MetCCS

MetCCS predicts collision cross-section (CCS) values for metabolites to support structural identification in ion mobility-mass spectrometry (IMS)-based metabolomics.

Key Features:

• CCS prediction: Predicts collision cross-section (CCS) values for metabolites relevant to ion mobility-mass spectrometry (IMS) analyses.
• Rapid prediction: Computes CCS values quickly using computational models and molecular descriptors.
• Molecular-descriptor-based modeling: Uses molecular descriptors integrated into a predictive model to derive CCS estimates.

Scientific Applications:

• Metabolite identification: Provides predicted CCS values to increase confidence and aid structural elucidation of metabolites, including distinguishing structurally similar compounds.
• Metabolomics studies: Supports interpretation of complex biological samples and investigation of metabolic pathways and their implications for health and disease.

Methodology:

Employs molecular descriptors integrated into a predictive model to estimate CCS values for metabolites and simulate their behavior under ion mobility conditions.