MetIDfyR

MetIDfyR predicts and detects metabolites from high-resolution mass spectrometry (mzML) data to analyze small-molecule drug metabolism based on a compound's raw chemical formula.

Key Features:

• mzML support: Processes high-resolution mass spectrometry mzML files from LC-HRMS/MS datasets.
• In silico phase I/II prediction: Generates predicted phase I and phase II biotransformations from a drug's raw chemical formula.
• Metabolite detection: Automates identification and detection of metabolites in LC-HRMS/MS datasets.
• Mass-spectrometric data mining: Mines mass-spectrometric data to support advanced metabolite identification.
• R package implementation: Implements analytical functions and prediction routines as an R package.

Scientific Applications:

• Metabolite Discovery: Automates discovery of drug metabolites in LC-HRMS/MS datasets.
• Toxicology: Identifies metabolites relevant to toxicological assessment.
• Pharmacokinetics: Supports pharmacokinetic studies by characterizing small-molecule drug biotransformations.
• Data Mining: Enables mining of mass-spectrometric datasets for advanced metabolite identification.

Methodology:

Processes high-resolution mzML mass spectrometry data, performs in silico prediction of phase I/II biotransformations from the raw chemical formula, automates metabolite identification in LC-HRMS/MS datasets, and mines mass-spectrometric data.