• 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.

• Bulletin of the Korean Chemical Society
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• v.34 no.3
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• pp.899-906
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• 2013

Using generated conformations from docking analysis by Gold algorithm, some 3D-QSAR models; CoMFA and CoMSIA have been created on 39 N-benzoylated phenoxazines and phenothiazines, including their S-oxidized analogues. These molecules inhibit the polymerization of tubulin into microtubules and thus they have been studied for the development of antitumor drugs. Training set for the CoMFA and CoMSIA models using 30 docked conformations gives $q^2$ Leave one out (LOO) values of 0.756 and 0.617, and $r^2$ ncv values of 0.988 and 0.956, respectively. The ability of prediction and robustness of the models were evaluated by test set, cross validation (leave-one-out and leave-ten-out), bootstrapping, and progressive scrambling approaches. The all-orientation search (AOS) was used to achieve the best orientation to minimize the effect of initial orientation of the structures. The docking results confirmed CoMFA and CoMSIA contour maps. The docking and 3D-QSAR studies were thoroughly interpreted and discussed and confirmed the experimental $pIC_{50}$ values.

• The Korean Journal of Pesticide Science
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• v.11 no.1
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• pp.8-17
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• 2007

Three-dimensional quantitative structure-activity relationships (3D-QSARs) on the fungicidal activity against damping-off (Pythium ultimum) with N-phenylbenzenesulfonamide and N-phenyl-2-thienylsulfonamide analogues (1-34) were studied quantitatively using CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indeces analysis) methodologies. On the whole, the statistical qualities of CoMSIA models with field fit alignment (FF1-FF5) were slightly higher than that of atom based fit alignment (AF1-AF5) but, the deviations of statistical quality between two alignments in case of CoMFA models were slightly lower. The statistical results of CoMFA and CoMSIA model showed that the optimized CoMSIA model (FF1: $r_{cv.}^2\;(q^2)=0.674$ & $r_{ncv.}^2=0.964$) for damping-off is better predictability and fitness for fungicidal activities than CoMFA model (AF5: $r_{cv.}^2\;(q^2)=0.616$ & $r_{ncv.}^2=0.930$). The fungicidal activities according to the information of the CoMSIA (FF1) model were dependence upon the electrostatic and hydrophobic field of the N-phenylbenzene sulfonamide analogues. Therefore, from the results of graphical analyses on the contour maps with CoMSIA (FF3) model, it is expected that the characters of R4-substituent on the N-phenyl ring as hydrophobic and hydrogen bond acceptor will be contributed to the fungicidal activity against damping-off.

• Journal of Integrative Natural Science
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• v.8 no.4
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• pp.258-266
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• 2015

Xanthine Oxidase is an enzyme, which oxidizes hypoxanthine to xanthine, and xanthine to uric acid. It is widely distributed throughout various organs including the liver, gut, lung, kidney, heart, brain and plasma. It is involved in gout pathogenesis. In this study, we have performed Comparative Molecular Field Analysis (CoMFA) on a series of 2-(indol-5-yl) thiazole derivatives as xanthine oxidase (XO) inhibitors to identify the structural variations with their inhibitory activities. Ligand based CoMFA models were generated based on atom-by-atom matching alignment. In atom-by-atom matching, the bioactive conformation of highly active molecule 11 was generated using systematic search. Compounds were aligned using the bioactive conformation and it is used for model generation. Different CoMFA models were generated using different alignments and the best model yielded a cross-validated $q^2$ of 0.698 with five components and non-cross-validated correlation coefficient ($r^2$) of 0.992 with Fisher value as 236.431, and an estimated standard error of 0.068. The predictive ability of the best CoMFA models was found to be $r^2_{pred}$0.653. The CoMFA study revealed that the $R_3$ position of the structure is important in influencing the biological activity of the inhibitors. Electro positive groups and bulkier substituents in this position enhance the biological activity.

• The Korean Journal of Pesticide Science
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• v.12 no.2
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• pp.111-117
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• 2008

The comparative molecular field analysis (CoMFA) for the fungicidal activity with N-phenylbenzenesulfonamide analogues (1-45) against gray mold (Botriyts cinerea) were studied quantitatively. The statistical values of CoMFA models had much better predictability and fitness than those of comparative molecular similarity indices analysis (CoMSIA) models. The statistical values of the optimized CoMFA I model were predictablity, $r^2_{cv.}(or\;q^2)=0.457$ and correlation coefficient, $r^2_{ncv.}=0.959$, and their fungicidal activity was dependent on the steric field (52%) and electrostatic field (35.6%) of the substrate molecules. And also, it was found that the optimized CoMFA I model with the sensitivity to perturbation ($d_q^{2'}/dr^2_{yy'}=0.898$) and prediction ($q^2=0.346$ & SDEP=0.614) produced by a progressive scrambling analysis was not dependent on chance correlation. From the results of graphical analyses on the contour maps with the optimized CoMFA I model, it is expected that the $R_3$ and $R_4$-substituents on the N-phenyl ring as steric favor group and para-substituents ($R_1$) on the S-phenyl ring as steric disfavor group will contribute to the fungicidal activity. Therefore, the optimized CoMFA I model should be applicable to the prediction of the fungicidal activities against gray mold.

• Bulletin of the Korean Chemical Society
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• v.34 no.6
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• pp.1823-1828
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• 2013

Tetraoxanes (1,2,4,5-tetraoxanes) have been reported to exhibit potent antimalarial activity. In the present study, the three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on a series of tetraoxanes derivatives using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. The best predictive CoMFA model with atom fit alignment resulted in cross-validated coefficient ($q^2$) value of 0.719, non-cross-validated coefficient ($r^2$) value of 0.855 with standard error of estimate (SEE) 0.335. Similarly, the best predictive CoMSIA model was derived with $q^2$ of 0.739, $r^2$ of 0.847 and SEE of 0.344. The generated models were externally validated using test sets. The final QSAR models as well as the information gathered from 3D contour maps should be useful for the design of novel tetraoxanes having improved antimalarial activity.

• The Korean Journal of Pesticide Science
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• v.7 no.1
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• pp.1-11
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• 2003

Acoording to improvement of HTOS (high throughput organic synthesis) and HTS (high throughput screening) technique, the CoMFA (comparative molecular field analysis), CoMSIA (comparative molecular similarity indeces analysis) and molecular HQSAR (hologram quantitative structure-activity relationship) analysis techniques as methodology of computer assisted molecular design (CAMD) were introduced generally and summarized for some application cases.

• Bulletin of the Korean Chemical Society
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• v.32 no.7
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• pp.2433-2442
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• 2011

The three dimensional quantitative structure activity relationship (3D QSAR) models were developed using Comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and docking studies. The fit of Quinazolinone antifolates inside the active site of modeled bovine dihydrofolate reductase (DHFR) was assessed. Both ligand based (LB) and receptor based (RB) QSAR models were generated, these models showed good internal and external statistical reliability that is evident from the $q^2_{loo}$, $r^2_{ncv}$ and $r^2_{pred}$. The identified key features enabled us to design new Quinazolinone analogues as DHFR inhibitors. This study is a building bridge between docking studies of homology modeled bovine DHFR protein as well as ligand and target based 3D QSAR techniques of CoMFA and CoMSIA approaches.

• Bulletin of the Korean Chemical Society
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• v.26 no.6
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• pp.952-958
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• 2005

Angiotensin-converting enzyme (ACE) is known to be primarily responsible for hypertension. Threedimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a series of 28 ACE inhibitors. The availability of ACE crystal structure (1UZF) provided the plausible biological orientation of inhibitors to ACE active site (C-domain). Alignment for CoMFA obtained by docking ligands to 1UZF protein using FlexX program showed better statistical model as compared to superposition of corresponding atoms. The statistical parameters indicate reasonable models for both CoMFA ($q^2$ = 0.530, $r^2$ = 0.998) and CoMSIA ($q^2$ = 0.518, $r^2$ = 0.990). The 3D-QSAR analyses provide valuable information for the design of ACE inhibitors with potent activity towards C-domain of ACE. The group substitutions involving the phenyl ring and carbon chain at the propionyl and sulfonyl moieties of captopril are essential for better activity against ACE.

• Journal of Integrative Natural Science
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• v.4 no.3
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• pp.197-201
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• 2011

3D-QSAR techniques including CoMFA have been used a lot for more than two decades now. For now, the perspective of 3D-QSAR has been changed. The realization of gorge activity cliffs and higher chance correlation with many independent variables (IVs) has changed the requirements. Some suggested the benchmarking datasets for 3D-QSAR. However, were they still useful for right reasons? Here, we propose the requirement of any general purpose 3D-QSAR benchmarking datasets for lead optimization, especially for feasibility test of any IVs. Specifically, we summarize the conceptual requirements for an ideal settings for 3D-QSAR especially CoMFA.