Evaluation of relative MS response factors of drug metabolites for semi‐quantitative assessment of chemical liabilities in drug discovery

化学 代谢物 生物转化 药物发现 药品 药物代谢 色谱法 质谱法 初级代谢物 药理学 新陈代谢 生物化学 医学
作者
Joachim Blanz,Gareth Williams,Jérôme Dayer,Thierry Délémonté,Werner Gertsch,Philippe Ramstein,Reiner Aichholz,Markus Trunzer,David Pearson
出处
期刊:Journal of Mass Spectrometry [Wiley]
卷期号:52 (4): 210-217 被引量:8
标识
DOI:10.1002/jms.3918
摘要

Drug metabolism studies are performed in drug discovery to identify metabolic soft spots, detect potentially toxic or reactive metabolites and provide an early insight into potential species differences. The relative peak area approach is often used to semi-quantitatively estimate the abundance of metabolites. Differences in the liquid chromatography-mass spectrometry responses result in an underestimation or overestimation of the metabolite and misinterpretation of results. The relative MS response factors (RF) of 132 structurally diverse drug candidates and their 233 corresponding metabolites were evaluated using a capillary-liquid chromatography/high-resolution mass spectrometry system. All of the synthesized metabolites discussed here were previously identified as key biotransformation products in discovery investigations or predicted to be formed. The most commonly occurring biotransformation mechanisms such as oxygenation, dealkylation and amide cleavage are represented within this dataset. However, relatively few phase II metabolites were evaluated because of the limited availability of authentic standards. Approximately 85% of these metabolites had a relative RF in the range between 0.2 (fivefold under-prediction) and 2.0 (twofold over-prediction), and the median MS RF was 0.6. Exceptions to this included very small metabolites that were hardly detectable. Additional experiments performed to understand the impact of the MS platform, flow rate and concentration suggested that these parameters do not have a significant impact on the RF of the compounds tested. This indicates that the use of relative peak areas to semi-quantitatively estimate the abundance of metabolites is justified in the drug discovery setting in order to guide medicinal chemistry efforts. Copyright © 2017 John Wiley & Sons, Ltd.
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