A Flexible, Automated Workflow for Collision Cross Section Calculations Utilizing MobCal-MPI

Abstract Accurate ion mobility predictions are critical for IMS-based structural annotation, yet generating collision cross sections (CCS) and high-field mobility data in silico remains a multi-step process requiring both computational expertise and an understanding of gas phase ion chemistry, limiting broader adoption within the ion mobility spectrometry (IMS) community. To address this limitation, we present MobCal-MPI-X, an automated workflow for fully automated calculation of low-field CCS and high-field mobility from minimal user input. Starting with a SMILES string, PubChem CID, or user-supplied structure, the pipeline autonomously samples relevant ionic forms to identify the lowest-energy charge-site, then samples the conformational space of that species to generate an ensemble of low-energy conformers, refines the ensemble with density functional theory, and computes field-dependent CCS, K0, and α-functions. Benchmarking against three independent datasets demonstrates that MobCal-MPI-X reproduces both low- and high-field mobility observed experimentally. For low-field CCS predictions, Boltzmann-averaged values across conformers yield a mean absolute error of 2.0% for positive and 3.3% for negative ions, consistent with the error associated with MobCal-MPI 2.0. For high-field mobility, the workflow yields (on average) good agreement with experimental α-functions in terms of absolute error and shape of the curves across APCI and (−)ESI datasets spanning environmental contaminants, pharmaceuticals, and forensic analytes. Together, MobCal-MPI-X substantially reduces the barrier to performing mobility calculations by automating conformer curation, quantum-chemical calculations, and the set up of trajectory method simulations. In doing so, we believe it makes routine use of CCS and mobility predictions more practical within IMS-based structural annotation workflows.