RESUMO
Introduction of ion mobility mass spectrometry (IMS/MS) into the proteomic workflow provides an orthogonal separation to the widely used LC-MS platforms. IMS also provides structural information that could facilitate peptide identification. However, the lack of tools capable of predictive power in a high-throughput fashion makes peptide global profiling quite challenging. To target this issue, a computational workflow was developed based on biophysical principles to predict the collision cross-section area (CCS) of peptides as measured from IMS/MS experiments. Hosted on a web server, it allows the user to input a primary sequence (query) and retrieve information on peptide structure, sequence, and corresponding CCS. The current version is designed to identify peptide sequences up to 23 residues in length, in its higher charge state, based on a match of the molecule m/z and CCS. The protocol was validated against a 128-sequences-dataset and CCS predicted within 2.8% average error.
