Johannes Gorges

@jogorges.bsky.social

PhD student | computational chemist @GrimmeLab @ @UniBonn (he/him)

QCxMS2 can now also simulate CID mass spectra. Just published in #JASMS : doi.org/10.1021/jasms.5c00234 Grateful to my coauthors Stefan Grimme @grimmelab.bsky.social & Marianne Engeser @unibonn.bsky.social - this is the last project of my PhD and completes my work on QCxMS2! #MassSpec #compchem

Evaluation of the QCxMS2 Method for the Calculation of Collision-Induced Dissociation Spectra via Automated Reaction Network Exploration

Collision-induced dissociation mass spectrometry (CID-MS) is an important tool in analytical chemistry for the structural elucidation of unknown compounds. The theoretical prediction of the CID spectra plays a critical role in supporting and accelerating this process. To this end, we adapt the recently developed QCxMS2 program originally designed for the calculation of electron ionization (EI) spectra to enable the computation of CID-MS. To account for the fragmentation conditions characteristic of CID within the automated reaction network discovery approach of QCxMS2 we adapted the internal energy distribution to match the experimental conditions. This distribution can be adjusted via a single parameter to approximate various activation settings, thereby eliminating the need for explicit simulations of the collisional process. We evaluate our approach on a test set of 13 organic molecules with diverse functional groups, compiled specifically for this study. All reference spectra were recorded consistently under the same measurement conditions, including both CID and higher-energy collisional dissociation (HCD) modes. Overall, QCxMS2 achieves a good average entropy similarity score (ESS) of 0.687 for the HCD spectra and 0.773 for the CID spectra. The direct comparison to experimental data demonstrates that the QCxMS2 approach, even without explicit modeling of collisions, is generally capable of computing both CID and HCD spectra with reasonable accuracy and robustness. This highlights its potential as a valuable tool for integration into structure elucidation workflows in analytical mass spectrometry.

doi.org