• Applied Biological Chemistry
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• v.35 no.5
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• pp.382-388
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• 1992

Mycelial growth inhibition activity of forty-one N-substituted phenyl 5-chloro-1,3-dimethylpyrazole-4-carboxamides against Rhizoctonia solani was analysed quantitatively by multiple regression analysis using physicochemical parameters of substituents as independent variables and $pEC_{50}$ as dependent variable. As a result, a quantitative structure-activity relationship was formulated using eight physicochemical parameters, which explains 83% of variance of the fungicidal activity. The most important parameter for the biological activity was log k', as related to the penetration and transport processes in the biological system. The activity also correlated with other hydrophobic parameters$({\pi}_2,\;{\pi}_3)$, an electronic parameter$({\Sigma}{\sigma})$, and steric parameters$(STERIMOL\;parameters\;L_3,\;L_4)$.

• Environmental Mutagens and Carcinogens
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• v.21 no.2
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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.

• Environmental Analysis Health and Toxicology
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• v.24 no.2
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• pp.79-93
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• 2009

오염물질에 대한 생태위해성평가(ecological risk assessment)를 위해서는 노출평가(exposure assessment)와 함께 생물영향에 대한 평가(effect assessment)를 수행해야 한다. 노출평가의 경우는 지화학적 과정에 대한 이해를 바탕으로 환경농도를 예측하기 위한 화학평형모델이나 다매체환경거동모델 등 다양한 평가 및 예측모델을 활용해 왔다. 이와 달리 생물영향평가는 실험실 조건에서 제한된 독성자료를 대상으로 외부노출농도에 기반한 농도-반응관계를 통계적 방법을 통해서 추정하는 '경험적 모델(empirical model)'에 주로 의존해 왔다. 최근에 와서 생체 내 잔류량을 기반으로 농도-시간-반응관계를 기술하고 예측하는 독성동태학 및 독성역학 모델(toxicokinetic-toxicodynamic model)과 같은 독성작용에 기반한 모델(processbased model)들이 개발되어 활용되고 있다. 본 논문에서는 여러 종류의 독성동태학 및 독성역학 모델을 소개하고, 이를 통계적 추론에 기반한 전통적인 독성학 모델과 비교하였다. 서로 다른 종류의 독성동태학 및 독성역학 모델로부터 도출된 노출농도-시간 -반응관계식을 비교하고, 동일 독성기작을 보이는 오염물질 그룹 내에서 미측정 오염물질의 독성을 예측할 수 있게 해주는 구조-활성관계(Quantitative Structure-Activity Relationship, QSAR) 모델을 여러 독성동태 및 독성역학모델로부터 유도하였다. 마지막으로 독성동태학 및 독성역학 파라미터를 추정하기 위한 실험계획을 제안하였고, 앞으로 독성동태학 및 독성역학 모델을 생태계 위해성평가에 활용하기 위해서 해결해야 될 연구과제를 검토하였다.

• 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.

• Bulletin of the Korean Chemical Society
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• v.26 no.1
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• pp.139-145
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• 2005

Artificial neural networks (ANNs), for a first time, were successfully developed for the modeling and prediction of solvent effects on rate constant of [2+2] cycloaddition reaction of diethyl azodicarboxylate with ethyl vinyl ether in various solvents with diverse chemical structures using quantitative structure-activity relationship. The most positive charge of hydrogen atom (q$^+$), dipole moment ($\mu$), the Hildebrand solubility parameter (${\delta}_H^2$) and total charges in molecule (q$_t$) are inputs and output of ANN is log k$_2$ . For evaluation of the predictive power of the generated ANN, the optimized network with 68 various solvents as training set was used to predict log k$_2$ of the reaction in 16 solvents in the prediction set. The results obtained using ANN was compared with the experimental values as well as with those obtained using multi-parameter linear regression (MLR) model and showed superiority of the ANN model over the regression model. Mean square error (MSE) of 0.0806 for the prediction set by MLR model should be compared with the value of 0.0275 for ANN model. These improvements are due to the fact that the reaction rate constant shows non-linear correlations with the descriptors.

• Journal of the Korean Chemical Society
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• v.42 no.4
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• pp.378-382
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• 1998

A Quantitative Structure-Activity Relationship of 1-phenylcyclohexyl amine(PCA) and dexoxadral as a receptor has been investigated using semiempirical PM3 MO and Hyper Chem calculation. A set of 19 analogues of PCA was chosen for the study using a selection procedure aimed at minimizing the interparameter correlations, while ensuring that the frontier orbital covered the maximum possible range of LogP. The results show that the FOS and LogP is a good structural parameter to predict the maximum electroshock effective dose ($MES\;ED_{50}$) and toxicity dose ($TD_{50}$) for PCA derivatives.

• The Korean Journal of Pesticide Science
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• v.6 no.3
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• pp.209-217
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• 2002

Two different QSAR methods, the comparative molecular similarity indices analyses (CoMSIA) and hologram quantitative structure activity relationship (HQSAR) are studied for the fungicidal activities ($pI_{50}$) of 2-N-benzyl-5-phenoxy-3-isothiazolone derivatives against sensitive (SPC: 95CC7105) and resisitive (RPC: 95CC7303) phytophthora blight fungus (Phytaphthora capsici). According to the findings from these QSAR investigation, the cross-validation value, $q^2$ and Pearson correlation coefficient, $r^2$ in the two methods were CoMSIA: RPC; $q^2=0.675,\;r^2=0.942$, SPC; $q^2=0.350,\;r^2=0.876$ and HQSAR: RPC; $q^2=0.519,\;r^2=0.869$, SPC; $q^2=0.483,\;r^2=0.990$, respectively. Therefore, the two models of comparative statistical significance were obtained. From the CoMSIA contour maps, the important factors for selective fungicidal activity against RPC are to be expected that the lower hydrophobic and not bulkiness substituent as hydrogen bonding acceptor have to introduce to meta and para-position (C1-C6) on the phenoxy moiety. And the results of prediction suggest that HQSAR method showed higher fungicidal activity than CoMSIA method.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.210-218
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• 2004

Poly(ADP-ribose)polymerase-1 (PARP-1) is a nuclear enzyme involved in various physical functions related to genomic repair, and PARP inhibitors have therapeutic application in a variety of neurological diseases. Docking and the QSAR (quantitative structure-activity relationships) studies for 52 PARP-1 inhibitors were conducted using FlexX algorithm, comparative molecular field analysis (CoMFA), and hologram quantitative structure-activity relationship analysis (HQSAR). The resultant FlexX model showed a reasonable correlation (r$^{2}$ = 0.701) between predicted activity and observed activity. Partial least squares analysis produced statistically significant models with q$^{2}$ values of 0.795 (SDEP=0.690, r$^{2}$=0.940, s=0.367) and 0.796 (SDEP=0.678, r$^{2}$ = 0.919, s=0.427) for CoMFA and HQSAR, respectively. The models for the entire inhibitor set were validated by prediction test and scrambling in both QSAR methods. In this work, combination of docking, CoMFA with 3D descriptors and HQSAR based on molecular fragments provided an improved understanding in the interaction between the inhibitors and the PARP. This can be utilized for virtual screening to design novel PARP-1 inhibitors.

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

Quantitative structure-activity relationship (QSAR) methodologies have been applied for many years, to correlate the relationship between physicochemical properties of chemical substances and their biological activities to generate a statistical model for prediction of the activities of new chemical entities. The basic principle behind the QSAR models is that, how structural variation is responsible for the difference in biological activities of the compounds. 3D-QSAR has emerged as a natural extension to the classical Hansch and Free-Wilson approaches, which develops the 3D properties of the ligands to predict their biological activities using various chemometric techniques (PLS, G/PLS, ANN etc). It has served as a valuable predictive tool in the design of pharmaceuticals and agrochemicals. This review seeks to provide different 3D-QSAR approaches involved in drug designing process to develop structure-activity relationships and also discussed the fundamental limitations, as well as those that might be overcome with the improved methodologies.

• Journal of the Korean Chemical Society
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• v.57 no.1
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• pp.99-103
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• 2013

The present communication deals with the Pharmacophore modeling, 3D QSAR and docking analysis on series of Pyrimidine derivatives as potential calcium channel blockers. The computational studies showed hydrogen bond donor, hydrogen bond acceptor, and hydrophobic group are important features for calcium channel blocking activity. These studies showed that Pyrimidine scaffold can be utilized for designing of novel calcium channels blockers for CVS disorders.