Abstract

Cytochrome P450 2D6 (CYP2D6) is an enzyme that is involved in the metabolism of roughly 25% of all marketed drugs and therefore belongs to the most important enzymes in drug metabolism. CYP2D6 features a high degree of genetic polymorphism that can significantly affect the metabolic activity of an individual. In extreme cases, structural changes at the level of single amino acids can either increase its enzymatic activity abolishing the drug therapeutic effect or completely disable the enzyme and elevate drug plasma level potentially leading to adverse effects. In this study, starting from the crystal structure, we built a full-length membrane-anchored all-atom model of the wild-type CYP2D6 as well as five of its variants differing in the enzymatic activity. We validated our models with available experimental data and compared their structural properties with molecular dynamics simulations. The main focus of this study was to identify differences that could mechanistically explain the altered activity of the variants and improve our understanding of their functioning. We observed differences in the opening frequencies and minimal diameters of tunnels that connect the buried active site to the surrounding solvent environment. The variants CYP2D6*4 and CYP2D6*10 associated with missing or decreased activity showed less frequent opening of the tunnels compared to the wild-type. Both CYP2D6*10 and CYP2D6*17 showed a deprivation of an important ligand tunnel suggesting a feasible reason for their altered substrate specificity. Next, the altered fold at the N-terminal anchor region and the decreased active site volume caused by the amino acid mutations of the CYP2D6*4 variant offer an explanation for the absence of its metabolic activity. The mutations in CYP2D6*53 contributed to a significant enlargement of an important ligand tunnel and an extension of the active site cavity. This could explain the altered metabolic profile as well as the enhanced metabolic rates of this particular variant supporting its designation as a possible cause for the ultrarapid metabolizer phenotype. We believe these novel structural insights could advance the fields of personalized medicine and enzyme engineering. Furthermore, they could aid in guiding laboratory as well as computational experiments in the future.

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