• Bulletin of the Korean Chemical Society
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• v.32 no.7
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• pp.2433-2442
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• 2011

The three dimensional quantitative structure activity relationship (3D QSAR) models were developed using Comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and docking studies. The fit of Quinazolinone antifolates inside the active site of modeled bovine dihydrofolate reductase (DHFR) was assessed. Both ligand based (LB) and receptor based (RB) QSAR models were generated, these models showed good internal and external statistical reliability that is evident from the $q^2_{loo}$, $r^2_{ncv}$ and $r^2_{pred}$. The identified key features enabled us to design new Quinazolinone analogues as DHFR inhibitors. This study is a building bridge between docking studies of homology modeled bovine DHFR protein as well as ligand and target based 3D QSAR techniques of CoMFA and CoMSIA approaches.

• Bulletin of the Korean Chemical Society
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• v.25 no.10
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• pp.1513-1520
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• 2004

We investigate a series of synthesized ${\beta}$-methoxyacrylate analogues for their 3D QSAR & HQSAR against Magnaporthe grisea (Rice Blast Disease). We perform the three-dimensional Quantitative Structure-Activity Relationship (3D-QSAR) studies, using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) procedure. In addition, we carry out a two-dimensional Quantitative Structure-Activity Relationship (2D-QSAR) study, using the Hologram QSAR (HQSAR). We perform these studies, using 53 compounds as a training set and 10 compounds as a test set. The predictive QSAR models have conventional $r^2$ values of 0.955 at CoMFA, 0.917 at CoMSIA, and 0.910 at HQSAR respectively; similarly, we obtain cross-validated coefficient $q^2$ values of 0.822 at CoMFA, 0.763 at CoMSIA, and 0.816 at HQSAR, respectively. From these studies, the CoMFA model performs better than the CoMSIA model.

• The Korean Journal of Physiology and Pharmacology
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• v.13 no.6
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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.

• Journal of Photoscience
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• v.8 no.3_4
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• pp.119-121
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• 2001

Three-Dimensional Quantitative Structure-Activity Relationship(QSAR) has been investigated over 67 flavonoids to correlate and predict GI$\sub$50/ values. The partial least-squares(PLS) model was performed to calculate the activity of each derivatives, and this was compared with the actual value. The results of the cross-validated(${\gamma}$$^2$=0.997) values show that cytotoxic activities play an important role which is in good agreement with the observed GI$\sub$50/ values.

• Bulletin of the Korean Chemical Society
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• v.27 no.2
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• pp.266-272
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• 2006

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed for 67 molecules of 2-amino-benzothiazole-6-anilide derivatives against lymphocyte-specific protein tyrosine kinase (P56 LCK). The molecular field analysis (MFA) and receptor surface analysis (RSA) were employed for QSAR studies and the predictive ability of the model was validated by 15 test set molecules. Structure-based investigations using molecular docking simulation were performed with the crystal structure of P56 LCK. Good correlation between predicted fitness scores versus observed activities was demonstrated. The results suggested that the nature of substitutions at the 2-amino and 6-anilide positions were crucial in enhancing the activity, thereby providing new guidelines for the design of novel P56 LCK inhibitors.

• Bulletin of the Korean Chemical Society
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• v.34 no.4
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• pp.1212-1220
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• 2013

The human coagulation factor XI (FXI) is a serine protease that plays a significant role in blocking of the blood coagulation cascade as an attractive antithrombotic target. Selective inhibition of FXIa (an activated form of factor XI) disrupts the intrinsic coagulation pathway without affecting the extrinsic pathway or other coagulation factors such as FXa, FIIa, FVIIa. Furthermore, targeting the FXIa might significantly reduce the bleeding side effects and improve the safety index. This paper reports on a docking-based three dimensional quantitative structure activity relationship (3D-QSAR) study of the potent FXIa inhibitors, the chloro-phenyl tetrazole scaffold series, using comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods. Due to the characterization of FXIa binding site, we classified the alignment of the known FXIa inhibitors into two groups according to the docked pose: S1-S2-S4 and S1-S1'-S2'. Consequently, highly predictive 3D-QSAR models of our result will provide insight for designing new potent FXIa inhibitors.

• 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.

• 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.

• Proceedings of the PSK Conference
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• 2002.10a
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• pp.356.2-356.2
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• 2002

The structure of 1-phenyl-2-substituted thiourea derivatives have been studied and optimized for their cytotoxic activity. The three dimensional quantitative structure activity relationship (3D-QSAR) was investigated using comparative molecular field analysis (CoMFA). The result suggested that electrostatic and steric factors of 2-alkylureido-1-phenyl propanol derivatives were correlated well with cytotoxic activity. (omitted)

• 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.