The wide diversity of proteins expressed in a cell or a tissue as a result of gene variants, RNA editing or PTMs results in several hundred thousand distinct functional proteins called proteoforms. The large-scale analysis of proteomes has been driven by bottom-up MS approaches. This allowed to identify and quantify large numbers of gene products and perform PTM profiling which yielded a significant number of biological discoveries. Trypsin is the gold standard enzyme for the production of peptides in bottom-up approaches. Several investigators argued recently that the near exclusive use of trypsin provided only a partial view of the proteome and hampered the discovery of new isoforms. The use of multiple proteases in a complementary fashion can increase sequence coverage providing more extensive PTM and sequence variant profiling. Here the various approaches to characterize proteoforms are discussed, including the use of alternative enzymes to trypsin in shotgun approaches to expand the observable sequence space by LC-MS/MS. The technical considerations associated with the use of alternative enzymes are discussed.

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. File list (2) download file view on ChemRxiv MetIDfyR_Manuscript.pdf (1.05 MiB) download file view on ChemRxiv MetIDfyR_smat.pdf (127.83 KiB)

Peptide and protein quantification based on isotope dilution and mass spectrometry analysis are widely employed for the measurement of biomarkers and in system biology applications. The accuracy and reliability of such quantitative assays depend on the quality of the stable-isotope labeled standards. Although the quantification using stable-isotope labeled peptides is precise, the accuracy of the results can be severely biased by the purity of the internal standards, their stability and formulation, and the determination of their concentration. Here we describe a rapid and cost-efficient method to recalibrate stable isotope labeled peptides in a single LC-MS analysis. The method is based on the equimolar release of a protein reference peptide (used as surrogate for the protein of interest) and a universal reporter peptide during the trypsinization of a concatenated polypeptide standard. The quality and accuracy of data generated with such concatenated polypeptide standards are highlighted by the quantification of two clinically important proteins in urine samples and compared with results obtained with conventional stable isotope labeled reference peptides. Furthermore, the application of the UCRP standards in complex samples is described.

<div>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.</div><div><br> </div>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.<br>

According to international sport institutions, the use of peroxisome proliferator activated receptor (PPAR)-δ agonists is forbidden at any time in athlete career due to their capabilities to increase physical and endurance performances. The (PPAR)-δ agonist GW501516 is prohibited for sale but is easily available on internet and can be used by cheaters. In the context of doping control, urine is the preferred matrix because of the non-invasive nature of sampling and providing broader exposure detection times to forbidden molecules but often not detected under its native form due to the organism's metabolism. Even if urinary metabolism of G501516 has been extensively studied in human subjects, knowledge on GW501516 metabolism in horses remains limited. To fight against doping practices in horses' races, GW501516 metabolism has to be studied in horse urine to identify and characterize the most relevant target metabolites to ensure an efficient doping control. In this article, in vitro and in vivo experiments have been conducted using horse S9 liver microsome fractions and horse oral administration route, respectively. These investigations determined that the detection of GW501516 must be performed in urine on its metabolites because the parent molecule was extremely metabolized. To maximize analytical method sensitivity, the extraction conditions have been optimized. In accordance with these results, a qualitative analytical method was validated to detect the abuse of GW501516 based on its most relevant metabolites in urine. This work enabled the Laboratoire des Courses Hippiques (LCH) to highlight two cases of illicit administration of this forbidden molecule in post-race samples.