The use of collision cross-section (CCS) values obtained in ion mobility − mass spectrometry (IM-MS) effectively increases identification confidence of metabolites, however, it is restricted by the limited number of available CCS values for metabolites. MetCCS Predictor is developed to predict CCS values for metabolites in IM-MS. Users can simply import 14 common molecular descriptors of one metabolite to calculate its CCS values within seconds. The software employs a machine-learning algorithm for prediction, and the general principle has been published on Analytical Chemistry (2016). We also provided database search and metabolite match function in this software to help users use it more conveniently.
The molecular descriptors for metabolites (except exact mass) were calculated by ChemAxon and ALOGPS using the molecular structure. Human Metabolome Database (HMBD) also provides values of molecular descriptors in the database. Users can search metabolites in HMDB and import the values of molecular descriptors into MetCCS Predictor.
More information and help documents please see here.
Z. Zhou, X. Shen, J. Tu, and Z.-J. Zhu*(Corresponding author), Large-Scale Prediction of Collision Cross-Section Values for Metabolites in Ion Mobility - Mass Spectrometry, Analytical Chemistry, 2016, 88, 11084-11091. [link]
Z. Zhou, X. Xiong, and Z.-J. Zhu*(Corresponding author), MetCCS Predictor: A Web Server for Predicting Collision Cross-Section Values of Metabolite in Metabolomics, Bioinformatics, 2017, 33, 2235-2237. [link]
Human Metabolome Database
McLean Group Collision Cross-Section Database
Clemmer Group Collision Cross-Section Database
Bush Group Collision Cross-Section Database