• Bulletin of the Korean Chemical Society
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• v.23 no.3
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• pp.417-422
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• 2002

Comparison studies of the Quantitative Structure Activity Relationship (QSAR) methods with new imidazo-quinolinedione derivatives were conducted using Comparative Molecular Field Analysis (CoMFA), Comparative Molecular Similarity Indices Analysis (CoMSIA), and the Hologram Quantitative Structure Activity Relationship (HQSAR). When the CoMFA crossvalidation value, q2, was 0.625, the Pearson correlation coefficient, r2, was 0.973. In CoMSIA, q2 was 0.52 and r2 was 0.979. In the HQSAR, q2 was 0.501 and r2 was 0.924. The best result was obtained using the CoMSIA method according to a comparison of the calculated values with the real in vitro cytotoxic activities against human ovarian cancer cell lines.

• 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.15 no.10
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• pp.889-890
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• 1994

A comparative molecular field analysis (CoMFA) on the substituent effect of the palladium(Ⅱ) catalyzed [3,3]-sigmatropic rearrangement of allylic esters was studied to show a good correlation between the electrostatic property of substituents and the reaction rate. The CoMFA result suggests that the reaction rate will increase as the electron-donating ability of substituents increases.

• Bulletin of the Korean Chemical Society
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• v.16 no.12
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• pp.1189-1193
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• 1995

The comparative molecular field analysis (CoMFA) method has been employed to correlate the apparent lipophilicity (logkw) and global lipophilicity (logP) for orthopramide derivatives. This study demonstrated that CoMFA is an excellent method in predicting the complex properties of molecules such as apparent lipophilicity (logkw) or lipophilicity (logP). The better predictability of lipophilicity by introducing logkw as an independent descriptor suggests that the HPLC capacity factor measured in a buffer of pH 7.5 (logkw) can be effectively utilized in the prediction of global lipophilicity.

• Proceedings of the PSK Conference
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• 2003.04a
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• pp.250.1-250.1
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• 2003

In this work, we have conducted 3D-QSAR studies on a series of acanthonic acid derivatives that act as COX-2 inhibitors, using two different methods: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). CoMFA and CoMSIA analysis of twenty five pimarane analogues produced good models with high predictive abilities. (omitted)

• Bulletin of the Korean Chemical Society
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• v.17 no.7
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• pp.653-655
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• 1996

A comparative molecular field analysis (CoMFA) was carried out for the correlation of the transition state structures and the reaction rates for the SN2 reaction of 4-nitrophenyl benzoate and its sulfur analogs with anionic nucleophiles. The CoMFA analysis showed that both steric and electrostatic effects are important, and the steric contribution increased when nucleophiles are alkoxides or arylsulfides. In this study, we have demonstrated that the CoMFA analysis can be expanded beyond the scope of dealing with reactants and products. The reactant complex and transition state conformations generated along the reaction path can be more appropriately used for the correlation of structures and reaction rates.

• Bulletin of the Korean Chemical Society
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• v.27 no.2
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• pp.273-276
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• 2006

Three dimensional quantitative structure-activity relationship studies for a series of isatin derivatives as a nonpeptidyl caspase-3 enzyme inhibitor were investigated using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The first approach of non-peptidyl small molecules by 3D QSAR may be useful in guiding further development of potent caspase-3 inhibitors.

• Proceedings of the PSK Conference
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• 2003.10b
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• pp.181.3-181.3
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• 2003

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 60 PPAR-g agonists. Partial Least Squars (PLS) analysis produced good predicted models with $q^2$ value of 0.62 (SDEP=0.33, F value=93.22, $r^2$=0.92) and 0.56 (SDEP=0.47 F value=27.65, $r^2$=0.86), respectivly. The key spatial properties were detected by careful analysis of the isocontour maps.

• 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.