The directive of the protein: how does cytochrome P450 select the mechanism of dopamine formation?
ABSTRACT Dopamine can be generated from tyramine via arene hydroxylation catalyzed by a cytochrome P450 enzyme (CYP2D6). Our quantum mechanical/molecular mechanical (QM/MM) results reveal the decisive impact of the protein in selecting the 'best' reaction mechanism. Instead of the traditional Meisenheimer-complex mechanism, the study reveals a mechanism involving an initial hydrogen atom transfer from the phenolic hydroxyl group of the tyramine to the iron-oxo of the compound I (Cpd I), followed by a ring-π radical rebound that eventually leads to dopamine by keto-enol rearrangement. This mechanism is not viable in the gas phase since the O-H bond activation by Cpd I is endothermic and the process does not form a stable intermediate. By contrast, the in-protein reaction has a low barrier and is exothermic. It is shown that the local electric field of the protein environment serves as a template that stabilizes the intermediate of the H-abstraction step and thereby mediates the catalysis of dopamine formation at a lower energy cost. Furthermore, it is shown that external electric fields can either catalyze or inhibit the process depending on their directionality.
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ABSTRACT: The past decades have seen an explosive growth in the application of density functional theory (DFT) methods to molecular systems that are of interest in a variety of scientific fields. Owing to its balanced accuracy and efficiency, DFT plays particularly useful roles in the theoretical investigation of large molecules. Even for biological molecules such as proteins, DFT finds application in the form of, e.g., hybrid quantum mechanics and molecular mechanics (QM/MM), in which DFT may be used as a QM method to describe a higher prioritized region in the system, while a MM force field may be used to describe remaining atoms. Iron-containing molecules are particularly important targets of DFT calculations. From the viewpoint of chemistry, this is mainly because iron is abundant on earth, iron plays powerful (and often enigmatic) roles in enzyme catalysis, and iron thus has the great potential for biomimetic catalysis of chemically difficult transformations. In this paper, we present a brief overview of several recent applications of DFT to iron-containing non-heme synthetic complexes, heme-type cytochrome P450 enzymes, and non-heme iron enzymes, all of which are of particular interest in the field of bioinorganic chemistry. Emphasis will be placed on our own work.Frontiers in Chemistry 01/2014; 2:14.
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ABSTRACT: Transition metal complexes with terminal oxo and dioxygen ligands exist in metal oxidation reactions, and many are key intermediates in various catalytic and biological processes. The prototypical oxo-metal [(OC)5 CrO, (OC)4 FeO, and (OC)3 NiO] and dioxygen-metal carbonyls [(OC)5 CrOO, (OC)4 FeOO, and (OC)3 NiOO] are studied theoretically. All three oxo-metal carbonyls were found to have triplet ground states, with metal-oxo bond dissociation energies of 77 (CrO), 74 (FeO), and 51 (NiO) kcal/mol. Natural bond orbital and quantum theory of atoms in molecules analyses predict metal-oxo bond orders around 1.3. Their featured ν(MO, M = metal) vibrational frequencies all reflect very low IR intensities, suggesting Raman spectroscopy for experimental identification. The metal interactions with O2 are much weaker [dissociation energies 13 (CrOO), 21 (FeOO), and 4 (NiOO) kcal/mol] for the dioxygen-metal carbonyls. The classic parent compounds Cr(CO)6 , Fe(CO)5 , and Ni(CO)4 all exhibit thermodynamic instability in the presence of O2 , driven to displacement of CO to form CO2 . The latter reactions are exothermic by 47 [Cr(CO)6 ], 46 [Fe(CO)5 ], and 35 [Ni(CO)4 ] kcal/mol. However, the barrier heights for the three reactions are very large, 51 (Cr), 39 (Fe), and 40 (Ni) kcal/mol. Thus, the parent metal carbonyls should be kinetically stable in the presence of oxygen. © 2014 Wiley Periodicals, Inc.Journal of Computational Chemistry 03/2014; · 3.84 Impact Factor
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ABSTRACT: Cytochrome P450 enzymes (P450s) are important in drug metabolism and have been linked to adverse drug reactions. P450s display broad substrate reactivity, and prediction of metabolites is complex. QM/MM studies of P450 reactivity have provided insight into important details of the reaction mechanisms and have the potential to make predictions of metabolite formation. Here we present a comprehensive study of the oxidation of three widely used pharmaceutical compounds (S-ibuprofen, diclofenac, and S-warfarin) by one of the major drug-metabolizing P450 isoforms, CYP2C9. The reaction barriers to substrate oxidation by the iron-oxo species (Compound I) have been calculated at the B3LYP-D/CHARMM27 level for different possible metabolism sites for each drug, on multiple pathways. In the cases of ibuprofen and warfarin, the process with the lowest activation energy is consistent with the experimentally preferred metabolite. For diclofenac, the pathway leading to the experimentally observed metabolite is not the one with the lowest activation energy. This apparent inconsistency with experiment might be explained by the two very different binding modes involved in oxidation at the two competing positions. The carboxylate of diclofenac interacts strongly with the CYP2C9 Arg108 side chain in the transition state for formation of the observed metabolite—but not in that for the competing pathway. We compare reaction barriers calculated both in the presence and in the absence of the protein and observe a marked improvement in selectivity prediction ability upon inclusion of the protein for all of the substrates studied. The barriers calculated with the protein are generally higher than those calculated in the gas phase. This suggests that active-site residues surrounding the substrate play an important role in controlling selectivity in CYP2C9. The results show that inclusion of sampling (particularly) and dispersion effects is important in making accurate predictions of drug metabolism selectivity of P450s using QM/MM methods.Journal of the American Chemical Society 05/2013; 135(21):8001–8015. · 10.68 Impact Factor