A new (and freely available) original research article by Barbara M. Zietek et al., now available ahead-of-print at SLAS Discovery Online, presents a fast, robust and accurate methodology for correlating compound identity to CYP1A2 potency of inhibitors in metabolic mixtures.
The methodology is centered around an at-line nanofractionation platform in which a metabolic mixture is chromatographically separated followed by parallel on-line mass spectrometric (MS) analysis and at-line nanofractionation on high-density microtiter well plates that are then directly exposed to a bioassay.
Correlation of reconstructed bioactivity chromatograms with MS data allows direct identification of compounds with inhibitory properties toward CYP1A2 enzymes, indicating CYP-involved drug-drug interactions. In a similar fashion, the methodology can be implemented in assaying metabolic mixtures for other CYPs relevant in drug discovery. Next to traditional Met-ID metabolic profiling, the approach presented in this new article provides direct profiles of the relative contribution of each metabolite to the assayed activity, in this case CYP1A2 inhibition.
Drug-drug interactions caused by inhibition of CYP450 enzymes (or CYPs) can lead to serious adverse reactions in patients. These inhibitory properties can be exhibited by parent compounds and by their metabolites. Together, the properties of one or more metabolites can outweigh the benefits of a drug candidate, thus leading to its failure in the drug development phase or removal from the pharmaceutical market after introduction.
In recent years, increases in drug (candidate) attrition is especially seen in the later stages of drug development. This process can be improved by implementing new screening methods that rapidly assess the biological/biochemical properties and correlate them directly to compound identities. This can rapidly deliver profiles of pharmacokinetic properties of a drug and its metabolites together with their biological properties and can be achieved by the methodology presented in this article.
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SLAS (Society for Laboratory Automation and Screening) is an international community of nearly 20,000 professionals and students dedicated to life sciences discovery and technology. The SLAS mission is to bring together researchers in academia, industry and government to advance life sciences discovery and technology via education, knowledge exchange and global community building.
SLAS DISCOVERY: 2016 Impact Factor 2.444. Editor-in-Chief Robert M. Campbell, Ph.D., Eli Lilly and Company, Indianapolis, IN (USA). SLAS Discovery (Advancing Life Sciences R&D) was previously published (1996-2016) as the Journal of Biomolecular Screening (JBS).
SLAS TECHNOLOGY: 2016 Impact Factor 2.850. Editor-in-Chief Edward Kai-Hua Chow, Ph.D., National University of Singapore (Singapore). SLAS Technology (Translating Life Sciences Innovation) was previously published (1996-2016) as the Journal of Laboratory Automation (JALA).
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