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Activity Relationship Model (activity + relationship_model)
Selected AbstractsKinetics for the gas-phase reactions of OH radicals with the hydrofluoroethers CH2FCF2OCHF2, CHF2CF2OCH2CF3, CF3CHFCF2OCH2CF3, and CF3CHFCF2OCH2CF2CHF2 at 268,308 KINTERNATIONAL JOURNAL OF CHEMICAL KINETICS, Issue 6 2003L. Chen Rate constants were determined for the reactions of OH radicals with the hydrofluoroethers (HFEs) CH2FCF2OCHF2(k1), CHF2CF2OCH2CF3 (k2), CF3CHFCF2OCH2CF3(k3), and CF3CHFCF2OCH2CF2CHF2(k4) by using a relative rate method. OH radicals were prepared by photolysis of ozone at UV wavelengths (>260 nm) in 100 Torr of a HFE,reference,H2O,O3,O2,He gas mixture in a 1-m3 temperature-controlled chamber. By using CH4, CH3CCl3, CHF2Cl, and CF3CF2CF2OCH3 as the reference compounds, reaction rate constants of OH radicals of k1 = (1.68) × 10,12 exp[(,1710 ± 140)/T], k2 = (1.36) × 10,12 exp[(,1470 ± 90)/T], k3 = (1.67) × 10,12 exp[(,1560 ± 140)/T], and k4 = (2.39) × 10,12 exp[(,1560 ± 110)/T] cm3 molecule,1 s,1 were obtained at 268,308 K. The errors reported are ± 2 SD, and represent precision only. We estimate that the potential systematic errors associated with uncertainties in the reference rate constants add a further 10% uncertainty to the values of k1,k4. The results are discussed in relation to the predictions of Atkinson's structure,activity relationship model. The dominant tropospheric loss process for the HFEs studied here is considered to be by the reaction with the OH radicals, with atmospheric lifetimes of 11.5, 5.9, 6.7, and 4.7 years calculated for CH2FCF2OCHF2, CHF2CF2OCH2CF3, CF3CHFCF2OCH2CF3, and CF3CHFCF2OCH2CF2CHF2, respectively, by scaling from the lifetime of CH3CCl3. © 2003 Wiley Periodicals, Inc. Int J Chem Kinet 35: 239,245, 2003 [source] Predicting P-glycoprotein substrates by a quantitative structure,activity relationship modelJOURNAL OF PHARMACEUTICAL SCIENCES, Issue 4 2004Vijay K. Gombar Abstract A quantitative structure,activity relationship (QSAR) model has been developed to predict whether a given compound is a P-glycoprotein (Pgp) substrate or not. The training set consisted of 95 compounds classified as substrates or non-substrates based on the results from in vitro monolayer efflux assays. The two-group linear discriminant model uses 27 statistically significant, information-rich structure quantifiers to compute the probability of a given structure to be a Pgp substrate. Analysis of the descriptors revealed that the ability to partition into membranes, molecular bulk, and the counts and electrotopological values of certain isolated and bonded hydrides are important structural attributes of substrates. The model fits the data with sensitivity of 100% and specificity of 90.6% in the jackknifed cross-validation test. A prediction accuracy of 86.2% was obtained on a test set of 58 compounds. Examination of the eight "mispredicted" compounds revealed two distinct categories. Five mispredictions were explained by experimental limitations of the efflux assay; these compounds had high permeability and/or were inhibitors of calcein-AM transport. Three mispredictions were due to limitations of the chemical space covered by the current model. The Pgp QSAR model provides an in silico screen to aid in compound selection and in vitro efflux assay prioritization. © 2004 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 93: 957,968, 2004 [source] Establishment of a quantitative structure,activity relationship model for evaluating and predicting the protective potentials of phenolic antioxidants on lipid peroxidationJOURNAL OF PHARMACEUTICAL SCIENCES, Issue 3 2003Zhiyong Cheng Abstract Antioxidant activities of phenolic compounds have been extensively explored, but the determinant factors underlying their mechanisms of action remain to be elucidated. In the present work, a series of phenolic compounds (hydroxylated connamic, benzoic acid, and polyphenol) were studied for their protection against lipid peroxidation (LPO) in two model experiments, pre-emulsified linoleic acid system and phosphate buffered linolenic acid system. The mechanisms of action as well as activity determinants were investigated by computational chemistry and multiple-linear regression analysis. Upon elucidating the LPO inhibition properties and the relationship between their structural natures and antioxidant activities (SAR), a fairly satisfactory multidescriptor quantitative SAR model was derived, which extended our understanding of LPO inhibition mechanisms and should be valuable in assessing or predicting the anti-LPO activity of phenolic antioxidants. © 2003 Wiley-Liss, Inc. and the American Pharmaceutical Association J Pharm Sci 92:475,484, 2003 [source] QSAR Models for the Dermal Penetration of Polycyclic Aromatic Hydrocarbons Based on Gene Expression ProgrammingMOLECULAR INFORMATICS, Issue 7 2008Tao Wang Abstract Gene Expression Programming (GEP) is a novel machine learning technique. The GEP is used to build nonlinear quantitative structure activity relationship model for the prediction of the Percent of Applied Dose Dermally Absorbed (PADA) over 24,h for polycyclic aromatic hydrocarbons. This model is based on descriptors which are calculated from the molecular structure. Three descriptors are selected from the descriptors pool by Heuristic Method (HM) to build a multivariable linear model. The GEP method produced a nonlinear quantitative model with a correlation coefficient and a mean error of 0.92 and 4.70 for the training set, 0.91 and 7.65 for the test set, respectively. It is shown that the GEP predicted results are in good agreement with experimental ones. [source] | ||||||||||