• Bulletin of the Korean Chemical Society
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• v.32 no.5
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• pp.1604-1612
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• 2011

We developed three-dimensional quantitative structure activity relationship (3D-QASR) models for 17 adamantyl derivatives as P-glycoprotein (P-gp) inhibitors. Eighteen different partial charge calculation methods were tested to check the feasibility of the 3D-QSAR models. Best predictive comparative molecular field analysis (CoMFA) model was obtained with the Austin Model 1-Bond Charge Correction (AM1-BCC) atomic charge. The 3D-QSAR models were derived with CoMFA and comparative molecular similarity indices analysis (CoMSIA). The final CoMFA model ($q^2$ = 0.764, $r^2$ = 0.988) was calculated with an AM1-BCC charge and electrostatic parameter, whereas the CoMSIA model ($q^2$ = 0.655, $r^2$ = 0.964) was derived with an AM1-BCC charge and combined steric, electrostatic, hydrophobic and HB-acceptor parameters. Leave-five-out (LFO) cross-validation was also performed, which yielded good correlation coefficient for both CoMFA (0.801) and CoMSIA (0.656) models. Robustness of the developed models was checked further with 1000 run bootstrapping analyses, which gave an acceptable correlation coefficient for CoMFA (BS-$r^2$ = 0.997, BS-SD = 0.003) and CoMSIA (BS-$r^2$ = 0.996, BS-SD = 0.018).

• Applied Biological Chemistry
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• v.51 no.1
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• pp.38-43
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• 2008

3D-QSARs on the fungicidal activity with N-phenylbenzenesulfonamide and N-phenyl-2-thienylsul-fonamide analogues (1-34) against Fusarium wilt (Fusarium oxysporum) were discussed quantitatively using CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis) methods, respectively. Generally, the CoMFA models have better predictability and fitness than the CoMSIA models. The fungicidal activities, according to the information of the optimized CoMF A 2 model $(r^2\;_{cv.}=0.523\;&\;r^2\;_{ncv.}=0.956)$, were dependent on the electrostatic field of the N-phenylbenzenesulfonamide analogues. Therefore, from the results of graphical analyses on the contour maps with the optimized CoMFA 2 model, it is expected that the characters of $R_4-substituents$ on the N-phenyl ring as steric and positive charge favor will contribute to the fungicidal activity against Fusarium wilt.

• The Korean Journal of Pesticide Science
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• v.6 no.2
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• pp.72-79
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• 2002

3D-QSAR between fungicidal activitives ($pI_{50}$) against metalaxyl-sensitive (SPC: 95CC7105) or metalaxyl-resisitant (RPC: 95CC7303) isolate of phytophthora blight fungus (Phytophthora capsici), and a set of 3-phenylisoxazole (A) and 3-phenyl-2,5-dihydroisoxazole (B) derivatives as substrates were conducted using comparative molecular field analyses (CoMFA). The antifungal activities of (A) were generally higher than those of (B). And it is assumed that the most stable conformation of the active substrate was approximately planar from conformational search. The CoMFA models proved a good predictive ability and suggested that the electronic field of substrates were higher than hydropohobic field and steric field requirements for recognition forces of the receptor site. And the factors were strongly correlated (cross-validated $q^2>0.570$ & conventional $r^2>0.968$) with the fungicidal activitives. According to the CoMFA analyses, the selectivity factors for RPC suggested that the sterically bulky groups (C14 & C15) and electron withdrawing groups (C15 & C16) have to be introduced to the ortho, meta and para-position on the benzoyl moiety of substrates.

• Applied Biological Chemistry
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• v.49 no.3
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• pp.238-242
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• 2006

The herbicidal activities against the pre-emergence of rice plant (Oryza sativa L.) and barnyard grass (Echinochloa crus-gall) with changing substituents $(R_1-R_4)$ of new 5-benzofuryl-2-[1-(alkoxyimino) alkyl]-3-hydroxycyclohex-2-en-1-one derivatives as substrate molecules were studied quantitatively using comparative molecular field analyses (CoMFA). The optimized CoMFA models (rice plant: A5 & barnyard grass: B3) were derived from atom based fit alignment and a combination of CoMFA fields. The two models for herbicidal activity against two plants showed the best predictability and fitness ($q^2$>0.6 & ${r^2}_{ncv.}$>0.94) for the herbicidal activities. Also, CoMFA-HINT contour maps showed that the selective herbicidal activity between rice plant and barnyard grass depends on the hydrophobicity of $R_2\;and\;R_3$ groups in molecule. Therefore, it is expected that the herbicidal activity against barnyard grass will be improved by the introduction of the steric bulk small and hydrophobic group.

• The Korean Journal of Pesticide Science
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• v.2 no.2
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• pp.16-21
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• 1998

Bis-aromatic ${\alpha},{\beta}$-unsaturated ketone derivatives represented as substrate(S) were synthesized and their fungicidal activities in vivo against rice blast(Pyricularia oryzae) and tomato leaf blight(Phytophthora infestans) were examined with the quantitative structure activity relationships(QSAR) using 3D QSAR, comparative molecular field analysis (CoMFA). The 3D CoMFA results and those of 2D QSAR were compared and the results reveal that both results show similar trend. The two important factors, steric and electronic, contribute toward the activity. We assumed that fungicidal activity for rice blast was greatly improved by increasing with positive charge of ${\beta}$-carbon and introduction of bulky derivatives into $R_{2}$ group, while that for tomato leaf blight was improved by decreasing the positive charge of ${\beta}$-carbon and introduction of smaller molecular derivative into $R_{2}$ group. The CoMFA analyses clearly demonstrate its potential in unraveling the steric and electronic features of the molecules through contour maps.

• The Korean Journal of Pesticide Science
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• v.7 no.2
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• pp.108-116
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• 2003

A series of new quinclorac family, herbicidal 3-phenyl-5-(3,7-dichloro-8-quinolinyl)-1,2,4-oxadiazole derivatives as substrate were synthesized and their growth inhibition activity $(pI_{50})$ against root and shoot of rice plant (Oryza sativa L.) and barnyard grass (Echinochloa crus-galli) were determined. And then comparative molecular field analysis (CoMFA) and molecular holographic quantitative structure- activity relationship (HQSAR) were compared in terms of their potential for predictiability. The statistical results were suggested that HQSAR based model had better predictability than CoMFA model. The selective factors to remove barnyard grass take electron withdrawing groups which can be created positive charge and steric bulky on the phenyl ring. Results revealed that the unknown 2,6-dichloro-substituent, U5 and 2,4,6-trichloro-substituent, U6(${\Delta}pI_{50}$=CoMFA: 1.18 & HQSAR: 1.82) were predicted as compound with higher activity and selectivity.

• The Korean Journal of Pesticide Science
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• v.14 no.4
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• pp.319-325
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• 2010

To understand the influences of the substituents ($R_1{\sim}R_4$) on insecticidal activity of N'-phenyl-N-methylformamidine analogues (1~22) against two spotted spider mite (Tetranychus urticae), comparative molecular field analysis (CoMFA) model and comparative molecular similarity indices analysis (CoMSIA) model as three dimensional quantitative structure-activity relationships (3D-QSARs) model were derived and discussed quantitatively. From the results, the correlativity and predictability ($r^2{_{cv.}}=0.575$ and $r^2{_{ncv.}}=0.945$) of the CoMFA 1 model were higher than those of the rest models. The the CoMFA 1 and CoMSIA 1 model with the sensitivity of the perturbation and the prediction produced ($d_q{^{2'}}/dr^2{_{yy}}=1.071{\sim}1.146$ & $q^2=0.545{\sim}0.626$) by a progressive scrambling analysis were not dependent on chance correlation. The insecticidal activities from the optimized CoMFA 1 model were depend upon the steric field (62.5%), electrostatic field (28.9%), and hydrophobic field (8.6%) of N'-phenyl-N-methylformamidine analogues. Therefore, the inhibitory activities with optimized CoMFA 1 model were dependent upon steric factor. From the contour maps of the optimized models, it is predicted that the structural distinctions that contribute to the insecticidal activity will be able to applied new potent insecticides design.

• Journal of Integrative Natural Science
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• v.9 no.2
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• pp.113-120
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• 2016

Monopolar spindle 1 (Mps1) is an attractive cancer target due to its high expression levels in a wide range of cancer cells. Mps1 is a dual specificity kinase. It plays an essential role in mitosis. The high expression od Mps1 was observed in various grades of breast cancers. In the current study, we have developed a CoMFA model of pyridazine derivatives as Mps1 kinase inhibitors. The developed CoMFA model ($q^2=0.797$; ONC=6; $r^2=0.992$) exhibited a good predictive ability. The model was then validated by Leave out five, progressive sampling and bootstrapping and found to be robust. The analysis of the CoMFA contour maps depicted favorable and unfavorable regions to enhance the activity. Bulky positive substitution at $R^3$ position and Negative substitution in $R^1$ position is favored could increase the activity. In contrast, bulky substitution in $R^1$ position is not favored. Our results can be used in designing a potent Mps1 (TTK) inhibitor.

• 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.

• Molecular & Cellular Toxicology
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• v.1 no.3
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• pp.157-163
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• 2005

Because of their widespread occurrence and substantial biological activity, halogenated aromatic hydrocarbons are one of the important classes of contaminants in the environment. We have performed comparative molecular field analysis (CoMFA) on structurally diverse ligands of Ah (dioxin) receptor to explore the physico-chemical requirements for binding. All CoMFA models have given $q^{2}$ value of more than 0.5 and $r^{2}$ value of more than 0.83. The predictive ability of the models was validated by an external test set, which gave satisfactory predictive $r^{2}$ values. Best predictions were obtained with CoMFA model of combined modified training set ($q^{2}=0.631,\;r^{2}=0.900$), giving predictive residual value = 0.002 log unit for the test compound. We have suggested a model comprises of four structurally different compounds, which offers a good predictability for various ligands. Our QSAR model is consistent with all previously established QSAR models with less structurally diverse ligands. The implications of the CoMFA/QSAR model presented herein are explored with respect to quantitative hazard identification of potential toxicants.