• 제목/요약/키워드: Quantitative relationship

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정량적인 구조-활성상관(QSAR) 기법에 의한 새로운 농약의 개발 -IV. 국내의 연구 동향과 전망- (Development of New Agrochemicals by Quantitative Structure-Activity Relationship (QSAR) Methodology -IV. A Tendency of Research and Prospect in Korea-)

  • 성낙도
    • 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.

A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

  • Ghasemi, Jahan B.;Zolfonoun, Ehsan
    • 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.

Prediction on the Chiral Behaviors of Drugs with Amine Moiety on the Chiral Cellobiohydrolase Stationary Phase Using a Partial Least Square Method

  • Choi, Sun-Ok;Lee, Seok-Ho;Park Choo , Hea-Young
    • Archives of Pharmacal Research
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    • 제27권10호
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    • pp.1009-1015
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    • 2004
  • Quantitative Structure-Resolution Relationship (QSRR) using the Comparative Molecular Field Analysis (CoMFA) software was applied to predict the chromatographic behaviors of chiral drugs with an amine moiety on the chiral cellobiohydrolase (CBH) columns. As a result of the Quantitative CoMFA-Resolution Relationship study, using the partial least square method, prediction of the behavior of drugs with amine moiety upon chiral separation became possible from their three dimensional molecular structures. When a mixed mobile phase of 10 mM aqueous phosphate buffer (pH 7.0) - isopropanol (95 : 5) was employed, the best Quantitative CoMFA-Resolution Relationship, derived from the study, provided a cross-validated $q^2$ = 0.933, a normal $r^2$ = 0.995, while the best Quantitative CoMFA-Separation Factor Relationship, also derived from the study, yielded a cross-validated $q^2$ = 0.939, a normal $r^2$ = 0.991. When all of these results are considered, this QSRR-CoMFA analysis appears to be a very useful tool for the preliminary prediction on the chromatographic behaviors of drugs with an amine moiety inside chiral CBH columns.

What Holds the Future of Quantitative Genetics? - A Review

  • Lee, Chaeyoung
    • Asian-Australasian Journal of Animal Sciences
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    • 제15권2호
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    • pp.303-308
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    • 2002
  • Genetic markers engendered by genome projects drew enormous interest in quantitative genetics, but knowledge on genetic architecture of complex traits is limited. Complexities in genetics will not allow us to easily clarify relationship between genotypes and phenotypes for quantitative traits. Quantitative genetics guides an important way in facing such challenges. It is our exciting task to find genes that affect complex traits. In this paper, landmark research and future prospects are discussed on genetic parameter estimation and quantitative trait locus (QTL) mapping as major subjects of interest.

정량적인 구조-활성상관 (QSAR) 기법에 의한 새로운 농약의 개발. III. 3D QSAR 기법들과 컴퓨터를 이용한 분자설계(CAMD) (Development of new agrochemicals by quantitative structure-activity relationship (QSAR) methodology. III. 3D QSAR methodologies and computer-assisted molecular design (CAMD))

  • 성낙도
    • 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.

퍼지 전문가 시스템을 이용한 강관 하이드로포밍의 성형성 예측에 관한 연구 (Optimization of tube hydroforming process by using fuzzy expert system)

  • 박광수;김동규;이동활;문영훈
    • 한국소성가공학회:학술대회논문집
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    • 한국소성가공학회 2004년도 춘계학술대회 논문집
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    • pp.194-197
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    • 2004
  • In the tube hydroforming process, a tube is placed into the die cavity and the ends of the tube are sealed by fixing the axial cylinder piston into the ends. Then the tube is pressurized with a hydraulic fluid and simultaneously the axial cylinders move to feed the material into the expansion zone. Therefore, the quantitative relationship between process parameters such as internal pressure and feeding amount and hydroformabillity, is hard to establish because of their high complexity and many unknown factors. In this study, the empirical and the quantitative relationship between process parameters and hydroformabillity are analyzed by fuzzy rules. Fuzzy expert system is an advanced expert system which uses fuzzy rule and approximate reasoning. Many process parameters are converted to the quantitative relationship by use of approximate reasoning of fuzzy expert system. The comparison between experimentally measured hydroformabillity from hydroforming experiments and the predicted values by fuzzy expert system shows a good agreement.

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Quantitative Structure Activity Relationship Prediction of Oral Bioavailabilities Using Support Vector Machine

  • Fatemi, Mohammad Hossein;Fadaei, Fatemeh
    • 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.

Comparison of QSAR Methods (CoMFA, CoMSIA, HQSAR) of Anticancer 1-N-Substituted Imidazoquinoline-4,9-dione Derivatives

  • Suh, Myung-Eun;Park, So-Young;Lee, Hyun-Jung
    • 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.

Hologram Quantitative Structure Activity Relationship (HQSAR) Study of Mutagen X

  • Cho, Seung-Joo
    • 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.

정량적인 구조-활성상관(QSAR) 기법에 의한 새로운 농약의 개발 I. 기본 개념과 QSAR 기법의 유형 (Development of new agrochemicals by quantitative structure-activity relationship (QSAR) methodologies. I. The basic concepts and types of QSAR methodologies)

  • 성낙도
    • 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.