Prediction of gas-phase reduced ion mobility constants (K0).

A method of predicting reduced ion mobility values, K0, for use in ion mobility spectrometry is described. While the method is very similar to a previously reported method based on a neural network, the method described in this paper uses a purely statistical regression approach. Furthermore, it has been applied to a wider class of compounds, including chemical agents. Various molecular parameters were evaluated in the predictive model to determine the qualitative dynamics that have the greatest effect on K0. An R2 value of 80.1% was obtained when calculated K0 values were plotted against measured K0 values for 162 compounds for which experimental K0 values were available. However, when chloroacetophenone and 3-xylyl bromide (3-methylbenzyl bromide) were removed from the set due to their large residual values, the predictability increased to an R2 value of 87.4%. This compares well with the value of 88.7%, which was obtained in a regression step of a previous neural network study for a less diverse set of 168 compounds.