Structure-Based Virtual Screening, Compound Synthesis, and Bioassay for the Design of Chitinase Inhibitors

Article abstract of DOI:10.1021/acs.jafc.8b00017

Chitinases play a vital part in the molting phase of insect pests. Inhibiting their activities by the use of drug-like small chemical molecules is thought to be an efficient strategy in pesticide design and development. On the basis of the crystal structure of OfChtI, a chitinase indispensable for the molting of the insect pest Ostrinia furnacalis (Asian corn borer), here we report a chemical fragment and five variant compounds as inhibitors of OfChtI obtained from a library of over 200?000 chemicals by a structure-based-virtual-screening approach. The compounds were synthesized with high atom economy and tested for their OfChtI-inhibitory activities in a bioassay. Compound 3 showed preferential inhibitory activity with a K_i value of 1.5 μΜ against OfChtI. Analysis of the structure-activity relationships of the compounds provided insight into their interactions with the enzyme active site, which may inform future work in improving the potencies of their inhibitory activities.

Full text of DOI:10.1021/acs.jafc.8b00017

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Agricultural and Environmental Chemistry
Structure-based Virtual Screening, Compound Synthesis
and Bioassay for the Design of Chitinase Inhibitors
Yawen Dong, Xi Jiang, Tian Liu, Yun Ling, Qing Yang, Li Zhang, and Xiongkui He
J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b00017 • Publication Date (Web): 20 Mar 2018
Downloaded from http://pubs.acs.org on March 20, 2018
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Structure-based Virtual Screening, Compound Synthesis and Bioassay for the Design of
Chitinase Inhibitors
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Yawen Dong,† Xi Jiang,‡ Tian Liu,‡ Yun Ling,† Qing Yang,*,‡ Li Zhang,*,† and Xiongkui He†
† Department of Applied Chemistry, College of Science, China Agricultural University, Beijing
100193, China.
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‡ State Key Laboratory of Fine Chemicals and School of Life Science and Biotechnology, Dalian
University of Technology, Dalian 116024, China.
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*Corresponding Author:
Dr. Li Zhang,
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Tel: +86ꢀ010ꢀ6273ꢀ0345
Fax: +86ꢀ010ꢀ6273ꢀ0345
Eꢀmail: zhang_li@cau.edu.cn
Prof. Qing Yang,
Tel: +86ꢀ411ꢀ8470ꢀ7245
Fax: +86ꢀ411ꢀ8470ꢀ7245
Eꢀmail: qingyang@dlut.edu.cn
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ABSTRACT
Chitinases play a vital part in the molting phase of insect pests. Inhibiting their activities by the use
of drugꢀlike small chemical molecules is thought to be an efficient strategy in pesticide design and
development. Based on the crystal structure of OfChtI, a chitinase indispensable for molting of the
insect pest Ostrinia furnacalis (Asian corn borer), here we report a chemical fragment and five
variant compounds as inhibitors of OfChtI obtained from a library of over 200,000 chemicals by a
structureꢀbased virtual screening approach. The compounds were synthesized with high atom
economy and tested for their OfChtI inhibitory activities in a bioassay. Compound 3 showed
preferential inhibitory activity with a Ki value of 1.5 ꢁΜ against OfChtI. Analysis of the
structureꢀactivity relationships of the compounds provided insight into their interactions with the
enzyme active site, which may inform future work to improve the potency of the inhibitory activity.
KEYWORDS: chitinase, inhibitors, fragment, structureꢀbased virtual screening, structureꢀactivity
relationship
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INTRODUCTION
Chitin, a longꢀchain polymer composed of βꢀ1,4 linked NꢀacetylꢀDꢀglucosamine (GlcNAc), is a
vital structural component of insects.1 As well as being important for insect growth and development,
it also supports the integrity of the cuticle that is secreted by the epidermal cells. The cuticle takes the
shape of the exoskeleton and has only a limited ability to expand as the insect grows, so it undergoes
periodic degradation to allow molting, and is then reꢀsynthesized as part of the new exoskeleton that
is formed after molting has occurred.2 Solid state NMR spectroscopy has shown that the composition
of chitin differs considerably between different types of insect cuticles, and that it can make up to 40%
of the exuvial dry mass depending upon the insect species.3 Given the obvious importance of chitin
as a structural component of insects, there is much interest in understanding whether and how its
activity or production could be inhibited as a novel approach to the control of insect pests.
During the molting stage of insects, the glycoside hydrolase family 18 (GH18) chitinases (EC
3.2.1.14),4,5 that are secreted from epithelial cells, are key enzymes that catalyze the hydrolysis of
chitinous components of the old cuticle into constituent oligosaccharides.6,7 It is clear that if the
activities of GH18 chitinases were blocked by small molecule inhibitors, the molting process would
be disrupted and growth and development would not continue in the normal way, possibly even
resulting in death. Thus, small molecule chitinase inhibitors represent promising candidates for the
design and development of novel pesticides for the control of insect pests.8ꢀ13
Several known GH18 chitinase inhibitors have already been described in the literatures; some of
these are natural products, such as allosamidin,14ꢀ16 argifin,17 argadin,18 cycloꢀ(LꢀArgꢀDꢀPro),19
psammaplin,20 styloguanidine,21 and (GlcN)5;22 others are chemically manufactured, such as
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pentoxifylline and its analogs,23 and biodionin B and its derivatives.24 However, whilst such chitinase
inhibitors have been reported, their widespread use is impeded by the fact that they are difficult to be
synthesized and their effects can be relatively weak. Thus, researches need to be carried out to
identify more potent and easily synthesizable inhibitors of chitinase.
Recently, structureꢀbased virtual screening (SBVS) and fragmentꢀbased drug discovery have been
rapidly developed as e ective methods to identify hits.25ꢀ28 Having characterized the crystal
structures of chitinase as well as the coꢀcrystal structures of enzymeꢀinhibitor complexes, the
structureꢀactivity relationships have been revealed, and SBVS has been used to identify potential
chitinase inhibitors.29ꢀ31 A typical GH18 chitinase usually possesses a long cleftꢀlike catalytic domain
with multiple binding subsites labelled by +2, +1, ꢀ1, ꢀ2, ꢀ3, ꢀ4, and ꢀ5, respectively, and catalysis
always occurs between the subsites +1 and ꢀ1.32 Not surprisingly, chitinase structural biology studies
have offered valuable opportunities in the rational design of new and bioꢀavailable inhibitors via in
silico analysis.33
A chitinase of GH18 from the agricultural pest Ostrinia furnacalis (Asian corn borer), OfChtI,
plays a critical role in the degradation of old cuticle during the molting stage, and is deemed to be a
potential target for the development of effective chitinase inhibitors. To date, there have been few
reports of OfChtI inhibitors. They are known to have complex structures.22,30,34 In this study, we
utilized the reported crystal structure of the chitinase OfChtI with its bound ligand, (GlcNAc)3,35 to
obtain inhibitors with high potency and that are easy to synthesize. Using a combination of SBVS
and
biological
evaluation,
we
sought
to
obtain
a
fragment
of
2ꢀaminoꢀ6ꢀmethylꢀ4,5,6,7ꢀtetrahydroꢀbenzo[b]thiopheneꢀ3ꢀcarboxylic acid ethyl ester, from which to
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develop potent inhibitors against OfChtI. The synthetic route used in the synthesis of the inhibitor
compound facilitated an atomꢀeconomic means of designing the final compound, which would
improve the sustainability of its manufacture on a larger scale.
MATERIALS AND METHODS
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Chemical Database Preparation. The chemical database SPECS,36 a library of 200,000 single
synthesized wellꢀcharacterized small molecules, was used for structureꢀbased virtual screening in
order to identify potential candidate compounds. The descriptors of all the screened molecules, such
as their molecular weight (MW), octanolꢀwater partition coefficient (Clog P), number of rotatable
bonds (ROB), number of aromatic bonds (ARB), number of Hꢀbond acceptors (HBA), and number
of Hꢀbond donors (HBD), were calculated by the Descriptors Program of Molecular Operating
Environment drug discovery modelling software (MOE 2016.08).37 The molecules were then
evaluated according to whether they fulfilled certain ‘pesticideꢀlikeness’ parameters, as defined by
Gefei Hao et al.,38 and those that did not meet the criteria were filtered out of the database.
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Pharmacophore-based Screening. Pharmacophoreꢀbased screening was carried out using the
Virtual Screening program of MOE modelling software (MOE 2016.08). Two crystal structures of
OfChtI with the bound ligands were downloaded from the RCSB Protein Data Bank (PDB ID: 3WL1
and 3WQV),35 and were used to establish a wellꢀtested pharmacophore model. On the basis of the
alignment and superposition of the two crystal structures, the spatial positioning and interactions
between receptor and ligand were analyzed carefully and the common features, such as the
hydrophobic center and hydrogen bond acceptor and donor, were set as pharmacophore features.
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These features were then used to screen the dataset of molecular candidates obtained from the
SPECS database. Molecules not containing the defined pharmacophore features were screened out of
the dataset.
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Molecular Docking. Molecular docking was employed in order to generate elementary prediction
of the binding modes and energies between the protein (OfChtI) and the candidate molecules. The
coꢀcrystal structure of OfChtI with its bound ligand (GlcNAc)3 (PDB ID: 3WL1) was used as a
template for the molecular docking. To prepare the protein structure, the Structure Preparation
function in MOE was used. The process included assessing the quality of the protein structure data
using defined temperature factors, protein geometry checks and electron density checks, adding
hydrogen atoms and optimizing their positions, and performing final energy minimization of the
structure. Following this, molecular docking was performed by the Dock application of MOE, with
two rounds of calculation. A collection of poses were generated from the pool of ligand
conformations using the Triangle Matcher method, and were further refined using the Rigid Receptor
method in MOE. Finally, a generalized Born/volume integral implicit solvent model, GBVI/WSA dG,
developed by Labute39 was used for scoring each of the generated poses, and for each compound the
pose with the lowest score was retained. Compounds were then ranked low to high based on the
scores.
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Cluster Analysis. In order to categorize the compounds obtained by molecular docking on the
basis of their structural diversity, the SAReport program in MOE was used in accordance with the
method presented by Alex.40 A grid of molecule fragments was constructed to reveal common
molecular scaffold classes and statistics on the number of matched molecules, number of heavy
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atoms and maximum similarity to any already picked molecular scaffold were calculated.
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Chemicals and Instruments. All laboratory reagents were acquired from Ouhe Corporation
(Beijing, China) and were of analytical grade. The target compounds were purified by column
chromatography on silica gel 60, 200ꢀ300 mesh (Puke Corporation, Qingdao, China). Melting points
of the compounds were measured using an Xꢀ4 binocular microscope (Fukai Corporation, Beijing,
China) with uncorrected values. The 1H NMR and 13C NMR spectra of the purified target compounds
were determined by an AMꢀ300 spectrometer (Bruker, Bremen, Germany) at 300 MHz for 1H and 75
13
MHz for C, respectively. Deuteriochloroform (CDCl3) or DMSOꢀd6 was used as the solvent and
tetramethylsilane (TMS) was used as the internal standard. High resolution mass spectrometry
(HRMS) data were obtained on a 7.0T FTICRꢀMS instrument (Varian, Palo Alto, CA).
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General Procedure for the Synthesis of the Precursors 2aꢀ5a and 1. As shown in Figure 1, the
elemental sulfur (1 equiv.) was added into the mixture of substituted cyclohexanone (1 equiv.) and
cyano compound (1 equiv.) in ethanol. Then the morpholine (1 equiv.) was added dropwise as a base
of catalyst. The reaction mixture was stirred at 85
for about 5 h. After that, the solvent was
evaporated and the residue was dissolved in ethyl acetate. The organic layer was washed with water,
dried with anhydrous sodium sulfate, filtered and evaporated for purification.
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2ꢀAminoꢀ5ꢀmethylꢀ4,5,6,7ꢀtetrahydroꢀbenzo[b]thiopheneꢀ3ꢀcarboxylic acid ethyl ester (2a) was
synthesized in line with the general procedure with 3ꢀmethylcyclohexanone (1 g, 8.9 mmol), ethyl
cyanoacetate (1.007 g, 8.9 mmol) and elemental sulfur (0.285 g, 8.9 mmol) in ethanol (8 mL). The
crude product was purified with column chromatography on silica gel (Petroleumether ether/ethyl
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acetate = 10:1, v/v). White solid; yield 89.12%; mp: 70ꢀ71 ; 1H NMR (300 MHz, CDCl3) δ 5.94 (s,
2H), 4.26 (q, J = 7.1 Hz, 2H), 2.99ꢀ2.84 (m, 1H), 2.66ꢀ2.34 (m, 2H), 2.27ꢀ2.09 (m, 1H), 1.90ꢀ1.68 (m,
2H), 1.46ꢀ1.27 (m, 1H), 1.33 (t, J = 7.1 Hz, 3H), 1.04 (d, J = 6.6 Hz, 3H).
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2ꢀAminoꢀ6ꢀmethylꢀ4,5,6,7ꢀtetrahydroꢀbenzo[b]thiopheneꢀ3ꢀcarboxylic acid propyl ester (3a) was
synthesized in line with the general procedure with 4ꢀmethylcyclohexanone (0.5 g, 4.5 mmol), propyl
cyanoacetate (0.572 g, 4.5 mmol) and elemental sulfur (0.144 g, 4.5 mmol) in ethanol (5 mL). The
crude product was purified with column chromatography on silica gel (Petroleumether ether/ethyl
acetate = 10:1, v/v). White solid; yield 82.80%; mp: 62ꢀ63 ; 1H NMR (300 MHz, CDCl3) δ 7.21 (s,
2H), 4.06 (t, J = 6.5 Hz, 2H), 2.77 (d, J = 16.9 Hz, 1H), 2.59ꢀ2.39 (m, 2H), 2.12ꢀ1.96 (m, 1H),
1.84ꢀ1.71 (m, 2H), 1.71ꢀ1.55 (m, 2H), 1.36ꢀ1.16 (m, 1H), 0.98 (d, J = 6.5 Hz, 3H), 0.93 (t, J = 7.4 Hz,
3H).
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2ꢀAminoꢀ6ꢀtertꢀbutylꢀ4,5,6,7ꢀtetrahydroꢀbenzo[b]thiopheneꢀ3ꢀcarboxylic acid ethyl ester (4a) was
synthesized in line with the general procedure with 4ꢀtertꢀbutylcyclohexanone (1 g, 6.5 mmol), ethyl
cyanoacetate (0.735 g, 6.5 mmol) and elemental sulfur (0.208 g, 6.5 mmol) in ethanol (10 mL). The
crude product was purified with column chromatography on silica gel (Petroleumether ether/ethyl
acetate = 30:1, v/v). Yellow liquid; yield 85.70%; 1H NMR (300 MHz, CDCl3) δ 5.93 (s, 2H), 4.25 (q,
J = 7.1 Hz, 2H), 3.04ꢀ2.89 (m, 1H), 2.58ꢀ2.41 (m, 2H), 2.35ꢀ2.21 (m, 1H), 2.02ꢀ1.88 (m, 1H),
1.53ꢀ1.39 (m, 1H), 1.33 (t, J = 7.1 Hz, 3H), 1.30ꢀ1.18 (m, 1H), 0.91 (s, 9H).
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2ꢀAminoꢀ6ꢀmethylꢀ4,5,6,7ꢀtetrahydroꢀbenzo[b]thiopheneꢀ3ꢀcarboxylic acid isopropyl ester (5a)
was synthesized in line with the general procedure with 4ꢀmethylcyclohexanone (1.000 g, 8.9 mmol),
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isopropyl cyanoacetate (1.134 g, 8.9 mmol) and elemental sulfur (0.286 g, 8.9 mmol) in ethanol (10
mL). The crude product was purified with column chromatography on silica gel (Petroleumether
1
ether/ethyl acetate = 50:3, v/v). Yellow solid; yield 86.68%; mp: 67ꢀ68 ; H NMR (300 MHz,
CDCl3) δ 5.89 (s, 2H), 5.31ꢀ5.04 (m, 1H), 2.94ꢀ2.79 (m, 1H), 2.68ꢀ2.48 (m, 2H), 2.19ꢀ2.01 (m, 1H),
1.94ꢀ1.76 (m, 2H), 1.42ꢀ1.21 (m, 1H), 1.32 (d, J = 2.9 Hz, 3H), 1.30 (d, J = 2.9 Hz, 3H), 1.04 (d, J =
6.5 Hz, 3H).
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2ꢀAminoꢀ6ꢀmethylꢀ4,5,6,7ꢀtetrahydroꢀbenzo[b]thiopheneꢀ3ꢀcarboxylic acid ethyl ester (1) was
synthesized in line with the general procedure with 4ꢀmethylcyclohexanone (1 g, 8.9 mmol), ethyl
cyanoacetate (1.009 g, 8.9 mmol) and elemental sulfur (0.286 g, 8.9 mmol) in ethanol (10 mL). The
crude product was purified with column chromatography on silica gel (Petroleumether ether/ethyl
1
acetate = 50:1, v/v). Yellow solid; yield 86.98%; mp: 106ꢀ107 ; H NMR (300 MHz, DMSOꢀd6) δ
7.19 (s, 2H), 4.13 (q, J = 7.1 Hz, 2H), 2.75 (d, J = 17.3 Hz, 1H), 2.56ꢀ2.29 (m, 2H), 2.13ꢀ1.88 (m,
13
1H), 1.82ꢀ1.51 (m, 2H), 1.37ꢀ1.10 (m, 1H), 1.23 (t, J = 7.1 Hz, 3H), 0.97 (d, J = 6.5 Hz, 3H). C
NMR (75 MHz, DMSOꢀd6) δ 165.11, 163.07, 130.98, 115.03, 102.63, 58.62, 32.12, 30.73, 29.01,
26.32, 21.30, 14.40.
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General Procedure for the Synthesis of the Target Compounds 2-6. As shown in Figure 1, the
acyl chloride (1.1 equiv.) was added dropwise in the mixture of the precursor (1 equiv.) and TEA (1.2
equiv.) in dichloromethane at 0 . The reaction mixture was stirred overnight at room temperature.
After that, the organic layer was washed with 1 mol/L HCl solution, saturated sodium bicarbonate
solution and water, dried with anhydrous sodium sulfate, filtered and evaporated for purification.
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2ꢀ(3,4ꢀDimethoxybenzamido)ꢀ5ꢀmethylꢀ4,5,6,7ꢀtetrahydroꢀbenzo[b]thiopheneꢀ3ꢀcarboxylate acid
ethyl ester (2) was synthesized in line with the general procedure with compound 2a (0.7 g, 2.9
mmol) and 3,4ꢀdimethoxybenzoyl chloride (0.64 g, 3.2 mmol). The crude product was purified with
1
crystallization from ethyl acetate. White solid; yield 87.0%; mp: 114ꢀ115 ; H NMR (300 MHz,
CDCl3) δ 12.26 (s, 1H), 7.62 (d, J = 2.0 Hz, 1H), 7.55 (dd, J = 8.4, 2.0 Hz, 1H), 6.94 (d, J = 8.4 Hz,
1H), 4.37 (q, J = 7.1 Hz, 2H), 3.97 (s, 3H), 3.94 (s, 3H), 3.05ꢀ2.95 (m, 1H), 2.75ꢀ2.66 (m, 2H),
2.32ꢀ2.20 (m, 1H), 1.87 (t, J = 13.4 Hz, 2H), 1.50ꢀ1.34 (m, 1H), 1.40 (t, J = 7.1 Hz, 3H), 1.08 (d, J =
13
6.5 Hz, 3H). C NMR (75 MHz, CDCl3) δ 166.65, 162.71, 152.23, 148.92, 148.30, 130.65, 126.13,
124.89, 119.76, 111.17, 110.61, 110.22, 60.17, 55.72, 55.69, 34.49, 30.77, 28.62, 23.83, 21.39, 14.01.
HRMS calculated for C21H25NO5S (M+H)+: 404.1526, found: 404.1524.
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2ꢀ(3ꢀCyclopentylpropanamido)ꢀ6ꢀmethylꢀ4,5,6,7ꢀtetrahydroꢀbenzo[b]thiopheneꢀ3ꢀcarboxylic acid
propyl ester (3) was synthesized in line with the general procedure with compound 3a (0.4 g, 1.6
mmol) and 3ꢀcyclopentylpropanoyl chloride (0.283 g, 1.8 mmol). The crude product was purified
with column chromatography on silica gel (Petroleumether ether/ethyl acetate = 30:1, v/v). White
solid; yield 85.10%; mp: 60ꢀ61 ; 1H NMR (300 MHz, CDCl3) δ 11.28 (s, 1H), 4.23 (t, J = 6.5 Hz,
2H), 2.99ꢀ2.87 (m, 1H), 2.76ꢀ2.59 (m, 2H), 2.51ꢀ2.42 (m, 2H), 2.30ꢀ2.17 (m, 1H), 1.92ꢀ1.70 (m, 9H),
1.65ꢀ1.46 (m, 4H), 1.43ꢀ1.28 (m, 1H), 1.26ꢀ0.97 (m, 2H), 1.05 (d, J = 6.5 Hz, 3H), 1.02 (t, J = 7.4 Hz,
3H). 13C NMR (75 MHz, CDCl3) δ 169.20, 165.78, 146.94, 129.30, 125.22, 110.08, 65.15, 38.62,
35.24, 31.43, 30.49, 30.18, 28.24, 25.22, 24.14, 21.08, 20.36, 9.75. HRMS calculated for
C21H31NO3S (M+H)+: 378.2097, found: 378.2095.
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6ꢀ(Tertꢀbutyl)ꢀ2ꢀ(cyclopropanecarboxamido)ꢀ4,5,6,7ꢀtetrahydroꢀbenzo[b]thiopheneꢀ3ꢀcarboxylate
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acid ethyl ester (4) was synthesized in line with the general procedure with compound 4a (0.350 g,
1.2 mmol) and cyclopropanecarbonyl chloride (0.142 g, 1.4 mmol). The crude product was purified
with column chromatography on silica gel (Petroleumether ether/ethyl acetate = 250:9, v/v). White
1
solid; yield 87.23%; mp: 130ꢀ131 ; H NMR (300 MHz, DMSOꢀd6) δ 11.21 (s, 1H), 4.28 (q, J =
7.1 Hz, 2H), 3.02ꢀ2.88 (m, 1H), 2.67ꢀ2.39 (m, 2H), 2.38ꢀ2.22 (m, 1H), 2.03ꢀ1.87 (m, 2H), 1.46ꢀ1.36
13
(m, 1H), 1.32 (t, J = 7.1 Hz, 3H), 1.26ꢀ1.08 (m, 1H), 1.00ꢀ0.82 (m, 4H), 0.90 (s, 9H). C NMR (75
MHz, DMSOꢀd6) δ 170.42, 165.05, 146.48, 130.25, 126.41, 110.56, 60.25, 44.39, 32.11, 27.07, 26.93,
25.25, 23.99, 14.63, 8.32. HRMS calculated for C19H27NO3S (M+H)+: 350.1784, found: 350.1779.
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6ꢀMethylꢀ2ꢀ(thiopheneꢀ2ꢀcarboxamido)ꢀ4,5,6,7ꢀtetrahydroꢀbenzo[b]thiopheneꢀ3ꢀcarboxylic acid
isopropyl ester (5) was synthesized in line with the general procedure with compound 5a (0.8 g, 3.2
mmol) and thiopheneꢀ2ꢀcarbonyl chloride (0.695 g, 4.7 mmol). The crude product was purified with
column chromatography on silica gel (Petroleumether ether/ethyl acetate = 30:1, v/v). Yellow solid;
yield 85.64%; mp: 183ꢀ184 ; 1H NMR (300 MHz, CDCl3) δ 12.20 (s, 1H), 7.75 (d, J = 3.6 Hz, 1H),
7.58 (d, J = 4.9 Hz, 1H), 7.17ꢀ7.11 (m, 1H), 5.33ꢀ5.18 (m, 1H), 3.02ꢀ2.89 (m, 1H), 2.80ꢀ2.60 (m, 2H),
2.34ꢀ2.21 (m, 1H), 1.94ꢀ1.83 (m, 2H), 1.49ꢀ1.24 (m, 1H),1.38 (d, J = 10.1 Hz, 3H), 1.38 (d, J = 2.3
13
Hz, 3H), 1.07 (d, J = 6.5 Hz, 3H). C NMR (75 MHz, CDCl3) δ 166.53, 158.36, 147.69, 137.89,
131.75, 130.85, 129.31, 128.09, 126.90, 112.10, 68.36, 32.61, 31.24, 29.33, 26.38, 22.20, 22.17,
21.47. HRMS calculated for C18H21NO3S2 (M+H)+: 364.1036, found: 364.1032.
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2ꢀ(4ꢀChlorobutanamido)ꢀ6ꢀmethylꢀ4,5,6,7ꢀtetrahydroꢀbenzo[b]thiopheneꢀ3ꢀcarboxylate acid ethyl
ester (6) was synthesized in line with the general procedure with compound 1 (0.598 g, 2.5 mmol)
and 4ꢀchlorobutanoyl chloride (0.389 g, 2.8 mmol). The crude product was purified with column
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chromatography on silica gel (Petroleumether ether/ethyl acetate = 20:1, v/v). White solid; yield
1
88.83%; mp: 64ꢀ65 ; H NMR (300 MHz, DMSOꢀd6) δ 11.01 (s, 1H), 4.26 (q, J = 7.1 Hz, 2H),
3.69 (t, J = 6.6 Hz, 2H), 2.83 (d, J = 17.4 Hz, 1H), 2.65 (t, J = 7.3 Hz, 2H), 2.62ꢀ2.47 (m, 2H),
2.21ꢀ2.11 (m, 1H), 2.11ꢀ1.98 (m, 2H), 1.85ꢀ1.69 (m, 2H), 1.36ꢀ1.16 (m, 1H), 1.30 (t, J = 7.1 Hz, 3H),
13
0.99 (d, J = 6.4 Hz, 3H). C NMR (75 MHz, DMSOꢀd6) δ 168.90, 165.07, 146.19, 129.97, 125.57,
111.04, 60.30, 44.55, 39.60, 32.97, 31.75, 30.57, 28.71, 27.76, 25.62, 21.17, 14.07. HRMS calculated
for C16H22ClNO3S (M+H)+: 344.1082, found: 344.1079.
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Protein Expression and Purification. Chitinase OfChtI was overexpressed and purified
according to the methods of Chen et al.41 Briefly, the DNA segment of OfCht was amplified by
PCR, then the products were ligated to pPIC9 (Invitrogen, Carlsbad, CA). The plasmid
pPIC9ꢀOfChtI was transformed into Pichia pastoris GS115 (Invitrogen, Carlsbad, CA) by
electroporation. P. pastoris cells expressing OfChtI were grown in 100 ml of BMGY medium (1%
yeast extract, 2% peptone, 1% glycerol, 0.2% biotin, 1.34% yeast nitrogen, 10 ml of 100 mM
potassium phosphate, and 90 ml water, pH 6.0) at 30 for 24 h. Then the cells were resuspended in
500 ml of BMMY medium (1% yeast extract, 2% peptone, 1% methanol, 0.2% biotin, 1.34% yeast
nitrogen, 50 ml of 100 mM potassium phosphate, and 450 ml water, pH 6.0) at 30 for 72 h, and 5
ml methanol was added to the mixture every 24 hours as an inducer. After that, the supernatant was
obtained by centrifuging and placed in ammonium sulfate (70% saturation) precipitation at 4 . The
precipitation was dissolved in buffer (20 mM sodium dihydrogen phosphate, 500 mM sodium
chloride, and 20 mM imidazole, pH 7.4), and then purified by metalꢀchelating chromatography with
a nickelꢀNTAꢀSepharose high performance column, 5 ml (GE Healthcare, Shanghai, China). Finally,
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the target protein was eluted in the buffer (20 mM sodium dihydrogen phosphate, 500 mM sodium
chloride, and 200 mM imidazole, pH 7.4) and then collected. The BCA protein assay kit (TaKaRa,
Dalian, China) was used to quantitate the protein and its purity was analyzed by SDSꢀPAGE.
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Enzymatic
Assay.
Enzymatic
activity
was
determined
using
4ꢀmethylumbelliferylꢀN,N'ꢀdiacetylꢀβꢀDꢀchitobioside (Sigma, Shanghai, China) as substrate. The
reaction mixture used for inhibitor screening consisted of 100 ꢁL of 30 ꢁM of substrate, 10 nM
enzyme, 100 ꢁM inhibitor, and 2% dimethylsulfoxide in a 20 mM sodium phosphate buffer (pH 6.0).
The reaction mixture without inhibitor was used as a positive control. After incubation at 30 for 20
min, 100 ꢁL of 0.5 M Na2CO3 was added to the reaction mixture, and the fluorescence of the released
4ꢀmethylumbelliferone was quantitated by a microplate reader with excitation and emission
wavelengths of 360 and 450 nm, respectively. Experiments were performed in triplicate unless
specified otherwise. For Ki value determination, three substrate concentrations (1, 2 and 4 ꢁM) and
varied inhibitor concentrations were used. The Ki values and types of inhibition were determined by
linear fitting of data in Dixon plots.
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RESULTS AND DISCUSSION
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Compounds Obtained by Structure-based Virtual Screening. It is reasonable to expect that the
constraints imposed by the physical properties of a molecule on its ability to express pesticideꢀlike
activity are important in the selection of potential molecular candidates. The SPECS database
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contains a large number of compounds whose properties are unlike those of pesticides. Therefore, in
order to limit the amount of time spent screening inappropriate molecules, established
pesticideꢀlikeness rules38 were used to filter out unsuitable compounds from the database. This led to
the formation of a reduced and refined dataset (dataset 1) which consisted of 72,720 small molecules.
This strategy effectively reduced the breadth of screening, and at the same time increasing the
chances of identifying suitable candidate molecules.
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The dataset 1 was then screened by a wellꢀestablished pharmacophore model. 3WL1 is the first
reported crystal structure of OfChtI with two substrates (GlcNAc)2 and (GlcNAc)3 together. The
(GlcNAc)2 takes up the binding subsites +1 and +2, while the (GlcNAc)3 extends from the subsites
ꢀ1, to ꢀ3. 3WQV is the OfChtI with inhibitor (GlcN)5, and the ligand occupied the subsites ꢀ1 to ꢀ5.
Compared the two structures, they share the same binding subsites ꢀ1, ꢀ2 and ꢀ3, which are thought to
be more important in the binding process.35 According to these considerations, the pharmacophore
model was firstly generated by the interactions between OfChtI and (GlcNAc)3. The key animo acids
Trp372, Glu148, Trp107, and Trp34 were used to create pharmacophore features. However, less than
1,000 molecules were filtered out by this model, due to too many feature restraints. Thus, this
pharmacophore model was not suitable for the present purpose. In order to optimize the
pharmacophore model, the crystal structures of 3WL1 and 3WQV were superposed, and three
common residues, Trp107, Glu148, Trp372 were found. So, these residues were used to refine a
pharmacophore model. Based on the modified model, 17,000 compounds were obtained and used to
formulate a new dataset: dataset 2.
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Molecular docking was employed in order to generate elementary prediction of the binding modes
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and affinities between the protein and the candidate inhibitors contained in the dataset 2. The
bioactive conformation of OfChtI in complex with (GlcNAc)3 was used as a template for the
molecular docking, and docking was accomplished at subsites ꢀ1 to ꢀ3 of OfChtI, using MOE
modelling software. The obtained poses were rankꢀordered according to their scores, which provided
the indication of accuracy and stability of the docking, the more negative the score, the more stable
the interaction. On that basis, for each compound the pose with the lowest score was retained, and
the top 20% of the resulting compounds, whose scores ranged from ꢀ8.76 to ꢀ6.96, were selected to
form dataset 3.
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Cluster analysis of dataset 3 using the SAReport program resulted in 27 clusters with diverse
scaffolds. The largest cluster contained 225 compounds with a 4,5,6,7ꢀtetrahydrobenzo[b]thiophene
chemical scaffold. Somewhat surprisingly, almost 16.1% of the dataset 3 was comprised of
molecules with this scaffold, while less than 1% of compounds in the entire SPECS database did so.
For this reason, this scaffold type was considered as a top priority for further investigations of OfChtI
enzyme inhibitory activity. The utilization of cluster analysis to discover a common chemical
fragment markedly increased the efficiency of the screening process.
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A fragment of 2ꢀaminoꢀ6ꢀmethylꢀ4,5,6,7ꢀtetrahydroꢀbenzo[b]thiopheneꢀ3ꢀcarboxylic acid ethyl
ester, 1 (Figure 3) was selected and its OfChtI inhibitory activity was cautiously assessed via a
bioassay. As predicted, it showed an inhibitory effect against OfChtI, but the effect was relatively
weak (Ki = 26.3 ꢁΜ) (Table 1). Nevertheless, the results verified that a new type of scaffold with
inhibitory activity had been identified. Furthermore, the fragment was observed to exhibit a variety
of structural forms comprising a number of different varied subunits. Five different compounds, 2ꢀ6
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(Figure 3) from the largest subunit were selected for chemical synthesis and used to test their
inhibitory activities against OfChtI. The results showed that the inhibitory activities of four of these
compounds, 3ꢀ6 were largely improved, compared with the parent fragment 1, and also better than
the control (GlcN)5 (Ki = 15.2 ꢁΜ). Especially compound 3, which had excellent inhibitory effect (Ki
= 1.5 ꢁΜ), while compounds 4ꢀ6 exhibited Ki values of 2.4 ꢁΜ, 3.5 ꢁΜ and 9.7 ꢁΜ, respectively
(Table 1). And, they were determined to be competitive inhibitors against OfChtI (Figure 4).
Strangely, the OfChtI inhibitory effect of compound 2 decreased to 1.3% at 100 ꢁΜ (Table 1).
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Structural comparison of compounds 3ꢀ6 revealed that there were three major variants influencing
the inhibitory activity, at positions R1, R2 and R3, respectively, but the differences between the
compounds were only minor (Figure 3). The primary difference between compound 2 and the other
compounds was the position of the R1 group, which is the most likely reason for its lower inhibitory
activity. This will be further explored in our future research. It should be noted that the chemicals
required to synthesize the compounds are readily available and easy to obtain, and the synthetic route
of manufacture resulted in high atom economy with perfect utilization of reactant atoms in the end
product (Figure 1). Nevertheless, the novel scaffold identified herein warrants further exploration as
an inhibitor of OfChtI. Whilst the inhibitory activities of the identified compounds are somewhat
limited, through efficient optimization it may well be possible to magnify their inhibitory effects
further.
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Structure-activity Relationship Analysis. In order to obtain insights into the different OfChtI
inhibition activities of the selected compounds 2ꢀ6, their structureꢀactivity relationships and
dockingꢀpredicted binding modes with the active sites of OfChtI were analyzed carefully. The
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chitinase OfChtI is a monomer that contains a TIMꢀbarrel catalytic domain which is composed of an
eightꢀstranded βꢀbarrel surrounded by eight αꢀhelices. It possesses a long cleftꢀlike active pocket with
multiple binding subsites ranging from +2 to ꢀ5, these representing the nonꢀreducingꢀend subsite and
reducingꢀend subsite, respectively. Among the selected compounds, compounds 3ꢀ6 exhibited strong
inhibition activities against OfChtI, while compound 2 showed weak inhibition. Through analysis of
the predicted binding modes of these compounds it could readily be seen that the compounds 3ꢀ6
exhibited the same binding modes with the ligand (GlcNAc)3 in the active site. They all took up the
binding subsites from ꢀ1 to ꢀ3, and binding via hydrophobic and stacking interactions with certain
aromatic residues, including Trp372, Trp34, Trp107, Tyr272, Tyr30, Phe309, and Phe61 (Figure 5).
However, the predicted binding mode of compound 2 indicated a very poor substitution of the
5ꢀmethyl at R1 position which could result in the entire compound far away from subsite ꢀ1 in the
active site than the other compounds because of the limited space available. Thus, in compound
2ꢀOfChtI, the stacking interactions with Trp372 could be destroyed. In fact, the rear end of the
OfChtI active site was so large that it could easily accommodate a number of varied chemical groups
and big groups seemed to be useful, which might explain the observed differences in inhibition
effects of the compounds 3ꢀ6 and also provide a focus for future attempts to design inhibitors with
improved potency. Taken together, our findings suggest that the 5ꢀgroup substitution at the R1
position is not a useful target for improving the inhibitory activities of these compounds. However,
the stacking interactions with Trp372 and the hydrophobic interactions are indispensable, and the
space at the end of active site presents further opportunities for the future design of more potent
inhibitor compounds.
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In the present study, we develop and employ a structureꢀbased virtual screening methodology to
identify a novel and potent scaffold against OfChtI efficiently, which has the simpler structure than
known inhibitors. Furthermore, the chemicals applied to the synthesis are easy to obtain. The
synthetic route of compounds results in high atom economy with perfect utilization of reactant atoms
in the end product. The inhibitory activities of four out of the five synthesized compounds (3ꢀ6)
against OfChtI were determined as relatively strong, and analysis of their structureꢀactivity
relationships provided insight into their interactions with the active site, which would inform future
research to improve the potency of the inhibitory activity. This work presents a novel scaffold for
inhibition of chitinases that warrants further exploitation and, in addition, offers an alternative
approach for the application of virtual screening for pesticide identification more widely.
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ABBREVIATIONS USED
GlcNAc, NꢀacetylꢀDꢀglucosamine; GH18, glycoside hydrolase family 18; SBVS, structureꢀbased
virtual screening; GlcN, Dꢀglucosamine; MW, molecular weight; Clog P, octanolꢀwater partition
coefficient; ROB, number of rotatable bonds; ARB, number of aromatic bonds; HBA, number of
Hꢀbond acceptors; HBD, number of Hꢀbond donors;
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ACKNOWLEDGEMENTS
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This work was supported by the National Key R&D Program of China (No. 2017YFD0200504,
2017YFD0200501), and the National Natural Science Foundation of China (No. 21672257).
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SUPPORTING INFORMATION
Predicted binding energies of the screened compounds; the initial pharmacophore model; Ki values of
compounds 4-6, and (GlcN)5 against OfChtI; dockingꢀpredicted binding modes of compounds 1ꢀ6 in
the OfChtI active site; 1H NMR and 13C NMR spectra of the compounds 1ꢀ6, 2a-5a.
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FIGURE CAPTIONS:
Figure 1. Synthetic route for preparation of compounds 2ꢀ6 and their precursors 2a-5a and 1.
Reagents and conditions: EtOH, morpholine, reflux, 5 h; CH2Cl2, TEA, r.t., overnight.
Figure 2. The final pharmacophore model used in the screening of OfChtI inhibitors. Don|Acc:
hydrogen bond donor or acceptor. Don2|Acc2: projection of the donor or the acceptor. Hyd:
hydrophobic centroid.
Figure 3. Structures of compounds 1ꢀ6 identified by structureꢀbased virtual screening.
Figure 4. Inhibitory kinetics of compounds 1 (A) and 3 (B) against OfChtI.
483
484
485
Figure 5. A, Dockingꢀpredicted binding modes of compounds (GlcNAc)3 (red), 3 (green), 4 (blue), 5
(orange), 6 (carmine) in the OfChtI active site. B, Dockingꢀpredicted binding mode of compound 3 in
the OfChtI active site.
486
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Table:
Table 1. Inhibitory Activities of Compounds 1ꢀ6 against OfChtI.
Inhibition Rate (%)
Ki
(ꢁM)
(mean ± SD)
Compounds
100 ꢁM 20 ꢁM
1
2
3
4
5
6
54.1 ± 3.1 24.8 ± 4.9
1.3 ± 3.4
26.3
NDa
1.5
0
99.0 ± 0.1 95.1 ± 1.2
95.2 ± 0.5 68.4 ± 5.9
100 ± 3.4 62.1 ± 2.2
96.2 ± 0.3 52.9 ± 4.0
75.6 ± 0.2 45.9 ± 0.4
2.4
3.5
9.7
b
(GlcN)5
15.2
a Not determined. b Control compound.
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Figure Graphics:
Figure 1
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Figure 2
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Figure 3
O
O
O
H3C
H3C
S
S
S
S
S
O
O
N
NH2
N
H
H
H3C
O
O
O
O
O
O
O
O
O
O
O
2
O
O
(H3C)3C
H3C
H3C
S
Cl
S
N
H
N
N
H
H
O
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