Prediction of electrophoretic mobilities. 1. Monoamines

The mobility of an ion is of fundamental importance in capillary electrophoresis, The size, shape, and other physicochemical parameters of monoamines are determined using molecular modeling, These parameters are used to generate regression expressions to predict absolute (infinite dilution) mobilities, Molecular volume or mass is the strongest determinant of electrophoretic mobility, However, molecular volumes calculated via molecular modeling varied systematically depending on the software used, and so molecular mass is the favored descriptor, Neither the classical spherical (Huckel) nor ellipsoidal (Perrin) models were reasonable predictors of mobility, In accord with empirical expressions, such as the Wilke-Chang equation for diffusion, the absolute mobilities correlate with mass (or volume) to a much greater power than predicted by Stokes's law. Incorporation of the effects of hydration using the McGowan waters of hydration increments further improved the predictions, The best equation for predicting absolute mobilities of monoamines is mu(0) = [(5.55 +/- 0.73) x 10(-3)]/[W(0.579 +/- 0.026) + (0.171 +/- 0.054)H] where W is the molecular weight and H is the mean waters of hydration calculated using the McGowan increments, The uncertainties are the standard deviations of the parameters, This equation yielded an average prediction error of 4.1% for the data set used to generate the expression (literature absolute mobilities for 34 monoamines possessing no other functional groups), 7.2% for an independent data set from the literature (absolute mobilities for seven monoamines possessing other functional groups), and 3.3% for an experimentally determined data set (13 monoamines determined using capillary electrophoresis).