| Literature DB >> 28746366 |
Guanghui Zong1, Xiaojing Yan2, Jiawei Bi1, Rui Jiang1, Yinan Qin1, Huizhu Yuan2, Huizhe Lu1, Yanhong Dong1, Shuhui Jin1, Jianjun Zhang1.
Abstract
1,3,4-Thiadiazole and sugar-derived molecules have proven to be promising agrochemicals with growth promoting, insecticidal and fungicidal activities. In the research field of agricultural fungicide, applying union of active group we synthesized a new set of 1,3,4-thiadiazole xylofuranose derivatives and all of the compounds were characterized by 1H NMR and HRMS. In precise toxicity measurement, some of compounds exhibited more potent fungicidal activities than the most widely used commercial fungicide Chlorothalonil, promoting further research and development. Based on our experimental data, 3D-QSAR (three-dimensional quantitative structure-activity relationship) was established and investigated using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques, helping to better understand the structural requirements of lead compounds with high fungicidal activity and environmental compatibility.Entities:
Mesh:
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Year: 2017 PMID: 28746366 PMCID: PMC5528880 DOI: 10.1371/journal.pone.0181646
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Design strategy for target compounds.
Fig 2Synthesis of the title compounds k/l.
Fig 3Key COSY (bold) and HMBC (arrows) correlations in l8.
EC50 and EC90 values of target compounds against S. sclerotiorum.
| Compd. | toxic regression equation | EC50 | EC90 | correlation coefficient R |
|---|---|---|---|---|
| Y = 5.24+0.85x | 0.52 | 16.78 | 0.9377 | |
| Y = 5.08+0.62x | 0.75 | 86.27 | 0.9266 | |
| Y = 4.24+0.87x | 7.51 | 221.00 | 0.9772 | |
| Y = 3.48+1.44x | 11.42 | 89.25 | 0.9654 | |
| Y = 4.87+1.17x | 1.29 | 16.04 | 0.9798 | |
| Y = 4.06+1.48x | 4.34 | 32.03 | 0.9471 | |
| Y = 5.00+0.93x | 0.99 | 23.50 | 0.9691 | |
| Y = 5.36+1.00x | 0.43 | 8.40 | 0.9673 | |
| Y = 3.71+1.23x | 11.07 | 121.16 | 0.9347 | |
| Y = 3.26+1.86x | 8.55 | 41.71 | 0.9332 | |
| Y = 4.73+0.73x | 2.35 | 135.00 | 0.9488 | |
| Y = 5.26+0.79x | 0.46 | 19.42 | 0.8998 | |
| Y = 4.85+1.04x | 1.39 | 23.99 | 0.9375 | |
| Y = 4.19+1.18x | 4.83 | 58.36 | 0.9979 | |
| Y = 4.56+1.18x | 2.35 | 28.96 | 0.9506 | |
| Y = 5.24+0.99x | 0.57 | 11.25 | 0.9729 | |
| Y = 4.56+1.34x | 2.12 | 19.15 | 0.9719 | |
| Y = 3.83+1.73x | 4.78 | 26.37 | 0.9955 | |
| Y = 5.21+1.14x | 0.66 | 8.73 | 0.9993 | |
| Y = 3.08+1.79x | 11.69 | 60.51 | 0.9573 | |
| Y = 3.63+1.86x | 5.43 | 26.55 | 0.9996 | |
| Y = 4.72+1.00x | 1.92 | 36.40 | 0.9723 | |
| Y = 5.19+0.84x | 0.59 | 19.56 | 0.9784 |
Fig 4Image of superimposed structures.
COMFA and COMSIA analysis results*.
| Parameter | COMFA | COMSIA | COMSIA | COMSIA | COMSIA |
|---|---|---|---|---|---|
| 0.639 | 0.528 | 0.508 | 0.486 | 0.495 | |
| 0.968 | 0.964 | 0.962 | 0.913 | 0.945 | |
| SE | 0.110 | 0.116 | 0.120 | 0.174 | 0.144 |
| F | 67.036 | 59.371 | 55.513 | 31.587 | 37.969 |
| Components relative field contributions(%) | 5 | 5 | 5 | 4 | 5 |
| S | 59.5 | 11.9 | 11.5 | - | - |
| E | 40.5 | 35.3 | 33.3 | 40.2 | 48.8 |
| H | - | 37.0 | 35.5 | 44.3 | 51.2 |
| D | - | 15.9 | 14.6 | 15.5 | - |
| A | - | - | 5.1 | - | - |
*Model 1: S+E+H+D; Model 2: S+E+H+D+A; Model 3: E+H+D; Model 4: E+H.
Training set: k1, k3, k4, k5, k6, k8, k9, k10, l1, l2, l3, l5, l6, l7, l8, l10, l11.
Test set: k2, k7, k11, l4, l9.
Fig 5The correlation between the experimental values and predicted of COMFA (training set ■, test set ▲).
Fig 6The correlation between the experimental values and predicted of COMSIA (training set ■, test set ▲).
The experimental value, forecast and difference of CoMFA and CoMSIA models.
| Compd. | Experimental values of p(EC50) | CoMFA | CoMSIA Model 1 | ||
|---|---|---|---|---|---|
| predicted values | D-value | predicted values | D-value | ||
| 6.284 | 6.24 | 0.044 | 6.301 | -0.017 | |
| 6.1249 | 6.125 | 0 | 6.125 | 0 | |
| 5.1244 | 5.111 | 0.013 | 5.192 | -0.068 | |
| 4.9423 | 4.922 | 0.02 | 5.079 | -0.137 | |
| 5.8894 | 5.8 | 0.089 | 5.827 | 0.062 | |
| 5.3625 | 5.449 | -0.087 | 5.429 | -0.067 | |
| 6.0044 | 6.004 | 0 | 6.004 | 0 | |
| 6.3665 | 6.39 | -0.023 | 6.359 | 0.007 | |
| 4.9559 | 5.143 | -0.187 | 5.046 | -0.09 | |
| 5.068 | 4.956 | 0.112 | 4.9 | 0.168 | |
| 5.6289 | 5.998 | -0.369 | 5.998 | -0.369 | |
| 6.3372 | 6.144 | 0.193 | 6.318 | 0.019 | |
| 5.857 | 5.906 | -0.049 | 5.679 | 0.178 | |
| 5.3161 | 5.239 | 0.077 | 5.274 | 0.042 | |
| 5.6289 | 5.629 | 0 | 5.629 | 0 | |
| 6.2441 | 6.36 | -0.115 | 6.331 | -0.087 | |
| 5.6737 | 5.625 | 0.049 | 5.549 | 0.124 | |
| 5.3206 | 5.359 | -0.038 | 5.278 | 0.042 | |
| 6.1805 | 6.207 | -0.027 | 6.19 | -0.01 | |
| 4.9322 | 4.932 | 0 | 4.932 | 0 | |
| 5.2652 | 5.283 | -0.018 | 5.412 | -0.147 | |
| 5.7167 | 5.769 | -0.053 | 5.738 | -0.021 | |
Fig 7Contour plots (a) CoMSIA Steric. (b) CoMFA Electrostatic. (c) CoMSIA Steric. (d) CoMSIA Electrostatic. (e) CoMSIA Hydrophobic. (f) CoMSIA Hydrogen bond receptor. Compound k8 in cap and stick is shown.
The target name, the PDB ID and fit score of 22 compounds.
| Compd. | PDB ID | Target Name | Fit Score |
|---|---|---|---|
| 2CEK | Acetylcholinesterase | 6.575 | |
| 1TCX | Gag-Pol polyprotein | 7.332 | |
| 1LWL | Camphor 5-monooxygenase | 6.511 | |
| 1LN3 | Phosphatidylcholine transfer protein | 7.411 | |
| 2R43 | Gag-Pol polyprotein | 7.044 | |
| 1LN3 | Phosphatidylcholine transfer protein | 7.143 | |
| 3FNH | Enoyl-[acyl-carrier-protein] reductase [NADH] | 6.916 | |
| 3DCT | Bile acid receptor | 7.8 | |
| 1LWL | Camphor 5-monooxygenase | 6.477 | |
| 1LN3 | Phosphatidylcholine transfer protein | 7.093 | |
| 3DCT | Bile acid receptor | 7.8 | |
| 1TCX | Gag-Pol polyprotein | 7.371 | |
| 3DCU | Bile acid receptor | 7.298 | |
| 1MEU | Gag-Pol polyprotein | 7.384 | |
| 1LN3 | Phosphatidylcholine transfer protein | 7.518 | |
| 2CEK | Acetylcholinesterase | 7.24 | |
| 1MEU | Gag-Pol polyprotein | 7.835 | |
| 1TCX | Gag-Pol polyprotein | 7.511 | |
| 2CEK | Acetylcholinesterase | 7.208 | |
| 1MEU | Gag-Pol polyprotein | 6.798 | |
| 1G2N | NONE | 7.338 | |
| 1G2N | NONE | 8.602 |
The target name, the PDB ID and normalized fit score of 22 compounds.
| Compd. | PDB ID | Target Name | Normalized Fit Score |
|---|---|---|---|
| 1ZGF | Carbonic anhydrase 2 | 0.79 | |
| 1ZGF | Carbonic anhydrase 2 | 0.856 | |
| 1ZGF | Carbonic anhydrase 2 | 0.7274 | |
| 1ZGF | Carbonic anhydrase 2 | 0.8581 | |
| 1ZGF | Carbonic anhydrase 2 | 0.8229 | |
| 1G48 | Carbonic anhydrase 2 | 0.8733 | |
| 1IF8 | Carbonic anhydrase 2 | 0.8492 | |
| 1F4F | Thymidylate synthase | 0.7001 | |
| 1ZGF | Carbonic anhydrase 2 | 0.7231 | |
| 1ZGF | Carbonic anhydrase 2 | 0.8161 | |
| 1F4F | Thymidylate synthase | 0.7001 | |
| 1BN4 | Carbonic anhydrase 2 | 0.8544 | |
| 1ZGF | Carbonic anhydrase 2 | 0.8562 | |
| 1I8Z | Carbonic anhydrase 2 | 0.8473 | |
| 1ZGF | Carbonic anhydrase 2 | 0.8551 | |
| 1ZGF | Carbonic anhydrase 2 | 0.8229 | |
| 1G48 | Carbonic anhydrase 2 | 0.877 | |
| 1IF8 | Carbonic anhydrase 2 | 0.8658 | |
| 1BN4 | Carbonic anhydrase 2 | 0.8351 | |
| 1ZGF | Carbonic anhydrase 2 | 0.7259 | |
| 1ZGF | Carbonic anhydrase 2 | 0.8185 | |
| 1G48 | Carbonic anhydrase 2 | 0.8677 |