Identification of Selectivity Determinants in CYP Monooxygenases by Modelling and Systematic Analysis of Sequence and Structure

Alexander      Seifert; Jurgen      Pleiss

doi:10.2174/138920012798918444

Abstract

Cytochrome P450 monooxygenases (CYPs) form a large, ubiquitous enzyme family and are of great interest in red and white biotechnology. To investigate the effect of protein structure on selectivity, the binding of substrate molecules near to the active site was modelled by molecular dynamics simulations. From a comprehensive and systematic comparison of more than 6300 CYP sequences and 31 structures using the Cytochrome P450 Engineering Database (CYPED), residues were identified which are predicted to point close to the heme centre and thus restrict accessibility for substrates. As a result, sequence-structure-function relationships are described that can be used to predict selectivity-determining positions from CYP sequences and structures. Based on this analysis, a minimal library consisting of bacterial CYP102A1 (P450BM3) and 24 variants was constructed. All variants were functionally expressed in E. coli, and the library was screened with four terpene substrates. Only 3 variants showed no activity towards all 4 terpenes, while 11 variants demonstrated either a strong shift or improved regio- or stereoselectivity during oxidation of at least one substrate as compared to CYP102A1 wild type. The minimal library also contains variants that show interesting side products which are not generated by the wild type enzyme. By two additional rounds of molecular modelling, diversification, and screening, the selectivity of one of these variants for a new product was optimised with a minimal screening effort. We propose this as a generic approach for other CYP substrates.

Keywords: Cytochrome P450 monooxygenases, molecular dynamics, stereoselectivity, molecular modelling, screening, inert hydrocarbons, detoxification, drug metabolis, pharmacokinetic, single nucleotide polymorphisms (SNPs), CYPED, MD-simulations, protein engineering, minimal mutant library