Molecular dynamics simulations of the interaction of wild type and mutant human CYP2J2 with polyunsaturated fatty acids.

OBJECTIVES: The data presented here is part of a study that was aimed at characterizing the molecular mechanisms of polyunsaturated fatty acid metabolism by CYP2J2, the main cytochrome P450 enzyme active in the human cardiovasculature. This part comprises the molecular dynamics simulations of the binding of three eicosanoid substrates to wild type and mutant forms of the enzyme. These simulations were carried out with the aim of dissecting the importance of individual residues in the active site and the roles they might play in dictating the binding and catalytic specificity exhibited by CYP2J2. DATA DESCRIPTION: The data comprise: (a) a new homology model of CYP2J2, (b) a number of predicted low-energy complexes of CYP2J2 with arachidonic acid, docosahexaenoic acid and eicosapentaenoic acid, produced with molecular docking and (c) a series of molecular dynamics simulations of the wild type and four mutants interacting with arachidonic acid as well as simulations of the wild type interacting with the two other eicosanoid ligands. The simulations may be helpful in identifying the determinants of substrate specificity of this enzyme and in unraveling the role of individual mutations on its function. They may also help guide the generation of mutants with altered substrate preferences.

Computational modelling of the binding of arachidonic acid to the human monooxygenase CYP2J2.

An experimentally determined structure for human CYP2J2-a member of the cytochrome P450 family with significant and diverse roles across a number of tissues-does not yet exist. Our understanding of how CYP2J2 accommodates its cognate substrates and how it might be inhibited by other ligands thus relies on our ability to computationally predict such interactions using modelling techniques. In this study we present a computational investigation of the binding of arachidonic acid (AA) to CYP2J2 using homology modelling, induced fit docking (IFD) and molecular dynamics (MD) simulations. Our study reveals a catalytically competent binding mode for AA that is distinct from a recently published study that followed a different computational pipeline. Our proposed binding mode for AA is supported by crystal structures of complexes of related enzymes to inhibitors, and evolutionary conservation of a residue whose role appears essential for placing AA in the right site for catalysis. Graphical Abstract Arachidonic acid docked in the active site of CYP2J2 assumes a catalytically competent binding mode stabilised by hydrogen bonds to Arg117.