• YAKHAK HOEJI
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• v.55 no.2
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• pp.98-105
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• 2011

To search the minimum structural requirement of tricyclic isoxazole analogues (1~30) as new class potent antidepressant, thee-dimensional quanti- tative-structure relationship (3D-QSAR) models between substituents ($R_1{\sim}R_5$) of tricyclic isoxazoles and their antidepressant activity against medetomidine-induced loss of righting were performed and discussed quantitatively using comparative molecular field analysis (CoMFA) and comparative molecular similarity indies analysis (CoMSIA) methods. The correlativity and predictability ($r^2$=0.484 and $q^2$=0.947) of CoMSIA-2 model were higher than those of the rest models. The inhibitory activity against medetomidine-induced loss of righting was dependent on electrostatic field (43.4%), hydrophobic field (35.3%), and steric field (21.2%) of tricyclic isoxazoles. From the CoMSIA-2 contour maps, it is predicted that the antidepressant activity of potent antidepressants against medetomidine-induced loss of righting will be able to increase by the substituents ($R_1{\sim}R_5$) which were in accord with CoMSIA field.

• 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.

• 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.9 no.1
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• pp.1-9
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• 2016

Leucine rich repeat kinase 2 (LRRK2) is a highly promising target for Parkinson's disease (PD) that affects millions of people worldwide. A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was performed on a series of pyrrolopyrimidine-based selective LRRK2 kinase inhibitors. This study was performed to rationalize the structural requirements responsible for the inhibitory activity of these compounds. A reliable 3D-QSAR model was developed using comparative molecular field analysis (CoMFA) technique. The model produced statistically acceptable results with a cross-validated correlation coefficient ($q^2$) of 0.539 and a non-cross-validated correlation coefficient ($r^2$) of 0.871. Robustness of the model was further evaluated by bootstrapping and progressive scrambling analysis. This work could assist in designing more potent LRRK2 inhibitors.

• Journal of Integrative Natural Science
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• v.4 no.4
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• pp.266-272
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• 2011

Focal adhesion kinase (FAK) is a potential target for the treatment of primary cancers as well as prevention of tumor metastasis. To understand the structural and chemical features of FAK inhibitors, we report comparative molecular field analysis (CoMFA) for the series of 7H-pyrrolo(2,3-d)pyrimidines. The CoMFA models showed good correlation between the actual and predicted values for training set molecules. Our results indicated the ligand-based alignment has produced better statistical results for CoMFA ($q^2$ = 0.505, $r^2$ = 0.950). Both models were validated using test set compounds, and gave good predictive values of 0.537. The statistical parameters from the generated 3D-QSAR models were indicated that the data are well fitted and have high predictive ability. The contour map from 3D-QSAR models explains nicely the structure-activity relationships of FAK inhibitors and our results would give proper guidelines to further enhance the activity of novel inhibitors.

• Journal of Integrative Natural Science
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• v.8 no.3
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• pp.176-183
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• 2015

Corticotropin-releasing actor receptors (CRFRs) activates the hypothalamic pituitary adrenal axis, one of the 2 parts of the fight or flight response to stress. Increased CRH production has is associated with Alzheimer's disease and major depression and hypoglycemia. In this study, we report the important structural and chemical parameters for CRFR inhibitors using the derivatives of 8-substituted-2-aryl-5-alkylaminoquinolines. A 3D QSAR study, Comparative molecular field analysis (CoMFA) was performed. The best predictions were obtained for the best CoMFA model with a $q^2$ of 0.607 with 6 components and $r^2$ of 0.991. The statistical parameters from the generated CoMFA models indicated that the data are well fitted and have high predictive ability. The contour map resulted from the CoMFA models might be helpful in the future designing of novel and more potent CRFR derivatives.

• Analytical Science and Technology
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• v.24 no.6
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• pp.533-543
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• 2011

The hERG (human ether-a-go-go related gene) ion channel is a main factor for cardiac repolarization, and the blockade of this channel could induce arrhythmia and sudden death. Therefore, potential hERG ion channel inhibitors are now a primary concern in the drug discovery process, and lots of efforts are focused on the minimizing the cardiotoxic side effect. In this study, $IC_{50}$ data of 202 organic compounds in HEK (human embryonic kidney) cell from literatures were used to develop predictive 2D-QSAR model. Multiple linear regression (MLR), Support Vector Machine (SVM), and artificial neural network (ANN) were utilized to predict inhibition concentration of hERG ion channel as machine learning methods. Population based-forward selection method with cross-validation procedure was combined with each learning method and used to select best subset descriptors for each learning algorithm. The best model was ANN model based on 14 descriptors ($R^2_{CV}$=0.617, RMSECV=0.762, MAECV=0.583) and the MLR model could describe the structural characteristics of inhibitors and interaction with hERG receptors. The validation of QSAR models was evaluated through the 5-fold cross-validation and Y-scrambling test.

• The Korean Journal of Pesticide Science
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• v.2 no.2
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• pp.16-21
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• 1998

Bis-aromatic ${\alpha},{\beta}$-unsaturated ketone derivatives represented as substrate(S) were synthesized and their fungicidal activities in vivo against rice blast(Pyricularia oryzae) and tomato leaf blight(Phytophthora infestans) were examined with the quantitative structure activity relationships(QSAR) using 3D QSAR, comparative molecular field analysis (CoMFA). The 3D CoMFA results and those of 2D QSAR were compared and the results reveal that both results show similar trend. The two important factors, steric and electronic, contribute toward the activity. We assumed that fungicidal activity for rice blast was greatly improved by increasing with positive charge of ${\beta}$-carbon and introduction of bulky derivatives into $R_{2}$ group, while that for tomato leaf blight was improved by decreasing the positive charge of ${\beta}$-carbon and introduction of smaller molecular derivative into $R_{2}$ group. The CoMFA analyses clearly demonstrate its potential in unraveling the steric and electronic features of the molecules through contour maps.

• Journal of Integrative Natural Science
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• v.8 no.3
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• pp.214-220
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• 2015

Cancer has emerged as one of the leading cause of deaths worldwide. A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was performed on a series of quinazoline-based anticancer agents. Purpose of the study is to understand the structural basis for their inhibitory activity. Comparative molecular field analysis (CoMFA) technique was employed to develop 3D-QSAR model. Ligand-based alignment scheme was used to generate a reliable CoMFA model. The model produced statistically significant results with a cross-validated correlation coefficient ($q^2$) of 0.589 and a non-cross-validated correlation coefficient ($r^2$) of 0.928. Model was further validated by bootstrapping and progressive scrambling analysis. This study could assist in the design of novel and more potent anticancer agents.

• Bulletin of the Korean Chemical Society
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• v.33 no.1
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• pp.149-152
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• 2012

The (S)-(+)-decursin and its analogues are reported as potent inhibitors of melanin production in B16 murine melanoma cells. In order to understand the factors responsible for potency as well as inhibition of potency of (S)-(+)-decursin and its analogues, three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed. Since receptor structures are not available, a pharmacophore model was constructed. Using PHASE, we generated 3 different models and selected the seven-site model, which returned excellent statistical values ($r^2$ = 0.9127, $Q^2$ = 0.6878, Pearson-R = 0.9014). Using the generated pharmacophore model, we screened a natural products library and obtained 4'-epi-decursin as the most related compound. 4'-epidecursin is similar to (S)-(+)-decursin, but shows additional interaction possibilities with tyrosinase. The study thus sheds some light on possibility of developing more potent tyrosinase inhibitors.