• Journal of Integrative Natural Science
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• v.5 no.1
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• pp.6-12
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• 2012

c-Jun N-terminal kinase-3 (JNK-3) has been identified as a promising target for neuronal apoptosis and has the effective therapeutic for neurodegenerative diseases such as Parkinson's disease, Alzheimer's disease, and other CNS disorders. Herein, we report the essential structural and chemical parameters for JNK-3 inhibitors utilizing comparative molecular field similarity indices analysis (CoMSIA) using the derivatives of 3,5-disubstituted quinolines. The best predictions were obtained CoMSIA model (q2=0.834, r2=0.987) and the statistical parameters from the generated 3D-QSAR models were indicated that the data are well fitted and have high predictive ability. The resulting contour map from 3D-QSAR models might be helpful to design novel and more potent JNK3 derivatives.

• Journal of the Korean Chemical Society
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• v.57 no.6
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• pp.744-754
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• 2013

Quantitative structure-activity relationship (QSAR) analysis for recently synthesized imidazole-(benz)azole and imidazole - piperazine derivatives was studied for their anticancer activities against breast (MCF-7) cell lines. The statistically significant 2D-QSAR models ($r^2=0.8901$; $q^2=0.8130$; F test = 36.4635; $r^2$ se = 0.1696; $q^2$ se = 0.12212; pred_$r^2=0.4229$; pred_$r^2$ se = 0.4606 and $r^2=0.8763$; $q^2=0.7617$; F test = 31.8737; $r^2$ se = 0.1951; $q^2$ se = 0.2708; pred_$r^2=0.4386$; pred_$r^2$ se = 0.3950) were developed using molecular design suite (VLifeMDS 4.2). The study was performed with 18 compounds (data set) using random selection and manual selection methods used for the division of the data set into training and test set. Multiple linear regression (MLR) methodology with stepwise (SW) forward-backward variable selection method was used for building the QSAR models. The results of the 2D-QSAR models were further compared with 3D-QSAR models generated by kNN-MFA, (k-Nearest Neighbor Molecular Field Analysis) investigating the substitutional requirements for the favorable anticancer activity. The results derived may be useful in further designing novel imidazole-(benz)azole and imidazole-piperazine derivatives against breast (MCF-7) cell lines prior to synthesis.

• Bulletin of the Korean Chemical Society
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• v.30 no.9
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• pp.2117-2120
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• 2009

• 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.14 no.3
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• pp.191-198
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• 2010

To predict and design of new potent insecticidal compounds, the two dimensional quantitative structure-activity relationships (2D-QSARs) and molecular hologram quantitative structure-activity relationships (HQSARs) between the various physicochemical parameters as descripters of N'-phenyl-N-methylformamidine analogues (1-22) and their insecticidal activity against the two spotted spider mite (Tetranychus urticae) were discussed quantitatively. From 2D-QSAR models (1 & 3), the width ($B_2$) of $R_3$-group as sterically factor and optimal total dipole moment (TDM=2.025D) of $R_4$-group were mainly influenced to increase the activity. Therefore, the activities were depend upon the $R_3$- and $R_4$-groups. Particularly, it is predicted that the activity of newly designed potent compound (PI; $EC_{50}$=0.516 ppm) by 2D-QSAR models (3) and HQSAR model F2 was about 34.3 fold higher than that of the commercialized insecticide, Amitraz ($EC_{50}$=17.7 ppm).

• Journal of the Society of Cosmetic Scientists of Korea
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• v.40 no.4
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• pp.383-390
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• 2014

The following conclusion was made from the 2D-QSAR model for the tyrosinase inhibitory activity according to the variation of the substituents R1 and R2 in analogues of compound 2-[(2,6-dioxocyclohexyl)methyl]cyclohexane- 1,3-dione (1-23). The best optimized 2D-QSAR model was $Obs.pI_{50}=-0.295({\pm}0.031)TDM$ $-0.120({\pm}0.014)DMZ+0.135({\pm}0.050)DMX.R_2+6.382({\pm}0.17)$, and the correlation $r^2=0.905$) of which was greater than its predictability ($q^2=0.843$). The magnitude of the effect of tyrosinase inhibitory activities was in order of TDM > $DMX.R_2{\geq}DMZ$, and it tended to increase as the hydrophobicity of substrate molecule (ClogP > 0) as well as the steric favor of substituent $R_1$ increased. The analysis of the model implies that inhibitory activity of substrate molecule will increase as $DMX.R_2$ (Dipole moment X component of $R_2$-substituent) increases, while TDM (Total Dipole Moment) and DMZ(Dipole Moment of Z-Component) decrease. As such, it is deemed feasible to conclude, that in order to increase the inhibitory effect, it would be rather desirable to replace the polar groups within the molecules with non-polar functional groups.

• 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.

• Journal of Korean Traditional Oncology
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• v.11 no.1
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• pp.95-103
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• 2006

Objective: Gami-Samhwang-San, a herbal prescription for obesity treatment, is composed of seven crude herbs such as Ephedrae Herba, Scutellariae Radix, Acori Gramineri Rhizoma, Polygalae Radix, Typhae Pollen, Armeniacae Semen, Nelumbo Folium. This study was aimed to evaluate marker substances in n-butanol fraction (SH-21-B) from Gami-Samhwang-San by high performance liquid chromatography (HPLC). And we predicted inhibition activity of major compounds of Gami-Samhwang-San using Quantitative Structure Activity Relationships (QSAR) Methods: The separation was performed on a YMC J,sphere-H80 CI8(250${\times}$4.6 mm I.D) column by gradient elution with $H_3PO_4$ buffers in acetonitrile as the moblie phase at a flow-rate of 1.0ml/min. Results: HPLC was employed to determine the quantities and the qualities of several marker substances such as ephedrine, pseudoephedirne, baicalin, ${\beta}-asarone$, tenuifoliside, naringenin, amygdalin and hyperoside in the SH-21-B. Conclusion: We suggest this results could be a useful evidence for quality control of SH-21-B.

• Journal of Applied Biological Chemistry
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• v.50 no.2
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• pp.52-57
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• 2007

Quantitative structure-activity relationships (QSARs) on the inhibition activities by oleanolic acid analogues (1-19) as a potent inhibitor against protein tyrosine phosphatase-1B were studied quantitatively using 2D-QSAR and HQSAR methodologies. The inhibition activity was dependent on the variations of $R_{4-}$substituent, and as shown in 2D-QSAR model ($r^2=0.928$), it has a tendency to increase as the negative Randic Indice (RI) goes up. The size of the molecular fragments used in HQSAR varied from five to eight. The fragment distinctions had the best statistic value, whose predictability is $q^2=0.785$ and correlation coefficient is $r^2=0.970$, on condition of connections. From the atomic contribution maps, the factor that contributes to the inhibition activities is the $C_{15}{\sim}C_{17}$ bond in the D ring. From the analysis result of these two the models, the structural distinctions and descriptors that contribute to the inhibition activities were obtained.

• Bulletin of the Korean Chemical Society
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• v.34 no.3
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• pp.837-850
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• 2013

Bovine viral diarrhea virus (BVDV), a major pathogen of cattle, is a well-characterized pestivirus which has been used as a good model virus for HCV. The RNA-dependent RNA polymerase (RdRp) plays a key role in the RNA replication process, thus it has been targeted for antivirus drugs. We employed two-dimensional quantitative structure-activity relationship (2D-QSAR) and molecular field analysis (MFA) to identify the molecular substructure requirements, and the particular characteristics resulted in increased inhibitory activity for the known series of compounds to act as effective BVDV inhibitors. The 2D-QSAR study provided the rationale concept for changes in the structure to have more potent analogs focused on the class of arylazoenamines, benzimidazoles, and acridine derivatives with an optimal subset of descriptors, which have significantly contributed to overall anti-BVDV activity. MFA represented the molecular patterns responsible for the actions of antiviral compound at their receptors. We conclude that the polarity and the polarizability of a molecule play a main role in the inhibitory activity of BVDV inhibitors in the QSAR modeling.