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Optimized Experimental Design for the Estimation of Enzyme Kinetic Parameters: An Experimental Evaluation
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmacy.
2012 (English)In: Drug Metabolism And Disposition, ISSN 0090-9556, E-ISSN 1521-009X, Vol. 40, no 12, 2273-2279 p.Article in journal (Refereed) Published
Abstract [en]

A set of compounds (n = 30), including traditional cytochrome P450 substrates and compounds from AstraZeneca's compound library, was used in an experimental evaluation of an optimal design approach (ODA) for the estimation of enzyme kinetic parameters (CLint, V-max, and K-m). A depletion method previously shown to provide reliable results, the multiple depletion curves method (MDCM), was used as reference. Experiments were conducted with human liver microsomes, and samples were analyzed using liquid chromatography-tandem mass spectrometry. CLint estimated with the ODA were in >90% of the cases within a 2-fold difference compared with MDCM estimates. In addition, good agreement was generally seen for V-max and K-m estimates between the two methods as >80% of the estimates were within or almost within a 2-fold difference. The variability in V-max and K-m estimates were generally higher than for CLint estimates. In addition, decreased substrate turnover considerably increased the variability in V-max and Km estimates, whereas only a modest increase was observed for CLint estimates. The experimental design of using multiple starting concentrations for the estimation of enzyme kinetics was shown to be appropriate even when there was a limitation to the number of samples. The method allowed for good estimates of CLint and also for V-max and K-m in many cases. Hence, this approach is a good alternative for the estimation of enzyme kinetic parameters, especially if enzyme saturation and an assessment of a potential risk for nonlinear metabolism are of interest.

Place, publisher, year, edition, pages
2012. Vol. 40, no 12, 2273-2279 p.
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:uu:diva-188399DOI: 10.1124/dmd.112.047373ISI: 000311106300007OAI: oai:DiVA.org:uu-188399DiVA: diva2:578807
Available from: 2012-12-19 Created: 2012-12-17 Last updated: 2017-12-06Bibliographically approved

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Sjögren, Erik

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