H), 7.40 (d, J = 8.0 Hz, 3H), 7.36 (d, J = 6.5 Hz, 1H), 2.46 (s, 3H), 2.31 (s, 3H).
13C NMR (125 MHz, DMSOꢀd6) δ: 163.8, 150.7, 145.6, 139.7, 137.7, 134.7, 133.7, 131.4,
130.2, 128.2, 127.8, 127.4, 126.8, 125.3, 124.5, 124.0, 121.5, 112.7, 20.9, 14.7. ESIꢀMS: m/z
(%): 432 ([M+H]+, 100). HRMS (ESI): calcd for C24H22N3O3S ([M+H])+, 432.1376; found,
432.1379.
Data for V-19: Yield = 83%, white solid. mp = 189ꢀ190 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.74 (d, J = 3.0 Hz, 1H), 8.31 (s, 1H), 7.96 (d, J = 7.5 Hz, 3H), 7.74 (s, 2H), 7.37ꢀ7.40 (m,
6H), 2.47 (s, 3H), 2.40 (s, 3H), 2.30 (s, 3H). 13C NMR (125 MHz, DMSOꢀd6) δ: 163.9, 150.6,
145.6, 137.5, 134.7, 133.7, 132.0, 130.1, 128.1, 127.8, 127.4, 126.8, 125.3, 124.9, 124.5,
123.9, 121.6, 112.7, 20.9, 20.8, 14.7. ESIꢀMS: m/z (%): 446 ([M+H]+, 100). HRMS (ESI):
calcd for C25H24N3O3S ([M+H])+, 446.1532; found, 446.1541.
Data for V-20: Yield = 86%, white solid; mp = 191ꢀ192 oC. 1H NMR (500 MHz, DMSOꢀd6) δ:
8.74 (d, J = 5.0 Hz, 1H), 8.31 (s, 1H), 8.02 (d, J = 8.0 Hz, 2H), 7.93ꢀ7.96 (m, 3H), 7.59 (d, J
14
ACS Paragon Plus Environment

Page 15 of 42
Journal of Agricultural and Food Chemistry
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
= 7.0 Hz, 1H), 7.54 (d, J = 7.5 Hz, 2H), 7.35ꢀ7.42 (m, 2H), 7.10 (d, J = 9.0 Hz, 2H), 3.78 (s,
3H), 2.47 (s, 3H). 13C NMR (125 MHz, DMSOꢀd6) δ: 163.8, 150.9, 134.7, 133.9, 131.5,
129.3, 128.2, 127.9, 127.8, 127.4, 127.0, 125.3, 124.6, 123.9, 121.4, 115.1, 114.9, 112.7, 55.7,
14.7. ESIꢀMS: m/z (%): 448 ([M+H]+, 100). HRMS (ESI): calcd for C24H22N3O4S ([M+H])+,
448.1325; found, 448.1321.
Assay of Nematicidal Activity.36 Acetone solutions of compounds V-1
~V-54 and emamectin
benzoate (used as a positive control) were firstly prepared at the concentrations of 5, 10, 25,
50, and 100 mg/L, respectively. Then 10 ꢁL of the above solutions were added to the aqueous
suspension (90 ꢁL) containing approximate 2500 living nematodes (thirdꢀinstar and
fourthꢀinstar larvae of B. xylophilus) per mL. The blank control group was prepared in the
same way but lacked the tested compound. Three replicates in each trial were made and kept
o
at 25 C for 24 h. Finally, the activities of five concentrations of the tested compounds were
monitored under a microscope by recording the death rate of the tested nematodes.
Nematodes that did not move when prodded with a needle were considered dead. The LC50
values of tested compounds were calculated using the probit method.
QSAR Model Development.
Data Set. The experimental data used in this work contained 54 compounds (V-1~V-54). The
nematicidal activity of 54 compounds was expressed as LC50 values (ꢁmol/L) and used as the
dependent variable in the following QSAR study.
Molecular Descriptor Calculation. To obtain a QSAR model, the compound was represented
by structural descriptors. The molecular descriptors were calculated by the following process.
All the compound structures were sketched in HyperChem37 program and preꢀoptimized with
the MM+ molecular mechanics force filed. In order to obtain more precise optimization, the
15
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 16 of 42
343
344
semiꢀempirical quantum chemistry method AM138 was used. The resulted minimum energy
conformations of 54 compounds were input into DRAGON 5.439 software to calculate
345
346
molecular descriptors.
In DARGON, 1664 molecular descriptors were calculated, which including: (a)
347
348
349
350
351
352
353
354
355
356
357
358
359
360
0Dꢀconstitutional descriptors, (b) 1Dꢀfunctional groups counts, atomꢀcentered fragments, (c)
2Dꢀtopological descriptors, walk and path counts, connectivity indices, information indices,
2D autocorrelations, edge adjacency indices, Burden eigenvalues, topological charge index,
eigenvalueꢀbased index, (d) 3DꢀRandic molecular profiles, geometrical descriptors, RDF
descriptors, 3DꢀMoRSE descriptors, WHIM descriptors40, GETAWAY descriptors41, (e)
charge descriptors, (f) molecular properties. The Handbook of Molecular Descriptors42, detail
calculation procedure could be found in which. The list of the aboveꢀmentioned descriptors
and corresponding meanings could be found in the literature references of the DRAGON
package.
To obtain the nonꢀredundant information, constant or nearꢀconstant variables and two
descriptors found to be correlated pairwise (one of any two descriptors with a correlation
coefficient greater than 0.99 was removed) were exlcuded. After the preꢀreduction step, 851
molecular parameters were obtained. Thus, 851 structural descriptors were retained for
subsequent subvariable selection.
361
362
363
364
365
366
Splitting Dataset into Training Set and Test Set. To build and validate the QSAR model, the
studied dataset were divided training set was used to develop the model and test set was used
to validate the external predictive ability of the proposed model. In this study, the Kennard &
Stone (KS) method43 was used to split dataset into a training set and a test set due to its good
performance in other studies. The KS method can be used to rationally select training set and
test set based on the descriptor space.
16
ACS Paragon Plus Environment

Page 17 of 42
Journal of Agricultural and Food Chemistry
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
Feature Selection and QSAR Construction by Genetic AlgorithmꢀMultiple Linear Regression
(GAꢀMLR). In this work, the relationship between bioactivity and structural descriptors was
built by the Genetic algorithmꢀMultiple linear regression (GAꢀMLR) method. Genetic
algorithm44 was performed to search the descriptors pool and select the descriptors relevant to
the bioactivity. Multiple linear regression is a classical linear regression method, the model
constructed by which is simple and could be interpreted easily. In the present work, GAꢀMLR
procedure were performed by the MobyDigs software45 using the correlation coefficient of
leaveꢀoneꢀout cross validation (LOO) as fitness function. When increasing the number of the
descriptors did not increase the crossꢀvalidated correlation coefficient (Q 2LOO) value to any
significant degree, the GA selection was stopped. The corresponding parameters used in the
model building process can be found as follows: population size 100, maximum allowed
descriptors in a model 8 and reproduction/mutation tradeꢀoff 0.5 and the other parameters
were set as default values.
Performance and Applicability Domain Evaluation of the QSAR Model. Several statistic
parameters were adopted to assess the quality of the developed QSAR models such as the
correlation coefficient (R2) for fitness ability, Q2
for internal predictive ability and root
LOO
mean square error (RMSE). Moreover, sevenꢀfold crossꢀvalidation correlation coefficient
(Q27ꢀfold) was also employed to check for reliability and robustness. The external predictive
power of the QSAR model was estimated by the external crossꢀvalidation correlation
coefficient (Q2ext) defined as follows:
m
2
( −
yi y pred
)
∑
Q2
i=1
387
388
=1−
m
( − )2
ext
yi
∑
ytr
i=1
where yi and ypred are the experimental and predicted values of the bioactivity of the
17
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 18 of 42
tr
389
compounds in the test set, respectively;
y
is the averaged value of the dependent variable
390
391
392
393
394
for the training set; and m is the number of the compounds in the test set.
The applicability domain is important for a proposed QSAR model, which is defined by
the nature of the chemicals in the dataset and can be characterized in different way. The
leverage (h) approach46 is the commonly used methodology, which defined as follows:
T
(i =1, …, n )
=
(
hi
−1xTi
)
xi X X
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
where xi is the descriptor rowꢀvector of the query chemical, and X is the n × k matrix of the
dataset (k is the number of model descriptors and n is the number of query compounds). The
warning leverage h* was calculated by 3k’/n, where k’ is the number of variables used in the
QSAR model plus one. If the leverage value of a compound is higher than h*, it is mean that
the predicted activity was the result of extrapolation of the model and may be unreliable. The
Williams plot (leaveꢀoneꢀout crossꢀvalidated standardized errors versus leverage values)
could provide an efficient way for verifing the presence of Y outliers (i.e., compounds with
cross validated standardized residuals greater than three standard deviation units, >3σ) and X
outliers (i.e., compounds with leverage values greater than h*).
RESULTS AND DISCUSSION
Synthesis. As shown in Scheme 1, 3ꢀformylindoles (II-1
VilsmeierꢀHaack formylation reaction of indoles (I-1 I-4) with N,Nꢀdimethylformamide
(DMF) in the presence of phosphorus oxychloride (POCl3). Subsequently, II-1 II-4 reacted
with arylsulfonyl chlorides to afford 3ꢀformylꢀNꢀarylsulfonylindoles (IV-1 IV-13).
3ꢀAcylꢀNꢀarylsulfonylindoles (IV-14 IV-33) were prepared as shown in Scheme 2. Starting
from I-1 I-4, the arylsulfonyl substituents were firstly introduced at their Nꢀ1 position to
afford Nꢀarylsulfonylindoles (III-1
~II-4) were easily obtained by
~
~
~
~
~
~
III-17). Then introduction of the different acyl groups at
18
ACS Paragon Plus Environment

Page 19 of 42
Journal of Agricultural and Food Chemistry
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
the Cꢀ3 position of III-1
~III-17 gave 3ꢀacylꢀNꢀarylsulfonylindoles (IV-14~IV-33). Finally, as
described in Scheme 3, Nꢀarylsulfonylꢀ3ꢀacylindole arylcarbonyl hydrazone derivatives
(V-1~
V-54) were smoothly prepared by the reaction of IV-1
~
IV-33 with the corresponding
hydrazides. The structures of all target compounds were well characterized by 1H NMR, C
NMR, HRMS, MS, and mp. Additionally, to confirm the threeꢀdimensional structural
13
information of V-1~V-54, the singleꢀcrystal structure of V-33 was determined by Xꢀray
crystallography as illustrated in Figure 1. It demonstrated that the substituents on the C=N
bond of V-33 adopted trans configuration. And if the substituents on the C=N bond of V-33
adopted cis configuration, big steric effects could be observed between the indolyl ring and
the arylcarbonylamino group. Crystallographic data (excluding structure factors) for the
structure of V-33 have been deposited with the Cambridge Crystallographic Data Centre as
supplementary publication number CCDC 915720. Copies of the data can be obtained, free of
charge, on application to CCDC, 12 Union Road, Cambridge CB2 1EZ, UK [fax: +44
(0)1223 336033 or eꢀmail: deposit@ccdc.cam.ac.uk].
Nematicidal Activity. The nematicidal activity of V-1~V-54 against B. xylophilus was
indicated in Table 1. Some compounds such as V-6, V-12, V-19, V-20, V-27, V-38, V-39, and
V-49 showed the potent nematicidal activity with the LC50 values ranging from 1 to 2 mg/L.
Especially V-12 and V-39 displayed the best promising nematicidal activity with the LC50
values of 1.0969 and 1.2632 mg/L, respectively. On the other hand, some interesting results
of the structureꢀactivity relationships of V-1
R4 = Ph, introduction of R1 and R2 together as the electronꢀwithdrawing substituents could
lead to the pronounced compound (e.g., V-12 vs. V-1 V-11 and V-13). For example, the LC50
~
V-54 were also observed: a) When R3 = H and
~
of V-12 (containing R1 = 5ꢀCN and R2 = 3ꢀNO2) was 1.0969 mg/L. It is noteworthy that if
19
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 20 of 42
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
introduction of R2 as two electronꢀwithdrawing substituents (such as NO2 and Cl) could result
in the more potent compound V-6 than those containing R2 as one electronꢀwithdrawing
substituent (e.g., V-4 and V-5). That is, electronꢀdeficient of the indolyl ring and the phenyl
ring of Nꢀarylsulfonyl group could favour their nematicidal activity. b) When R1 = H and R3 =
Me, introduction of R2 and R4 together as electronꢀdonating substituents could generally
afford the promising compound (e.g., V-19 vs. V-14
V-19 contains R2 as 4ꢀMe and R4 as (3ꢀMe)Ph with the LC50 value of 1.5955 mg/L. c) When
R1 = 6ꢀMe and R3 = Me (V-27 V-45), introduction of R2 as H, 4ꢀOMe or 4ꢀCl and R4 as Ph
could produce the promising compounds (e.g., V-27, V-38 and V-39). d) When R3 = Me and
R4 = Ph (V-46 V-51), introduction of R1 as 5ꢀNO2 and R2 as H could lead to the pronounced
~V-18 and V-20~V-26). For example,
~
~
compound (e.g., V-49). e) Interestingly, the proper chain length of R3 was essential for the
nematicidal activity. For example, the LC50 values of V-52 (R3 = Et) and V-53 (R3 = nꢀpentyl)
were 3.7058 and 6.6758 mg/L, respectively; whereas the LC50 value of V-14 (R3 = Me) was
2.3985 mg/L. All in all, introduction of R1 and R2 together as the electronꢀwithdrawing
substituents, R3 as the methyl group, and R4 as the phenyl with the electronꢀdonating
substituents could be taken into account for further preparation of this kind of compounds as
nematicidal agents.
QSAR Model. Through the KS method, a training set containing 40 compounds and a test set
containing 14 compounds were obtained. To select the molecular parameters that are most
relevant to the LC50 values of the compounds, 851 structural descriptors calculated by the
DRAGON 5.4 were used as the inputs for GA selection procedure. When adding another
variable did not improve the performance of the model significiently, the optimal subset size
was believed to obtain. In the current work, the LOO cross validation was used to evaluate
20
ACS Paragon Plus Environment

Page 21 of 42
Journal of Agricultural and Food Chemistry
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
the proposed QSAR models. On the basis of this principle, the sixꢀvariable model was
selected as the best model. The corresponding regression equation and the statistical
parameters were
Y = –0.377EEig05x – 0.421EEig13d + 0.467BEHm8 + 0.967E1m + 0.693R1m+ –
0.694R3m+ –17.276
Where Y is the LC50 values (ꢁmol/L).
ntraining set = 40
R2
= 0.791
RMSEtraining set = 3.279
Q2
= 0.701
LOO
training set
RMSELOO = 3.929
Q27ꢀfold = 0.715
RMSE7ꢀfold = 0.370
ntest set =14
Q2ext = 0.774 RMSEtest set = 3.412
The best sixꢀparameter model gave the correlation coefficient (R2training set), Q2
and
LOO
Q2
were 0.791, 0.701 and 0.715, respectively. The prediction ability of a QSAR model is
7ꢀfold
very important, and statistical parameters for the test set were Q2ext = 0.774 and RMSEtest set
=
3.412, which is satisfactory. From the statistical parameters discussed above, it indicates that
the proposed model is stable, robust and predictive. The predicted LC50 values by the derived
model are listed in Table 2, and the regression plot of the developed best model is shown in
Figure 2.
From a deep analysis of the descriptors used in the proposed model, we could gain some
insight into the factors that would influence the bioactivity of the compounds. The relative
importance of the descriptors is weighted by the standardized regression coefficient value of
the descriptor. The most important descriptor is the E1m (1st component accessibility
directional WHIM index/weighted by atomic masses), which is a WHIM descriptor. WHIM
descriptors are built in such a way to capture relevant molecular 3D information regarding
molecular size, shape, symmetry, and atom distribution with respect to invariant reference
21
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 22 of 42
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
frames. R1m+ is a GETAWAY descriptor, which represents R maximal autocorrelation of lag
1/weighted by atomic masses. Another important descriptor is R3m+ (R maximal
autocorrelation of lag 3/weighted by atomics masses), which also belongs to GETAWAY
descriptor. GETAWAY (Geometry, Topology, and AtomꢀWeightsꢀAssembly) is derived from
the leverage matrix which is deduced by the centering all of the atomic coordinates. BEHm8
is a Burden eigenvalues descriptor weighted by atomics masses. The above four descriptors
all are weighted by atomics masses, that represents atomics masses having an important
correlation with the bioꢀability. EEig05x represents Eigenvalue 05 from edge adjacency
matrix weighted by edge degrees, which belongs to edge adjacency indices. EEig13d is an
edge adjacency indices descriptor similar to EEig05x, and the difference is that EEig13d is
weighted by dipole moments. It can be seen from the above discussion about the descriptors
that the structural factors that are likely to govern the activities of these compounds including:
molecular masses (a negative correlation with the bioactivity) and molecular polarity (a
positive correlation with bioactivity).
QSAR model should be verified by their chemical domain applicability. In this work, as
shown in Figure 3, the applicability domain (AD) of the model and the reliability of the
prediction were evaluated by the leverage approach expressed as Williams plot. It is obvious
that only one compound (V-6) in the training set has the hat value higher than the warning h*
value of 0.525, and thus is regarded as a structural outlier. The predicted value of this
compound would be more reliable when regarded as extrapolation of the model, but the
compound has a small residual, so it is a “good leverage” compound. There is no response
outlier both for the training set and test set.
In conclusion, fiftyꢀfour novel Nꢀarylsulfonylꢀ3ꢀacylindole arylcarbonyl hydrazone
22
ACS Paragon Plus Environment

Page 23 of 42
Journal of Agricultural and Food Chemistry
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
derivatives (V-1
~
V-54) were prepared and tested for their nematicidal activity against B.
xylophilus in vivo. Among all the compounds, V-12 and V-39 displayed the best promising
nematicidal activity with the LC50 values of 1.0969 and 1.2632 mg/L, respectively. It
generally suggested that introduction of R1 and R2 together as the electronꢀwithdrawing
substituents, R3 as the methyl group, and R4 as the phenyl with the electronꢀdonating
substituents can be considered for future preparation of this kind of compounds as
nematicidal agents. QSAR model demonstrated that the structural factors, such as molecular
masses (a negative correlation with the bioactivity) and molecular polarity (a positive
correlation with bioactivity), are likely to govern the nematicidal activities of these
compounds.
ASSOCIATED CONTENT
Supporting Information
1H NMR, HRMS, MS, mp, or 13C NMR data for compounds III-3~III-17, IV-3~IV-13,
IV-16~IV-33, and V-21~V-54. This material is available free of charge via the Internet at
http://pubs.acs.org.
AUTHOR INFORMATION
Corresponding Author
*Telephone:
+86ꢀ029ꢀ87091952.
Fax:
+86ꢀ029ꢀ87091952.
Email:
orgxuhui@nwsuaf.edu.cn.
Funding
The present research was supported by National Natural Science Foundation of China
No.31171896), and the Special Funds of Central Colleges Basic Scientific Research
23
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 24 of 42
527
528
529
Operating Expenses (YQ2013008).
Notes
The authors declare no competing financial interest.
24
ACS Paragon Plus Environment

Page 25 of 42
Journal of Agricultural and Food Chemistry
530
25
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 26 of 42
REFERENCES
(1) Park, I. K.; Park, J. Y.; Kim, K. H.; Choi, K. S.; Choi, I. H.; Kim, C. S.; Shin, S. C.
Nematicidal activity of plant essential oils and components from garlic (Allium sativum)
and cinnamon (Cinnamomum verum) oils against the pine wood nematode
(Bursaphelenchus xylophilus). Nematology 2005, 7, 767−774.
(2) Qui, S. J.; Can, J. Y.; Liu, W. P.; Becker, J. O. Degradation and absorption of fosthiazate
in soil. J. Agric. Food Chem. 2004, 52, 6239−6242.
(3) Meher, H. C.; Gajbhiye, V. T.; Chawla, G.; Singh, G. Virulence development and genetic
polymorphism in Meloidogyne incognita (Kofoid & White) Chitwood after prolonged
exposure to sublethal concentrations of nematicides and continuous growing of resistant
tomato cultivars. Pest Manag. Sci. 2009, 65, 1201−1207.
(4) Ntalli, N. G.; Caboni, P. Botanical nematicides: A review. J. Agric. Food Chem. 2012, 60,
9929−9940.
(
5) Seo, S. –M.; Kim, J.; Kim, E.; Park, H. –M.; Kim, Y. –J.; Park, I. –K. Structure−activity
relationship of aliphatic compounds for nematicidal activity against pine wood nematode
(Bursaphelenchus xylophilus). J. Agric. Food Chem. 2010, 58, 1823–1827.
(6) Faizi, S.; Fayyaz, S.; Bano, S.; Iqbal, E. Y.; Lubna, Siddiqi, H.; Naz, A. Isolation of
nematicidal compounds from Tagetes patula L. yellow flowers: Structure–activity
relationship studies against cyst nematode Heterodera zeae infective stage larvae. J. Agric.
Food Chem. 2011, 59, 9080–9093.
(7) Caboni, P.; Ntalli, N. G.; Aissani, N.; Cavoski, I.; Angioni, A. Nematicidal activity of
(E,E)ꢀ2,4ꢀdecadienal and (E)ꢀ2ꢀdecenal from Ailanthus altissima against meloidogyne
javanica. J. Agric. Food Chem. 2012, 60, 1146–1151.
26
ACS Paragon Plus Environment

Page 27 of 42
Journal of Agricultural and Food Chemistry
(8) Caboni, P.; Sarais, G.; Aissani, N.; Tocco, G.; Sasanelli, N.; Liori, B.; Carta, A.; Angioni, A.
Nematicidal activity of 2ꢀthiophenecarboxaldehyde and methylisothiocyanate from caper
(Capparis spinosa) against Meloidogyne incognita. J. Agric. Food Chem. 2012, 60,
7345–7351.
(9) Ntalli, N. G.; Ferrari, F.; Giannakou, I. O.; MenkissogluꢀSpiroudi, U. Synergistic and
antagonistic interactions of terpenes against Meloidogyne incognita and nematicidal
activity of essential oils from 7 plants indigenous in Greece. Pest Manag. Sci. 2011, 67,
341−351.
(10) Zasada, I. A.; Meyer, S. L. F.; Morra, M. J. Brassicaceous seed meals as soil amendments
to suppress the plantꢀparasitic nematodes Pratylenchus penetrans and Meloidogyne
incognita. J. Nematol. 2009, 41, 221−227.
(11) Campbell, B. E.; Tarleton, M.; Gordon, C. P.; Sakoff, J. A.; Gilbert, J.; McCluskey, A.;
Gasser, R. B. Norcantharidin analogues with nematocidal activity in Haemonchus
contortus. Bioorg. Med. Chem. Lett. 2011, 21, 3277−3281.
(12) Isman, M.B. Botanical insecticides, deterrents, and repellents in modern agriculture and
an increasingly regulated world. Annu. Rev. Entomol. 2006, 51, 45−66.
(13) Chitwood, D. J. Phytochemical based strategies for nematode control. Annu. Rev.
Phytopathol. 2002, 40, 221−249.
(14) Chen, J. T.; Su, H. J.; Huang, J. W. Isolation and identification of secondary
metabolites of Clitocybe nuda responsible for inhibition of zoospore germination of
phytophthora capsici. J. Agric. Food Chem. 2012, 60, 7341−7344.
(15) Zhou, Y. Y. ; Luo, S. H.; Yi, T. S.; Li, C. H.; Luo, Q.; Hua, J.; Liu, Y.; Li, S. H.
Secondary metabolites from Glycine soja and their growth inhibitory effect against
27
ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry
Page 28 of 42
Spodoptera litura. J. Agric. Food Chem. 2011, 59, 6004−6010.
(16) Isman, M. B. Botanical insecticides: for richer, for poorer. Pest Manag. Sci. 2008, 64,
8−11.
(17) RegnaultꢀRoger, C.; Philogène, B. J. R. Past and current prospects for the use of
botanicals and plant allelochemicals in integrated pest management. Pharmaceut. Biol.
2008, 46, 41−52.
(18) Dayan, F. E.; Cantrell, C. L.; Duke, S. O. Natural products in crop protection. Bioorg.
Med. Chem. 2009, 17, 4022−4034.
(19) Xu, H.; Lv, M. Developments of indoles as antiꢀHIVꢀ1 inhibitors. Curr. Pharm. Des.
2009, 15, 2120−2148.
(20) Silvestri, R.; Artico, M. Indolyl aryl sulfones (IASs): Development of highly potent
NNRTIs active against wtꢀHIVꢀ1 and clinically relevant drug resistant mutants. Curr.
Pharm. Des. 2005, 11, 3779−3806.
(21) Chen, K. X.; Vibulbhan, B.; Yang, W. Y.; Sannigrahi, M.; Velazquez, F.; Chan, T. Y.;
Venkatraman, S.; Anilkumar, G. N.; Zeng, Q. B.; Bennet, F.; Jiang, Y. H.; Lesburg, C.
A.; Duca, J.; Pinto, P.; Gayalas, S.; Huang, Y. H.; Wu, W. L.; Selyutin, O.; Agrawal, S.;
Feld, B.; Huang, H. C.; Li, C.; Cheng, K. C.; Shih, N. Y.; Kozlowski, J. A.; Rosenblum,
S. B.; Njoroge, F. G. Structureꢀactivity relationship (SAR) development and discovery of
potent indoleꢀbased inhibitors of the hepatitis C virus (HCV) NS5B polymerase. J. Med.
Chem. 2012, 55, 754−765.
(22) Singh, P.; Verma, P.; Yadav, B.; Komath, S. S. Synthesis and evaluation of indoleꢀbased
new scaffolds for antimicrobial activitiesꢀidentification of promising candidates. Bioorg.
Med. Chem. Lett. 2011, 21, 3367−3372.
28
ACS Paragon Plus Environment

Page 29 of 42
Journal of Agricultural and Food Chemistry
(23) Grella, B.; Adams, J.; Berry, J. F.; Delahanty, G.; Ferraris, D. V.; Majer, P.; Ni, C. Y.;
Shukla, K.; Shuler, S. A.; Slusher, B. S.; Stathis, M.; Tsukamoto, T. The discovery and
structureꢀactivity relationships of indoleꢀbased inhibitors of glutamate carboxypeptidase II.
Bioorg. Med. Chem. Lett. 2010, 20, 7222−7225.
(24) Xu, H.; Fan, L. Synthesis and antifungal activities of novel
5,6ꢀdihydroꢀindolo[1,2ꢀa]quinoxaline derivatives. Eur. J. Med. Chem. 2011, 46,
1919−1925.
(25) Guo, Y.; Yan, Y.; Yang, C.; Yu, X.; Zhi, X.; Xu, H. Regioselective synthesis of
fraxinelloneꢀbased hydrazone derivatives as insecticidal agents. Bioorg. Med. Chem. Lett.
2012, 22, 5384–5387.
(26) Ran, J. Q.; Huang, N.; Xu, H.; Yang, L. M.; Lv, M.; Zheng, Y. T. Anti HIVꢀ1 agents 5:
Synthesis and antiꢀHIVꢀ1 activity of some Nꢀarylsulfonylꢀ3ꢀacetylindoles in vitro. Bioorg.
Med. Chem. Lett. 2010, 20, 3534–3536.
(27) Guo, Y.; Yan, Y.; Yu, X.; Wang, Y.; Xu, H. Synthesis and insecticidal activity of some
novel fraxinelloneꢀbased esters. J. Agric. Food Chem. 2012, 60, 7016–7021.
(28) Wang, Y.; Shao, Y.; Wang, Y.; Fan, L.; Yu, X.; Zhi, X.; Yang, C.; Qu, H.;Yao, X.; Xu, H.
Synthesis and quantitative structureꢀactivity relationship (QSAR) study of novel
isoxazoline and oxime derivatives of podophyllotoxin as insecticidal agents. J. Agric.
Food Chem. 2012, 60, 8435–8443.
(29) Ge, Y. H.; Wu, Y. M.; Xue, Z. J. Synthesis of substituted indoleꢀ3ꢀcarboxaldehyde
derivatives. Chin. J. Org. Chem. 2006, 26, 563–567.
(30) Nishimura, T.; Yamada, T.; Takebe, T.; Yokoshima, S.; Fukuyama, T.
(1ꢀNosylꢀ5ꢀnitroindolꢀ3ꢀyl)methyl ester: A novel protective group for carboxylic acids.
29
ACS Paragon Plus Environment