MetIDfyR: An Open-Source R Package to Decipher Small-Molecule Drug Metabolism through High-Resolution Mass Spectrometry.
Vivian DelcourtAgnès BarnabéBenoit LoupPatrice GarciaFrançois AndréBenjamin ChabotStéphane TrévisiolYves MoulardMarie-Agnès PopotLudovic Bailly-ChouriberryPublished in: Analytical chemistry (2020)
With recent advances in analytical chemistry, liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS) has become an essential tool for metabolite discovery and detection. Even if most of the common drug transformations have already been extensively described, manual search of drug metabolites in LC-HRMS/MS datasets is still a common practice in toxicology laboratories, complicating metabolite discovery. Furthermore, the availability of free open-source software for metabolite discovery is still limited. In this article, we present MetIDfyR, an open-source and cross-platform R package for in silico drug phase I/II biotransformation prediction and mass-spectrometric data mining. MetIDfyR has proven its efficacy for advanced metabolite identification in semi-complex and complex mixtures in in vitro or in vivo drug studies and is freely available at github.com/agnesblch/MetIDfyR.
Keyphrases
- liquid chromatography
- high resolution mass spectrometry
- mass spectrometry
- tandem mass spectrometry
- ultra high performance liquid chromatography
- small molecule
- simultaneous determination
- gas chromatography
- high performance liquid chromatography
- high resolution
- solid phase extraction
- ms ms
- high throughput
- adverse drug
- primary care
- healthcare
- drug induced
- emergency department
- multidrug resistant
- machine learning
- protein protein
- molecular dynamics simulations
- big data
- sensitive detection
- deep learning