AutoCCS

AutoCCS automates calculation of collision cross sections (CCS) from ion mobility-mass spectrometry (IMS-MS) data to support molecular characterization and identification.

Key Features:

• Automation: Eliminates manual, user-assisted processing by automating CCS determination from IMS-MS data.
• Supported IMS methods: Implements stepped-field methods for drift tube IMS (DTIMS), single-field DTIMS with two calibration options (a standard method and an enhanced method), linear calibration for Bruker timsTOF, and non-linear calibration methods for traveling wave-based IMS in Waters Synapt and Structures for Lossless Ion Manipulations.
• Calibration methods: Provides a range of calibration strategies tailored to different IMS techniques to generate precise CCS values.
• Analysis modes: Handles both targeted and untargeted analyses for diverse experimental designs.
• Accuracy and reproducibility: Produces accurate and reproducible CCS determinations across IMS-MS platforms, field methods, ionization modes, and collision gases.

Scientific Applications:

• Molecular identification: Incorporates CCS data into MS-based workflows to enhance specificity and confidence in distinguishing similar species within complex mixtures.
• Proteomics: Supports peptide and protein characterization by providing orthogonal CCS information to mass measurements.
• Metabolomics: Aids small-molecule identification and discrimination of isomers through CCS comparisons.
• Structural biology: Provides gas-phase CCS values that can be used to support structural interpretation of ions.

Methodology:

Applies calibration methods tailored to specific IMS techniques (stepped-field DTIMS, single-field DTIMS with a standard and an enhanced calibration option, linear calibration for Bruker timsTOF, and non-linear calibration for traveling wave IMS in Waters Synapt and Structures for Lossless Ion Manipulations), supports multiple ionization modes and collision gases, and computes CCS values from IMS-MS measurements; demo datasets are available at MassIVE (Dataset ID: MSV000085979).