• 통합자연과학논문집
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• 제8권1호
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• pp.40-47
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• 2015

Glycogen synthase kinase 3 (GSK-3) is a serine/threonine protein kinase that has recently emerged as a promising target in drug discovery. It is involved in multiple cellular processes and associated with the pathogenesis of several diseases. A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was performed on a series of GSK-3 inhibitors to understand the structural basis for inhibitory activity. Comparative molecular field analysis (CoMFA) method was used to derive 3D-QSAR models. A reliable CoMFA model was developed using ligand-based alignment scheme. The model produced statistically acceptable results with a cross-validated correlation coefficient ($q^2$) of 0.594 and a non-cross-validated correlation coefficient ($r^2$) of 0.943. Robustness of the model was checked by bootstrapping and progressive scrambling analysis. This study could assist in the design of novel compounds with enhanced GSK-3 inhibitory activity.

• Environmental Analysis Health and Toxicology
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• 제14권1_2호
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• pp.45-54
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• 1999

Quantitative strucrure-activity relationships between the toxicity (LD$\_$50/) and molecular properties of amine and nitro compounds were tested. The all 19 compounds showed low correlations below 0.500 to their LD$\_$50/ values. When amine or nitro compounds were taken separately, the correlation between the calculated chemphysico parameters and LD$\_$50/ were also poor (r$^2$=0.4911, 3967 repectively). The overall relationships among the QSAR parameters were investigated. Molecular weight shows a high correlation with total surface area (r$^2$=0.9287); 0.9090 for zero-order connectivity and second-order connectivity : 0.8784 for bioconcentration factor and second-order connectivity. When amine compounds were taken to perform the statistical treatment, the relationships between parameters were as follows: 0.8436 for volume-negentropy; 0.8925 for volume-bioconcentration factor; 0.9929 for zero-order connectivity-Kow; zero-order connectivity-bioconcentration factor; 0.9141 for zero-order connectivity-solubility; 0.9718 for solubility-bioconcentration factor; 0.9894 for solubility-bioconcentration factor and 0.9319 for Kow-bioconcentration factor. On the other hand, nitro compounds showed different relationships as follows: 0.8952 for volume-I/O character; 0.9520 for volume-total surface area: 0.9351 for volume-molecular weight; 0.9351 for volume-MW; 0.9961 for Kow-Koc; 0.8455 for Kow-bioconcentration factor; 0.8879 for Koc-bioconcentration factor; 0.9987 for MW-total surface area respectively.

• Molecular & Cellular Toxicology
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• 제1권3호
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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.

• 한국환경성돌연변이발암원학회지
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• 제21권2호
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• pp.113-117
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• 2001

The screening of various molecular descriptors for predicting carcinogenic, mutagenic and teratogenic activities of chlorinated aliphatic compounds as drinking water disinfection byproducts (DBPs) has been investigated for the application of quantitative structure-activity relationships (QSAR). The present work embodies the study of relationship between molecular descriptors and toxicity parameters of the genotoxicity endpoints for the screening of relevant molecular descriptors. The toxicity Indices for 29 compounds constituting the testing set were computed by the PASS program and active values were chosen. We investigate feasibility of screening descriptors and of their applications among different genotoxic endpoints. The correlation to teratogenicity of all 29 compounds was significantly improved when the same analysis was done with 20 alkanes only without alkene compounds. The HOMO (highest occupied molecular orbital) energy and number of Cl parameters were dominantly contributed.

• The Korean Journal of Physiology and Pharmacology
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• 제13권6호
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• pp.511-516
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• 2009

A series of substituted 2-arylnaphthyridin-4-one analogues, which were previously synthesized in our laboratory, were evaluated for their in vitro cytotoxic activity against human lung cancer A549 and human renal cancer Caki-2 cells using MTT assay. Some compounds (11, 12, and 13) showed stronger cytotoxicity than colchicine against both tumor cell lines, and compound 13 exhibited the most potent activity with $IC_{50}$ values of 2.3 and $13.4\;{\mu}M$, respectively. Three-dimensional quantitative structure activity relationship (3D-QSAR) studies of comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed. Predictive 3D-QSAR models were obtained with $q^2$ values of 0.869 and 0.872 and $r^2_{ncv}$ values of 0.983 and 0.993 for CoMFA and CoMSIA, respectively. These results demonstrate that CoMFA and CoMSIA models could be reliably used in the design of novel cytotoxic agents.

• 약학회지
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• 제54권4호
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• pp.288-294
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• 2010

Three dimensional quantitative-structure relationships (3D-QSARs) models between structures of phenoxy, phenylthio or benzyloxy substituted quinolone analogues and their antitrypanosomal activity against Chagas disease (Trypanosoma cruzi) were derived and discussed quantitatively using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. The optimized CoMFA 1 model ($q^2$=0.528 and $r^2$=0.964) showed the best statistical results. According to the optimized CoMFA 1 model, the antitrypanosomal activities were dependent on the steric (60.0%) and electrostatic (36.2%) factors of quinolone derivatives. From the contour maps, it is predicted that the activity will be increased when sterically favored groups were located in $R_4$ and $R_5$ position and sterically disfavored groups were located in $R_2$ position. Also, the positively charged groups on $R_2$ would be able to increase the antitrypanosomal activities.

• Bulletin of the Korean Chemical Society
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• 제35권11호
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• pp.3181-3187
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• 2014

A series of 3,4-dihydroquinazoline derivatives with anti-cancer activities against human colon cancer HT-29 cell were subjected to three-dimensional quantitative structure-activity relationship (3D-QSAR) studies using the comparative molecular similarity indices analysis (CoMSIA) approaches. The most potent compound, BK10001 was used to align the molecules. As a result, the best prediction was obtained with CoMSIA combined electrostatic, hydrophobic, and hydrogen-bond acceptor fields ($q^2=0.648$, $r^2=0.882$). This model was validated by an external test set of six compounds giving satisfactory predictive $r^2$ values of 0.879. This model would guide the design of potent 3,4-dihydroquinazoline derivatives as anti-cancer agent for the treatment of human colon cancer.

• Molecular & Cellular Toxicology
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• 제5권1호
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• pp.14-22
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• 2009

In vitro cytotoxicity of 23 alkyl phenols (APs) on human cervical cancer cell lines (HeLa) was determined using the lactate dehydrogenase (LDH) cytotoxicity assay. Two different sets of descriptors were used to construct the calibration model based on Genetic Algorithm-Multiple Linear Regression (GA-MLR) based on the experimental data. A statistically robust Structure-Activity Relationships (QSAR) model was achieved ($R^2$=95.05%, $Q^2_{LOO}$=91.23%, F=72.02 and SE= 0.046) using three Dragon descriptors based on Me (0D-Constitutional descriptor), BELp8 (2D-Burden eigenvalue descriptor) and HATS8p (3D-GETAWAY descriptor). However, external validation could not fully prove its validity of the selected QSAR in characterization of the cytotoxicity of APs towards HeLa cells. Nevertheless, the cytotoxicity profiles showed a finding that 4-n-octylphenol (4-NOP), 4-tert-octyl-phenol (4-TOP), 4-n-nonylphenol (4-NNP) had a more potent cytotoxic effect than other APs tested, inferring that increased length and molecular bulkiness of the substituent had important influence on the LDH cytotoxicity.

• Bulletin of the Korean Chemical Society
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• 제32권12호
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• pp.4352-4360
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• 2011

A four dimensional quantitative structure activity relationship analysis was applied to a series of 50 flavonoid inhibitors of $p56^{lck}$ protein tyrosine kinase by the molecular comparative electron topological method. It was found that the -log (IC50) values of the compounds were highly dependent on the topology, size and electrostatic character of the substituents at seven positions of the flavonoid scaffold in this study. Depending on the negative or positive charge of the groups correctly embedded in these substituents, three-dimensional bio-structure to increase or decrease -log (IC50) values in the training set of 39 compounds was predicted. The test set of 11 compounds was used to evaluate the predictivity of the model. To generate 4D-QSAR model, the defined function groups and pharmacophore used as topological descriptors in the calculation of activity were of sufficient statistical quality ($R^2$ = 0.72 and $Q^2$ = 0.69). Ligand docking approach by using Dock 6.0. These compounds include many flavonoid analogs, They were docked onto human families of p56lck PTKs retrieved from the Protein Data Bank, 1lkl.pdb.

• Bulletin of the Korean Chemical Society
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• 제32권7호
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• pp.2397-2404
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• 2011

Variable selection k nearest neighbor QSAR modeling approach was applied to a data set of 80 3-arylisoquinolines exhibiting cytotoxicity against human lung tumor cell line (A-549). All compounds were characterized with molecular topology descriptors calculated with the MolconnZ program. Seven compounds were randomly selected from the original dataset and used as an external validation set. The remaining subset of 73 compounds was divided into multiple training (56 to 61 compounds) and test (17 to 12 compounds) sets using a chemical diversity sampling method developed in this group. Highly predictive models characterized by the leave-one out cross-validated $R^2$ ($q^2$) values greater than 0.8 for the training sets and $R^2$ values greater than 0.7 for the test sets have been obtained. The robustness of models was confirmed by the Y-randomization test: all models built using training sets with randomly shuffled activities were characterized by low $q^2{\leq}0.26$ and $R^2{\leq}0.22$ for training and test sets, respectively. Twelve best models (with the highest values of both $q^2$ and $R^2$) predicted the activities of the external validation set of seven compounds with $R^2$ ranging from 0.71 to 0.93.