The Experts below are selected from a list of 309795 Experts worldwide ranked by ideXlab platform
Botao Fan - One of the best experts on this subject based on the ideXlab platform.
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Quantitative Structure retention relationships for organic pollutants in biopartitioning micellar chromatography
Analytica Chimica Acta, 2007Co-Authors: Binbin Xia, Xiaoyun Zhang, Botao FanAbstract:Abstract Quantitative Structure–retention relationship (QSRR) models have been successfully developed for the prediction of the retention factor (log k ) in the biopartitioning micellar chromatography (BMC) of 66 organic pollutants. Heuristic method (HM) and radial basis function neural networks (RBFNN) were utilized to construct the linear and non-linear QSRR models, respectively. The optimal QSRR model was developed based on a 6-17-1 radial basis function neural network architecture using molecular descriptors calculated from molecular Structure alone. The RBFNN model gave a correlation coefficient ( R 2 ) of 0.8464 and root-mean-square error (RMSE) of 0.1925 for the test set. This paper provided a useful model for the predicting the log k of other organic compounds when experiment data are unknown.
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Quantitative Structure property relationships for pesticides in biopartitioning micellar chromatography
Journal of Chromatography A, 2006Co-Authors: Feng Luan, Haixia Zhang, Xiaoyun Zhang, Mancang Liu, Botao FanAbstract:The retention factor (log k) in the biopartitioning micellar chromatography (BMC) of 79 heterogeneous pesticides was studied by Quantitative Structure-property relationships (QSPR) method. Heuristic method (HM) and support vector machine (SVM) method were used to build linear and nonlinear models, respectively. Compared the results of these two methods, those obtained by the SVM model are much better. For the test set, a predictive correlation coefficient (R) of 0.9755 and root-mean-square (RMS) error of 0.1403 were obtained. The proposed QSPR models, both by HM and SVM, contain the same descriptors that agree with the classical Abraham parameters of well-known linear solvation energy relationships (LSER).
John C Dearden - One of the best experts on this subject based on the ideXlab platform.
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how not to develop a Quantitative Structure activity or Structure property relationship qsar qspr
Sar and Qsar in Environmental Research, 2009Co-Authors: John C Dearden, Mark T D Cronin, K L E KaiserAbstract:Although thousands of Quantitative Structure–activity and Structure–property relationships (QSARs/QSPRs) have been published, as well as numerous papers on the correct procedures for QSAR/QSPR analysis, many analyses are still carried out incorrectly, or in a less than satisfactory manner. We have identified 21 types of error that continue to be perpetrated in the QSAR/QSPR literature, and each of these is discussed, with examples (including some of our own). Where appropriate, we make recommendations for avoiding errors and for improving and enhancing QSAR/QSPR analyses.
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Quantitative Structure property relationships for prediction of boiling point vapor pressure and melting point
Environmental Toxicology and Chemistry, 2003Co-Authors: John C DeardenAbstract:Boiling point, vapor pressure, and melting point are important physicochemical properties in the modeling of the distribution and fate of chemicals in the environment. However, such data often are not available, and therefore must be estimated. Over the years, many attempts have been made to calculate boiling points, vapor pressures, and melting points by using Quantitative Structure-property relationships, and this review examines and discusses the work published in this area, and concentrates particularly on recent studies. A number of software programs are commercially available for the calculation of boiling point, vapor pressure, and melting point, and these have been tested for their predictive ability with a test set of 100 organic chemicals.
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Quantitative Structure activity relationships of chemicals acting by non polar narcosis theoretical considerations
Quantitative Structure-activity Relationships, 1998Co-Authors: Yuan H Zhao, Mark T D Cronin, John C DeardenAbstract:Theoretical Quantitative Structure-activity relationships have been established based on narcotic mechanisms of action and toxicity data to the fathead minnow, Daphnia magna and Vibrio fischeri. The results confirmed that hydrophobicity is important in modelling narcosis. However, the results of the present investigation also confirmed that molecular bulk may play an important role in toxicity to aqueous organisms, especially in the toxicity to organisms with lower lipid content, for example, V. fischeri. The results are discussed in the light of other inter-species differences that may occur as a consequence of accumulation and clearance kinetics and the relative metabolism of xenobiotics by each organism. Because of the complex tissue Structure of organisms, classification of narcotic compounds using hydrophobicity parameters alone can sometimes lead to errors.
Rishay Kumar - One of the best experts on this subject based on the ideXlab platform.
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development of predictive Quantitative Structure activity relationship models of epipodophyllotoxin derivatives
Journal of Biomolecular Screening, 2010Co-Authors: Pradeep Kumar Naik, Abhishek Dubey, Rishay KumarAbstract:Epipodophyllotoxins are the most important anticancer drugs used in chemotherapy for various types of cancers. To further, improve their clinical efficacy a large number of epipodophyllotoxin derivatives have been synthesized and tested over the years. In this study, a Quantitative Structure-activity relationship (QSAR) model has been developed between percentage of cellular protein-DNA complex formation and structural properties by considering a data set of 130 epipodophyllotoxin analogues. A systematic stepwise searching approach of zero tests, missing value test, simple correlation test, multicollinearity test, and genetic algorithm method of variable selection was used to generate the model. A statistically significant model (r(train)2 = 0.721; qcv2 = 0.678) was obtained with descriptors such as solvent-accessible surface area, heat of formation, Balaban index, number of atom classes, and sum of E-state index of atoms. The robustness of the QSAR models was characterized by the values of the internal l...
Alya A Arabi - One of the best experts on this subject based on the ideXlab platform.
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electron density descriptors as predictors in Quantitative Structure activity property relationships and drug design
Future Medicinal Chemistry, 2011Co-Authors: Cherif F Matta, Alya A ArabiAbstract:The use of electron density-based molecular descriptors in drug research, particularly in Quantitative Structure–activity relationships/Quantitative Structure–property relationships studies, is reviewed. The exposition starts by a discussion of molecular similarity and transferability in terms of the underlying electron density, which leads to a qualitative introduction to the quantum theory of atoms in molecules (QTAIM). The starting point of QTAIM is the topological analysis of the molecular electron-density distributions to extract atomic and bond properties that characterize every atom and bond in the molecule. These atomic and bond properties have considerable potential as bases for the construction of robust Quantitative Structure–activity/property relationships models as shown by selected examples in this review. QTAIM is applicable to the electron density calculated from quantum-chemical calculations and/or that obtained from ultra-high resolution x-ray diffraction experiments followed by nonspher...
Marković Bojan - One of the best experts on this subject based on the ideXlab platform.
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Estimation of passive gastrointestinal absorption and membrane retention using PAMPA test, Quantitative Structure-permeability and Quantitative Structure-retention relationship analyses of ethylenediamine-N,N'-di-2-(3-cyclohexyl)propanoic acid and 1,
'Elsevier BV', 2020Co-Authors: Tubić Biljana, Dobričić Vladimir, Poljarević Jelena, Savić Aleksandar, Sabo Tibor, Marković BojanAbstract:Passive gastrointestinal absorption and membrane retention of twelve esters of (S,S)-ethylenediamine-N,N'-di-2-(3-cyclohexyl)propanoic acid (EDCP) and (S,S)-1,3-propanediamine-N,N'-di-2-(3-cyclohexyl)propanoic acid (PDCP), as well as of these two non-esterified acids were estimated using PAMPA test. Artificial PAMPA membrane used in this study for the simulation of gastrointestinal barrier was solution of egg lecithin in dodecane (1 % w/v). All tested compounds belong to class III (high membrane retention and low permeation), whereas EDCP, dipentyl ester of PDCP (DPE-PDCP) and diisopentyl ester of PDCP (DIPE-PDCP) belong to class I (negligible membrane retention and low permeation). Finally, Quantitative Structure – permeability and Structure – retention relationships models were created in order to find Quantitative relationships between physico-chemical properties of tested compounds and PAMPA membrane permeability/membrane retention parameters. Statistically the most reliable models were analysed and used for the design of new compounds for which favourable membrane permeability and retention can be expected.This is the peer-reviewed version of the following article: Tubić, B.; Dobričić, V.; Poljarević, J.; Savić, A.; Sabo, T.; Marković, B. Estimation of Passive Gastrointestinal Absorption and Membrane Retention Using PAMPA Test, Quantitative Structure-Permeability and Quantitative Structure-Retention Relationship Analyses of Ethylenediamine-N,N’-Di-2-(3-Cyclohexyl)Propanoic Acid and 1,3-Propanediamine-N,N’-Di-2-(3-Cyclohexyl)Propanoic Acid Derivatives. Journal of Pharmaceutical and Biomedical Analysis 2020, 184. [https://doi.org/10.1016/j.jpba.2020.113213
