• 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.

• Molecular & Cellular Toxicology
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• v.2 no.3
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• pp.216-221
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• 2006

The cholinesterase-inhibiting organophosphorous (OP) compounds known as nerve agents are highly toxic. The principal toxic mechanism of OP compounds is the inhibition of acethylcholine esterase (AChE) by phosphorylation of its catalytic site. The reversible competitive inhibition of AChE may prevent the subsequent OP intoxication. In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR) was performed to investigate the relationship between the 29 compounds with structural diversity and their bioactivities against AChE. In particular, predictive models were constructed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The results indicate reasonable model for CoMFA ($q^{2}=0.453,\;r^{2}=0.697$) and CoMSIA ($q^{2}=0.518,\;r^{2}=0.696$). The presence of steric and hydophobic group at naphtyl moiety of the model may lead to the design of improved competitive inhibitors for organophosphorous intoxication.

• Archives of Pharmacal Research
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• v.27 no.5
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• pp.467-470
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• 2004

Comparative molecular field analysis and comparative molecular similarity indices analysis were performed on twenty five analogues of pimarane COX-2 inhibitor to optimize their cyclooxygenase-2 (COX-2) selective anti-inflammatory activities.

• Bulletin of the Korean Chemical Society
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• v.27 no.12
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• pp.1969-1975
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• 2006

3D-QSAR model that correlates the biological activities with the chemical structures of quipazine derivatives acting on the serotonine transporter (SERT) was developed by comparative molecular field analysis (CoMFA). Total 8 models were constructed and a more accurate model, using close 1 $\AA$ grid spacing and StDev*Coefficients weight value gave better results. The contour maps with the best model, the resulting cross-validated correlation ($q^2$ : 0.744), and non-cross-validated correlation ($r^2$ : 0.966) indicate the steric and electrostatic environment of inhibitors in the SERT binding pocket. This study can be used as a putative picture of the pharmacophore in the design of novel and potent inhibitors.

• Bulletin of the Korean Chemical Society
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• v.26 no.1
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• pp.85-90
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• 2005

MX and its analogs are synthesized and modeled by quantitative structure activity relationship (QSAR) study including comparative molecular field analysis (CoMFA). As a result, factors affecting this class of compounds have been found to be steric and electrostatic effects. Because hologram quantitative structure activity relationship (HQSAR) technique is based on the 2-dimensional descriptors, this is free of ambiguity of conformational selection and molecular alignment. In this study we tried to include all the data available from the literature, and modeled with the HQSAR technique. Among the parameters affecting fragmentation, connectivity was the most important one for the whole compounds, giving good statistics. Considering additional parameters such as bond specification only slightly improved the model. Therefore connectivity has been found to be the most appropriate to explain the mutagenicity for this class of compounds.

• Bulletin of the Korean Chemical Society
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• v.30 no.11
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• pp.2717-2722
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• 2009

The use of the classification and regression tree (CART) methodology was studied in a quantitative structure-activity relationship (QSAR) context on a data set consisting of the binding affinities of 39 imidazobenzodiazepines for the α1 benzodiazepine receptor. The 3-D structures of these compounds were optimized using HyperChem software with semiempirical AM1 optimization method. After optimization a set of 1481 zero-to three-dimentional descriptors was calculated for each molecule in the data set. The response (dependent variable) in the tree model consisted of the binding affinities of drugs. Three descriptors (two topological and one 3D-Morse descriptors) were applied in the final tree structure to describe the binding affinities. The mean relative error percent for the data set is 3.20%, compared with a previous model with mean relative error percent of 6.63%. To evaluate the predictive power of CART cross validation method was also performed.

• Proceedings of the PSK Conference
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• 2003.10b
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• pp.186.3-186.3
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• 2003

The three-dimensional quantitative structure-activity relationship (3D-QSAR) study using the comparative molecular field analysis (CoMFA) was performed on indolinones derivatives as an inhibitor of the protein tyrosine kinase of fibroblast growth factor receptor (FGFR). In the training set, twenty-four indolinone derivatives were aligned based on the indole fragment and the steric and electrostatic fields were included in the analysis. The best predicted model showed the cross-validated coefficient (r$^2$$\sub$cv/) of 0.804 and bib-cross validated coefficient (r$^2$) of 0.942. The CoMFA study can be used to predict several new inhibitors of the FGFR.

• The Korean Journal of Pesticide Science
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• v.15 no.1
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• pp.68-85
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• 2011

• Proceedings of the PSK Conference
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• 2000.04a
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• pp.158.1-158.1
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• 2000

• Journal of the Korean Chemical Society
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• v.56 no.2
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• pp.236-245
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• 2012

The main mycobacterial infection in human is tuberculosis caused by Mycobacterium tuberculosis. Tuberculosis is the leading infectious cause of death in the world. Therefore there is continuing and compelling need for new and improved treatment for tuberculosis. The entire logic towards design of new compounds containing 4-hydroxy-N'-(1,3-thiazoldin- 2-yldene)benzohydrazide moiety is basically for superior antimycobacterial activity. The recent advances in QSAR and computer science have provided a systematic approach to design a structure of any compound and further, the biological activity of the compound can be predicted before synthesis. The 3D-QSAR studies for the set of 4-hydroxy-N'-(1,3-thiazoldin- 2-yldene)benzohydrazide and their derivatives were carried out by using V-life MDS (3.50). The various statistical methods such as Multiple Linear Regression (MLR), Partial Least Square Regression (PLSR), Principle Component Regression(PCR) and K nearest neighbour (kNN) were used. The kNN showed good results having cross validated $r^2$ 0.9319, $r^2$ for external test set 0.8561 and standard error of estimate 0.2195. The docking studies were carried out by using Schrodinger GLIDE module which resulted in good docking score in comparison with the standard isoniazid. The designed compounds were further subjected for synthesis and biological evaluation. Antitubercular evaluation of these compounds showed that (4.a), (4.d) and (4.g) found as potent inhibitor of H37RV.