Substituierte 2-(Thiazol-4-yl)-phenole als Liganden und potentielle Extraktionsmittel für Kupfer(II)

Substituted 2-(Thiazol-4-yl)-phenols as Ligands and Potential Extractants for Copper (II) Substituted 2-(thiazol-4-yl)-phenols are obtained by the HANTZSCH synthesis. Their solubility in toluene is higher than in n-octane depending on the position, the chain length, and the polarity of the substituents. From alcoholic solutions complexes of the type CuL₂ⁿ are precipitated. According to the substituents their structure is distorted octahedral (CuL₂², CuL₂³) or distorted tetrahedral (CuL₂⁸, CuL₂⁹). The new complexes are nearly insoluble in toluene and aliphatic hydrocarbons, but CuL₂⁸ and CuL₂⁹ are soluble in chloroform. Therefore copper(II) may be extracted by HL⁸ and HL⁹ using chloroform as a diluent.     

Models of steroid binding based on the minimum deviation of structurally assigned 13C NMR spectra analysis (MiDSASA)

This paper develops a quantitative k-nearest neighbors modeling technique. The technique is used to demonstrate that a compound's biological binding activity to a receptor can be calculated from the minimum of the square root of the sum of squared deviations (SSSD) of a structurally assigned chemical shift on a template between the unknown compound to be predicted and a set of known compounds with known activities. When building models of biological activity, nonlinear relationships are built into the input training data. If a model is developed by selecting only compounds with minimum structurally assigned chemical shift deviations from the unknown compound, some of the nonlinear relationships can be removed. The smaller the total chemical shift deviation between a compound with known activity and another compound with unknown activity, the more likely it will have similar biological, chemical, and physical properties. This means that a model can be produced without rigorous statistics or neural networks. This technique is similar to structure-activity relationship (SAR) modeling, but instead of relying on substructure fragments to produce a model, this new model is based on minimum chemical shift differences on those substructure fragments. We refer to this method as minimum deviation of structurally assigned spectra analysis (MiDSASA) modeling. Modeling by the minimum deviation concept can be applied to other chemoinformatic data analyses such as metabolite concentrations in metabolic pathways for metabolomics research. A MiDSASA template model for 30 steroids binding the corticosterone binding globulin based on the activity factors of the two nearest compounds had a correlation of 0.88. A MiDSASA template model for 50 steroids binding the aromatse enzyme based on the average activity of the four nearest compounds had a correlation of 0.71.     

Metallextraktion und Komplexbildung mit α-Aminoximen

Metal Extraction and Complex Formation by α-Amino Oximes Cyclic secondary α-amino oximes (RNHR′NOH) in toluene as a diluent extract copper(II) from weakly acid solutions. The distribution ratio D_Cu amounts to 80. The extraction process is connected with the elimination of two protons (formation of [Cu(RNHR′NOH)₂? H]NO₃). Apart from this 1,2-complex 1,1-complexes Cu(RNHR′NOH)X₂ (X ? Cl, Br) are obtained. A blue and a black isomer of Cu(RNHDodNOH)Cl₂ are described. According to x-ray structure analysis, the latter isomer is square-planar with the amino oxime in the E-configuration. Basing on the i.r. spectrum, for the blue isomer a monodentate coordination of the Z-isomer of RNHDodNOH is discussed. In the case of nickel(II) only the 1,2-chelates [Ni(RNHR′NOH)₂? H]Y (Y ? NO₃, ClO₄, I), in the case of palladium(II) only the 1,1-chelates Pd(RNHR′NOH)Cl₂ were isolated.     

Aus der analytischen Praxis

Ohne ZusammenfassungMitteilungen aus der Königl. Württembergischen landwirtschaftlichen Versuchsstation Hohenheim.     

Use of 13C NMR spectrometric data to produce a predictive model of estrogen receptor binding activity

We have developed a spectroscopic data-activity relationship (SDAR) model based on 13C NMR spectral data for 30 estrogenic chemicals whose relative binding affinities (RBA) are available for the alpha (ERalpha) and beta (ERbeta) estrogen receptors. The SDAR models segregated the 30 compounds into strong and medium binding affinities. The SDAR model gave a leave-one-out (LOO) cross-validation of 90%. Two compounds that were classified incorrectly in the SDAR model were in the transition zone between classifications. Real and predicted 13C NMR chemical shifts were used with test compounds to evaluate the predictive behavior of the SDAR model. The 13C NMR SDAR model using predicted 13C NMR data for the test compounds provides a rapid, reliable, and simple way to screen whether a compound binds to the estrogen receptors.     

Producing 13C NMR, infrared absorption, and electron ionization mass spectrometric data models of the monodechlorination of chlorobenzenes, chlorophenols, and chloroanilines

We have developed four spectroscopic data-activity relationship (SDAR) models of monodechlorination of 32 chlorinated benzene compounds in anaerobic estuarine sediment. The SDAR models were based on combinations of 13C nuclear magnetic resonance (NMR), infrared absorption (IR), and electron ionization mass spectrometric (EI MS) data. The SDAR models segregated the 32 compounds into 17 readily monodechlorinated compounds and 15 not readily monodechlorinated compounds. The SDAR model based on 13C NMR, IR, and EI MS data gave a leave-one-out cross-validation of 93.8%. The SDAR model based on a composite of 13C NMR and IR data gave a leave-one-out cross-validation of 90.6%. The SDAR model based on a composite of IR and EI MS data gave a leave-one-out cross-validation of 84.4%. The SDAR model based on a composite of 13C NMR and EI MS data gave a leave-one-out cross-validation of 84.4%. These reliable SDAR models provide a rapid and simple way to predict whether a chlorinated benzene compound will readily go through monodechlorination. The FDA has filed a patent application on methods of using any combination of spectral data (NMR, MS, UV-vis, IR, and fluorescence, phosphorescence) to model a chemical, physical, or biological endpoint.     

Surface activity and fluorite flotation with myristic acid derivatives containing oxygen and sulphur atoms

Surface tension isotherms and fluorite flotation were studied in systems containing myristic acid derivatives in which carbon atoms in the hydrocarbon skeleton were partly replaced by oxygen and/or sulphur atoms. The location of the oxygen and sulphur atoms affects significantly compound hydrophobicity, adsorption at the air/water interface and fluorite flotation. The most effective collectors were the compounds with one oxygen or sulphur atom close to the carboxylic group.     

Whole-molecule calculation of log p based on molar volume, hydrogen bonds, and simulated 13C NMR spectra

The prediction of Log P is usually accomplished using either substructure or whole-molecule approaches. However, these methods are complicated, and previous whole-molecule approaches have not been successful for the prediction of Log P in very complex molecules. The observed chemical shifts in nuclear magnetic resonance (NMR) spectroscopy are related to the electrostatics at the nucleus, which are influenced by solute-solvent interactions. The different solvation effects on a molecule by either water or methanol have a strong effect on the NMR chemical shift value. Therefore, the chemical shift values observed in an aqueous and organic solvent should correlate to Log P. This paper develops a rapid, objective model of Log P based on molar volume, hydrogen bonds, and differences in calculated 13C NMR chemical shifts for a diverse set of compounds. A partial least squares (PLS) model of Log P built on the sum of carbon chemical shift differences in water and methanol, molar volume, number of hydrogen bond donors and acceptors in 162 diverse compounds gave an r2 value of 0.88. The average r2 for 10 training models of Log P made from 90% of the data was 0.87+/-0.01. The average q2 for 10 leave-10%-out cross-validation test sets was 0.87+/-0.05.     

Influence of ligand structure and solvent effects on complexation of neutral guests by several crown ethers

The formation of complexes between crown ethers and acetonitrile, chloroform, and nitromethane were investigated in carbon tetrachloride at 25°C. A significant influence of the ring size on the selectivity of the host is evident. The host 18-crown-6 forms complexes for which the reaction enthalpy and entropy are quite high. Host molecules with benzene side groups form complexes of lower reaction enthalpy and entropy and therefore the complexes formed are less stable than that of the analogous crown ethers without aromatic groups. Solvent effects on the stability constant K, the reaction enthalpy H, and the reaction entropy S were studied for the complexation of malonitrile by 18-crown-6. The reaction enthalpy and entropy values change in accordance with the dielectric constant of the solvent used, but no overall effect on complex stability with change in solvent dielectric constant was observed.