Phenols, quantitative structure-activity relationship

Aptula, A.O., Netzeva, T.I., Valkova, I.V. et at (2002). Multivariate discrimination between modes of toxic action of phenols. Quantitative Structure-Activity Relationships 21,12-22. 

Nishioka and Fujita78) have also determined the Kd values fora- and (S-cyclodextrin complexes with p- and/or m-substituted phenyl acetates through kinetic investigations on the alkaline hydrolysis of the complexes. The Kd values obtained were analyzed in the same manner as those for cyclodextrin-phenol complexes to give the Kd(X) values (Table 5). The quantitative structure-activity relationships were formulated as Eqs. 30 to 32 ... 

Ethell BT, Ekins S, Wang J, Burchell B. Quantitative structure activity relationships for the glucuronidation of simple phenols by expressed human UGT1A6 and UGT1A9. Drug Metab Dispos 2002 30 734-8. 

Hodson, P.V., R. Parisella, B. Blunt, B. Gray, and K.L.E. Kaiser. 1991. Quantitative structure-activity relationships for chronic toxicity of phenol, p-chlorophcnol, 2,4-dichlorophenol, pentachlorophenol, p-nitro-phenol and 1,2,4-trichlorobenzene to early life stages of the rainbow trout (Oncorhynchus mykiss). Canad. Tech. Rep. Fish. Aquat. Sci. 1784. 56 pp. 

Partial least squares regression analysis (PLS) has been used to predict intensity of sweet odour in volatile phenols. This is a relatively new multivariate technique, which has been of particular use in the study of quantitative structure-activity relationships. In recent pharmacological and toxicological studies, PLS has been used to predict activity of molecular structures from a set of physico-chemical molecular descriptors. These techniques will aid understanding of natural flavours and the development of synthetic ones. 

Barratt, M.D. (1995) Quantitative structure-activity relationships for skin corrosivity of organic adds, bases and phenols. Toxicol. Lett., 75 (1—3), 169—176. 

Gruber, C. and Buh, V. (1989) Quantum mechanically calculated properties for the development of quantitative structure-activity relationships (QSARs). pfCa values of phenols and aromatic and aliphatic carboxylic acids. Chemosphere, 19, 1595-1609. 

Tratnyek, P.G. and Hoigne, Chlorine dioxide (OCIO) in Water. II. Quantitative structure-activity relationships for phenolic compounds, Water Res., 28(1), 57-66, 1994. 

Purdy, R., Quantitative structure-activity relationships for predicting toxicity of nitrobenzenes, phenols, anilines, and alkylamines to fathead minnows, in QSAR 88. Proceedings of the Third International Workshop on Quantitative Structure-Activity Relationships in Environmental Toxicology, Turner, J.E., England, M.W., Schultz, T.W., and Kwaak, N.J., Eds., National Technical Information Service, U.S. Department of Commerce, Springfield, VA, 1988, pp. 99-110. 

Properties for the Development of Quantitative Structure-Activity Relationships (QSARs). pKa Values of Phenols and Aromatic and Aliphatic Carboxylic Acids. 

Itokawa, H., Totsuka, N., Hakahara, K., Meazuru, M., Takeya, K., Konda, M., Inamatsu, M., Morita, H. (1989) A quantitative structure-activity relationship for antitumor activity of long-chain phenols from Ginkgo biloba L. Chem. Pharm. Bull. 36, 1619-1621. 

Cheng Z, Ren J, Li Y, et al. Establishment of a quantitative structure-activity relationship model for evaluating and predicting the protective potentials of phenolic antioxidants on lipid peroxidation. ] Pharm Sci 2003 92(3) 475-484. 

Grtlber, C. and Buss, V. (1989), Quantum-Mechanically Calculated Properties for the Development of Quantitative Structure-Activity Relationships (QSARs). pKa-Values of Phenols and Aromatic and Aliphatic Carboxylic Acids. Chemosphere, 19,1595-1609. 

Xu, L., Ball, J., Dixon, S.L. and Jurs, PC. (1994). Quantitative Structure-Activity Relationships for Toxicity of Phenols Using Regressions Analysis and Computational Networks. Environ. Toxicol.Chem., 13,841-851. 

Wang XD, Dong YY, Wang LS, Han SK. Acute toxicity of substituted phenols to Rana japonica tadpoles and mechanism-based quantitative structure-activity relationship (QSAR) study. Chemosphere 2001 44(3) 447-55. 

MLC has been applied for the determination of partition properties and the hydropho-bicity of monosubstituted phenols. The enthalpy and entropy of partition were estimated from the temperature dependence of the partition properties these values were interpreted in terms of molecular size and the ability of the solute to establish a hydrogen bond. The 7T, jt(H) and jt(S) constants were determined from the experimental partition properties and applied to quantitative structure-activity relationship (QSAR) analysis . 

Ivanciuc, O. (1998a) Artificial neural networks applications. Part 4. Quantitative structure-activity relationships for the estimation of the relative toxicity of phenols for Tetrahymena. Rev. Roum. Chim., 43, 255-260. 

Samata, A.K., Ray, S.K, Basak, S.C. and Bose, S.K. (1982) Molecular connectivity and antifungal activity. A quantitative structure-activity relationship study of substituted phenols against... 

Wang, X., Sun, C., Wang, Yu. and Wang, L.-S. (2002) Quantitative structure-activity relationships for the inhibition toxicity to root elongation of Cucumis sativus of selected phenols and interspedes correlation with Tetrahymena pyriformis. Chemosphere, 46, 153—161. 

H. Itokawa, N. Totsuka, K. Nakahara, M. Maezuru, K. Takeya, M. Kondo, M. Inamatsu and H. Morita, A Quantitative Structure-Activity Relationship for Antitumor Activity of Long-Chain Phenols from Ginkgo biloba L. , Chem. Pharm. Bull, 1989, 37, 1619 - 1621. 

T. Esaki, "Quantitative Drug Design Studies. VI Quantitative Structure-Activity Relationships of lonizable Substances Antibacterial Activities of Phenols", Chem. Pharm. Bull, 1987, 35, 3105 - 3111. 

Barratt, M. D. Quantitative structure-activity relationships (QSARs) for skin corrosivity of organic acids, bases and phenols principal components and neural network analysis of extended datasets. Toxicol, in Vitro 1996,10, 85-94. 

The aromatic amines phenothiazine, phenoxa-cine, and iminostUbene (formula [276]) proved to be about two orders of magnitude more effective than common phenolic antioxidants in their protective activity against oxidative nerve cell death (Moosmann et al. 2001). This remarkable efficacy could be directly correlated to calculated properties of the compound by means of a novel, quantitative structure-activity relationship model. 

Su, L.M., Y.H. Zhao, X. Yuan, C.F. Mu, N. Wang, and J.C. Yan. 2010. Evaluation of combined toxicity of phenols and lead to Photobacteriumphosphoreum and quantitative structure-activity relationships. Bull Environ. Contam. Toxicol. 84 311-314. 

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