- Email: [email protected]
3D-QSAR based optimization of insect neuropeptide allatostatin analogs
Accepted Manuscript 3D-QSAR based optimization of insect neuropeptide allatostatin analogs Meizi Wang, Xinlu Li, Mengting Chen, Xiaoqing Wu, Yiduo Mi, Zhenpeng Kai, Xinling Yang PII: DOI: Reference:
S0960-894X(19)30065-4 https://doi.org/10.1016/j.bmcl.2019.02.001 BMCL 26281
To appear in:
Bioorganic & Medicinal Chemistry Letters
Received Date: Revised Date: Accepted Date:
9 October 2018 28 January 2019 1 February 2019
Please cite this article as: Wang, M., Li, X., Chen, M., Wu, X., Mi, Y., Kai, Z., Yang, X., 3D-QSAR based optimization of insect neuropeptide allatostatin analogs, Bioorganic & Medicinal Chemistry Letters (2019), doi: https://doi.org/10.1016/j.bmcl.2019.02.001
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Graphical Abstract To create your abstract, type over the instructions in the template box below. Fonts or abstract dimensions should not be changed or altered.
3D-QSAR based optimization of insect neuropeptide allatostatin analogs
Leave this area blank for abstract info.
Meizi Wang, Xinlu Li, Mengting Chen, Xiaoqing Wu, Yiduo Mi, Zhenpeng Kai, Xinling Yang
Bioorganic & Medicinal Chemistry Letters journal homepage: www.elsevier.com
3D-QSAR based optimization of insect neuropeptide allatostatin analogs Meizi Wanga, Xinlu Lia, Mengting Chena, Xiaoqing Wua, Yiduo Mia, Zhenpeng Kaib, *, Xinling Yanga, a b
*
Department of Applied Chemistry, College of Science, China Agricultural University, Beijing, 100193, China School of Chemical and Environmental Engineering, Shanghai Institute of Technology, Shanghai, 201418, China
ARTICLE INFO
ABSTRACT
Article history: Received Revised Accepted Available online
Allatostatins (AST) are neuropeptides originally described as inhibitors of juvenile hormone (JH) synthesis in insects. Consequently, they have been considered as potential lead compounds for the discovery of new insect growth regulators (IGRs). In the present work, receptor-based three-dimensional quantitative structure-activity relationship (3D-QSAR) was studied with 48 AST analogs, and a general approach for novel potent bioactive AST analogs is proposed. Hence, six novel AST analogs were designed and synthesized. Bioassays indicated that the majority novel analogs exhibited potent JH inhibitory activity, especially analog A6 (IC50: 3.79 nmol/L), which can be used as lead compound to develop new IGRs
Keywords: Neuropeptides Allatostatins analogs 3D-QSAR Optimization IGRs
The use of insect neuropeptides as pest control agents offers several advantages in pest management. They can be highly selective and could be used in very low concentration. In addition, they are environmentally friendly, and harmless to human health. Some insect neuropeptides have been already proposed for pest control1, such as allatostatins2, insect kinins3, PHAN/pyrokinin peptide ligands4 and adipokinetic hormone (AKH)5. Allatostatins (ASTs) comprise a family of insect neuropeptides that can inhibit juvenile hormone (JH) biosynthesis2. Therefore, it was regarded as potential lead for the discovery of new insect growth regulators (IGRs). In the last decade, our research group has been working on the study of cockroach type allatostatins (AST-As)6-17, a type of neuropeptides that range from 6 to 18 amino acids in length and share a common conserved C-terminal sequence Tyr/Phe-Xaa-Phe-Gly-Leu-NH2 (Xaa = Ala, Asn, Gly, Ser) in the cockroach Diploptera punctata18. These ASTs strongly inhibit JH biosynthesis by the corpora allata (CA) of Diplotera punctata19, and were therefore considered as potential candidates for the development of new IGRs. Using a peptidomimetics strategy, we selected the core pentapeptide (YDFGLa: where a = amide) as the lead, and found the highly active analog H17 (Figure 6)9. We later designed and synthesized a series of peptidomimetic analogs, among them analog B1 (Figure S1) (IC50: 0.09μmol/L) was more active than the original lead core pentapeptide (IC50: 0.13μmol/L)10. These studies demonstrated that ASTs accept a range of chemical modifications, and these modified analogs have improved biological activity. We evaluated the relationship between two-dimensional structure and biological activity of *
2009 Elsevier Ltd. All rights reserved.
previously synthesized AST analogs and established a general approach for the design of potential AST analogs7. Those analogs should include an aromatic group, a linker of an appropriate length and a conserved C-terminal Leu-NH2 region. However, a compound interacts with its receptor actually in a three-dimensional (3D) structure. Therefore, exploring the relationship between the 3D conformation and the inhibitory activity of analogs is significant for guiding the design of novel compounds. Recently, homology modeling was used to build a 3D structure of the AST receptor of D. punctata (Dippu-AstR). The FGLa domain of AST was successfully docked into Dippu-AstR and the docking results are consistent with the findings of biological assays20. There are few articles about 3D-QSAR studies of peptides, mainly because of the flexibility of peptide molecules. Therefore, determining the 3D conformation of peptides should permit reliable construction of 3D-QSAR models. Recently, receptor-based 3D-QSAR approaches have been widely used, because this method can generate accurate 3D conformations of molecules and therefore produce reliable models21,22. We anticipate that a study on the relationship between the 3D structure conformation of AST analogs and their receptors was meaningful for understanding the mode of action of these peptides, as well as guiding the design of new active analogs. In this work, 48 FGLa AST analogs, previously synthesized in our lab, were docked into the above-mentioned model19 and their 3D conformations were used for receptor-based 3D-QSAR modeling. The 3D-QSAR model showed good predictive capability and was further applied to design novel AST analogs.
Corresponding author. Tel /fax: +86-010-62732223.E-mail address: [email protected] (Xinling Yang) and [email protected] (Zhenpeng Kai)
The designed AST analogs showed significant inhibitory activity, and the most potent analog A6 exhibited an IC50 value in the nanomolar range, which indicated that this model is reliable and useful for further design of new AST analogs. The molecular structures and biological activities of the 48 AST analogs were taken from our previous results 7, 9, 13, 14. The IC50 values were
converted to the corresponding pIC50 (-log IC50) and used as dependent variables in the QSAR experiments. The samples were divided into a training set of 41 compounds and a test set of 7 compounds23. The chemical structures, experimental and predicted pIC50 are provided in Table 1.
Table 1. Chemical structures, experimental and predicted pIC50 values of CoMFA and CoMSIA
NO.
R1
R2
R3
R4
Actual pIC50
CoMFA Predicted pIC50
Residual
CoMSIA Predicted pIC50
Residual
I1
9-ethoxy-9H-fluorene
carboxy methyl
benzyl
isobutyl
6.00
6.03
-0.03
6.01
-0.01
I2
4-hydroxyphenylethylamine
carboxy methyl
benzyl
sec-butyl
4.57
4.67
-0.10
4.55
0.02
I3
4-hydroxyphenylethylamine
carboxy methyl
benzyl
isobutyl
4.91
4.77
0.14
4.95
-0.04
I4
styryl
H
benzyl
isobutyl
7.40
7.17
0.23
7.01
0.39
I5
4-bromostyryl
H
benzyl
isobutyl
8.16
7.45
0.71
7.46
0.70
I6
3-methoxystyryl
H
benzyl
isobutyl
6.74
7.11
-0.37
6.98
-0.24
I7
4-fluorostyryl
H
benzyl
isobutyl
7.97
7.16
0.81
7.25
0.73
I8
2-nitrophenyl
H
benzyl
isobutyl
7.01
6.99
0.02
6.91
0.10
I9
4-methylphenyl
H
benzyl
isobutyl
6.88
6.85
0.03
6.93
-0.05
I10
phenyl
H
benzyl
isobutyl
6.81
6.90
-0.09
6.90
-0.09
I11
phenylethoxy
H
benzyl
isobutyl
7.81
7.85
-0.04
7.75
0.06
I12
4-nitrostyryl
H
4-pyridinylmethyl
isobutyl
7.05
6.82
0.23
7.10
-0.05
I13
4-nitrostyryl
H
phenyl
isobutyl
7.41
7.26
0.15
7.42
-0.01
I14
4-nitrostyryl
H
4-hydroxyphenylmethyl
isobutyl
6.38
6.57
-0.19
6.41
-0.03
I15
4-nitrostyryl
H
4-methoxyphenylmethyl
isobutyl
6.38
6.26
0.12
6.48
-0.10
I16
4-nitrostyryl
H
2-methylphenylmethyl
isobutyl
6.64
6.60
0.04
6.50
0.14
I17
4-nitrostyryl
H
3-methylphenylmethyl
isobutyl
6.18
6.29
-0.11
6.44
-0.26
I18
4-nitrostyryl
H
4-methylphenylmethyl
isobutyl
6.85
6.40
0.45
6.52
0.33
I19
4-nitrostyryl
H
3-chlorophenylmethyl
isobutyl
6.47
6.48
-0.01
6.38
0.09
I20
2-hydroxystyryl
H
benzyl
isobutyl
6.54
6.51
0.03
6.35
0.19
I21
2-fluorostyryl
H
benzyl
isobutyl
6.25
6.78
-0.53
6.71
-0.46
I22
2-chlorostyryl
H
benzyl
isobutyl
6.79
6.80
-0.01
6.77
0.02
I23
3-chlorostyryl
H
benzyl
isobutyl
7.01
7.11
-0.10
7.04
-0.03
I24
4-chlorostyryl
H
benzyl
isobutyl
7.32
7.30
0.03
7.35
-0.03
I25
3-bromostyryl
H
benzyl
isobutyl
7.11
7.08
0.03
6.98
0.13
I26
2,5-dichlorostyryl
H
benzyl
isobutyl
6.74
6.63
0.12
6.49
0.25
I27
3-trichloromethylstyryl
H
benzyl
isobutyl
7.11
7.08
0.03
7.08
0.03
I28
4-trifluoromethylstyryl
H
benzyl
isobutyl
7.56
7.67
-0.11
7.76
-0.20
I29
3-cyanostyryl
H
benzyl
isobutyl
6.99
6.87
0.13
7.03
-0.04
I30
4-cyanostyryl
H
benzyl
isobutyl
7.36
7.56
-0.20
7.57
-0.21
I31
2-nitrostyryl
H
benzyl
isobutyl
6.54
6.73
-0.19
6.48
0.06
I32
3-hydroxystyryl
H
benzyl
isobutyl
6.74
6.82
-0.08
6.77
-0.03
I33
4-hydroxystyryl
H
benzyl
isobutyl
7.55
7.35
0.20
7.52
0.03
I34
2-methylstyryl
H
benzyl
isobutyl
6.58
6.80
-0.22
6.83
-0.25
I35
4-methylstyryl
H
benzyl
isobutyl
7.28
7.17
0.11
7.16
0.12
I36
2-methoxystyryl
H
benzyl
isobutyl
6.51
6.49
0.02
6.63
-0.12
I37
2-trifluoromethylstyryl
H
benzyl
isobutyl
6.74
6.78
-0.04
6.84
-0.10
I38
4-methoxystyryl
H
benzyl
isobutyl
7.03
7.32
-0.29
7.14
-0.11
I39
4-(N,N-dimethylamino) styryl
H
benzyl
isobutyl
7.24
7.22
0.02
7.28
-0.04
I40
3-methylstyryl
H
benzyl
isobutyl
6.74
6.68
0.06
6.73
0.01
I41
2,6-dichlorostyryl
H
benzyl
isobutyl
6.62
6.71
-0.09
6.65
-0.03
T1a
N-methyl-4-toluenesulfona mide
H
benzyl
isobutyl
6.40
6.87
-0.47
6.92
-0.52
T2
2-chlorostyryl
H
benzyl
isobutyl
6.93
6.86
0.07
6.86
0.07
T3
3-nitrostyryl
H
benzyl
isobutyl
6.94
6.77
0.17
6.36
0.58
T4
3-fluorostyryl
H
benzyl
isobutyl
6.50
7.26
-0.76
6.96
-0.46
T5
2-bromostyryl
H
benzyl
isobutyl
6.89
6.83
0.06
6.74
0.15
T6
2-isopropylstyryl
H
benzyl
isobutyl
6.86
7.28
-0.42
7.28
-0.42
T7
3,4-dichlorostyryl
H
benzyl
isobutyl
7.03
7.17
-0.14
7.37
-0.34
a
T=Test set compounds markerd with underline
Figure 1. Molecular Docking of the AST analog I5 into the D. punctata AST receptor. (A) Hydrogen bonds and π−π interactions of the analog I5 with the receptor. The hydrogen bond is shown with a dotted yellow line. (B) Hydrophobicity of the binding pocket.
Molecular alignment is a crucial step in 3D-QSAR studies. Conventional 3D-QSAR alignments are usually constructed without considering the 3D structural information of receptors, often resulting in meaningless models. 3D-QSAR docking-based alignment are developed using the structural information of receptors, and often result in valuable models 21. In this study, 48 AST analogs were docked into the binding site of the AST receptor, and the 3D conformations of analogs were aligned, based on docking-based alignment methods. Figure S2 shows the alignment of training set. Additional parameters were set by default in the SYBYLX 2.0 program. The Partial Least Squares (PLS) method was used to generate statistically significant 3D-QSAR models in regression analyses24. The template of analog I5 and the pentapeptide were well matched in the homology Dippu-AstR model shown in Figure 1 and Figure S 3 respectively. Figure 1A shows that the C-terminal amide of Leu-NH2 is forming a hydrogen bond with the His336
of the receptor. In addition, the N-terminal amide of Gly has a hydrogen bond with Tyr253. Finally, the benzene rings of Phe and 4-bromocinnamic acid have π−π interactions with the benzene rings of Phe227 and Phe248 of homology Dippu-AstR respectively. In addition, pentapeptide (Figure S 3A) and FGLa 22 both have π−π interactions with the benzene ring of Tyr253. For the Tyr253 residues of homology Dippu-AstR, these compounds show different modes of action. This may provide an explanation for the higher potency of analog I5 in comparison to the pentapeptide. We propose that the structural conformation of analog I5 has higher affinity for the receptor. Figure 1B shows the hydrophobicity of the binding pocket. It indicates that the benzene ring of Phe and the N-terminal have strong hydrophobic interaction with the receptor, whereas sections rich in amide bonds are more hydrophilic. Interestingly, the hydrophobicity and hydrophilicity are consistent with the π−π effect and hydrogen bond interactions respectively. The docking results provided 3D conformation for the AST analogs and revealed the
Figure 2. Plot of predicted pIC50 against the experimental pIC50 by CoMFA(A) and CoMSIA(B)
interaction between the AST analogs and the receptor. The CoMFA and CoMSIA models were developed based on a set of 41 AST analogs. The values of the cross-validation correlation coefficient q2 > 0.5 and r2> 0.9 indicated that the 3D-QSAR models were reasonable and reliable enough for the prediction of biological activities. For the CoMFA analyses, the optimal number of components (ONC), q2 and r2 were 6, 0.741 and 0.900 respectively. In the CoMSIA model, the ONC, q 2 and r2 were 7, 0.658 and 0.912 respectively. The scatter plot of the predicted activity data versus the experimental data (training, test and new compounds) is shown in Figure 2. Two (steric and electrostatic) and five (steric, electrostatic, hydrophobic and hydrogen-bonding acceptor/donor) contour maps were derived by CoMFA and CoMSIA model, respectively, and were shown in Figures 3,4 and 5. The steric contours of the CoMFA (Figure 3A) and CoMSIA (Figure 3B) models displayed a green contour near position 4 of the
N-terminal benzene ring. This green contour indicated a favorable effect of bulky groups on the biological activities. In addition, CoMSIA steric contours revealed a yellow contour near positions 2 and 3 on benzene ring. The yellow contours illustrated the unfavorable effect of bulkier groups. This is consistent with the experimental data. For example, using the bulkier group -Br at position 4 (molecule I5 with pIC50 = 8.16) instead of a -H (molecule I4 with pIC50 = 7.40), significantly increased the biological activity. However, introduction of Br at position 3 (molecule I25 with pIC50 = 7.11) decreased biological activity. These effects were observed in other analogs, such as I33, I4 and I32 (4-OH, pIC50 = 7.55 > -H, pIC50 = 7.40 > 3-OH, pIC50 = 6.74); I7, I4 and T4 (4-F, pIC50 = 7.97 > -H, pIC50 = 7.40 > 3-F, pIC50 = 6.50). Figures 4A (CoMFA) and 4B (CoMSIA) display electrostatic contour maps. Two large red contours sandwiched position 4 of the N-terminal benzene ring (Figure 4A), which suggests that
Figure 3. Steric contour maps of CoMFA (A) and CoMSIA (B) based on compound I5. Steric fields: favored (green) and disfavored (yellow).
Figure 4. Electrostatic contour maps of CoMFA (A) and CoMSIA (B) based on compound I5. Electrostatic fields: the blue color shows the favored positive electrostatic area and the red color shows the favored negative electrostatic area.
Figure 5. Contour maps of CoMSIA based on compound I5. (A) Hydrophobic field: the yellow color shows the favored hydrophobic area and the white color shows the disfavored hydrophobic area. (B) H-bond donor/acceptor field: the cyan color shows the favored H-bond donor area. The red color represents the disfavored H-bond donor area. The magenta color shows the favored H-bond acceptor area. The white color shows the disfavored H-bond acceptor area.
Figure 6. General approach for the design of AST analogs. Elucidation of the structural formula. Modifications that are beneficial to the inhibition of JH biosynthesis: (1) Electron withdrawing group in the para site of the benzene ring at N-terminal (red block of region A). (2) Large group in the para site of the benzene ring at N-terminal (green block of region B). (3) Hydrophilic group in the site chain of the 2-site amino acid (cyan block of region C). (4) Proper electron density group in the benzene ring of the Phe (fuchsia block of region D).
negative electrostatic or decreased positive electrostatic in this region enhanced biological activity. For N-terminal benzene ring modification, molecules I7 and I24 (4-F, pIC50 = 7.97 > 4-Cl, pIC50 = 7.32), which the negative charged (Cl < F) increased, the pIC50 values (7.32 < 7.97) increased. The bromine substitution was an exception. The electronegativity of bromine is less than that of chlorine and fluorine, but the biological activity is much higher. Steric field effect indicated that introduction of a larger group at position 4 of the N-terminal benzene ring is beneficial for the improvement of activity. The radius of a bromine atom is larger than that of chlorine and fluorine atoms, which can explain the high activity of bromine substitution compound I5 (pIC50 = 8.16). Therefore, steric and electrostatic effects should be taken into consideration when designing compounds. The negative electrostatic properties can be further investigated considering compounds I28 and I33 (4-CF3, pIC50= 7.56 > 4-OH, pIC50 = 7.55). The electron withdrawing effect of the hydroxyl group is weaker than electron-donating effect of the p-π conjugation, which showed electron-donating effect. While trifluoromethyl is a strong electron-withdrawing group. Therefore, the electronegativity of the trifluoromethyl group is stronger than hydroxyl group. A large blue contour near position 2 of the N-terminal benzene ring and positions 3, 4 of the benzene ring of Phe (Figure 4A) indicate that the positive electrostatic or decreased negative electrostatic forces improve bioactivity. However, Figure 4B reveals a red contour at position 4 of the benzene ring of Phe, which means that position 4 of the benzene ring on the Phe is a controversial structural modification site. The benzene ring of Phe has a π−π interaction with Phe227
(Figure 1A). According to Hunter-Sanders rules for π-π interactions, the electron cloud density on the benzene ring has an effect on the π-π interaction25. Therefore, a suitable electron cloud density on the Phe is beneficial for biological activity. The bioassay results (Table 1) demonstrate that the substitution of the pyridine (molecular I12: R3 = 4-pyridylmethyl, pIC50 = 7.05) is more active than the electron-withdrawing or electron-donating substitutions (molecular I14-I19 pIC50<7.00). It has been proposed that the electron cloud density of the pyridine ring is uniform, whereas substituents could destroy the electron cloud density on the benzene ring. Hydrophobic contour map is shown in Figure 5A. A yellow contour at position 4 of the N-terminal benzene ring suggested that the introduction of hydrophobic substituents would benefit inhibitory activity. This can be explained by considering molecules I28, which have a hydrophobic substituent of 4-trifluoromethyl group with pIC50 = 7.56, in contrast to molecule I4 (having H with pIC50 = 7.40), the inhibitory activity is increased. A large white contour surrounding 2-site amino acid (Gly) indicated that the introduction of hydrophilic substituents would favor inhibitory activities. This is consistent with the results of our previous work17. Figure 5B reveals the H-bond donor/acceptor contour map. One medium-size red contour near the 3-position of the benzene ring of the N-terminus indicates that the introduction of an H-bond donor group in this region would result in low activities. A magenta contour at the position 4 of benzene ring of N-terminal demonstrate that H-bond acceptor substituents would be beneficial for biological activity. For instance, the activity of I33 (pIC50 =7.55) having 4-
Table 2 Chemical structures, experimental IC50 and predicted CoMFA and CoMSIA pIC50 values of new designed analogs
Compd
R3
R5
IC50 (nmol/L) (95%CIb)
Actual pIC50
CoMFA Predicted pIC50
Residual
CoMSIA Predicted pIC50
Residual
H17
-
-
40.64 (9.174-180)
7.39
7.20
0.19
7.00
0.39
A1
benzyl
4-NO2
16.46(4.407-61.49)
7.78
6.02
1.76
6.88
0.90
A2
4-iodobenzyl
4-NO2
25.29(8.265-77.40)
7.60
6.50
1.10
6.64
0.96
A3
4-methylbenzyl
4-NO2
164.20(78.71-342.7)
6.79
6.36
0.43
6.58
0.21
A4
4-pyridylmethyl
4-NO2
17.62(3.106-99.96)
7.75
6.95
0.80
6.70
1.05
A5
4-pyridylmethyl
4-Br
10.88(4.236-27.96)
7.97
7.14
0.83
7.61
0.36
A6
4-pyridylmethyl
4-CF3
3.79(0.8625-16.66)
8.41
7.33
1.07
7.84
0.56
b
95% CI=95% confidence intervals - H17 is different from designed analogs structure
hydroxystyryl at R1 is higher than I4 (having styryl at R1 with pIC50 = 7.40). The area in which H-bond acceptors are favorable for activity in Figure 5B may be due to the 4-OH group. This effect can be seen in molecules I7 (having 4-fluorostyryl at R1 with pIC50=7.97). However, this SAR results requires more experimental data to prove. Based on 3D-QSAR analyses, a general structure for novel potent bioactive AST analogs is proposed. The structure should have four critical substitutions (A, B, C and D): (1) potent electron withdrawing group at the 4 position of the benzene ring of the N-terminal (Region A); (2) large group at the 4 position of the benzene ring of the N-terminal (Region B); (3) hydrophilic group in the side chains of the 2-site amino acids (Region C); (4) appropriate electron density of the benzene ring of Phe (Region D). This strategy of modifications should be helpful for the design of novel potent AST analogs. Hence, six novel AST analogs were designed and synthesized with H17 as lead compound. This design strategy was shown in Figure 6. Their synthetic route is illustrated in the Scheme S1. The physical parameters and identification data of target compounds are provided in the supporting information. Their ability to inhibit JH biosynthesis by the CA in vitro was evaluated and the IC50 results were listed in Table 2. Analog A1, in which Gly2 was replaced by Asp2, showed lower IC 50 values (IC50: 16.46 nmol/L) than H17 (IC50: 40.64 nmol/L), validating the concept that the introduction of a hydrophilic group improves the inhibitory activity. Hence, Asp2 was introduced into other five analogs. After modification of the benzene ring of Phe, analog A4 (R3=4-pyridylmethyl; IC50: 17.62 nmol/L) showed similar bioactivity to A1. Following a change in the electron density of benzene ring, the analog A3 (R3=4-methylbenzyl; IC50: 164.2 nmol/L), with an electron donating group, and A2 (R3=4-iodobenzyl; IC50: 25.29 nmol/L) containing an electron-withdrawing group, showed lower activity than A1. The introduction of aromatic groups with the proper electron cloud density (such as a pyridine or a benzene ring) can enhance the inhibition of JH biosynthesis (strategy 4). Based on strategy (1) and (2), electron withdrawing and large groups (NO2, Br, CF3) were introduced at the para site of the benzene ring at the N-terminal，and the whole series(A4, A5,
A6)，particularly analog A6 (IC50: 3.79 nmol/L), showed potent activity in the inhibition of JH biosynthesis. These results indicated that replacing of Gly with Asp is good for in vitro activity. However, Asp has an ionizable group, COOH in its side chain, it may not be good for in vivo activity because the permeability of a compound having an ionizable group through cell membranes will be poor. Thus, we will design and synthesize new analogs containing some hydrophilic amino acids that are difficult to ionize (such Asn, etc) so as to increase their hydrophilicity and reduce the ionization ability in our future work. It is speculated that these analogs may be easier to penetrate the cell membrane and have good activity in vivo. In summary, a receptor-based 3D-QSAR model of AST analogs was built, which indicated that the position of Phe3, Gly2 and N-terminal of peptides are key parts for designing new analogs. Six novel analogs were therefore designed and synthesized using the modified design strategy. The in vitro bioassay results showed that the activity of most analogs was higher than H17, particularly analog A6, exhibited potent inhibitory activity on JH biosynthesis. This implies that the receptor-based 3D-QSAR model is accurate and reliable for new active AST analogs design.
Acknowledgments This work was supported by the grants from the National Key Research and Development Plan (No. 2017YFD0200504) and the National Natural Science Foundation of China (No. 21877126 & 21372257). References and notes 1. 2. 3. 4. 5. 6. 7.
Evans, P. D.; Robb, S.; Cuthbert, B. A. Pestic. Sci. 1989, 25, 71. Stay B.; Tobe S.S. Annu. Rev. Entomol. 2007, 52, 277. Zhang, C.L.; Qu, Y.Y.; Wu, X.Q.; Song, D.L.; Ling, Y.; Yang, X.L. J. Agric Food Chem. 2015, 63,4527. Choi, M. Y.; Meer, R. K. V. U.S. Patent 10 017 538, 2018. Gade, G.; Marco, H.G. Arch Insect Biochem Physiol. 2017, 95, 21399. DOI: 10.1002/arch.21399. Kai, Z.P.; Huang, J.; Tobe, S.S.; Yang, X.L. Peptides. 2009, 30, 1249. Kai, Z.P.; Huang, J.; Xie, Y.; Tobe, S.S.; Ling, Y.; Zhang, L, Zhao, Y.C.; Yang, X.L.; J. Agric Food Chem. 2010, 58, 2652.
8. 9.
10. 11. 12. 13. 14. 15. 16. 17.
Kai, Z.P.; Ling, Y, Liu, W.J.; Zhao, F.; Yang, X.L. Biochim Biophys Acta. 2006, 1764, 70. Kai, Z.P.; Xie, Y.; Huang, J.; Tobe, S.S.; Zhang, J.R.; Ling, Y.; Zhang, L.; Zhao, Y.C.; Yang, X.L. J. Agric Food Chem 2011, 59, 2478. Xie, Y.; Kai, Z.P.; Tobe, S.S.; Deng, X.L.; Ling, Y.; Wu, X.Q.; Huang, J.; Zhang, L.; Yang, X.L. Peptides. 2011, 32, 581. Xie, Y.; Zhang, L.; Wu, X.Q.; Zhang, C.L.; Yang, X.L.; Tobe, S.S. Peptides. 2015, 68, 214. Xie, Y.; Zhang, L.; Zhang, C.L.; Wu, X.Q.; Deng, X.L.; Yang, X.L.; Tobe, S.S. J. Agric Food Chem. 2015, 63, 2870. Wu, X Q.; Huang, J.; Wang, M.Z.; Zhang, Z.; Li, X.L.; Yang, X.L.; Tobe, S.S. Chin. Chem. Lett. 2016, 27, 559. Wu, X.Q.; Wang, M.Z.; Huang, J.; Zhang, L.; Zhang, Z.; Ling, Y.; Yang, X.L.; Tobe, S.S. Pest Manag Sci. 2017, 73, 500. Xie, Y.; Wang, M.Z.; Zhang, L.; Wu, X.Q.; Yang, X.L.; Tobe S.S. J. Pept Sci. 2016, 22, 600. DOI 10.1002/psc.2906. Wang, M.Z.; Wang, X.W.; Wu, X.Q.; Li, X.L.; Yang, X.L. Sci Sin Chim. 2016, 11, 1235. DOI 10.1360/N032016-00128. Wang, M.Z.; Zhang, L.; Wang, X.W.; Ling, Y.; Wu, X.Q.; Li, X.L.; Mi, Y.D.; Yang, X.L. Chin. Chem. Lett. 2018, 29, 1375.
18. Hans, P.V.; Ronald, J.N.; Jozef, V. B. Handbook of Biologically Active Peptides, Academic Press, San Diego, 2013. 19. Woodhead, A.P.; Stay, B.; Seidel, S.L.; Khan, M.A.; Tobe, S.S. P Proc. Natl. Acad. Sci. U.S.A. 1989, 86, 5997. 20. Huang, S.S.; Chen, S.S.; Zhang, H.L.; Yang, H.; Yang, H.J.; Ren, Y.J.; Kai, Z.P.; J. Agric Food Chem. 2018, 66, 3644. 21. Fang, C.; Xiao, Z.Y. Curr. Top. Med. Chem. 2016, 16, 1463. 22. Ding, L.N.; Wang, Z. Z.; Sun, X. D.; Yang, J.; Ma, C. Y.; Li, W.; Liu, H. M. Bioorg Med Chem Lett. 2017, 27, 3521. 23. Leonard, J.T.; Roy K.; QSAR Comb. Sci. 2006, 25, 235. DOI 10.1002/qsar.200510161. 24. Bush, B. L.; Nachbar Jr., R.B. J Comput Aided Mol Des. 1993, 7, 587. 25. Hunter, C.A.; Singh, J.; Thornton, J.M. J. Mol. Bio.1991, 218, 837.
Supplementary Material Supplementary data associated with this article can be found, in the online version，at
Highlights 1. Receptor-based 3D-QSAR model is accurate and reliable for designing new analogs. 2. Phe3, Gly2 and N-terminus in the allatostatin structure are key parts of a design. 3. Potent analogs have a hydrogen bond reaction with Tyr253 of homology Dippu-AstR. 4. Uniform electron cloud density on the benzene of Phe3 is beneficial for activity. 5. Analog A6 have a potent inhibitory activity on JH biosynthesis in nanomolar level.
S0960-894X(19)30065-4 https://doi.org/10.1016/j.bmcl.2019.02.001 BMCL 26281
To appear in:
Bioorganic & Medicinal Chemistry Letters
Received Date: Revised Date: Accepted Date:
9 October 2018 28 January 2019 1 February 2019
Please cite this article as: Wang, M., Li, X., Chen, M., Wu, X., Mi, Y., Kai, Z., Yang, X., 3D-QSAR based optimization of insect neuropeptide allatostatin analogs, Bioorganic & Medicinal Chemistry Letters (2019), doi: https://doi.org/10.1016/j.bmcl.2019.02.001
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Graphical Abstract To create your abstract, type over the instructions in the template box below. Fonts or abstract dimensions should not be changed or altered.
3D-QSAR based optimization of insect neuropeptide allatostatin analogs
Leave this area blank for abstract info.
Meizi Wang, Xinlu Li, Mengting Chen, Xiaoqing Wu, Yiduo Mi, Zhenpeng Kai, Xinling Yang
Bioorganic & Medicinal Chemistry Letters journal homepage: www.elsevier.com
3D-QSAR based optimization of insect neuropeptide allatostatin analogs Meizi Wanga, Xinlu Lia, Mengting Chena, Xiaoqing Wua, Yiduo Mia, Zhenpeng Kaib, *, Xinling Yanga, a b
*
Department of Applied Chemistry, College of Science, China Agricultural University, Beijing, 100193, China School of Chemical and Environmental Engineering, Shanghai Institute of Technology, Shanghai, 201418, China
ARTICLE INFO
ABSTRACT
Article history: Received Revised Accepted Available online
Allatostatins (AST) are neuropeptides originally described as inhibitors of juvenile hormone (JH) synthesis in insects. Consequently, they have been considered as potential lead compounds for the discovery of new insect growth regulators (IGRs). In the present work, receptor-based three-dimensional quantitative structure-activity relationship (3D-QSAR) was studied with 48 AST analogs, and a general approach for novel potent bioactive AST analogs is proposed. Hence, six novel AST analogs were designed and synthesized. Bioassays indicated that the majority novel analogs exhibited potent JH inhibitory activity, especially analog A6 (IC50: 3.79 nmol/L), which can be used as lead compound to develop new IGRs
Keywords: Neuropeptides Allatostatins analogs 3D-QSAR Optimization IGRs
The use of insect neuropeptides as pest control agents offers several advantages in pest management. They can be highly selective and could be used in very low concentration. In addition, they are environmentally friendly, and harmless to human health. Some insect neuropeptides have been already proposed for pest control1, such as allatostatins2, insect kinins3, PHAN/pyrokinin peptide ligands4 and adipokinetic hormone (AKH)5. Allatostatins (ASTs) comprise a family of insect neuropeptides that can inhibit juvenile hormone (JH) biosynthesis2. Therefore, it was regarded as potential lead for the discovery of new insect growth regulators (IGRs). In the last decade, our research group has been working on the study of cockroach type allatostatins (AST-As)6-17, a type of neuropeptides that range from 6 to 18 amino acids in length and share a common conserved C-terminal sequence Tyr/Phe-Xaa-Phe-Gly-Leu-NH2 (Xaa = Ala, Asn, Gly, Ser) in the cockroach Diploptera punctata18. These ASTs strongly inhibit JH biosynthesis by the corpora allata (CA) of Diplotera punctata19, and were therefore considered as potential candidates for the development of new IGRs. Using a peptidomimetics strategy, we selected the core pentapeptide (YDFGLa: where a = amide) as the lead, and found the highly active analog H17 (Figure 6)9. We later designed and synthesized a series of peptidomimetic analogs, among them analog B1 (Figure S1) (IC50: 0.09μmol/L) was more active than the original lead core pentapeptide (IC50: 0.13μmol/L)10. These studies demonstrated that ASTs accept a range of chemical modifications, and these modified analogs have improved biological activity. We evaluated the relationship between two-dimensional structure and biological activity of *
2009 Elsevier Ltd. All rights reserved.
previously synthesized AST analogs and established a general approach for the design of potential AST analogs7. Those analogs should include an aromatic group, a linker of an appropriate length and a conserved C-terminal Leu-NH2 region. However, a compound interacts with its receptor actually in a three-dimensional (3D) structure. Therefore, exploring the relationship between the 3D conformation and the inhibitory activity of analogs is significant for guiding the design of novel compounds. Recently, homology modeling was used to build a 3D structure of the AST receptor of D. punctata (Dippu-AstR). The FGLa domain of AST was successfully docked into Dippu-AstR and the docking results are consistent with the findings of biological assays20. There are few articles about 3D-QSAR studies of peptides, mainly because of the flexibility of peptide molecules. Therefore, determining the 3D conformation of peptides should permit reliable construction of 3D-QSAR models. Recently, receptor-based 3D-QSAR approaches have been widely used, because this method can generate accurate 3D conformations of molecules and therefore produce reliable models21,22. We anticipate that a study on the relationship between the 3D structure conformation of AST analogs and their receptors was meaningful for understanding the mode of action of these peptides, as well as guiding the design of new active analogs. In this work, 48 FGLa AST analogs, previously synthesized in our lab, were docked into the above-mentioned model19 and their 3D conformations were used for receptor-based 3D-QSAR modeling. The 3D-QSAR model showed good predictive capability and was further applied to design novel AST analogs.
Corresponding author. Tel /fax: +86-010-62732223.E-mail address: [email protected] (Xinling Yang) and [email protected] (Zhenpeng Kai)
The designed AST analogs showed significant inhibitory activity, and the most potent analog A6 exhibited an IC50 value in the nanomolar range, which indicated that this model is reliable and useful for further design of new AST analogs. The molecular structures and biological activities of the 48 AST analogs were taken from our previous results 7, 9, 13, 14. The IC50 values were
converted to the corresponding pIC50 (-log IC50) and used as dependent variables in the QSAR experiments. The samples were divided into a training set of 41 compounds and a test set of 7 compounds23. The chemical structures, experimental and predicted pIC50 are provided in Table 1.
Table 1. Chemical structures, experimental and predicted pIC50 values of CoMFA and CoMSIA
NO.
R1
R2
R3
R4
Actual pIC50
CoMFA Predicted pIC50
Residual
CoMSIA Predicted pIC50
Residual
I1
9-ethoxy-9H-fluorene
carboxy methyl
benzyl
isobutyl
6.00
6.03
-0.03
6.01
-0.01
I2
4-hydroxyphenylethylamine
carboxy methyl
benzyl
sec-butyl
4.57
4.67
-0.10
4.55
0.02
I3
4-hydroxyphenylethylamine
carboxy methyl
benzyl
isobutyl
4.91
4.77
0.14
4.95
-0.04
I4
styryl
H
benzyl
isobutyl
7.40
7.17
0.23
7.01
0.39
I5
4-bromostyryl
H
benzyl
isobutyl
8.16
7.45
0.71
7.46
0.70
I6
3-methoxystyryl
H
benzyl
isobutyl
6.74
7.11
-0.37
6.98
-0.24
I7
4-fluorostyryl
H
benzyl
isobutyl
7.97
7.16
0.81
7.25
0.73
I8
2-nitrophenyl
H
benzyl
isobutyl
7.01
6.99
0.02
6.91
0.10
I9
4-methylphenyl
H
benzyl
isobutyl
6.88
6.85
0.03
6.93
-0.05
I10
phenyl
H
benzyl
isobutyl
6.81
6.90
-0.09
6.90
-0.09
I11
phenylethoxy
H
benzyl
isobutyl
7.81
7.85
-0.04
7.75
0.06
I12
4-nitrostyryl
H
4-pyridinylmethyl
isobutyl
7.05
6.82
0.23
7.10
-0.05
I13
4-nitrostyryl
H
phenyl
isobutyl
7.41
7.26
0.15
7.42
-0.01
I14
4-nitrostyryl
H
4-hydroxyphenylmethyl
isobutyl
6.38
6.57
-0.19
6.41
-0.03
I15
4-nitrostyryl
H
4-methoxyphenylmethyl
isobutyl
6.38
6.26
0.12
6.48
-0.10
I16
4-nitrostyryl
H
2-methylphenylmethyl
isobutyl
6.64
6.60
0.04
6.50
0.14
I17
4-nitrostyryl
H
3-methylphenylmethyl
isobutyl
6.18
6.29
-0.11
6.44
-0.26
I18
4-nitrostyryl
H
4-methylphenylmethyl
isobutyl
6.85
6.40
0.45
6.52
0.33
I19
4-nitrostyryl
H
3-chlorophenylmethyl
isobutyl
6.47
6.48
-0.01
6.38
0.09
I20
2-hydroxystyryl
H
benzyl
isobutyl
6.54
6.51
0.03
6.35
0.19
I21
2-fluorostyryl
H
benzyl
isobutyl
6.25
6.78
-0.53
6.71
-0.46
I22
2-chlorostyryl
H
benzyl
isobutyl
6.79
6.80
-0.01
6.77
0.02
I23
3-chlorostyryl
H
benzyl
isobutyl
7.01
7.11
-0.10
7.04
-0.03
I24
4-chlorostyryl
H
benzyl
isobutyl
7.32
7.30
0.03
7.35
-0.03
I25
3-bromostyryl
H
benzyl
isobutyl
7.11
7.08
0.03
6.98
0.13
I26
2,5-dichlorostyryl
H
benzyl
isobutyl
6.74
6.63
0.12
6.49
0.25
I27
3-trichloromethylstyryl
H
benzyl
isobutyl
7.11
7.08
0.03
7.08
0.03
I28
4-trifluoromethylstyryl
H
benzyl
isobutyl
7.56
7.67
-0.11
7.76
-0.20
I29
3-cyanostyryl
H
benzyl
isobutyl
6.99
6.87
0.13
7.03
-0.04
I30
4-cyanostyryl
H
benzyl
isobutyl
7.36
7.56
-0.20
7.57
-0.21
I31
2-nitrostyryl
H
benzyl
isobutyl
6.54
6.73
-0.19
6.48
0.06
I32
3-hydroxystyryl
H
benzyl
isobutyl
6.74
6.82
-0.08
6.77
-0.03
I33
4-hydroxystyryl
H
benzyl
isobutyl
7.55
7.35
0.20
7.52
0.03
I34
2-methylstyryl
H
benzyl
isobutyl
6.58
6.80
-0.22
6.83
-0.25
I35
4-methylstyryl
H
benzyl
isobutyl
7.28
7.17
0.11
7.16
0.12
I36
2-methoxystyryl
H
benzyl
isobutyl
6.51
6.49
0.02
6.63
-0.12
I37
2-trifluoromethylstyryl
H
benzyl
isobutyl
6.74
6.78
-0.04
6.84
-0.10
I38
4-methoxystyryl
H
benzyl
isobutyl
7.03
7.32
-0.29
7.14
-0.11
I39
4-(N,N-dimethylamino) styryl
H
benzyl
isobutyl
7.24
7.22
0.02
7.28
-0.04
I40
3-methylstyryl
H
benzyl
isobutyl
6.74
6.68
0.06
6.73
0.01
I41
2,6-dichlorostyryl
H
benzyl
isobutyl
6.62
6.71
-0.09
6.65
-0.03
T1a
N-methyl-4-toluenesulfona mide
H
benzyl
isobutyl
6.40
6.87
-0.47
6.92
-0.52
T2
2-chlorostyryl
H
benzyl
isobutyl
6.93
6.86
0.07
6.86
0.07
T3
3-nitrostyryl
H
benzyl
isobutyl
6.94
6.77
0.17
6.36
0.58
T4
3-fluorostyryl
H
benzyl
isobutyl
6.50
7.26
-0.76
6.96
-0.46
T5
2-bromostyryl
H
benzyl
isobutyl
6.89
6.83
0.06
6.74
0.15
T6
2-isopropylstyryl
H
benzyl
isobutyl
6.86
7.28
-0.42
7.28
-0.42
T7
3,4-dichlorostyryl
H
benzyl
isobutyl
7.03
7.17
-0.14
7.37
-0.34
a
T=Test set compounds markerd with underline
Figure 1. Molecular Docking of the AST analog I5 into the D. punctata AST receptor. (A) Hydrogen bonds and π−π interactions of the analog I5 with the receptor. The hydrogen bond is shown with a dotted yellow line. (B) Hydrophobicity of the binding pocket.
Molecular alignment is a crucial step in 3D-QSAR studies. Conventional 3D-QSAR alignments are usually constructed without considering the 3D structural information of receptors, often resulting in meaningless models. 3D-QSAR docking-based alignment are developed using the structural information of receptors, and often result in valuable models 21. In this study, 48 AST analogs were docked into the binding site of the AST receptor, and the 3D conformations of analogs were aligned, based on docking-based alignment methods. Figure S2 shows the alignment of training set. Additional parameters were set by default in the SYBYLX 2.0 program. The Partial Least Squares (PLS) method was used to generate statistically significant 3D-QSAR models in regression analyses24. The template of analog I5 and the pentapeptide were well matched in the homology Dippu-AstR model shown in Figure 1 and Figure S 3 respectively. Figure 1A shows that the C-terminal amide of Leu-NH2 is forming a hydrogen bond with the His336
of the receptor. In addition, the N-terminal amide of Gly has a hydrogen bond with Tyr253. Finally, the benzene rings of Phe and 4-bromocinnamic acid have π−π interactions with the benzene rings of Phe227 and Phe248 of homology Dippu-AstR respectively. In addition, pentapeptide (Figure S 3A) and FGLa 22 both have π−π interactions with the benzene ring of Tyr253. For the Tyr253 residues of homology Dippu-AstR, these compounds show different modes of action. This may provide an explanation for the higher potency of analog I5 in comparison to the pentapeptide. We propose that the structural conformation of analog I5 has higher affinity for the receptor. Figure 1B shows the hydrophobicity of the binding pocket. It indicates that the benzene ring of Phe and the N-terminal have strong hydrophobic interaction with the receptor, whereas sections rich in amide bonds are more hydrophilic. Interestingly, the hydrophobicity and hydrophilicity are consistent with the π−π effect and hydrogen bond interactions respectively. The docking results provided 3D conformation for the AST analogs and revealed the
Figure 2. Plot of predicted pIC50 against the experimental pIC50 by CoMFA(A) and CoMSIA(B)
interaction between the AST analogs and the receptor. The CoMFA and CoMSIA models were developed based on a set of 41 AST analogs. The values of the cross-validation correlation coefficient q2 > 0.5 and r2> 0.9 indicated that the 3D-QSAR models were reasonable and reliable enough for the prediction of biological activities. For the CoMFA analyses, the optimal number of components (ONC), q2 and r2 were 6, 0.741 and 0.900 respectively. In the CoMSIA model, the ONC, q 2 and r2 were 7, 0.658 and 0.912 respectively. The scatter plot of the predicted activity data versus the experimental data (training, test and new compounds) is shown in Figure 2. Two (steric and electrostatic) and five (steric, electrostatic, hydrophobic and hydrogen-bonding acceptor/donor) contour maps were derived by CoMFA and CoMSIA model, respectively, and were shown in Figures 3,4 and 5. The steric contours of the CoMFA (Figure 3A) and CoMSIA (Figure 3B) models displayed a green contour near position 4 of the
N-terminal benzene ring. This green contour indicated a favorable effect of bulky groups on the biological activities. In addition, CoMSIA steric contours revealed a yellow contour near positions 2 and 3 on benzene ring. The yellow contours illustrated the unfavorable effect of bulkier groups. This is consistent with the experimental data. For example, using the bulkier group -Br at position 4 (molecule I5 with pIC50 = 8.16) instead of a -H (molecule I4 with pIC50 = 7.40), significantly increased the biological activity. However, introduction of Br at position 3 (molecule I25 with pIC50 = 7.11) decreased biological activity. These effects were observed in other analogs, such as I33, I4 and I32 (4-OH, pIC50 = 7.55 > -H, pIC50 = 7.40 > 3-OH, pIC50 = 6.74); I7, I4 and T4 (4-F, pIC50 = 7.97 > -H, pIC50 = 7.40 > 3-F, pIC50 = 6.50). Figures 4A (CoMFA) and 4B (CoMSIA) display electrostatic contour maps. Two large red contours sandwiched position 4 of the N-terminal benzene ring (Figure 4A), which suggests that
Figure 3. Steric contour maps of CoMFA (A) and CoMSIA (B) based on compound I5. Steric fields: favored (green) and disfavored (yellow).
Figure 4. Electrostatic contour maps of CoMFA (A) and CoMSIA (B) based on compound I5. Electrostatic fields: the blue color shows the favored positive electrostatic area and the red color shows the favored negative electrostatic area.
Figure 5. Contour maps of CoMSIA based on compound I5. (A) Hydrophobic field: the yellow color shows the favored hydrophobic area and the white color shows the disfavored hydrophobic area. (B) H-bond donor/acceptor field: the cyan color shows the favored H-bond donor area. The red color represents the disfavored H-bond donor area. The magenta color shows the favored H-bond acceptor area. The white color shows the disfavored H-bond acceptor area.
Figure 6. General approach for the design of AST analogs. Elucidation of the structural formula. Modifications that are beneficial to the inhibition of JH biosynthesis: (1) Electron withdrawing group in the para site of the benzene ring at N-terminal (red block of region A). (2) Large group in the para site of the benzene ring at N-terminal (green block of region B). (3) Hydrophilic group in the site chain of the 2-site amino acid (cyan block of region C). (4) Proper electron density group in the benzene ring of the Phe (fuchsia block of region D).
negative electrostatic or decreased positive electrostatic in this region enhanced biological activity. For N-terminal benzene ring modification, molecules I7 and I24 (4-F, pIC50 = 7.97 > 4-Cl, pIC50 = 7.32), which the negative charged (Cl < F) increased, the pIC50 values (7.32 < 7.97) increased. The bromine substitution was an exception. The electronegativity of bromine is less than that of chlorine and fluorine, but the biological activity is much higher. Steric field effect indicated that introduction of a larger group at position 4 of the N-terminal benzene ring is beneficial for the improvement of activity. The radius of a bromine atom is larger than that of chlorine and fluorine atoms, which can explain the high activity of bromine substitution compound I5 (pIC50 = 8.16). Therefore, steric and electrostatic effects should be taken into consideration when designing compounds. The negative electrostatic properties can be further investigated considering compounds I28 and I33 (4-CF3, pIC50= 7.56 > 4-OH, pIC50 = 7.55). The electron withdrawing effect of the hydroxyl group is weaker than electron-donating effect of the p-π conjugation, which showed electron-donating effect. While trifluoromethyl is a strong electron-withdrawing group. Therefore, the electronegativity of the trifluoromethyl group is stronger than hydroxyl group. A large blue contour near position 2 of the N-terminal benzene ring and positions 3, 4 of the benzene ring of Phe (Figure 4A) indicate that the positive electrostatic or decreased negative electrostatic forces improve bioactivity. However, Figure 4B reveals a red contour at position 4 of the benzene ring of Phe, which means that position 4 of the benzene ring on the Phe is a controversial structural modification site. The benzene ring of Phe has a π−π interaction with Phe227
(Figure 1A). According to Hunter-Sanders rules for π-π interactions, the electron cloud density on the benzene ring has an effect on the π-π interaction25. Therefore, a suitable electron cloud density on the Phe is beneficial for biological activity. The bioassay results (Table 1) demonstrate that the substitution of the pyridine (molecular I12: R3 = 4-pyridylmethyl, pIC50 = 7.05) is more active than the electron-withdrawing or electron-donating substitutions (molecular I14-I19 pIC50<7.00). It has been proposed that the electron cloud density of the pyridine ring is uniform, whereas substituents could destroy the electron cloud density on the benzene ring. Hydrophobic contour map is shown in Figure 5A. A yellow contour at position 4 of the N-terminal benzene ring suggested that the introduction of hydrophobic substituents would benefit inhibitory activity. This can be explained by considering molecules I28, which have a hydrophobic substituent of 4-trifluoromethyl group with pIC50 = 7.56, in contrast to molecule I4 (having H with pIC50 = 7.40), the inhibitory activity is increased. A large white contour surrounding 2-site amino acid (Gly) indicated that the introduction of hydrophilic substituents would favor inhibitory activities. This is consistent with the results of our previous work17. Figure 5B reveals the H-bond donor/acceptor contour map. One medium-size red contour near the 3-position of the benzene ring of the N-terminus indicates that the introduction of an H-bond donor group in this region would result in low activities. A magenta contour at the position 4 of benzene ring of N-terminal demonstrate that H-bond acceptor substituents would be beneficial for biological activity. For instance, the activity of I33 (pIC50 =7.55) having 4-
Table 2 Chemical structures, experimental IC50 and predicted CoMFA and CoMSIA pIC50 values of new designed analogs
Compd
R3
R5
IC50 (nmol/L) (95%CIb)
Actual pIC50
CoMFA Predicted pIC50
Residual
CoMSIA Predicted pIC50
Residual
H17
-
-
40.64 (9.174-180)
7.39
7.20
0.19
7.00
0.39
A1
benzyl
4-NO2
16.46(4.407-61.49)
7.78
6.02
1.76
6.88
0.90
A2
4-iodobenzyl
4-NO2
25.29(8.265-77.40)
7.60
6.50
1.10
6.64
0.96
A3
4-methylbenzyl
4-NO2
164.20(78.71-342.7)
6.79
6.36
0.43
6.58
0.21
A4
4-pyridylmethyl
4-NO2
17.62(3.106-99.96)
7.75
6.95
0.80
6.70
1.05
A5
4-pyridylmethyl
4-Br
10.88(4.236-27.96)
7.97
7.14
0.83
7.61
0.36
A6
4-pyridylmethyl
4-CF3
3.79(0.8625-16.66)
8.41
7.33
1.07
7.84
0.56
b
95% CI=95% confidence intervals - H17 is different from designed analogs structure
hydroxystyryl at R1 is higher than I4 (having styryl at R1 with pIC50 = 7.40). The area in which H-bond acceptors are favorable for activity in Figure 5B may be due to the 4-OH group. This effect can be seen in molecules I7 (having 4-fluorostyryl at R1 with pIC50=7.97). However, this SAR results requires more experimental data to prove. Based on 3D-QSAR analyses, a general structure for novel potent bioactive AST analogs is proposed. The structure should have four critical substitutions (A, B, C and D): (1) potent electron withdrawing group at the 4 position of the benzene ring of the N-terminal (Region A); (2) large group at the 4 position of the benzene ring of the N-terminal (Region B); (3) hydrophilic group in the side chains of the 2-site amino acids (Region C); (4) appropriate electron density of the benzene ring of Phe (Region D). This strategy of modifications should be helpful for the design of novel potent AST analogs. Hence, six novel AST analogs were designed and synthesized with H17 as lead compound. This design strategy was shown in Figure 6. Their synthetic route is illustrated in the Scheme S1. The physical parameters and identification data of target compounds are provided in the supporting information. Their ability to inhibit JH biosynthesis by the CA in vitro was evaluated and the IC50 results were listed in Table 2. Analog A1, in which Gly2 was replaced by Asp2, showed lower IC 50 values (IC50: 16.46 nmol/L) than H17 (IC50: 40.64 nmol/L), validating the concept that the introduction of a hydrophilic group improves the inhibitory activity. Hence, Asp2 was introduced into other five analogs. After modification of the benzene ring of Phe, analog A4 (R3=4-pyridylmethyl; IC50: 17.62 nmol/L) showed similar bioactivity to A1. Following a change in the electron density of benzene ring, the analog A3 (R3=4-methylbenzyl; IC50: 164.2 nmol/L), with an electron donating group, and A2 (R3=4-iodobenzyl; IC50: 25.29 nmol/L) containing an electron-withdrawing group, showed lower activity than A1. The introduction of aromatic groups with the proper electron cloud density (such as a pyridine or a benzene ring) can enhance the inhibition of JH biosynthesis (strategy 4). Based on strategy (1) and (2), electron withdrawing and large groups (NO2, Br, CF3) were introduced at the para site of the benzene ring at the N-terminal，and the whole series(A4, A5,
A6)，particularly analog A6 (IC50: 3.79 nmol/L), showed potent activity in the inhibition of JH biosynthesis. These results indicated that replacing of Gly with Asp is good for in vitro activity. However, Asp has an ionizable group, COOH in its side chain, it may not be good for in vivo activity because the permeability of a compound having an ionizable group through cell membranes will be poor. Thus, we will design and synthesize new analogs containing some hydrophilic amino acids that are difficult to ionize (such Asn, etc) so as to increase their hydrophilicity and reduce the ionization ability in our future work. It is speculated that these analogs may be easier to penetrate the cell membrane and have good activity in vivo. In summary, a receptor-based 3D-QSAR model of AST analogs was built, which indicated that the position of Phe3, Gly2 and N-terminal of peptides are key parts for designing new analogs. Six novel analogs were therefore designed and synthesized using the modified design strategy. The in vitro bioassay results showed that the activity of most analogs was higher than H17, particularly analog A6, exhibited potent inhibitory activity on JH biosynthesis. This implies that the receptor-based 3D-QSAR model is accurate and reliable for new active AST analogs design.
Acknowledgments This work was supported by the grants from the National Key Research and Development Plan (No. 2017YFD0200504) and the National Natural Science Foundation of China (No. 21877126 & 21372257). References and notes 1. 2. 3. 4. 5. 6. 7.
Evans, P. D.; Robb, S.; Cuthbert, B. A. Pestic. Sci. 1989, 25, 71. Stay B.; Tobe S.S. Annu. Rev. Entomol. 2007, 52, 277. Zhang, C.L.; Qu, Y.Y.; Wu, X.Q.; Song, D.L.; Ling, Y.; Yang, X.L. J. Agric Food Chem. 2015, 63,4527. Choi, M. Y.; Meer, R. K. V. U.S. Patent 10 017 538, 2018. Gade, G.; Marco, H.G. Arch Insect Biochem Physiol. 2017, 95, 21399. DOI: 10.1002/arch.21399. Kai, Z.P.; Huang, J.; Tobe, S.S.; Yang, X.L. Peptides. 2009, 30, 1249. Kai, Z.P.; Huang, J.; Xie, Y.; Tobe, S.S.; Ling, Y.; Zhang, L, Zhao, Y.C.; Yang, X.L.; J. Agric Food Chem. 2010, 58, 2652.
8. 9.
10. 11. 12. 13. 14. 15. 16. 17.
Kai, Z.P.; Ling, Y, Liu, W.J.; Zhao, F.; Yang, X.L. Biochim Biophys Acta. 2006, 1764, 70. Kai, Z.P.; Xie, Y.; Huang, J.; Tobe, S.S.; Zhang, J.R.; Ling, Y.; Zhang, L.; Zhao, Y.C.; Yang, X.L. J. Agric Food Chem 2011, 59, 2478. Xie, Y.; Kai, Z.P.; Tobe, S.S.; Deng, X.L.; Ling, Y.; Wu, X.Q.; Huang, J.; Zhang, L.; Yang, X.L. Peptides. 2011, 32, 581. Xie, Y.; Zhang, L.; Wu, X.Q.; Zhang, C.L.; Yang, X.L.; Tobe, S.S. Peptides. 2015, 68, 214. Xie, Y.; Zhang, L.; Zhang, C.L.; Wu, X.Q.; Deng, X.L.; Yang, X.L.; Tobe, S.S. J. Agric Food Chem. 2015, 63, 2870. Wu, X Q.; Huang, J.; Wang, M.Z.; Zhang, Z.; Li, X.L.; Yang, X.L.; Tobe, S.S. Chin. Chem. Lett. 2016, 27, 559. Wu, X.Q.; Wang, M.Z.; Huang, J.; Zhang, L.; Zhang, Z.; Ling, Y.; Yang, X.L.; Tobe, S.S. Pest Manag Sci. 2017, 73, 500. Xie, Y.; Wang, M.Z.; Zhang, L.; Wu, X.Q.; Yang, X.L.; Tobe S.S. J. Pept Sci. 2016, 22, 600. DOI 10.1002/psc.2906. Wang, M.Z.; Wang, X.W.; Wu, X.Q.; Li, X.L.; Yang, X.L. Sci Sin Chim. 2016, 11, 1235. DOI 10.1360/N032016-00128. Wang, M.Z.; Zhang, L.; Wang, X.W.; Ling, Y.; Wu, X.Q.; Li, X.L.; Mi, Y.D.; Yang, X.L. Chin. Chem. Lett. 2018, 29, 1375.
18. Hans, P.V.; Ronald, J.N.; Jozef, V. B. Handbook of Biologically Active Peptides, Academic Press, San Diego, 2013. 19. Woodhead, A.P.; Stay, B.; Seidel, S.L.; Khan, M.A.; Tobe, S.S. P Proc. Natl. Acad. Sci. U.S.A. 1989, 86, 5997. 20. Huang, S.S.; Chen, S.S.; Zhang, H.L.; Yang, H.; Yang, H.J.; Ren, Y.J.; Kai, Z.P.; J. Agric Food Chem. 2018, 66, 3644. 21. Fang, C.; Xiao, Z.Y. Curr. Top. Med. Chem. 2016, 16, 1463. 22. Ding, L.N.; Wang, Z. Z.; Sun, X. D.; Yang, J.; Ma, C. Y.; Li, W.; Liu, H. M. Bioorg Med Chem Lett. 2017, 27, 3521. 23. Leonard, J.T.; Roy K.; QSAR Comb. Sci. 2006, 25, 235. DOI 10.1002/qsar.200510161. 24. Bush, B. L.; Nachbar Jr., R.B. J Comput Aided Mol Des. 1993, 7, 587. 25. Hunter, C.A.; Singh, J.; Thornton, J.M. J. Mol. Bio.1991, 218, 837.
Supplementary Material Supplementary data associated with this article can be found, in the online version，at
Highlights 1. Receptor-based 3D-QSAR model is accurate and reliable for designing new analogs. 2. Phe3, Gly2 and N-terminus in the allatostatin structure are key parts of a design. 3. Potent analogs have a hydrogen bond reaction with Tyr253 of homology Dippu-AstR. 4. Uniform electron cloud density on the benzene of Phe3 is beneficial for activity. 5. Analog A6 have a potent inhibitory activity on JH biosynthesis in nanomolar level.