Quantitative structure behavior relationship

More recently (2006) we performed and reported quantitative structure-activity relationship (QSAR) modeling of the same compounds based on their atomic linear indices, for finding fimctions that discriminate between the tyrosinase inhibitor compounds and inactive ones [50]. Discriminant models have been applied and globally good classifications of 93.51 and 92.46% were observed for nonstochastic and stochastic hnear indices best models, respectively, in the training set. The external prediction sets had accuracies of 91.67 and 89.44% [50]. In addition to this, these fitted models have also been employed in the screening of new cycloartane compounds isolated from herbal plants. Good behavior was observed between the theoretical and experimental results. These results provide a tool that can be used in the identification of new tyrosinase inhibitor compounds [50]. 

A httle number of works performing Bfx and Fx quantitative structure-activity relationship (QSAR) studies have been described. On the other hand, to gain insight into the biological behavior of Bfxs and Fxs some studies... 

Aleksic et al. [47] estimated the hydrophobicity of miconazole and other antimycotic drugs by a planar chromatographic method. The retention behavior of the drugs have been determined by TLC by using the binary mobile phases acetone-n-hexane, methanol toluene, and methyl ethyl ketone toluene containing different amounts of organic modifier. Hydrophobicity was established from the linear relationships between the solute RM values and the concentration of organic modifier. Calculated values of RMO and CO were considered for application in quantitative structure activity relationship studies of the antimycotics. 

Fornal et al. [75] determined selectivity differences for bases in RP-HPLC under high pH conditions. They used quantitative structure retention relationships (QSRR) to model retention behavior. They reported that the stability of the columns they used (Waters XTerra MS, Zorbax Extend, Thermo BetaBasic) was limited with... 

Vera, A., Montes, M., Usero, J.L., Casado, J. (1992) Quantitative structure-activity relationship study of the biophysicochemical behavior of nitrosamine. J. Pharm. Sci. 61, 791-796. 

Many attempts to correlate the analyte structure with its HPLC behavior have been made in the past [4-6], The Quantitative structure-retention relationships (QSRR) theory was introduced as a theoretical approach for the prediction of HPLC retention in combination with the Abraham and co-workers adaptation of the linear solvation energy relationship (LSER) theory to chromatographic retention [7,8],... 

Stein, T.M., Gordon, S.H. and Greene, R.V. (1999). Amino Acids as Plasticizers - II. Use of Quantitative Structure-Property Relationships to Predict the Behavior of Monoammonium-monocarboxylate Plasticizers in Starch-Glycerol Blends. Carbohydr.Polym., 39,7-16. 

Jiskra, J., Claessens, H.A., Cramers, C.A. and Kaliszan, A. (2002) Quantitative structure-retention relationships in comparative studies of behavior of stationary phases under high-performance liquid chromatography and capillary electrochromatography conditions. /. Chromat., 977, 193-206. 

Timerbaev, A.R., Semenova, O.P. and Petrukhin, O. M. (2002) Migration behavior of metal complexes in capillary zone electrophoresis. Interpretation in terms of quantitative structure-mobility relationships. J. Chromat., 943, 263-274. 

Quantitative Structure-Activity Relationships (QSARs) are the final result of the process that starts with a suitable description of molecular structures and ends with some inference, hypothesis, and prediction on the behavior of molecules in environmental, biological, and physico-chemical systems in analysis. 

As will be discussed below, recent work has enhanced the understanding of thermoset mechanical behavior and unambiguously identified some important correlations. However, it has not yet provided robust quantitative structure-property relationships for predicting the mechanical properties in the absence of any data for structurally related types of thermosets. 

Offshore oil production requires many chemicals for well drilling, for the treatment of the produced oil, for the treatment of gas, and for the stimulation and workover of the wells [100,101]. Altogether,25 classes of chemicals are used in offshore oil production [102]. The chemicals are undergoing increasingly detailed testing. As in other Quantitative Structure-Activity Relationships (QSAR), the octanol/water partition coefficient (Kq, ) is a crucial factor determining the environmental behavior and toxicity of the chemicals [103]. Toxicity... 

The two major approaches currently in use and under discussion [50,57,58] for the prediction of Kqc of neutral compounds are KOCWIN, which is part of the EpiSuite package [39], and different pp-LEER equations [48,50,58]. KOCWIN is a quantitative structure-activity relationship (QSARs) developed with molecular connectivity indices (MCI) [59]. pp-LEERs describe partitioning based on a few fundamental solute-bulk phase intermolecular interactions such as van-der-Waals interactions and H-bonding. The partitioning behavior of a given solute can thus be represented by a small set of descriptors (Abraham solvation parameters), which indicate its capacity for a set of defined intermolecular interactions. 

The conclusion of Schumacher and Hpiland was not accepted by Richard et al. (305a) for reasons not mentioned in their paper. Using a method of quantitative structure-activity relationship determination, the above authors tried to evaluate the contribution of hydroxyl substituents to the toxicity of orellanine. The results appeared to be in total contradiction to the experimental data [e.g., calculated LD50 5 g/kg versus an experimentally determined LD50 of -4.9-12.5 mg/kg (276)] and led the authors to the conclusion that the proposal of the exact structure of orellanine may be questioned. It must be mentioned, however, that neither paraquat nor diquat were taken into account in the calculations. Three years later, more substantial arguments were made by Richard et al. 305b) as the result of their studies of the electrochemical behavior of orellanine which was shown to be different from diquat and paraquat. 

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