• 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.

• The Korean Journal of Physiology and Pharmacology
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• v.15 no.6
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• pp.423-429
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• 2011

B13 analogues are being considered as therapeutic agents for cancer cells, since B13 is a ceramide analogue and inhibits ceramidase to promote apoptosis in cancer cells. B13 sulfonamides are assumed to have biological activity similar to B13, since they are made by bioisosterically substituting the carboxyl moiety of B13 with sulfone group. Twenty B13 sulfonamides were evaluated for their in vitro cytotoxicities against human colon cancer HT-29 and lung cancer A549 cell lines using MTT assays. Replacement of the amide group with a sulfonamide group increased cytotoxicity in both cancer cell lines. The sulfonamides with long alkyl chains exhibited activities two to three times more potent than that of B13 and compound (15) had the most potent activity with $IC_{50}$ values of 27 and $28.7{\mu}M$ for HT-29 and A549, respectively. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used to carry out QSAR molecular modeling of these compounds. The predictive CoMSIA models for HT-29 and A549 gave cross-validated q2 values of 0.703 and 0.830, respectively. From graphical analysis of these models, we suppose that the stereochemistry of 1,3-propandiol is not important for activity and that introduction of a sulfonamide group and long alkyl chains into B13 can increase cytotoxicity.

• Bulletin of the Korean Chemical Society
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• v.32 no.2
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• pp.645-650
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• 2011

The 3D-QSAR study of 2-arylbenzoxazoles as novel cholesteryl ester transfer protein inhibitors was performed by comparative molecular field analysis (CoMFA), CoMFA region focusing (CoMFA-RF) for optimizing the region for the final PLS analysis, and comparative molecular similarity indices analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. The best orientation was searched by all-orientation search strategy using AOS, to minimize the effect of the initial orientation of the structures. The predictive ability of CoMFARF and CoMSIA were determined using a test set of twelve compounds giving predictive correlation coefficients of 0.886, and 0.754 respectively indicating good predictive power. Further, the robustness and sensitivity to chance correlation of the models were verified by bootstrapping and progressive scrambling analyses respectively. Based upon the information derived from CoMFA(RF) and CoMSIA, identified some key features that may be used to design new inhibitors for cholesteryl ester transfer protein.

• Bulletin of the Korean Chemical Society
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• v.35 no.7
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• pp.2065-2071
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• 2014

${\beta}$-Secretase (beta-amyloid converting enzyme 1 [BACE1]) is involved in the first and rate-limiting step of ${\beta}$-amyloid ($A{\beta}$) peptides production, which leads to the pathogenesis of Alzheimer's disease(AD). Therefore, inhibition of BACE1 activity has become an efficient approach for the treatment of AD. Ligand-based and docking-based 3D-quantitative structure-activity relationship (3D-QSAR) studies of acyl guanidine analogues were performed with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) to obtain insights for designing novel potent BACE1 inhibitors. We obtained highly reliable and predictive CoMSIA models with a cross-validated $q^2$ value of 0.725 and a predictive coefficient $r{^2}_{pred}$ value of 0.956. CoMSIA contour maps showed the structural requirements for potent activity. 3D-QSAR analysis suggested that an acyl guanidine and an amide group in the $R_6$ substituent would be important moieties for potent activity. Moreover, the introduction of small hydrophobic groups in the phenyl ring and hydrogen bond donor groups in 3,5-dichlorophenyl ring could increase biological activity.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.249-255
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• 2005

Angiotensin-converting enzyme (ACE) is primarily responsible for human hypertension. Current ACE drugs show serious cough and angiodema health problems due to the un-specific activity of the drug to ACE protein. The availability of ACE crystal structure (1UZF) provided the plausible biological orientation of inhibitors to ACE active site (C-domain). Three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecula. field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a series of 28 ACE inhibitors. 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 specific activity to ACE.

• Bulletin of the Korean Chemical Society
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• v.29 no.3
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• pp.656-662
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• 2008

Antagonists of the d -opioid receptor are effective in overcoming resistance against analgesic drugs such as morphine. To identify novel antagonists of the d -opioid receptor that display high potency and low resistance, we performed 3D-QSAR analysis using chemical feature-based pharmacophore models. Chemical features for d -opioid receptor antagonists were generated using quantitative (Catalyst/HypoGen) and qualitative (Catalyst/HipHop) approaches. For HypoGen analysis, we collected 16 peptide and 16 non-peptide antagonists as the training set. The best-fit pharmacophore hypotheses of the two antagonist models comprised identical features, including a hydrophobic aromatic (HAR), a hydrophobic (HY), and a positive ionizable (PI) function. The training set of the HipHop model was constructed with three launched opioid drugs. The best hypothesis from HipHop included four features: an HAR, an HY, a hydrogen bond donor (HBD), and a PI function. Based on these results, we confirm that HY, HAR and PI features are essential for effective antagonism of the d -opioid receptor, and determine the appropriate pharmacophore to design such antagonists.

• Bulletin of the Korean Chemical Society
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• v.30 no.11
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• pp.2523-2531
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• 2009

Effects of some diacid, diamine and dinitro aromatic compounds on the structure and activity of adenosine deaminase (ADA) were investigated by UV-Vis spectrophotometry in 50 mM phosphate buffer at pH = 7.5 and 27 ${^{\circ}C}$ and molecular docking studies. The results showed that all tested ligands are showing inhibition; five ligands are uncompetitive and other two ligands are mixed of competitive and noncompetetive inhibitors with majority of competitive behavior. For the later case analysis was done based on competitive inhibition. Diacids have larger size and higher inhibition constant ($K_I$) relative to others. A logical correlation between calculated free energy of binding and experimental values was obtained for un-competitive. Experimental and calculated data showed that competitive inhibitors are distributed near the active site of enzyme and form several cluster of ranks, whereas uncompetitive inhibitors bind to the enzyme-substrate complex and distributed far from the active site. Results of structure-activity relationship showed that, larger, more hydrophobe, less spherical and more aromatic ligands have higher inhibition constants.

• 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.