MetIDfyR, an Open-Source R Package to Decipher Small-Molecule Drugs Metabolism Through High Resolution Mass Spectrometry

27 May 2020, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

After administration to humans or animals, small-molecule drugs most frequently undergo several biochemical transformations by the endogenous enzymatic machinery, called phase I and phase II metabolism. These molecular processes allow organisms to eliminate xenobiotics through modification of their chemical properties and generate metabolites. With recent advances in analytical chemistry, LC-HRMS/MS has become an essential tool for metabolite discovery and detection. Even if most 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, disabling efficient 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 biotransformations prediction and mass-spectrometric data mining. MetIDfyR has proven efficacy for advanced metabolite identification in semi-complex and complex mixtures in in-vitro or in-vivo drug studies and is freely available at https://github.com/agnesblch/MetIDfyR.

Keywords

drug metabolism studies
Mass Spectrometric Analysis
Metabolite identification
HRMS data analysis

Supplementary materials

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Description
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Title
MetIDfyR smat
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Supplementary weblinks

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