Improving computational modeling coupled with ion mobility-mass spectrometry data for efficient drug metabolite structural determination

Ion mobility-mass spectrometry has lately become a widely popular tool for the structural identification of small molecules due to its high efficiency and a low amount requirement for samples. A combination of this technique along with a computational approach has proven to deliver a reliable identification of several compounds that were investigated by comparing experimental and calculated collisional cross sections of structures. Even though a corresponding experimental field has made some valuable developments over the last couple of years, its theoretical counterpart has seen a rather slow improvement. A recent work has introduced a computational protocol for collisional cross-section calculations, but thorough tests have shown that some effort has still to be done to improve its predictive power. The work developed here makes a contribution in that direction by considering possible ways of improving the agreement within different sets of theoretical results as well as between theoretical and experimental values. Special attention has been given to the efficiency of the algorithm along with its large-scale applicability. The importance of internal parameters of the conformational search in the protocol is carefully assessed and new reliable values are suggested.

Automated summary

Ion mobility-mass spectrometry, combined with a computational approach, has shown reliable identification of various compounds; while experimental advancements have been made, theoretical improvements have been slow; the work contributes to improving consistency between different theoretical results and between theoretical and experimental values.