• Bulletin of the Korean Chemical Society
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• v.27 no.7
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• pp.1025-1030
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• 2006

A 3D-CoMFA model with pranlukast analogues was constructed, which could be applied to predict the antagonistic activity of aryl benzyl ether analogues against LTD4. Molecular modeling and 3D-CoMFA studies were performed on 78 pranlukast analogues and 14 aryl benzyl ethers to evaluate the antagonistic behavior of aryl benzyl ethers and provide information for further modification of this kind of compounds. The aryl benzyl ether core was found to be in excellent three dimensional match with the central planar moiety of pranlukast analogues, and the pranlukast 3D-CoMFA model could be successfully applied to predict the biological activity of aryl benzyl ether analogues.

• Applied Biological Chemistry
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• v.47 no.3
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• pp.351-356
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• 2004

Holographic quantitative structure activity relationships (HQSAR) as 2D QSAR between the herbicidal activities against root and shoot of rice plant (Orysa sativa L.) and barnyardgrass (Echinochloa crus-galli), and structures of A=3,4,5,6-tetra-hydrophthalimino, B = 3-chloro-4,5,6,7-tetrahydro-2H-indazolyl and C = 3,4-dimethylmaleimino substituents in 1-(5-methyl-3-phenylisoxazolin-5-yl)methoxy-2-chloro-4-fluorobenzene derivatives were studied and discussed. The statistical results of four HQSAR models for the herbicidal activities against root and shoot of the two plants showed the best predictability of the herbicidal activities based on the cross-validated $r^2\;_{cv}\;(q^2=\;0.760{\sim}0.924)$, non cross-validated conventional coefficient $(r^2\;_{ncv}\;=\;0.868{\sim}0.970)$ and PRESS values $(0.123{\sim}0.261)$. The results indicated that the qualities of HQSAR models for barnyardgrass were slightly higher than that of rice plant. And also, the predictability of HQSAR models were higher $(q^2\;=\;HQSAR\;>\;CoMFA)$ than CoMFA but the conventional coefficients of HQSAR models lower $(r^2\;=\;HQSAR\;<\;CoMFA)$ than CoMFA. Moreover, from the contribution maps, it was founded that the selectivity between the two plants depends upon the 2-fluoro-4-chloro-5-alkoxyanilino and $R_3$ substituent on the C-phenyl ring. These features suggest where to modify a molecular structure in order to improve its selective of herbicidal activities against barnyardgrass.

• The Korean Journal of Pesticide Science
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• v.9 no.2
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• pp.140-145
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• 2005

Quantitative Structure Activity Relationship (QSAR) assumes the relatedness between physical property and biological activity. However, activity data measured at single concentration such as percent activity have not been used extensively for modeling purpose. This probably comes from the fact that these values are qualitative instead of quantitative. To utilize percent activity data for molecular modeling, we classified the whole data into two classes. One class represents the active while the other signifies the inactive. The percent activity data of ${\beta}$-Ketoacetoanilides measured for TLB (Tomato Late Blight) were investigated. CoMFA (Comparative Molecular Field Analysis) was used as a discriminant function. Using CoMFA provides 3D (three dimensional) information, which is crucial for chemical insight. It can also serve as a predictive model. The resultant model classified the given data correctly (98%). When LOO (leave-one-out) crossvalidation procedure was applied, the classification accuracy was 69%. Therefore two class approximation of percent activity data with CoMFA can be utilized to understand the relationship between chemical structure and biological activity and design subsequent chemical analogs.

• Journal of Integrative Natural Science
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• v.3 no.3
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• pp.162-167
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• 2010

A pseudoreceptor combines structure-based and ligand-based techniques to represent a unifying concept for both receptor mapping and ligand matching. In this molecular modeling approach, there are opportunities to construct the pseudoreceptor models using a set of small molecules. To build a reliable pseudoreceptor model, we need a set of ligand molecules with known affinity (biological activity) to generate 3D bioactive conformation for each of these ligand molecules. Several software packages are available to generate a pseudoreceptor model and this can provide an entry point for structure based drug discovery in cases where receptor structure information is not available. In this review, we presented the concept of pseudoreceptor, as well as discussed about various software packages available to generate a pseudoreceptor model.

• Applied Biological Chemistry
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• v.47 no.4
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• pp.414-421
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• 2004

3D QSAR studies for protox inhibition activities against root and shoot of the rice plant (Orysa sativa L.) and barnyardgrass (Echinochloa crus-galli) by a series of new 1-(5-methyl-3-phenylisoxazolin-5-yl)methoxy-2-chloro-4-fluorobenzene derivatives were conducted based on the results (Sung, N. D. et al.'s, (2004) J. Korean Soc. Appl. Biol. Chem. 47(3), 351-356) using comparative molecular similarity indices analysis (CoMSIA) methodology. Four CoMSIA models, without hydrogen bond donor field for the protox inhibition activities against root and shoot of the two plants, were derived from the combination of several fields using steric field, hydrophobic field, hydrogen bond acceptor field, LUMO molecular orbital field, dipole moment (DM) and molar refractivity (MR) as additional descriptors. The predictabilities and fitness of CoMSIA models for protox inhibition activities against barnyard-grass were higher than that of rice plant. The statistical results of these models showed the best predictability of the protox inhibition activities against barnyard-grass based on the cross-validated value $r^2\;_{cv}\;(q^2=0.635{\sim}0.924)$, non cross-validated, conventional coefficient $r^2\;_{ncv.}$ value $(r^2=0.928{\sim}0.977)$ and PRESS value $(0.255{\sim}0.273)$. The protox inhibition activities exhibited a strong correlation with the steric $(5.4{\sim}15.7%)$ and hydrophobic $(68.0{\sim}84.3%)$ factors of the molecules. Particularly, the CoMSIA models indicated that the groups of increasing steric bulk at ortho-position on the C-phenyl ring will enhance the protox inhibition activities against barnyard-grass and subsequently increase the selectivity.

• The Korean Journal of Pesticide Science
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• v.8 no.3
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• pp.162-167
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• 2004

In recent years, the diamondback moth (DBM), Plutella xylostella has become one of the most important pests for cruciferous plants in the world. A new type of the thiophosphoryl pyrazole insecticide, called KH502. Its outstanding insecticidal activity could be effective alternative against DBM. We investigated, using the comparative molecular field analysis (CoMPA) method, The structure-activity relationship of various thiophosphorylpyrazole derivatives and structure requirement for insecticidal activity. We found, the key substructures in pyrazole derivatives, the trifluoro-methyl group and the thiophosphoryl group. Both play an important role in insecticidal activity with the binding site. The three dimensional Quantitative Structure Activity Relationship (QSAR) analysis could provide useful information for the structural requirements of pyrazole insecticide as an insecticidal and the design of a new insecticide.

• The Korean Journal of Pesticide Science
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• v.8 no.3
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• pp.151-161
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• 2004

Three dimensional quantitative structure-activity relationships (3D-QSAR) studies for the protox inhibition activities against root and shoot of rice plant (Orysa sativa L.) and barnyardgrass (Echinochloa crus-galli) by a series of new A=3,4,5,6-tetrahydrophthalimino, B=3-chloro-4,5,6,7-tetrahydro-2H-indazolyl and C=3,4-dimethylmaleimino group, and R-group substituted on the phenyl ring in 1-(5-methyl-3-phenylisoxazolin-5-yl)methoxy-2chloro-4-fluorobenzene derivatives were performed using comparative molecular field analyses (CoMFA) methodology with Gasteiger-Huckel charge. Four CoMFA models for the protox inhibition activities against root and shoot of the two plants were generated using 46 molecules as training set and the predictive ability of the each models was evaluated against a test set of 8 molecules. And the statistical results of these models with combination (SIH) of standard field, indicator field and H-bond field showed the best predictability of the protox inhibition activities based on the cross-validated value $r^2_{cv.}$ $(q^2=0.635\sim0.924)$, conventional coefficient $(r^2_{ncv.}=0.928\sim0.977)$ and PRESS value $(0.091\sim0.156)$, respectively. The activities exhibited a strong correlation with steric $(74.3\sim87.4%)$, electrostatic $(10.10\sim18.5%)$ and hydrophobic $(1.10\sim8.30%)$ factors of the molecules. The steric feature of molecule may be an important factor for the activities. We founded that an novel selective and higher protox inhibitors between the two plants may be designed by modification of X-subsitutents for barnyardgrass based upon the results obtained from CoMFA analyses.

• Applied Biological Chemistry
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• v.48 no.1
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• pp.82-88
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• 2005

3D QSAR studies for the fungicidal activities against resistive phytophthora blight (RPC; 95CC7303) and sensitive phytophthora blight (Phytopthora capsici) (SPC; 95CC7105) by a series of new 2-alkoxyphenyl-3-phenylthioisoindoline-1-one derivatives (X: A=propynyl & B=2-chloropropenyl) were studied using comparative molecular field analyses (CoMFA) methodology. The CoMFA models were generated from the two different alignment, atom based fit (AF) alignment and field fit (FF) alignment. The atom based alignment exhibited a higher statistical results than that of field fit alignment. The best models, A3 and A7 using combination fields of H-bond field, standard field, LUMO and HOMO molecular orbital field as additional descriptors were selected to improve the statistic of the present CoMFA models. The statistical results of the two models showed the best predictability of the fungicidal activities based on the cross-validated value $q^2\;(r^2_{cv.}=RPC:\;0.625\;&\;SPC:\;0.834)$, non cross-validated value $(r^2_{ncv.}=RPC:\;0.894\;&\;SPC:\;0.915)$ and PRESS value (RPC: 0.105 & SPC: 0.103), respectively. Based on the findings, the predictive ability and fitness of the model for SPC was better than that of the model for RPC. The fugicidal activities exhibited a strong correlation with steric $(66.8{\sim}82.8%)$, electrostatic $(10.3{\sim}4.6%)$ and molecular orbital field (SPC: HOMO, 12.6% and RPC: LUMO, 22.9%) factors of the molecules. The novel selective character for fungicidal activity between two fungi depend on the positive charge of ortho, meta-positions on the N-phenyl ring and size of hydrophilicity of a substituents on the S-phenyl ring.

• The Korean Journal of Pesticide Science
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• v.9 no.1
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• pp.26-34
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• 2005

3D-QSAR studies for the fungicidal activities against resistance phytophthora blight (RPC; 95CC7303) and sensitive phytophthora blight (Phytopthora capsici) (SPC; 95CC7105) by a series of new 2-alkoxyphenyl-3-phenylthioisoindoline-1-one derivatives (A & B) were studieded using comparative molecular similarity indices analyses (CoMSIA) methodology. From the based on the results, the two CoMSIA models, R5 and S1: as the best models were derivated. The statistical results of the models showed the best predictability and fitness for the fungicidal activities based on the cross- validated value ($q^2=0.714{\sim}0.823$) and non cross-validated, value ($r^2_{ncv.}=0.918{\sim}0.954$), respectively. The model R5 for fungicidal activity of RPC generated from the field fit alignment and combination of electrostatic field, H-bond acceptor field and LUMO molecular orbital field. The model S1 (or S5) for fungicidal activity of SPC generated from the atom based fit alignment and combination of steric field and HOMO molecular orbital field. The models also shows that inclusion of H-bond acceptor field (A) improved the statistical significance of the models. From the based graphical analyses of CoMSIA contribution maps, it was revealed that the novel selective character for fungicidal activities between the two fungi by modify of X-sub-stituent on the N-phenyl group and R-substituent on the S-phenyl group will be able to achivement.

• Journal of Integrative Natural Science
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• v.9 no.2
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• pp.121-127
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• 2016

CXC chemokine receptor 2 (CXCR2) is a prominent chemokine receptor on neutrophils. The neutrophilic inflammation in the lung diseases is found to be largely regulated through CXCR2 receptor. Antagonist of CXCR2 may reduce the neutrophil chemotaxis and alter the inflammatory response. Hence, in the present study, ligand based Comparative molecular field analysis (CoMFA) was performed on a series of CXCR2 antagonist named pyrimidine-5-carbonitrile-6-alkyl derivatives. The optimum CoMFA model was obtained with statistically significant cross-validated coefficients ($q^2$) of 0.568 and conventional coefficients ($r^2$) of 0.975. The contour maps suggest the important structural modifications and this study can be used to guide the development of potent CXCR2 antagonist.