Application of a cocktail approach to screen cytochrome P450 BM3 libraries for metabolic activity and diversity

In the present study, the validity of using a cocktail screening method in combination with a chemometrical data mining approach to evaluate metabolic activity and diversity of drug-metabolizing bacterial Cytochrome P450 (CYP) BM3 mutants was investigated. In addition, the concept of utilizing an in-house-developed library of CYP BM3 mutants as a unique biocatalytic synthetic tool to support medicinal chemistry was evaluated. Metabolic efficiency of the mutant library towards a selection of CYP model substrates, being amitriptyline (AMI), buspirone (BUS), coumarine (COU), dextromethorphan (DEX), diclofenac (DIC) and norethisterone (NET), was investigated. First, metabolic activity of a selection of CYP BM3 mutants was screened against AMI and BUS. Subsequently, for a single CYP BM3 mutant, the effect of co-administration of multiple drugs on the metabolic activity and diversity towards AMI and BUS was investigated. Finally, a cocktail of AMI, BUS, COU, DEX, DIC and NET was screened against the whole in-house CYP BM3 library. Different validated quantitative and qualitative (U)HPLC-MS/MS-based analytical methods were applied to screen for substrate depletion and targeted product formation, followed by a more in-depth screen for metabolic diversity. A chemometrical approach was used to mine all data to search for unique metabolic properties of the mutants and allow classification of the mutants. The latter would open the possibility of obtaining a more in-depth mechanistic understanding of the metabolites. The presented method is the first MS-based method to screen CYP BM3 mutant libraries for diversity in combination with a chemometrical approach to interpret results and visualize differences between the tested mutants. [Figure: see text] ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00216-015-9241-x) contains supplementary material, which is available to authorized users.