Prediction of Reduced Ion Mobility Constants of Organic Compounds from Molecular Structure

Abstract

Quantitative structure-property relationships (QSPRs) are used to develop mathematical models that accurately predict the reduced ion mobility constants (K(0)) for a set of 168 organic compounds directly from molecular structure. The K(0) values are taken from an unpublished database collected by G. A. Eiceman, Chemistry Department, New Mexico State University. The data were collected using a Graseby Ionics environmental vapour monitor (EVM) gas chromatography/ion mobility spectrometer. Standardized conditions with controlled temperature, pressure, and humidity were used, and 2,4-lutidine was used as an internal standard. K(0) values were measured for all monomer peaks. The best model was found with a feature selection routine which couples the genetic algorithm with multiple linear regression analysis. The set of six descriptors was also analyzed with a fully connected, feed-forward neural network. The model contains six molecular structure descriptors and has a root-mean-square error of about 0.04 K(0) unit. The descriptors in the model lend insight into some of the important molecular features that influence ion mobility. The model can be utilized for prediction of K(0) values of compounds for which there are no empirical K(0) data.