MobCal-MPI
MobCal-MPI calculates collision cross sections (CCS) of ions and molecules using parallel computation to enable structural elucidation of gas-phase ions and characterization of complex mixtures.
Key Features:
- Parallel Computing: MobCal-MPI leverages parallelized computing to accelerate CCS calculations, achieving up to 64-fold speed improvements compared to traditional packages.
- Atom-Specific Parameters: It employs atom-specific parameters derived from the MMFF94 forcefield to tune ion-nitrogen van der Waals potentials for CCS computations.
- Calibration and Validation: The method was calibrated on 162 molecules with a root mean square error (RMSE) of 2.60% and externally validated on 50 compounds with an RMSE of 2.31%.
- Extensibility: Based on MMFF94, it can be extended to include additional elements including Li, Na, K, Si, Mg, Ca, Fe, Cu, and Zn.
Scientific Applications:
- Theoretical–Experimental CCS Comparison: Bridging theoretical modeling of chemical structures with experimental collision cross section determinations.
- Structural Studies with IMS–MS: Supporting structural elucidation of gas-phase ions using ion mobility spectrometry coupled to mass spectrometry.
- Complex Mixture Characterization: Facilitating characterization of complex molecular mixtures through rapid and precise CCS predictions.
- Omics and Pharmaceutical Research: Applied in proteomics, metabolomics, and pharmaceutical research for structural and compositional analyses.
Methodology:
Parallelized computation (MPI) with atom-specific parameters from the MMFF94 forcefield to model ion–nitrogen van der Waals interactions, calibrated on 162 molecules and externally validated on 50 compounds.
Topics
Details
- License:
- Unlicense
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Python
- Added:
- 5/25/2019
- Last Updated:
- 6/16/2020
Operations
Publications
Ieritano C, Crouse J, Campbell JL, Hopkins WS. A parallelized molecular collision cross section package with optimized accuracy and efficiency. The Analyst. 2019;144(5):1660-1670. doi:10.1039/c8an02150c. PMID:30649115.
DOI: 10.1039/c8an02150c
PMID: 30649115
Funding: - Natural Sciences and Engineering Research Council of Canada: Collaborative Research, Development Grant, Discovery Grant
- Ontario Centres of Excellence: VIP II Grant