Metabolic Regio- and Stereoselectivity of Cytochrome P450 2D6 towards 3,4-Methylenedioxy-N-alkylamphetamines: in Silico Predictions and Experimental Validation

New insights into aflatoxin B1 mechanistic toxicology in cattle liver: an integrated approach using molecular docking and biological evaluation in CYP1A1 and CYP3A74 knockout BFH12 cell lines

Aflatoxin B1 (AFB1) is a pro-carcinogenic compound bioactivated in the liver by cytochromes P450 (CYPs). In mammals, CYP1A and CYP3A are responsible for AFB1 metabolism, with the formation of the genotoxic carcinogens AFB1-8,9-epoxide and AFM1, and the detoxified metabolite AFQ1. Due to climate change, AFB1 cereals contamination arose in Europe. Thus, cattle, as other farm animals fed with grains (pig, sheep and broiler), are more likely exposed to AFB1 via feed with consequent release of AFM1 in milk, posing a great concern to human health. However, knowledge about bovine CYPs involved in AFB1 metabolism is still scanty. Therefore, CYP1A1- and CYP3A74-mediated molecular mechanisms of AFB1 hepatotoxicity were here dissected. Molecular docking of AFB1 into CYP1A1 model suggested AFB1 8,9-endo- and 8,9-exo-epoxide, and AFM1 formation, while docking of AFB1 into CYP3A74 pointed to AFB1 8,9-exo-epoxide and AFQ1 synthesis. To biologically confirm these predictions, CYP1A1 and CYP3A74 knockout (KO) BFH12 cell lines were exposed to AFB1. LC-MS/MS investigations showed the abolished production of AFM1 in CYP1A1 KO cells and the strong increase of parent AFB1 in CYP3A74 KO cells; the latter result, coupled to a decreased cytotoxicity, suggested the major role of CYP3A74 in AFB1 8,9-exo-epoxide formation. Finally, RNA-sequencing analysis indirectly proved lower AFB1-induced cytotoxic effects in engineered cells versus naïve ones. Overall, this study broadens the knowledge on AFB1 metabolism and hepatotoxicity in cattle, and it provides the weight of evidence that CYP1A1 and CYP3A74 inhibition might be exploited to reduce AFM1 and AFBO synthesis, AFB1 toxicity, and AFM1 milk excretion.

"Commandeuring" Xenobiotic Metabolism: Advances in Understanding Xenobiotic Metabolism

The understanding of how exogenous chemicals (xenobiotics) are metabolized, distributed, and eliminated is critical to determine the impact of the chemical and its metabolites to the (human) organism. This is part of the research and educational discipline ADMET (absorption, distribution, metabolism, elimination, and toxicity). Here, we review the work of Jan Commandeur and colleagues who have not only made a significant impact in understanding of phase I and phase II metabolism of several important compounds but also contributed greatly to the development of experimental techniques for the study of xenobiotic metabolism. Jan Commandeur’s work has covered a broad area of research, such as the development of online screening methodologies, the use of a combination of enzyme mutagenesis and molecular modeling for structure–activity relationship (SAR) studies, and the development of novel probe substrates. This work is the bedrock of current activities and brings the field closer to personalized (cohort-based) pharmacology, toxicology, and hazard/risk assessment.

CYP2D6 Allelic Variants *34, *17-2, *17-3, and *53 and a Thr309Ala Mutant Display Altered Kinetics and NADPH Coupling in Metabolism of Bufuralol and Dextromethorphan and Altered Susceptibility to Inactivation by SCH 66712

Metabolic phenotype can be affected by multiple factors, including allelic variation and interactions with inhibitors. Human CYP2D6 is responsible for approximately 20% of cytochrome P450-mediated drug metabolism but consists of more than 100 known variants; several variants are commonly found in the population, whereas others are quite rare. Four CYP2D6 allelic variants-three with a series of mutations distal to the active site (*34, *17-2, *17-3) and one ultra-metabolizer with mutations near the active site (*53), along with reference *1 and an active site mutant of *1 (Thr309Ala)-were expressed, purified, and studied for interactions with the typical substrates dextromethorphan and bufuralol and the inactivator SCH 66712. We found that *34, *17-2, and *17-3 displayed reduced enzyme activity and NADPH coupling while producing the same metabolites as *1, suggesting a possible role for Arg296 in NADPH coupling. A higher-activity variant, *53, displayed similar NADPH coupling to *1 but was less susceptible to inactivation by SCH 66712. The Thr309Ala mutant showed similar activity to that of *1 but with greatly reduced NADPH coupling. Overall, these results suggest that kinetic and metabolic analysis of individual CYP2D6 variants is required to understand their possible contributions to variable drug response and the complexity of personalized medicine.

Characterization of a polycyclic aromatic ring-hydroxylation dioxygenase from Mycobacterium sp. NJS-P

Ring-hydroxylating dioxygenases (RHDs) play a critical role in the biodegradation of polycyclic aromatic hydrocarbons (PAHs). In this study, genes pdoAB encoding a dioxygenase capable of oxidizing various PAHs with up to five-ring benzo[a]pyrene were cloned from Mycobacterium sp. NJS-P. The α-subunit of the PdoAB showed 99% and 93% identity to that from Mycobacterium sp. S65 and Mycobacterium sp. py136, respectively. An Escherichia coli expression experiment revealed that the enzyme is able to oxidize anthracene, phenanthrene, pyrene and benzo[a]pyrene, but not to fluoranthene and benzo[a]anthracene. Furthermore, the results of in silico analysis showed that PdoAB has a large substrate-binding pocket satisfying for accommodation of HMW PAHs, and suggested that the binding energy of intermolecular interaction may predict the substrate conversion of RHDs towards HMW PAHs, especially those may have steric constraints on the substrate-binding pocket, such as benzo[a]pyrene and benzo[a]anthracene.

Computationally efficient and accurate enantioselectivity modeling by clusters of molecular dynamics simulations

Computational approaches could decrease the need for the laborious high-throughput experimental screening that is often required to improve enzymes by mutagenesis. Here, we report that using multiple short molecular dynamics (MD) simulations makes it possible to accurately model enantioselectivity for large numbers of enzyme-substrate combinations at low computational costs. We chose four different haloalkane dehalogenases as model systems because of the availability of a large set of experimental data on the enantioselective conversion of 45 different substrates. To model the enantioselectivity, we quantified the frequency of occurrence of catalytically productive conformations (near attack conformations) for pairs of enantiomers during MD simulations. We found that the angle of nucleophilic attack that leads to carbon-halogen bond cleavage was a critical variable that limited the occurrence of productive conformations; enantiomers for which this angle reached values close to 180° were preferentially converted. A cluster of 20-40 very short (10 ps) MD simulations allowed adequate conformational sampling and resulted in much better agreement to experimental enantioselectivities than single long MD simulations (22 ns), while the computational costs were 50-100 fold lower. With single long MD simulations, the dynamics of enzyme-substrate complexes remained confined to a conformational subspace that rarely changed significantly, whereas with multiple short MD simulations a larger diversity of conformations of enzyme-substrate complexes was observed.

Mapping histamine H4 receptor–ligand binding modes

Computational prediction of ligand binding modes in G protein-coupled receptors (GPCRs) remains a challenging task. Systematic consideration of different protein modelling templates, ligand binding poses, and ligand protonation states in extensive molecular dynamics (MD) simulation studies enabled the prediction of ligand-specific mutation effects in the histamine H₄ receptor, a key player in inflammation.

Jahn-Teller dynamics in a series of high-symmetry Co(II) chelates determine paramagnetic relaxation enhancements

NMR paramagnetic relaxation enhancements (PREs) of a series of structurally characterized, trigonal bis-trispyrazolylborate (Tp) chelates of high-spin Co(II), spanning 100-850 MHz in field, are reported. Prior knowledge of the metal-nucleus distances allows numerical extraction of position-dependent electron spin relaxation rates (τ(c)(-1)) from direct measurement of the individual PREs of the four symmetry distinct protons in Co(Tp)(2), using available closed-form expressions. The data for this electronically complex system where spin-orbit coupling defines the ground state electronic structure are analyzed in terms of the Solomon-Bloembergen-Morgan (SBM) relations, as well as available zero-field splitting limit theories. A simple angular correction is shown to be sufficient to reconcile the individual τ(c)(T) data for the four classes of protons. The data identify a previously unrecognized dynamic Jahn-Teller effect in these historically important complexes, with a barrier of ~230 cm(-1), pointing to a level of dynamics in trispyrazolylborate chemistry that has not been described before, and further show that it is the Jahn-Teller that is responsible for the PREs in fluid solution. A field-dependent component is also identified for the two protons nearest g(//), which is suggested to arise due to Zeeman mixing of excited state character into the ground level.

Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms

Metabolism of xenobiotics remains a central challenge for the discovery and development of drugs, cosmetics, nutritional supplements, and agrochemicals. Metabolic transformations are frequently related to the incidence of toxic effects that may result from the emergence of reactive species, the systemic accumulation of metabolites, or by induction of metabolic pathways. Experimental investigation of the metabolism of small organic molecules is particularly resource demanding; hence, computational methods are of considerable interest to complement experimental approaches. This review provides a broad overview of structure- and ligand-based computational methods for the prediction of xenobiotic metabolism. Current computational approaches to address xenobiotic metabolism are discussed from three major perspectives: (i) prediction of sites of metabolism (SOMs), (ii) elucidation of potential metabolites and their chemical structures, and (iii) prediction of direct and indirect effects of xenobiotics on metabolizing enzymes, where the focus is on the cytochrome P450 (CYP) superfamily of enzymes, the cardinal xenobiotics metabolizing enzymes. For each of these domains, a variety of approaches and their applications are systematically reviewed, including expert systems, data mining approaches, quantitative structure–activity relationships (QSARs), and machine learning-based methods, pharmacophore-based algorithms, shape-focused techniques, molecular interaction fields (MIFs), reactivity-focused techniques, protein–ligand docking, molecular dynamics (MD) simulations, and combinations of methods. Predictive metabolism is a developing area, and there is still enormous potential for improvement. However, it is clear that the combination of rapidly increasing amounts of available ligand- and structure-related experimental data (in particular, quantitative data) with novel and diverse simulation and modeling approaches is accelerating the development of effective tools for prediction of in vivo metabolism, which is reflected by the diverse and comprehensive data sources and methods for metabolism prediction reviewed here. This review attempts to survey the range and scope of computational methods applied to metabolism prediction and also to compare and contrast their applicability and performance.

Ligand-Based Site of Metabolism Prediction for Cytochrome P450 2D6

A ligand-based method based on the SMARTCyp approach that predicts the sites of cytochrome P450 2D6-mediated metabolism of druglike molecules has been developed. The method uses only two descriptors besides the reactivity from SMARTCyp: the distance to a protonated nitrogen atom and the distance to the end of the molecule. Hence, the site of metabolism is predicted directly from the 2D structure of a molecule, without requiring calculation of electronic properties or generation of 3D structures. Testing on an independent test set gives an area under the curve value of 0.94, and a site of metabolism is found among the top two ranked atoms for 91% of the compounds.

Enhancing the anti-lymphoma potential of 3,4-methylenedioxymethamphetamine ('ecstasy') through iterative chemical redesign: mechanisms and pathways to cell death

While 3,4-methylenedioxymethamphetamine (MDMA/'ecstasy') is cytostatic towards lymphoma cells in vitro, the concentrations required militate against its translation directly to a therapeutic in vivo. The possibility of 'redesigning the designer drug', separating desired anti-lymphoma activity from unwanted psychoactivity and neurotoxicity, was therefore mooted. From an initial analysis of MDMA analogues synthesized with a modified α-substituent, it was found that incorporating a phenyl group increased potency against sensitive, Bcl-2-deplete, Burkitt's lymphoma (BL) cells 10-fold relative to MDMA. From this lead, related analogs were synthesized with the 'best' compounds (containing 1- and 2-naphthyl and para-biphenyl substituents) some 100-fold more potent than MDMA versus the BL target. When assessed against derived lines from a diversity of B-cell tumors MDMA analogues were seen to impact the broad spectrum of malignancy. Expressing a BCL2 transgene in BL cells afforded only scant protection against the analogues and across the malignancies no significant correlation between constitutive Bcl-2 levels and sensitivity to compounds was observed. Bcl-2-deplete cells displayed hallmarks of apoptotic death in response to the analogues while BCL2 overexpressing equivalents died in a caspase-3-independent manner. Despite lymphoma cells expressing monoamine transporters, their pharmacological blockade failed to reverse the anti-lymphoma actions of the analogues studied. Neither did reactive oxygen species account for ensuing cell death. Enhanced cytotoxic performance did however track with predicted lipophilicity amongst the designed compounds. In conclusion, MDMA analogues have been discovered with enhanced cytotoxic efficacy against lymphoma subtypes amongst which high-level Bcl-2--often a barrier to drug performance for this indication--fails to protect.

Structural features of cytochromes P450 and ligands that affect drug metabolism as revealed by X-ray crystallography and NMR

Cytochromes P450 (P450s) play a major role in the clearance of drugs, toxins, and environmental pollutants. Additionally, metabolism by P450s can result in toxic or carcinogenic products. The metabolism of pharmaceuticals by P450s is a major concern during the design of new drug candidates. Determining the interactions between P450s and compounds of very diverse structures is complicated by the variability in P450-ligand interactions. Understanding the protein structural elements and the chemical attributes of ligands that dictate their orientation in the P450 active site will aid in the development of effective and safe therapeutic agents. The goal of this review is to describe P450-ligand interactions from two perspectives. The first is the various structural elements that microsomal P450s have at their disposal to assume the different conformations observed in X-ray crystal structures. The second is P450-ligand dynamics analyzed by NMR relaxation studies.

Brain chemistry: how does P450 catalyze the O-demethylation reaction of 5-methoxytryptamine to yield serotonin?

Density functional theory has been applied to elucidate the mechanism of the O-demethylation reaction that generates serotonin from 5-methoxytryptamine (5-MT); a process that is efficiently catalyzed by P450 CYP2D6. Two substrates, the neutral 5-MT and the protonated 5-MTH(+), were used to probe the reactivity of CYP2D6 compound I. Notably, the H-abstraction process is found to be slightly more facile for 5-MT. However, our DFT augmented by docking results show that the amino acid Glu216 in the active site holds the NH(3)(+) tail of the 5-MTH(+) substrate in an upright conformation and thereby controls the regioselectivity of the bond activation. Thus, the substrate protonation serves an important function in maximizing the yield of serotonin. This finding is in accord with experimental conclusions that 5-MTH(+) serves as the substrate for the CYP2D6 enzyme. The study further shows that the H-abstraction follows two-state reactivity (TSR), whereas the rebound path may involve more states due to the appearance of both Fe(IV) and Fe(III) electromers during the reaction of 5-MTH(+).

Substrate specificity and structural characteristics of the novel Rieske nonheme iron aromatic ring-hydroxylating oxygenases NidAB and NidA3B3 from Mycobacterium vanbaalenii PYR-1

The Rieske nonheme iron aromatic ring-hydroxylating oxygenases (RHOs) NidAB and NidA3B3 from Mycobacterium vanbaalenii PYR-1 have been implicated in the initial oxidation of high-molecular-weight (HMW) polycyclic aromatic hydrocarbons (PAHs), forming cis-dihydrodiols. To clarify how these two RHOs are functionally different with respect to the degradation of HMW PAHs, we investigated their substrate specificities to 13 representative aromatic substrates (toluene, m-xylene, phthalate, biphenyl, naphthalene, phenanthrene, anthracene, fluoranthene, pyrene, benz[a]anthracene, benzo[a]pyrene, carbazole, and dibenzothiophene) by enzyme reconstitution studies of Escherichia coli. Both Nid systems were identified to be compatible with type V electron transport chain (ETC) components, consisting of a [3Fe-4S]-type ferredoxin and a glutathione reductase (GR)-type reductase. Metabolite profiles indicated that the Nid systems oxidize a wide range of aromatic hydrocarbon compounds, producing various isomeric dihydrodiol and phenolic compounds. NidAB and NidA3B3 showed the highest conversion rates for pyrene and fluoranthene, respectively, with high product regiospecificity, whereas other aromatic substrates were converted at relatively low regiospecificity. Structural characteristics of the active sites of the Nid systems were investigated and compared to those of other RHOs. The NidAB and NidA3B3 systems showed the largest substrate-binding pockets in the active sites, which satisfies spatial requirements for accepting HMW PAHs. Spatially conserved aromatic amino acids, Phe-Phe-Phe, in the substrate-binding pockets of the Nid systems appeared to play an important role in keeping aromatic substrates within the reactive distance from the iron atom, which allows each oxygen to attack the neighboring carbons.

New insights into the structural characteristics and functional relevance of the human cytochrome P450 2D6 enzyme

To date, the crystal structures of at least 12 human CYPs (1A2, 2A6, 2A13, 2C8, 2C9, 2D6, 2E1, 2R1, 3A4, 7A1, 8A1, and 46A1) have been determined. CYP2D6 accounts for only a small percentage of all hepatic CYPs (< 2%), but it metabolizes approximately 25% of clinically used drugs with significant polymorphisms. CYP2D6 also metabolizes procarcinogens and neurotoxins, such as 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, 1,2,3,4-tetrahydroquinoline, and indolealkylamines. Moreover, the enzyme utilizes hydroxytryptamines and neurosteroids as endogenous substrates. Typical CYP2D6 substrates are usually lipophilic bases with an aromatic ring and a nitrogen atom, which can be protonated at physiological pH. Substrate binding is generally followed by oxidation (5-7 A) from the proposed nitrogen-Asp301 interaction. A number of homology models have been constructed to explore the structural features of CYP2D6, while antibody studies also provide useful structural information. Site-directed mutagenesis studies have demonstrated that Glu216, Asp301, Phe120, Phe481, and Phe483 play important roles in determining the binding of ligands to CYP2D6. The structure of human CYP2D6 has been recently determined and shows the characteristic CYP fold observed for other members of the CYP superfamily. The lengths and orientations of the individual secondary structural elements in the CYP2D6 structure are similar to those seen in other human CYP2 members, such as CYP2C9 and 2C8. The 2D6 structure has a well-defined active-site cavity located above the heme group with a volume of approximately 540 A(3), which is larger than equivalent cavities in CYP2A6 (260 A(3)), 1A2 (375 A(3)), and 2E1 (190 A(3)), but smaller than those in CYP3A4 (1385 A(3)) and 2C8 (1438 A(3)). Further studies are required to delineate the molecular mechanisms involved in CYP2D6 ligand interactions and their implications for drug development and clinical practice.

Computer-based substrate specifity prediction for cytochrome P450

Cytochrome P450 is important class of enzymes metabolizing numerous drugs. The composition and activity of these enzymes are determined the drug distribution in organism, its pharmacological and toxic effect. Thus the prediction of the behaviour of compounds in organism is essential for discovery and development of new drugs in the early stages of this process. The different isoforms of cytochrome P450 can oxidized wide range of chemical compounds and their substrate specifity do not correlate with their taxonomical classification. The main methods of cytochrome P450 substrate specifity prediction is reviewed. These methods divided based on primary informations that used: prediction based on amino acid sequences, ligand-based (pharmacophore and QSAR models) and structure-based (molecular docking, affinity prediction) methods. The common problem of cytochrome P450 substrate prediction and advantage and disadvantages of these methods are discussed.

EaMEAD: Activation energy prediction of cytochrome P450 mediated metabolism with effective atomic descriptors

In an effort to improve drug design and predictions for pharmacokinetics (PK), an empirical model was developed to predict the activation energies (Ea) of cytochrome P450 (CYP450) mediated metabolism. The model, EaMEAD (Activation energy of Metabolism reactions with Effective Atomic Descriptors), predicts the Ea of four major metabolic reactions of the CYP450 enzyme: aliphatic hydroxylation, N-dealkylation, O-dealkylation, and aromatic hydroxylation. To build and validate the empirical model, the E(a) values of the substrates with diverse chemical structures (394 metabolic sites for aliphatic hydroxylation, 27 metabolic sites for N-dealkylation, 9 metabolic sites for O-dealkylation, and 85 metabolic sites for aromatic hydroxylation) were calculated by AM1 molecular orbital (MO). Empirical equations, Quantitative Structure Activity Relationship (QSAR) models, were derived using effective atomic charge, effective atomic polarizability, and bond dipole moments of the substrates as descriptors. EaMEAD is shown to accurately predict Ea with a correlation coefficient (R) of 0.94 and root-mean-square error (RMSE, unit is kcal/mol) of 0.70 for aliphatic hydroxylation, N-dealkylation, and O-dealkylation, and R of 0.83 and RMSE of 0.80 for aromatic hydroxylation, respectively. Physical origin and the role of the effective atomic descriptors of the models are presented in detail. With this model, the Ea of the metabolism can be rapidly predicted without any experimental parameters or time-consuming QM calculation. Regioselectivity prediction with our model is presented in the case of CYP3A4 metabolism. The reliability and ease of use of this model will greatly facilitate early stage PK predictions and rational drug design. Moreover, the model can be applied to develop the Ea prediction model of various types of chemical reactions.

Metabolism ofN-substituted 7-methoxy-4-(aminomethyl) -coumarins by cytochrome P450 2D6 mutants and the indication of additional substrate interaction points

Previous studies have shown the critical roles residues F120 and F483 play in the oxidative metabolism of 7-methoxy-4-(aminomethyl)-coumarin (MAMC) by cytochrome P450 2D6 (CYP2D6). In the present study, a series of N-alkyl-7-methoxy-4-(aminomethyl)-coumarins (MAMC analogues) were used as substrates for the F120A and F483A mutants in order to probe the CYP2D6 active site. The F120A and F483A mutants of CYP2D6 displayed significant activity towards the MAMC analogues. Automated docking studies of the MAMC analogues in a CYP2D6 homology model suggested a distal hydrophobic active site binding cleft for the substrate N-alkyl chains, consisting of the residues L213 and V308.

Understanding CYP2D6 interactions

Owing to the polymorphic nature of CYP2D6, clinically significant issues can arise when drugs rely on that enzyme either for clearance, or metabolism to an active metabolite. Available screening methods to determine if the compound is likely to cause drug-drug interactions, or is likely to be a victim of inhibition of CYP2D6 by other compounds will be described. Computational models and examples will be given on strategies to design out the CYP2D6 liabilities for both heme-binding compounds and non-heme-binding compounds.

Computational prediction of drug binding and rationalisation of selectivity towards cytochromes P450

BACKGROUND

Early in-vitro consideration of metabolism and inhibition of cytochrome P450 has proven its merits over the last 15 years. Simultaneously, many computational drug-design methods have been developed, and are being applied to study the interactions between drug candidates and cytochrome P450 enzymes (P450s).

OBJECTIVE

This review discusses the recent advances of these methods and the implications that are specific for P450s.

METHODS

Mainly focusing on the prediction of binding affinity and ligand selectivity, we outline the applicability of the different methods to answer specific questions. Special emphasis is put on the different levels of theory that are being used in recent computational descriptions of ligand-P450 interactions.

CONCLUSION

P450s offer an additional challenge for computational methods, considering the ambiguities of the catalytic cycle and the significant flexibility of the active site. Different computational methods display different limitations, which is crucial to take into account when choosing the method appropriate to each application.

AmineDB: Large scale docking of amines with CYP2D6 and scoring for druglike properties—towards defining the scope of the chemical defense against foreign amines in humans

Organic amines are prevalent in nature and in drugs, especially the psychotherapeutic agents, and a major defense against potentially toxic amines is metabolism by CYP2D6. In order to understand better the constraints on the broad specificity of CYP2D6, 4207 amines were docked into the binding site of this enzyme. Docking poses were found predominantly with the positively charged amino groups closest to Asp301, with aromatic rings close to Phe120 and sometimes extending as far as Phe483. Organic amines that bind best to CYP2D6 tend to have larger molecular weights and logP values. Organic amines that score highly as being druglike, based on a Bayesian model constructed using a 5223-drug training set, are least likely to bind to CYP2D6. This correlation suggests that the set of known drugs, which have been largely designed or selected to avoid high affinity CYP binding, partially encodes the binding site preferences (or rather anti-preferences) of CYP2D6. Finally, in order to benchmark our docking and druglike scoring procedures, an analysis of psychotherapeutic agents is presented. All of these data, including the 4207 AM1-optimized ligand structures in proper ionization states, docking poses and scores, Druglike Scores and Lipinski properties, can be viewed from an online database, the AmineDB.

Computational chemistry approaches to drug discovery in signal transduction

The advent of therapeutic strategies aimed at targeting specific macromolecular components of deregulated signaling pathways associated with particular disease states has given rise to the idea that it should be possible to design ligands as drug candidates to these targets from first principles. This concept has been beckoning for a long time but structure-based ligand design only became feasible once it was possible to determine the 3-D structures of molecular targets at atomic resolution. However, structure-based design turned out to be difficult, chiefly because under physiological conditions both receptors and ligands are not static but they behave dynamically. While it is possible to design ligands with high steric and electronic complementarity to a receptor site, it is always uncertain how biologically relevant the assumed conformations of both ligand and receptor actually are. The fact that it remains beyond our current abilities to predict with sufficient accuracy the affinity between hypothetical ligand and receptor poses is in part connected with this problem and continues to confound the reliable prediction of drug-like ligands for therapeutic targets. Nevertheless, significant progress has been made and so-called virtual screening methods that use computational methods to dock candidate ligands into receptor sites and to score the resulting complexes are now used routinely as one of the components in drug discovery screening campaigns. Here an overview is given of the underlying principles, implementations, and applications of structure-guided computational design technologies. Although the emphasis is on receptor-based strategies, mention will also be made of some of the more established ligand-based approaches, such as similarity analyses and quantitative structure-activity relationship methods.

Future directions for drug transporter modelling

Since the late 1980s computational methods such as quantitative structure-activity relationship (QSAR) and pharmacophore approaches have become more widely applied to assess interactions between drug-like molecules and transporters, starting with P-glycoprotein (P-gp). Identifying molecules that interact with P-gp and other transporters is important for drug discovery, but it is normally ascertained using laborious in vitro and in vivo studies. Computational QSAR and pharmacophore models can be used to screen commercial databases of molecules rapidly and suggest those likely to bind as substrates or inhibitors for transporters. These predictions can then be readily verified in vitro, thus representing a more efficient route to screening. Recently, the application of this approach has seen the identification of new substrates and inhibitors for several transporters. The successful application of computational models and pharmacophore models in particular to predict transporter binding accurately represents a way to anticipate drug-drug interactions of novel molecules from molecular structure. These models may also see incorporation in future pharmacokinetic-pharmacodynamic models to improve predictions of in vivo drug effects in patients. The implications of early assessment of transporter activity, current advances in QSAR, and other computational methods for future development of these and systems-based approaches will be discussed.

Active-site structure, binding and redox activity of the heme-thiolate enzyme CYP2D6 immobilized on coated Ag electrodes: a surface-enhanced resonance Raman scattering study

Surface-enhance resonance Raman scattering spectra of the heme-thiolate enzyme cytochrome P450 2D6 (CYP2D6) adsorbed on Ag electrodes coated with 11-mercaptoundecanoic acid (MUA) were obtained in various experimental conditions. An analysis of these spectra, and a comparison between them and the RR spectra of CYP2D6 in solution, indicated that the enzyme's active site retained its nature of six-coordinated low-spin heme upon immobilization. Moreover, the spectral changes detected in the presence of dextromethorphan (a CYP2D6 substrate) and imidazole (an exogenous heme axial ligand) indicated that the immobilized enzyme also preserved its ability to reversibly bind a substrate and form a heme-imidazole complex. The reversibility of these processes could be easily verified by flowing alternately solutions of the various compounds and the buffer through a home-built spectroelectrochemical flow cell which contained a sample of immobilized protein, without the need to disassemble the cell between consecutive spectral data acquisitions. Despite immobilized CYP2D6 being effectively reduced by a sodium dithionite solution, electrochemical reduction via the Ag electrode was not able to completely reduce the enzyme, and led to its extensive inactivation. This behavior indicated that although the enzyme's ability to exchange electrons is not altered by immobilization per se, MUA-coated electrodes are not suited to perform direct electrochemistry of CYP2D6.

Cytochrome P450 bio-affinity detection coupled to gradient HPLC: on-line screening of affinities to cytochrome P4501A2 and 2D6

Here we describe novel on-line human CYP1A2 and CYP2D6 Enzyme Affinity Detection (EAD) systems coupled to gradient HPLC. The use of the systems lies in the detection of individual inhibitory ligands in mixtures (e.g. metabolic mixtures or herbal extracts) towards two relevant drug metabolizing human CYPs. The systems can rapidly detect individual compounds in mixtures with affinities to CYP1A2 or 2D6. The HPLC-EAD systems were first evaluated and validated in flow injection analysis mode. IC50 values of known ligands for both CYPs, tested both in flow injection and in HPLC mode, were well comparable with those measured in microplate reader formats. Both EAD systems were also connected to gradient HPLC and used to screen known compound mixtures for the presence of CYP1A2 and 2D6 inhibitors. Finally, the on-line CYP2D6 EAD system was used to screen for the inhibitory activities of stereoisomers of a mixture of five methylenedioxy-alkylamphetamines (XTC analogs) on a chiral analytical column.

The bacterial P450 BM3: a prototype for a biocatalyst with human P450 activities

The use of cytochrome P450 (P450 or CYP) enzymes as biocatalysts for the production of fine chemicals, including pharmaceuticals, has been of increasing interest, primarily owing to their catalytic diversity and broad substrate range. CYP102A1 (P450 BM3) from Bacillus megaterium integrates an entire monooxygenase system into one polypeptide and represents an appropriate prokaryotic model for industrial applications of mammalian P450 activities. CYP102A1 not only exhibits the highest catalytic activity ever detected in a P450 monooxygenase but also provides a potentially versatile biocatalyst for the production of human P450 metabolites. CYP102A1 can be further engineered to be a drug-metabolizing enzyme, making it a promising candidate to use as a biocatalyst in drug discovery and synthesis.

Classification of highly unbalanced CYP450 data of drugs using cost sensitive machine learning techniques

In this paper, we study the classifications of unbalanced data sets of drugs. As an example we chose a data set of 2D6 inhibitors of cytochrome P450. The human cytochrome P450 2D6 isoform plays a key role in the metabolism of many drugs in the preclinical drug discovery process. We have collected a data set from annotated public data and calculated physicochemical properties with chemoinformatics methods. On top of this data, we have built classifiers based on machine learning methods. Data sets with different class distributions lead to the effect that conventional machine learning methods are biased toward the larger class. To overcome this problem and to obtain sensitive but also accurate classifiers we combine machine learning and feature selection methods with techniques addressing the problem of unbalanced classification, such as oversampling and threshold moving. We have used our own implementation of a support vector machine algorithm as well as the maximum entropy method. Our feature selection is based on the unsupervised McCabe method. The classification results from our test set are compared structurally with compounds from the training set. We show that the applied algorithms enable the effective high throughput in silico classification of potential drug candidates.

Free energies of binding of R- and S-propranolol to wild-type and F483A mutant cytochrome P450 2D6 from molecular dynamics simulations

Detailed molecular dynamics (MD) simulations have been performed to reproduce and rationalize the experimental finding that the F483A mutant of CYP2D6 has lower affinity for R-propranolol than for S-propranolol. Wild-type (WT) CYP2D6 does not show this stereospecificity. Four different approaches to calculate the free energy differences have been investigated and were compared to the experimental binding data. From the differences between calculations based on forward and backward processes and the closure of thermodynamic cycles, it was clear that not all simulations converged sufficiently. The approach that calculates the free energies of exchanging R-propranolol with S-propranolol in the F483A mutant relative to the exchange free energy in WT CYP2D6 accurately reproduced the experimental binding data. Careful inspection of the end-points of the MD simulations involved in this approach, allowed for a molecular interpretation of the observed differences.

Methods for Predicting Human Drug Metabolism

Drug metabolism information is a necessary component of drug discovery and development. The key issues in drug metabolism include identifying: the enzyme(s) involved, the site(s) of metabolism, the resulting metabolite(s), and the rate of metabolism. Methods for predicting human drug metabolism from in vitro and computational methodologies and determining relationships between the structure and metabolic activity of molecules are also critically important for understanding potential drug interactions and toxicity. There are numerous experimental and computational approaches that have been developed in order to predict human metabolism which have their own limitations. It is apparent that few of the computational tools for metabolism prediction alone provide the major integrated functions needed to assist in drug discovery. Similarly the different in vitro methods for human drug metabolism themselves have implicit limitations. The utilization of these methods for pharmaceutical and other applications as well as their integration is discussed as it is likely that hybrid methods will provide the most success.

Protein-ligand docking: current status and future challenges

Understanding the ruling principles whereby protein receptors recognize, interact, and associate with molecular substrates and inhibitors is of paramount importance in drug discovery efforts. Protein-ligand docking aims to predict and rank the structure(s) arising from the association between a given ligand and a target protein of known 3D structure. Despite the breathtaking advances in the field over the last decades and the widespread application of docking methods, several downsides still exist. In particular, protein flexibility-a critical aspect for a thorough understanding of the principles that guide ligand binding in proteins-is a major hurdle in current protein-ligand docking efforts that needs to be more efficiently accounted for. In this review the key concepts of protein-ligand docking methods are outlined, with major emphasis being given to the general strengths and weaknesses that presently characterize this methodology. Despite the size of the field, the principal types of search algorithms and scoring functions are reviewed and the most popular docking tools are briefly depicted. Recent advances that aim to address some of the traditional limitations associated with molecular docking are also described. A selection of hand-picked examples is used to illustrate these features.

Heterotropic and homotropic cooperativity by a drug-metabolising mutant of cytochrome P450 BM3

Recently, we described a triple mutant of the bacterial cytochrome P450 BM3 as the first mutant with affinity for drug-like compounds. In this paper, we show that this mutant, but not wild-type BM3, is able to metabolise testosterone and several drug-like molecules such as amodiaquine, dextromethorphan, acetaminophen, and 3,4-methylenedioxymethylamphetamine that are known substrates of human P450s. Interestingly, the metabolism of 3,4-methylenedioxymethylamphetamine and acetaminophen could be stimulated up to 70-fold by the addition of caffeine, a known activator of rat P450 3A2. With testosterone metabolism, homotropic cooperativity was observed. This shows that heterotropic and homotropic cooperativity, known to occur in the P450 3A family, can also take place in BM3. BM3 therefore can be used as a model system to study atypical kinetics in mammalian P450s. Second, this study shows that BM3 can be engineered to a drug-metabolising enzyme, making it a promising candidate to use as biocatalyst in drug discovery and synthesis.

Catalytic site prediction and virtual screening of cytochrome P450 2D6 substrates by consideration of water and rescoring in automated docking

Automated docking strategies successfully applied to binding mode predictions of ligands in Cyt P450 crystal structures in an earlier study (de Graaf et al. J. Med. Chem. 2005, 7, 2308-2318) were used for the catalytic site prediction (CSP) of 65 substrates in a CYP2D6 homology model. The consideration of water molecules at predicted positions in the active site and the rescoring of pooled docking poses from four different docking programs (AutoDock, FlexX, GOLD-Goldscore, and GOLD-Chemscore) with the SCORE scoring function enabled the successful prediction of experimentally reported sites of catalysis of more than 80% of the substrates. Three docking algorithms (FlexX, GOLD-Goldscore, and GOLD-Chemscore) were subsequently used in combination with six scoring functions (Chemscore, DOCK, FlexX, GOLD, PMF, and SCORE) to assess the ability of docking-based virtual screening methods to prioritize known CYP2D6 substrates seeded into a drug-like chemical database (in the absence and presence of active-site water molecules). Finally, the optimal docking strategy in terms of virtual screening accuracy, GOLD-Chemscore with the consideration of active-site water (60% of known substrates recovered in the top 5% of the ranked drug-like database), was verified experimentally; it was successfully used to identify high-affinity CYP2D6 ligands among a larger proprietary database.

IN SILICO PREDICTION OF DRUG BINDING TO CYP2D6: IDENTIFICATION OF A NEW METABOLITE OF METOCLOPRAMIDE

Patients with cancer often take many different classes of drugs to treat the effects of their malignancy and the side effects of treatment, as well as their comorbidities. The potential for drug-drug interactions that may affect the efficacy of anticancer treatment is high, and a major source of such interactions is competition for the drug-metabolizing enzymes, cytochromes P450 (P450s). We have examined a series of 20 drugs commonly prescribed to cancer patients to look for potential interactions via CYP2D6. We used a homology model of CYP2D6, together with molecular docking techniques, to perform an in silico screen for binding to CYP2D6. Experimental IC50 values were determined for these compounds and compared with the model predictions to reveal a correlation with a regression coefficient of r2= 0.61. Importantly, the docked conformation of the commonly prescribed antiemetic metoclopramide predicted a new site of metabolism that was further investigated through in vitro analysis with recombinant CYP2D6. An aromatic N-hydroxy metabolite of metoclopramide, consistent with predictions from our modeling studies, was identified by high-performance liquid chromatography/mass spectrometry. This metabolite was found to represent a major product of metabolism in human liver microsomes, and CYP2D6 was identified as the main P450 isoform responsible for catalyzing its formation. In view of the prevalence of interindividual variation in the CYP2D6 genotype and phenotype, we suggest that those experiencing adverse reactions with metoclopramide, e.g., extrapyramidal syndrome, are likely to have a particular CYP2D6 genotype/phenotype. This warrants further investigation.

Binding of bufuralol, dextromethorphan, and 3,4-methylenedioxymethylamphetamine to wild-type and F120A mutant cytochrome P450 2D6 studied by resonance Raman spectroscopy

Cytochrome P450 2D6 (CYP2D6) is one of the most important drug-metabolizing enzymes in humans. Resonance Raman data, reported for the first time for CYP2D6, show that the CYP2D6 heme is found to be in a six-coordinated low-spin state in the absence of substrates, and it is perturbed to different extents by bufuralol, dextromethorphan, and 3,4-methylenedioxymethylamphetamine (MDMA). Dextromethorphan and MDMA induce in CYP2D6 a significant amount of five-coordinated high-spin heme species and reduce the polarity of its heme-pocket, whereas bufuralol does not. Spectra of the F120A mutant CYP2D6 suggest that Phe120 is involved in substrate-binding of dextromethorphan and MDMA, being responsible for the spectral differences observed between these two compounds and bufuralol. These differences could be explained postulating a different substrate mobility for each compound in the CYP2D6 active site, consistently with the role previously suggested for Phe120 in binding dextromethorphan and MDMA.

Topological role of cytochrome P450 2D6 active site residues

Recent reports have identified Phe120, Asp301, Thr309, and Glu216 as important residues in cytochrome P450 2D6 (CYP2D6) substrate binding and catalysis. Complementary homology models have located these amino acids within the binding pocket of CYP2D6 and in the present study we have used aryldiazenes to test these models and gain further insight in the role these amino acids have in maintaining the integrity of the active site cavity. When Phe120 was replaced to alanine, there was a significant increase in probe migration to pyrrole nitrogens C and D, in agreement with homology models which have located the phenyl side-chain of Phe120 above these two pyrrole rings. No changes in topology were observed with the D301Q mutant, supporting claims that in this mutant the electrostatic interactions with the B/C-loop are largely maintained and the loop retains its native orientation. The T309V mutation resulted in significant topological alteration suggesting that, in addition to its potential role in dioxygen activation, Thr309 plays an important structural role within the active site crevice. Replacement of Ile106 with Glu, engineered to cause electrostatic repulsion with Glu216, had a profound topological effect in the higher region within the active site cavity and impaired the catalytic activity towards CYP2D6 probe substrates.

Binding of 7-methoxy-4-(aminomethyl)-coumarin to wild-type and W128F mutant cytochrome P450 2D6 studied by time-resolved fluorescence spectroscopy

Enzyme structure and dynamics may play a main role in substrate binding and the subsequent steps in the CYP (cytochrome P450) catalytic cycle. In the present study, changes in the structure of human CYP2D6 upon binding of the substrate are studied using steady-state and time-resolved fluorescence methods, focusing not only on the emission of the tryptophan residues, but also on emission of the substrate. As a substrate, MAMC [7-methoxy-4-(aminomethyl)-coumarin] was selected, a compound exhibiting native fluorescence. As well as the wild-type, the W128F (Trp128-->Phe) mutant of CYP2D6 was studied. After binding, a variety of energy transfer possibilities exist, and molecular dynamics simulations were performed to calculate distances and relative orientations of donors and acceptors. Energy transfer from Trp128 to haem appeared to be important; its emission was related to the shortest of the three average tryptophan fluorescence lifetimes observed for CYP2D6. MAMC to haem energy transfer was very efficient as well: when bound in the active site, the emission of MAMC was fully quenched. Steady-state anisotropy revealed that besides the MAMC in the active site, another 2.4% of MAMC was bound outside of the active site to wild-type CYP2D6. The tryptophan residues in CYP2D6 appeared to be less accessible for the external quenchers iodide and acrylamide in presence of MAMC, indicating a tightening of the enzyme structure upon substrate binding. However, the changes in the overall enzyme structure were not very large, since the emission characteristics of the enzyme were not very different in the presence of MAMC.

Role of the conserved threonine 309 in mechanism of oxidation by cytochrome P450 2D6

Based on sequence alignments and homology modeling, threonine 309 in cytochrome P450 2D6 (CYP2D6) is proposed to be the conserved I-helix threonine, which is supposed to be involved in dioxygen activation by CYPs. The T309V mutant of CYP2D6 displayed a strong shift from O-dealkylation to N-dealkylation reactions in oxidation of dextromethorphan and 3,4-methylenedioxymethylamphetamine. This may be explained by an elevated ratio of hydroperoxo-iron to oxenoid-iron of the oxygenating species. In consistence, using cumene hydroperoxide, which directly forms the oxenoid-iron, the T309V mutant again selectively catalyzed the O-dealkylation reactions. The changed ratio of oxygenating species can also explain the decreased activity and changed regioselectivity that were observed in 7-methoxy-4-(aminomethyl)-coumarin and bufuralol oxidation, respectively, by the T309V mutant. Interestingly, the T309V mutant always showed a significantly increased, up to 75-fold, higher activity compared to that of the wild-type when using cumene hydroperoxide. These results indicate that T309 in CYP2D6 is involved in maintaining the balance of multiple oxygenating species and thus influences substrate and regioselectivity.