• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.150-155
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• 2003

We discussed a quantitative structure-activity relationships (QSAR) technique on incomplete data set. We proposed a new solver that used 2 kinds of multi-layer neural networks. One is to compensate the defect data, and another is to evaluate the QSAR. The solver can predict the defects in model QSAR data. By using them, we get very high precision QSAR. It is 5-10 times higher than that of a traditional method. However, in case of anti-cancer Carboquone, the prediction is not so complete. It was about O(3) wrong than the model calculation. The predicted values would have rather large error. It is caused by noisy observations of Carboquone. However, if we used the uncertain predictions, new data are included in QSAR. If not, they were omitted. The effect would not be little. Therefore, we evaluated the QSAR. The results are contrary to the expectation, are not so wrong. We believe that the wrong effect is suppressed by including information of new data.

• Bulletin of the Korean Chemical Society
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• 제25권10호
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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.

• 농약과학회지
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• 제11권2호
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• pp.72-81
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• 2007

일련의 새로운 O,O-dialkyl-1-phenoxyacetoxy-1-methylphosphonate (S) 유도체들의 반응성과 치환기가 변화함에 따른 오이(Cucumus Sativa)씨에 대한 발아전 제초활성과의 관계를 2D-QSAR 및 HQSAR 방법으로 검토하였다. 통계적으로 HQSAR 모델이 2D-QSAR 모델보다 양호하였으며 기질분자(S)와 PDH 효소중 $BH^+$ 이온(I) 사이의 경계분자궤도(FMO) 상호작용은 친전자성 반응이 우세하였다. 치환기의 효과로부터 기질분자 (S)내 $R_2$-치환기는 carbonyl 산소원자에 대한 친전자성 반응을, 그리고 phenyl 고리상 X,Y-치환기는 carbonyl 탄소원자에 대한 친핵성 반응에 기여하였으며 $R_2$-치환기보다 X,Y-치환기의 영향이 더 컸다. 2D-QSAR모델 (I 및 II)과 HQSAR 모델의 기여도로부터 X,Y-치환기의 길이가 길수록 제초활성이 증가하는 경향이었으며 적정한 ${\epsilon}LUMO$ 에너지($({\epsilon}LUMO)_{opt.}$=-0.479 e.v.)가 제초활성에 중요한 요소이었다. 그러므로 PDH 효소의 저해활성으로 인한 제초활성은 친핵성반응으로 진행될 것으로 예상되었다. 2D-QSAR 및 HQSAR 두 모델로부터 제초활성에 기여하는 기질분자(S)의 구조 특이성과 요소들을 새로운 제초제 설계에 적용할 수 있음을 시사하였다.

• 한국환경보건학회지
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• 제39권2호
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• pp.130-137
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• 2013

Objectives: The OECD QSAR Application Toolbox was developed by the Organisation for Economic Cooperation and Development (OECD) to facilitate the practical use of QSAR approaches in regulatory contexts as well as to reduce the need for additional animal testing. In this study, human health and the ecotoxicity of chemicals were predicted by applying the OECD QSAR Application Toolbox and the results were compared with experimental data in order to evaluate the applicability of this program. Methods: Read-across, trend analysis, and QSAR of OECD QSAR Application Toolbox were used for the prediction of toxicity. Results: The toxicity prediction was conducted on 6,354 chemicals for which toxicity data have been produced on the six endpoints of skin sensitization, skin irritation, eye irritation, mutagenicity, and acute toxicities of fish and Daphnia. From the total of 6,354, we obtained prediction results for 1,621 chemicals (25.5%). Conclusions: The predicted properties of mutagenicity, skin sensitization, and acute aquatic toxicities were reasonably good when compared with experimental data, but other endpoints were not due to the limitation of applicable chemical groups.

• Bulletin of the Korean Chemical Society
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• 제29권3호
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• pp.647-655
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• 2008

Microsomal prostaglandin E2 synthase (mPGES-1) is a potent target for pain and inflammation. Various QSAR (quantitative structure activity relationship) analyses used to understand the factors affecting inhibitory potency for a series of MK886 analogues. We derived four QSAR models utilizing various quantum mechanical (QM) descriptors. These QM models indicate that steric, electrostatic and hydrophobic interaction can be important factors. Common pharmacophore hypotheses (CPHs) also have studied. The QSAR model derived by best-fitted CPHs considering hydrophobic, negative group and ring effect gave a reasonable result (q2 = 0.77, r2 = 0.97 and Rtestset = 0.90). The pharmacophore-derived molecular alignment subsequently used for 3D-QSAR. The CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis) techniques employed on same series of mPGES-1 inhibitors which gives a statistically reasonable result (CoMFA; q2 = 0.90, r2 = 0.99. CoMSIA; q2 = 0.93, r2 = 1.00). All modeling results (QM-based QSAR, pharmacophore modeling and 3D-QSAR) imply steric, electrostatic and hydrophobic contribution to the inhibitory activity. CoMFA and CoMSIA models suggest the introduction of bulky group around ring B may enhance the inhibitory activity.

• Archives of Pharmacal Research
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• 제23권4호
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• pp.324-328
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• 2000

Three dimensional QSAR studies for antihistamine and antibradykinin effects of new piperazine derivatives were conducted using the comparative molecular field analysis. Electrostatic and steric factors, but not hydrophobic factor, of the synthesized compounds were correlated with the antagonistic effect.

• Bulletin of the Korean Chemical Society
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• 제32권7호
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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.

• Environmental Analysis Health and Toxicology
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• 제18권4호
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• pp.271-276
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• 2003

The purpose of the present study was to perform experiments of cytotoxicity using HeLa cell and to evaluate the possibility that QSAR is applicable to the cytotoxicity of alkylphenols. Higher toxicities were found in four alkylphenols in the following order: 4-n-Nonylphenol) 4-tert-Octylphenol) 4-n-Octylphenol > 4-n Heptylpheonl. Whereas other alkylphenols were apparently less toxic. By using Percent Hydrophilic Surface Area (PHSA) quantitative structure-activity relationships (QSARs) models were developed: Cytotoxicity (%) = 90.14089-4.72224 PHSA ($R^2$=0.2046, $\alpha$=0.0265). It is concluded that some of the obtained data are useful to determine whether QSAR methods can be of general use in predicting that until further work is undertaken to develop QSARs for a much wider range of homologous series of alkylphenol compounds.

• 한국환경성돌연변이발암원학회지
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• 제20권1호
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• pp.21-25
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• 2000

Recently there is increasing interest in the use of structure activity relationships for predicting the biological activity of chemicals. The reasons for the interest include the decrease cost and time per chemical as compared with animal or cell system for identifying toxicological effects of chemicals and the reduction in the use of animals for toxicological testing. This study is to test the validity of the mutagenicity data generated from QSAR (Quantitative Structure Activity Relationship) program. Thirty chemicals, which had been evaluated by Ames test during 1997-1999, were assessed with TOPKAT QSAR mutagenicity prediction module. Among 30chemicals experimented, 28 were negative and 2 were positive for Ames test. On the contrary, 23 chemicals showed the high confidence level indicating high prediction rate in mutagenicity evaluation, and 7 chemicals showed the lsow to moderate confidence level indicating low prediction in mutagenicity evaluation. Overall mutagenicity prediction rate was 77% (23/30). The prediction rates for non-mutagenic chemicals were 79% (22/28) and mutagenic chemicals were 50% (1/2). QSAR could be a useful tool in providing toxicological data for newly introduced chemicals or in furnishing data for MSDS or in determining the dose in toxicity testing for chemicals with no known toxicological data.

• Reproductive and Developmental Biology
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• 제31권1호
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• pp.15-20
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• 2007

가축의 번식과 수요를 조절할 수 있는 생물학적 자극 통제 수단으로 새로운 돼지 페르몬성 냄새 물질를 탐색하고자, 기질 분자로서 2-cyclohexyloxytetrahydrofurane (A), 2-phenoxytetrahydrofurane (B) 유도체들의 설명인자인 물리화학 파라미터와 돼지 페로몬의 수용체 (pOBP)에 대한 결합 친화력 상수($p[Od.]_{50}$) 간의 2D-QSAR 모델을 유도하고 검토하였다. 2D-QSAR 모델은 결합 친화력 상수를 약 96.4% 설명하는 매우 양호한 모델($r^{2}=0.964$)로서 분자내 치환기의 소수성 (SL) 상수에 관한 적정값이 $(SL)_{opt.}=1.418$일 때 가장 높은 결합 친화력을 나타냄을 알았다. 그러므로 분자내 치환기의 소수성 인자가 결합 친화력 상수에 가장 큰 영향을 미치는 중요한 요소이었다.