• Applied Biological Chemistry
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• 제46권3호
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• pp.155-164
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• 2003

Biological Hammett Equation에 기초하여 Hansch-Fujita식으로 제안된 정량적인 구조 활성상관(QSAR) 기법 (Sung, Nack-Do (2002) Development of new agrochemicals by quantitative structure-activity relationship (QSAR) methodology. Kor. J. Pestic. Sci. 6: 166-174, 231-243 및 7: 1-11)에 따른 새로운 농약의 탐색과 개발에 관련하여 1990년도를 전후한 국내에서 이루어진 QSAR 기법중 주로 2D QSAR기법의 활용연구 현황에 대하여 조명하였다.

• 농약과학회지
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• 제7권1호
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• pp.1-11
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• 2003

새로운 농약을 탐색하고 개발하는데 있어서 고효율 유기함성 (HTOS) 기술과 고효율 검색 (HTS) 기술 등의 발전과 더불어 컴퓨터 화학을 이용한 분자설계 (CAMD) 방법으로 보편화되고 있는 비교 분자장 분석(CoMFA)과 비교 분자 유사성 지수분석(CoMSIA) 등, 3D QSAR 기법들을 위시하여 분자 홀로그램 구조 - 활성관계 (HQSAR) 분석방법 등, QSAR 기법들을 요약하고 그 활용 사례들을 간략하게 소개하였다.

• 대한화학회지
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• 제58권6호
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• pp.543-552
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• 2014

A quantitative structure activity relationship (QSAR) study is performed for modeling and prediction of oral bioavailabilities of 216 diverse set of drugs. After calculation and screening of molecular descriptors, linear and nonlinear models were developed by using multiple linear regression (MLR), artificial neural network (ANN), support vector machine (SVM) and random forest (RF) techniques. Comparison between statistical parameters of these models indicates the suitability of SVM over other models. The root mean square errors of SVM model were 5.933 and 4.934 for training and test sets, respectively. Robustness and reliability of the developed SVM model was evaluated by performing of leave many out cross validation test, which produces the statistic of $Q^2_{SVM}=0.603$ and SPRESS = 7.902. Moreover, the chemical applicability domains of model were determined via leverage approach. The results of this study revealed the applicability of QSAR approach by using SVM in prediction of oral bioavailability of drugs.

• Bulletin of the Korean Chemical Society
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• 제23권3호
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• pp.417-422
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• 2002

Comparison studies of the Quantitative Structure Activity Relationship (QSAR) methods with new imidazo-quinolinedione derivatives were conducted using Comparative Molecular Field Analysis (CoMFA), Comparative Molecular Similarity Indices Analysis (CoMSIA), and the Hologram Quantitative Structure Activity Relationship (HQSAR). When the CoMFA crossvalidation value, q2, was 0.625, the Pearson correlation coefficient, r2, was 0.973. In CoMSIA, q2 was 0.52 and r2 was 0.979. In the HQSAR, q2 was 0.501 and r2 was 0.924. The best result was obtained using the CoMSIA method according to a comparison of the calculated values with the real in vitro cytotoxic activities against human ovarian cancer cell lines.

• Bulletin of the Korean Chemical Society
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• 제26권1호
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• pp.85-90
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• 2005

MX and its analogs are synthesized and modeled by quantitative structure activity relationship (QSAR) study including comparative molecular field analysis (CoMFA). As a result, factors affecting this class of compounds have been found to be steric and electrostatic effects. Because hologram quantitative structure activity relationship (HQSAR) technique is based on the 2-dimensional descriptors, this is free of ambiguity of conformational selection and molecular alignment. In this study we tried to include all the data available from the literature, and modeled with the HQSAR technique. Among the parameters affecting fragmentation, connectivity was the most important one for the whole compounds, giving good statistics. Considering additional parameters such as bond specification only slightly improved the model. Therefore connectivity has been found to be the most appropriate to explain the mutagenicity for this class of compounds.

• 농약과학회지
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• 제6권3호
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• pp.166-174
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• 2002

정량적인 분자 구조와 물리-화학적인 성질 사이의 상관관계(QSAR)식을 이용하여 약효성을 예측하고 새로운 농약을 탐색하거나 개발하는데 있어서 효율적인 수단으로 활용되는 QSAR 기법의 발전 과정과 자유 에너지 직선관계(LFER)에 관한 기본 개념을 위시한 QSAR 기법의 목적과 유용성 그리고 장단점과 활용 상 제한점 등에 관한 일반적인 내용에 대하여 간략하게 논의하였다.

• Bulletin of the Korean Chemical Society
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• 제33권5호
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• pp.1527-1535
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• 2012

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.

• Bulletin of the Korean Chemical Society
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• 제22권4호
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• pp.388-394
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• 2001

Quantitative Structure-Activity Relationship (QSAR) have been established of 57 fluorovinyloxyacetamides compounds to correlate and predict EC50 values. Genetic algorithm (GA) and multiple linear regression analysis were used to select the descriptors and to generate the equations that relate the structural features to the biological activities. This equation consists of three descriptors calculated from the molecular structures with molecular mechanics and quantum-chemical methods. The results of MLR and GA show that dipole moment of z-axis, radius of gyration and logP play an important role in growth inhibition of barnyard grass.

• Food Science and Biotechnology
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• 제17권3호
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• pp.501-507
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• 2008

The quantitative structure-activity relationships (QSAR) study of antioxidative anthocyanidins and their glycosides were evaluated using 4 different assays of Trolox equivalent antioxidant capacity (TEAC), superoxide radical ($O_2^{{\cdot}-}$), hydrogen peroxide ($H_2O_2$), and peroxynitrite radical ($ONOO^-$) scavenging with TSAR software. Four models were developed with significant predictive values ($r^2$ and p value), which indicated that the antioxidant activities were mainly governed by the 3-dimensional structural energy (torsional energy), constitutional properties (the number of hydroxyl and methyl groups), and electrostatic properties (heat of formation, and dipole, quadrupole, and octupole components). This QSAR approach could contribute to a better understanding of structural properties of anthocyanidins and their glycosides that are responsible for their antioxidant activities. It might also be useful in predicting the antioxidant activities of other anthocyanins.

• Molecular & Cellular Toxicology
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• 제1권1호
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• pp.46-51
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• 2005

Mutagen X (MX) exists in our drinking water as the bi-products of chlorine disinfection. Being one of the most potent mutagen, it attracted much attention from many researchers. MX and its analogs are tested and modeled by quantitative structure activity relationship (QSAR) methods. As a result, factors affecting this class of compounds have been found to be steric and electrostatic effects. We tried to collect all the data available from the literature. The quantitative structure-activity relationship of a set of 29 MX was analyzed using Molecular Field Analysis (MFA) and Receptor Surface Analysis (RSA). The best models gave $q^{2}=0.918,\;r^{2}=0.949$ for MFA and $q^{2}=0.893,\;r^{2}=0.954$ for RSA. The models indicate that an electronegative group at C6 position of the furanone ring increases mutagenicity.