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Regression Diagnostics in the pKa Estimation by the Nonlinear Regression of Multiwavelength Spectrophotometric Data
Autoři: Meloun Milan | Ferenčíková Zuzana | Vrána Aleš
Rok: 2011
Druh publikace: ostatní - článek ve sborníku
Název zdroje: Spectroscopy: Biomedical Applications
Název nakladatele: IOS Press
Místo vydání: Amsterdam
Strana od-do: 107-108
Tituly:
Jazyk Název Abstrakt Klíčová slova
eng Regression Diagnostics in the pKa Estimation by the Nonlinear Regression of Multiwavelength Spectrophotometric Data Recent development in the computational diagnostic tools for the pK estimation of druglike molecules carried out by the nonlinear regression of multiwavelength spectrophotometric pH-titration data is demonstrated. Most indices-based methods in the a factor analysis of spectra predict the correct number of components even in the presence of a minor one or in cases of overlapping equilibria when the signal-to-error ratio SER is higher than 10. The Wernimont-Kankare procedure in the INDICES program performs a reliable determination of the instrumental standard deviation of the spectrophotometer used s (A) and correctly predicts thenumber of light-absorbing components present. It can also solve an ill-defined problem with severe inst colinearity in the data set, with very small changes in spectra and overlapping equilibria. The mixed dissociation constants of an example, the drug silybine and methotrexate, at ionic strength I = 0.03 and a temperature of 25°C were determined. dissociation constants;SPECFIT;SQUAD;signal-to-error;methotrexate;Cattell scree plot