A plain method of prediction of visibility of peptides in mass spectrometry with electrospray ionization

Abstract

A new method for screening of essential peptides for protein detection and quantification analysis in the direct positive electrospray mass spectrometry has been proposed. Our method is based on the prediction of the normalized abundance of the mass spectrometric peaks using a linear regression model. This method has the folowing limitations: (i) selected peptides should be taken so that at pH 2.5 the tested peptides must be presented mainly as the 2+ and 3+ ions; (ii) only peptides having C-terminal lysine or arginine residues are considered. The amino acid composition of the peptide, the peptide concentration, the ratio of the polar surface of peptide to common surface and ratio of the polar volume to common volume are used as independent variables in equation. Several combinations of variables were considered and the best linear regression model had a determination coefficient in leave-one-out validation procedure equal 0.54. This model confidently discriminates peptides with high response ability and peptides with low response ability, and therefore it allows to select only the most promising peptides. This screening method, a plain and fast, can be successfully applied to reduce the list of observed peptides.