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Prediction of epoxide formation in drug metabolism is a difficult but important task, as epoxide formation is linked to drug toxicity. A comparison of the energy barriers for cytochrome P450 mediated epoxidation of alkenes to the barriers for the hydroxylation of an aliphatic carbon atom next to a double bond has been performed using B3LYP and B3LYP-D3. Relevant experimental data on oxidation selectivity has also been assessed. The results show that density functional theory, when using B3LYP-D3, does well in reproducing the experimental trends. Considering that the comparison involves chemical steps with quite different features this is remarkable. We also find that B3LYP consistently underestimates the hydrogen abstraction barriers relative to the epoxidation barriers, and that including a dispersion correction reduces this problem.

Three different types of atom accessibility descriptors are investigated in relation to site of metabolism predictions. To enable the integration of local accessibility we have constructed 2DSASA, a method for the calculation of the atomic solvent accessible surface area that is independent of 3D coordinates. The method was implemented in the SMARTCyp site of metabolism prediction models and improved the results by up to 4 percentage points for nine cytochrome P450 isoforms. The final models are made available at http://www.farma.ku.dk/smartcyp.

Xenobiotic metabolism is an active research topic but the limited amount of openly available high-quality biotransformation data constrains predictive modeling. Current database often default to commonly available information: which enzyme metabolizes a compound, but neither experimental conditions nor the atoms that undergo metabolization are captured. We present XMetDB, an open access database for drugs and other xenobiotics and their respective metabolites. The database contains chemical structures of xenobiotic biotransformations with substrate atoms annotated as reaction centra, the resulting product formed, and the catalyzing enzyme, type of experiment, and literature references. Associated with the database is a web interface for the submission and retrieval of experimental metabolite data for drugs and other xenobiotics in various formats, and a web API for programmatic access is also available. The database is open for data deposition, and a curation scheme is in place for quality control. An extensive guide on how to enter experimental data into is available from the XMetDB wiki. XMetDB formalizes how biotransformation data should be reported, and the openly available systematically labeled data is a big step forward towards better models for predictive metabolism. Electronic supplementary material The online version of this article (doi:10.1186/s13321-016-0161-3) contains supplementary material, which is available to authorized users.

The mechanism of cytochrome P450(CYP)-catalyzed hydroxylation of primary amines is currently unclear, and is relevant to drug metabolism. Previous small model calculations have suggested two possible mechanisms: direct N-oxidation and H-abstraction/rebound. We have modeled the N-hydroxylation of (R)-mexiletine in CYP1A2 with hybrid quantum mechanics/molecular mechanics (QM/MM) methods, providing a more detailed and realistic model. Multiple reaction barriers have been calculated at the QM(B3LYP- D)/MM(CHARMM27) level for the direct N-oxidation and H-abstraction/rebound mechanisms. Our calculated barriers indicate that the direct N-oxidation mechanism is preferred and proceeds via the doublet spin state of Compound I. Molecular dynam- ics simulations indicate that the presence of an ordered water molecule in the active site assists in the binding of mexiletine in the active site, but is not a prerequisite for reaction via either mechanism. Several active site residues play a role in the binding of mexiletine in the active site, including Thr124 and Phe226. This work reveals key details in the N-hydroxylation of mexiletine and further demonstrates that mechanistic studies using QM/MM methods are useful for understanding drug metabolism. ispartof: Chemical Research in Toxicology vol:29 issue:6 pages:963-971 ispartof: location:United States status: published

The toxicity of phosphorodithioate pesticides is due to the formation of the active oxane product through desulfurization by cytochrome P450 enzymes, both in humans and insects. During this desulfurization, inhibition of cytochrome P450 and a loss of heme has been observed. Here, we study the mechanism of desulfurization and inhibition with density functional theory, using the B3LYP functional with and without dispersion correction. The results show that a reaction mechanism initiated by sulfur oxidation is most likely, with a reaction barrier of 47 kJ/mol. The sulfur oxidation is followed by a ring-closing mechanism with a barrier of 28 kJ/mol relative to the sulfur-oxidized intermediate. The enzymatic contribution to the ring-closing is very small. It is also shown that the apparent loss of heme might be due to the formation of a previously unknown inhibition complex, which changes the aromatic conjugation of the porphyrin ring. We also show that including dispersion correction has significant effects on a ring closure transition state (∼30 kJ/mol), whereas effects on the other steps in the reaction are relatively small (4-15 kJ/mol).

SMARTCyp is an in silico method that predicts the sites of cytochrome P450-mediated metabolism of druglike molecules. The method is foremost a reactivity model, and as such, it shows a preference for predicting sites that are metabolized by the cytochrome P450 3A4 isoform. SMARTCyp predicts the site of metabolism directly from the 2D structure of a molecule, without requiring calculation of electronic properties or generation of 3D structures. This is a major advantage, because it makes SMARTCyp very fast. Other advantages are that experimental data are not a prerequisite to create the model, and it can easily be integrated with other methods to create models for other cytochrome P450 isoforms. Benchmarking tests on a database of 394 3A4 substrates show that SMARTCyp successfully identifies at least one metabolic site in the top two ranked positions 76% of the time. SMARTCyp is available for download at http://www.farma.ku.dk/p450.

We have developed a method to dock a transition-state structure into the active site of an enzyme. Such an approach is more discriminative than standard docking when looking for substrates of an enzyme, because a transition state has more sterical restrictions than a nonreactive state. We use an accurate and tailored force field for the transition-state for the hydroxylation reaction in cytochrome P450, obtained with the Q2MM method. We apply this method to the docking of two drugs, progesterone and flunitrazepam, to the active sites of two human cytochromes P450, 2C9 and 3A4. We obtain a qualitative agreement compared to experiments, both for hydrogen atoms bound to the same carbon atom (for which the force-field energies are directly comparable) and for general sites on the drug molecules, if the method is combined with an estimate of the intrinsic reactivity of the various sites. However, the method does not rank all the sites correctly. It is not significantly improved if the proteins are allowed to relax locally or if it is combined with the MM/PBSA approach, which fully accounts for the protein flexibility and explicitly treats solvation and entropy effects. On the other hand our method performs. better than standard docking with the GOLD software or predictions of metabolic sites with the MetaSite software.

We have developed force-field parameters for the hydrogen-abstraction transition state of aliphatic hydroxylation by cytochrome P450 using the Q2MM approach. The parametrization is based on quantum chemical (B3LYP) transition-state structures and Hessian matrices for 24 diverse substrate models (14 in the training set and 10 in the test set). The force field is intended to be applicable to any druglike molecule by the use of the general Amber force field (GAFF) for the substrates. The parameters reproduce the geometries within 0.1 angstrom and 1.2 degrees for bond lengths and angles, respectively, with no significant differences between the training and test sets. The Hessian matrix is also well reproduced with a correlation coefficient of 0.99. The parametrization is performed by the ideal iterative approach of Norrby and Liljefors, which we have implemented for the Amber software.

We have studied the dynamics of water molecules in six crystal structures of four human cytochromes P450, 2A6, 2C8, 2C9, and 3A4, with molecular dynamics simulations. In the crystal structures, only a few water molecules are seen and the reported sizes of the active-site cavity vary a lot. In the simulations, the cavities are completely filled with water molecules, although with similar to 20% lower density than in bulk water. The 2A6 protein differs from the other three in that it has a very small cavity with only two water molecules and no exchange with the surroundings. The other three proteins have quite big cavities, with 41 water molecules on average in 2C8 and 54-58 in 2C9 and 3A4, giving a water volume of 1500-2100 angstrom(3). The two crystal structures of 2C9 differ quite appreciably, whereas those of 3A4 are quite similar. The active-site cavity is connected to the surroundings by three to six channels, through which there is a quite frequent exchange of water molecules (one molecule is exchanged every 30-200 ps), except in 2A6. Most of the channels are observed also in the crystal structures, but two to three channels in each protein open only during the simulations. There are no water molecules close to the heme iron ion in these simulations of the high-spin ferric state (the average distance to the closest water molecule is 3.3-5 angstrom), and there are few ordered water molecules in the active sites, none of which is conserved in all proteins.

Three possible mechanisms have been suggested for the hydroxylation of primary and secondary amines by the cytochrome P450 enzyme family. We show that for the hydroxylation of primary alkyl amines, both the hydrogen abstraction and rebound mechanism and the direct oxygen transfer mechanism can contribute to the formation of the hydroxylated product. We also show that in the hydrogen abstraction and rebound mechanism the rebound step has higher activation energy than the hydrogen abstraction step, which is the opposite of the hydroxylation of aliphatic carbon atoms.

Many drug compounds are oxidized by cytochrome P450 (CYP) enzymes to form reactive metabolites. This study presents density functional theory calculations of the CYP-mediated metabolism of acetaminophen and a series of related compounds that can form reactive metabolites by hydrogen abstraction. The substitution pattern affects the activation barrier for hydrogen abstraction by up to 30 kJ/mol. A correlation (R(2) = 0.72) between the transition-state energies and the corresponding substrate radical energies has been established. Using this correlation is significantly less time-demanding than using the porphyrin model to determine the activation energies. We have used this correlation on monosubstituted phenols to rationalize the effect of the various substituents in the drug compounds. In addition to facilitating a chemical interpretation, the approach is sufficiently fast and reliable to be used as an in silico method in the design of new compounds with improved metabolic stability.

Cytochrome P450 enzymes (CYPs) metabolize alkyl- and arylamines, generating several different products. For the primary and secondary amines, some of these reactions result in hydroxylated amines, which may be toxic. Thus, when designing new drugs containing amine groups, it is important to be able to predict if a given compound will be a substrate for CYPs, in order to avoid toxic metabolites, and hence to understand the mechanism that is utilized by CYPs. Two possible mechanisms, for the N-hydroxylation of primary and secondary amines mediated by CYPs, are studied by density functional theory (DFT) for four different amines (aniline, N-methylaniline, propan-2-amine, and dimethylamine). The hydrogen abstraction and rebound mechanism is found to be preferred over a direct oxygen transfer mechanism for all four amines. However, in contrast to the same mechanism for the hydroxylation of aliphatic carbon atoms, the rebound step is shown to be rate-limiting in most cases.

We have estimated the activation energy for hydrogen abstraction by compound I in cytochrome P450 for a diverse set of 24 small organic substrates using state-of-the-art density functional theory (B3LYP). We then show that these results can be reproduced by computationally less demanding methods, for example, by using small organic mimics of compound I with both B3LYP and the semiempirical AM1 method (mean absolute error of 3-4 kJ/mol) or by calculating the bond dissociation energy, without relaxation of the radical (B3LYP) or estimated from three-point fit to a Morse potential (AM1; errors of 4 and 5 kJ/mol, respectively). We can assign activation energies of 74, 61, 53, 47, and 30 kJ/mol to primary carbons, secondary/tertiary carbons, carbons with adjacent sp(2) or aromatic groups, ethers/thioethers, and amines, respectively, which gives a very simple and predictive model. Finally, some of the less demanding methods are applied to study the CYP3A4 metabolism of progesterone and dextromethorphan.

The cytochrome P450 enzymes (CYPs) metabolize many drug compounds. They catalyze a wide variety of reactions, and potentially, a large number of different metabolites can be generated. Density functional theory (DFT) has, over the past decade, been shown to be a powerful tool to rationalize and predict the possible metabolites generated by the CYPs as well as other drug-metabolizing enzymes.We review applications of DFT on reactions performed by the CYPs and other drug-metabolizing enzymes able to perform oxidation reactions, with an emphasis on predicting which metabolites are produced. We also cover calculations of binding energies for complexes in which the ligands interact directly with the heme iron atom.DFT is a useful tool for prediction of the site of metabolism. The use of small models of the enzymes work surprisingly well for most CYP isoforms. This is probably due to the fact that the binding of the substrates is not the major determinant. When binding of the substrate plays a significant role, the well-known issue of determining the free energy of binding is the challenge. How approaches taking the protein environment into account, like docking, MD and QM/MM, can be used are discussed.

FAst MEtabolizer (FAME) is a fast and accurate predictor of sites of metabolism (SoMs). It is based on a collection of random forest models trained on diverse chemical data sets of more than 20 000 molecules annotated with their experimentally determined SoMs. Using a comprehensive set of available data, FAME aims to assess metabolic processes from a holistic point of view. It is not limited to a specific enzyme family or species. Besides a global model, dedicated models are available for human, rat, and dog metabolism; specific prediction of phase I and II metabolism is also supported. FAME is able to identify at least one known SoM among the top-1, top-2, and top-3 highest ranked atom positions in up to 71%, 81%, and 87% of all cases tested, respectively. These prediction rates are comparable to or better than SoM predictors focused on specific enzyme families (such as cytochrome P450s), despite the fact that FAME uses only seven chemical descriptors. FAME covers a very broad chemical space, which together with its inter- and extrapolation power makes it applicable to a wide range of chemicals. Predictions take less than 2.5 s per molecule in batch mode on an Ultrabook. Results are visualized using Jmol, with the most likely SoMs highlighted.

The analysis of designer drugs in human plasma is highly complex, as most of these drugs are metabolized quickly, and often into multiple products. For novel designer drugs, it is common that reference compounds for these metabolites are unavailable at the time of analysis. Hence, the usage of in silico procedures to accurately predict the chemical structures of these metabolites would be very useful. In this study, the differences between several methods for prediction of site of metabolism for cytochrome P450 mediated drug metabolism are described, and their prediction accuracies are analyzed on a set of designer drugs. It is found that ligand-based methods, which are simpler and faster, are better than or at least as good as much more complex structure-based methods.

Chemokine receptors are involved in trafficking of leukocytes and represent targets for autoimmune conditions, inflammatory diseases, viral infections, and cancer. We recently published CCR1, CCR8, and CCR5 agonists and positive modulators based on a three metal-ion chelator series: 2,2'-bipyridine, 1,10-phenanthroline, and 2,2';6',2″-terpyridine. Here, we have performed an in-depth structure-activity relationship study and tested eight new optimized analogs. Using density functional theory calculations we demonstrate that the chelator zinc affinities depend on how electron-donating and -withdrawing substituents modulate the partial charges of chelating nitrogens. The zinc affinity was found to constitute the major factor for receptor potency, although the activity of some chelators deviate suggesting favorable or unfavorable interactions. Hydrophobic and halogen substituents are generally better accommodated in the receptors than polar groups. The new analog brominated terpyridine (29) resulted in the highest chelator potencies observed so far CCR1 (EC50: 0.49 μM) and CCR8 (EC50: 0.28 μM). Furthermore, we identified the first selective CCR5 agonist chelator, meta dithiomethylated bipyridine (23). The structure-activity relationships contribute to small-molecule drug development, and the novel chelators constitute valuable tools for studies of structural mechanisms for chemokine receptor activation.

To enhance the discrimination rate for methods applying structural alerts and biotransformation rules in the prediction of toxicity and drug metabolism we have developed a set of novel fragment based atomic descriptors. These atomic descriptors encode the properties of the fragments separating an atom from the closest end of a branch or the molecule. The end of a branch and the end of a molecule, as well as the selection of the fragments, are made by an algorithm that uses only the distance matrix of the molecule. The novel descriptors are applied to a small set of biotransformation rules and are shown to be able to reduce the number of unconfirmed positives by up to 58 %.

RS-Predictor is a tool for creating pathway-independent, isozyme-specific, site of metabolism (SOM) prediction models using any set of known cytochrome P450 (CYP) substrates and metabolites. Until now, the RS-Predictor method was only trained and validated on CYP 3A4 data, but in the present study, we report on the versatility the RS-Predictor modeling paradigm by creating and testing regioselectivity models for substrates of the nine most important CYP isozymes. Through curation of source literature, we have assembled 680 substrates distributed among CYPs 1A2, 2A6, 2B6, 2C19, 2C8, 2C9, 2D6, 2E1, and 3A4, the largest publicly accessible collection of P450 ligands and metabolites released to date. A comprehensive investigation into the importance of different descriptor classes for identifying the regioselectivity mediated by each isozyme is made through the generation of multiple independent RS-Predictor models for each set of isozyme substrates. Two of these models include a density functional theory (DFT) reactivity descriptor derived from SMARTCyp. Optimal combinations of RS-Predictor and SMARTCyp are shown to have stronger performance than either method alone, while also exceeding the accuracy of the commercial regioselectivity prediction methods distributed by Optibrium and Schrödinger, correctly identifying a large proportion of the metabolites in each substrate set within the top two rank-positions: 1A2 (83.0%), 2A6 (85.7%), 2B6 (82.1%), 2C19 (86.2%), 2C8 (83.8%), 2C9 (84.5%), 2D6 (85.9%), 2E1 (82.8%), 3A4 (82.3%), and merged (86.0%). Comprehensive datamining of each substrate set and careful statistical analyses of the predictions made by the different models revealed new insights into molecular features that control metabolic regioselectivity and enable accurate prospective prediction of likely SOMs.

By the use of knowledge gained through modeling of drug metabolism mediated by the cytochrome P450 2D6 and 3A4 isoforms, we constructed a 2D-based model for site-of-metabolism prediction for the cytochrome P450 2C9 isoform. The similarities and differences between the models for the 2C9 and 2D6 isoforms are discussed through structural knowledge from the X-ray crystal structures and trends in experimental data. The final model was validated on an independent test set, resulting in an area under the curve value of 0.92, and a site of metabolism was found among the top two ranked atoms for 77% of the compounds.

We review density functional theory studies of various types of reactions performed by the cytochrome P450 family of enzymes. We describe the various reactions on equal footing with an emphasisis on models to predict sites of metabolism for an arbitrary molecule. The activation barriers range between 0 and 109 kJ/mol, depending more on the atoms surrounding the reactive site than on the type of reaction. Therefore, the intrinsic reactivity can rather well be predicted by simple chemical rules. However, for a full predictive model, the steric effects of the enzyme surrounding the heme group need also to be modeled, which often is harder.

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.

This article describes RegioSelectivity-Predictor (RS-Predictor), a new in silico method for generating predictive models of P450-mediated metabolism for drug-like compounds. Within this method, potential sites of metabolism (SOMs) are represented as "metabolophores": A concept that describes the hierarchical combination of topological and quantum chemical descriptors needed to represent the reactivity of potential metabolic reaction sites. RS-Predictor modeling involves the use of metabolophore descriptors together with multiple-instance ranking (MIRank) to generate an optimized descriptor weight vector that encodes regioselectivity trends across all cases in a training set. The resulting pathway-independent (O-dealkylation vs N-oxidation vs Csp(3) hydroxylation, etc.), isozyme-specific regioselectivity model may be used to predict potential metabolic liabilities. In the present work, cross-validated RS-Predictor models were generated for a set of 394 substrates of CYP 3A4 as a proof-of-principle for the method. Rank aggregation was then employed to merge independently generated predictions for each substrate into a single consensus prediction. The resulting consensus RS-Predictor models were shown to reliably identify at least one observed site of metabolism in the top two rank-positions on 78% of the substrates. Comparisons between RS-Predictor and previously described regioselectivity prediction methods reveal new insights into how in silico metabolite prediction methods should be compared.

Summary: The SMARTCyp server is the first web application for site of metabolism prediction of cytochrome P450-mediated drug metabolism. Availability: The SMARTCyp server is freely available for use on the web at www.farma.ku.dk/smartcyp where the SMARTCyp Java program and source code is also available for download. Contact: smartcyp@farma.ku.dk; lo@farma.ku.dk Supplementary information: Supplementary data are available at Bioinformatics online.

Summary The ectodomain of olfactory cell adhesion molecule (OCAM/NCAM2/RNCAM) consists of five immunoglobulin (Ig) domains (IgI–V), followed by two fibronectin-type 3 (Fn3) domains (Fn3I–II). A complete structural model of the entire ectodomain of human OCAM has been assembled from crystal structures of six recombinant proteins corresponding to different regions of the ectodomain. The model is the longest experimentally based composite structural model of an entire IgCAM ectodomain. It displays an essentially linear arrangement of IgI–V, followed by bends between IgV and Fn3I and between Fn3I and Fn3II. Proteins containing IgI–IgII domains formed stable homodimers in solution and in crystals. Dimerization could be disrupted in vitro by mutations in the dimer interface region. In conjunction with the bent ectodomain conformation, which can position IgI–V parallel with the cell surface, the IgI–IgII dimerization enables OCAM-mediated trans- interactions with an intercellular distance of about 20 nm, which is consistent with that observed in synapses.

Iron porphyrin complexes are cofactors in many important proteins such as cytochromes P450, hemoglobin, heme peroxidases, etc. Many computational studies on these systems have been done over the past decade. In this study, the performance of some of the most commonly used density functional theory functionals is evaluated with regard to how they reproduce experimental structures. Seven different functionals (BP86, PBE, PBE0, TPSS, TPSSH, B3LYP, and B97-D) are used to study eight different iron porphyrin complexes. The results show that the TPSSH, PBE0, and TPSS functionals give the best results (absolute bond distance deviations of 0.015-0.016 A), but the geometries are well-reproduced by all functionals except B3LYP. We also test four different basis sets of double-zeta quality, and we find that a combination of double-zeta basis set of Schafer et al. on the iron atom and the 6-31G* basis set on the other atoms performs best. Finally, we remove the porphyrin side chains and increase the basis set size systematically to see if this affects the results. We show that basis sets larger than double-zeta quality are not necessary to get accurate geometries, and nonaromatic side chains do not affect the geometries.

Cytochrome P450 mediated metabolism of drugs is one of the major determinants of their kinetic profile, and prediction of this metabolism is therefore highly relevant during the drug discovery and development process. A new rule-based method, based on results from density functional theory calculations, for predicting activation energies for aliphatic and aromatic oxidations by cytochromes P450 is developed and compared with several other methods. Although the applicability of the method is currently limited to a subset of P450 reactions, these reactions describe more than 90% of the metabolites. The rules employed are relatively few and general, and when combined with solvent-accessible surface area calculations to account for steric accessibility, the method gives a major P450 metabolite as first-ranked position for 75% of the substrates, and ranked in the top three for 90% of substrates for a set of 20 substrates. In combination with docking, it can predict isoform-specific metabolism, and we apply this on CYP1A2 with very good results on 81 substrates, for which we find a major metabolite ranked in the top three for 90% of the substrates (100% in the training set and 87% in the larger test set). © 2009 Wiley-VCH Verlag GmbH & Co. KGaA.

This chapter illustrates how quantum chemical calculations can be used to elucidate structural and functional aspects of tetrapyrrole cofactors, focusing on porphyrins, cobalamins, coenzyme F430, and chlorophyll. A particular emphasis is put on the biochemical significance of axial ligands, which can tune the function of the tetrapyrroles. With the use of quantum chemical calculations, it is possible to draw important conclusions regarding aspects of tetrapyrroles that could not otherwise be accessed. The results show that the general reactivity is mainly determined by the metal and the tetrapyrrole ring system, whereas the electronic structure and reactivity are tuned by the choice of axial ligands, providing a unique insight into the design of cofactors in nature. (Less)

The heme peroxidases have a histidine group as the axial ligand of iron. This ligand forms a hydrogen bond to an aspartate carboxylate group by the other nitrogen atom in the side chain. The aspartate is not present in the globins and it has been suggested that it gives an imidazolate character to the histidine ligand. Quantum chemical calculations have indicated that the properties of the heme site strongly depend on the position of the proton in this hydrogen bond. Therefore, we have studied the location of this proton in all intermediates in the reaction mechanism, using a set of different quantum mechanical and combined experimental and computational methods. Quantum refinements of a crystal structure of the resting FeIII state in yeast cytochrome c peroxidase show that the geometric differences of the two states are so small that it cannot be unambiguously decided where the proton is in the crystal structure. Vacuum calculations indicate that the position of the proton is sensitive to the surroundings and to the side chains of the porphyrin ring. Combined quantum and molecular mechanics (QM/MM) calculations indicate that the proton prefers to reside on the His ligand in all states in the reaction mechanism of the peroxidases. QM/MM free energy perturbations confirm these results, but reduce the energy difference between the two states to 12-44 kJ/mol.

The oxidation and dealkylation of dimethylsulfoxide (DMSO), dimethylsulfide (DMS), and trimethylamine (TMA) by cytochrome P450 has been studied with density functional theory calculations. The results show that the oxidation reactions always occur on the doublet spin surface, whereas dealkylations can take place for both the doublet and quartet spin states. Moreover, DMS is more reactive than DMSO, and S-oxidation is more favorable than S-dealkylation, whereas N-dealkylation is more favorable than N-oxidation. This is in perfect agreement with experimental results, showing that density functional activation energies are reliable and comparable for widely different reactions with cytochrome P450.

We have estimated the activation energy for aromatic oxidation by compound I in cytochrome P450 for a diverse set of 17 substrates using state-of-the-art density functional theory (B3LYP) with large basis sets. The activation energies vary from 60 to 87 kJ/mol. We then test if these results can be reproduced by computationally less demanding methods. The best methods (a B3LYP calculation of the activation energy of a methoxy-radical model or a partial least-squares model of the semiempirical AM1 bond dissociation energies and spin densities of the tetrahedral intermediate for both a hydroxyl-cation and a hydroxyl-radical model) give correlations with r(2) of 0.8 and mean absolute deviations of 3 kJ/mol. Finally, we apply these simpler methods on several sets of reactions for which experimental data are available and show that we can predict the reactive sites by combining calculations of the activation energies with the solvent-accessible surface area of each site.

We compare free energy calculations for the methyl transfer reaction catalyzed by catechol O-methyltransferase using the quantum mechanical/molecular mechanical free energy method with implicit and explicit solvents. An analogous methylation reaction in a solution is also studied. For the explicit solvent model, we use the three-point transferable intermolecular potential model, and for the implicit model, we use the generalized Born molecular volume model as implemented in CHARMM. We find that activation and reaction free energies calculated with the two models are very similar, despite some structural differences that exist. A significant change in the polarization of the environment occurs as the reaction proceeds. This is more pronounced for the reaction in a solution than for the enzymatic reaction. For the enzymatic reaction, most of the changes take place in the protein rather than in the solvent, and, hence, the benefit of having an instantaneous relaxation of the solvent degrees of freedom is less pronounced for the enzymatic reaction than for the reaction in a solution. This is a likely reason why energies of the enzyme reaction are less sensitive to the choice of atomic radii than are energies of the reaction in a solution. (c) 2006 American Institute of Physics.

Peroxidases, oxygenases and catalases have similar high-valent metal-ion intermediates in their respective reaction cycles. In this review, haem-based examples will be discussed. The intermediates of the haem-containing enzymes have been extensively studied for many years by different spectroscopic methods like UV-Vis, EPR (electron paramagnetic resonance), resonance Raman, Mossbauer and MCD (magnetic circular dichroism). The first crystal structure of one of these high-valent intermediates was on cytochrome c peroxidase in 1987. Since then, structures have appeared for catalases in 1996, 2002, 2003, putatively for cytochrome P450 in 2000, for myoglobin in 2002, for horseradish peroxidase in 2002 and for cytochrome c peroxidase again in 1994 and 2003. This review will focus on the most recent structural investigations for the different intermediates of these proteins. The structures of these intermediates will also be viewed in light of quantum mechanical (QM) calculations on haem models. In particular quantum refinement, which is a combination of QM calculations and crystallography, will be discussed. Only small structural changes accompany the generation of these intermediates. The crystal structures show that the compound I state, with a so called pi-cation radical on the haem group, has a relatively short iron-oxygen bond (1.67-1.76A) in agreement with a double-bond character, while the compound II state or the compound I state with a radical on an amino acid residue have a relatively long iron-oxygen bond (1.86-1.92A) in agreement with a single-bond character where the oxygen-atom is protonated.

Summary: In this work we present WhichCyp, a tool for prediction of which cytochromes P450 isoforms (among 1A2, 2C9, 2C19, 2D6 and 3A4) a given molecule is likely to inhibit. The models are built from experimental high-throughput data using support vector machines and molecular signatures. Availability: The WhichCyp server is freely available for use on the web at http://drug.ku.dk/whichcyp, where the WhichCyp Java program and source code is also available for download. Contact: pry@sund.ku.dk Supplementary information: Supplementary data are available at Bioinformatics online.

Three microperoxidases--hemin-6(7)-gly-gly-his methyl ester (HGGH), mesohemin-6(7)-gly-gly-his methyl ester (MGGH) and deuterohemin-6(7)-gly-gly-his methyl ester (DGGH)--have been prepared as models for heme-containing peroxidases by condensation of glycyl-glycyl-L-histidine methyl ester with the propionic side chains of hemin, mesohemin and deuterohemin, respectively. The three microperoxidases differ in two substituents, R, of the protoporphyrin IX framework (HGGH: R=vinyl, MGGH: R=ethyl, DGGH: R=H). X-band and high field EPR spectra show that the microperoxidases exhibit spectroscopic properties similar to those of metmyoglobin, i.e. a high spin ferric S=5/2 signal at g(perpendicular)=6 and g parallel)=2 and an estimated D value of 7.5+/-1cm(-1). The catalytic activities of the microperoxidases towards K4[Fe(CN)6], L-tyrosine methyl ester and 2,2'-azino(bis(3-ethylbenzothiazoline-6-sulfonic acid)) (ABTS) have been investigated. It was found that all three microperoxidases exhibit peroxidase activity and that the reactions follow the generally accepted peroxidase reaction scheme [Biochem. J. 145 (1975) 93-103] with the exception that the initial formation of a Compound I analogue is the rate-limiting step for the whole process. The general activity trend was found to be MGGH approximately DGGH>HGGH. For each microperoxidase, DFT calculations (B3LYP) were made on the reactions of compounds 0, I and II with H+, e- and H+ + e-, respectively, in order to probe the possible relationship between the nature of the 2- and 4-substituents of the hemin and the observed reactivity. The computational modeling indicates that the relative energy differences are very small; solvation and electrostatic effects may be factors that decide the relative activities of the microperoxidases.

We present a systematic investigation of how the axial ligand in heme proteins influences the geometry, electronic structure, and spin states of the active site, and the energies of the reaction cycles. Using the density functional B3LYP method and medium-sized basis sets, we have compared models with His, His+Asp, Cys, Tyr, and Tyr+Arg as found in myoglobin and hemoglobin, peroxidases, cytochrome P450, and heme catalases, respectively. We have studied 12 reactants and intermediates of the reaction cycles of these enzymes, including complexes with H(2)O, OH(-), O(2-), CH(3)OH, O(2), H(2)O(2), and HO(2)(-) in various formal oxidation states of the iron ion (II to V). The results show that His gives ~0.6 V higher reduction potentials than the other ligands. In particular, it is harder to reduce and protonate the O(2) complex with His than with the other ligands, in accordance with the O(2) carrier function of globins and the oxidative chemistry of the other proteins. For most properties, the trend Cys

Summary: Regioselectivity-WebPredictor (RS-WebPredictor) is a server that predicts isozyme-specific cytochrome P450 (CYP)-mediated sites of metabolism (SOMs) on drug-like molecules. Predictions may be made for the promiscuous 2C9, 2D6 and 3A4 CYP isozymes, as well as CYPs 1A2, 2A6, 2B6, 2C8, 2C19 and 2E1. RS-WebPredictor is the first freely accessible server that predicts the regioselectivity of the last six isozymes. Server execution time is fast, taking on average 2s to encode a submitted molecule and 1s to apply a given model, allowing for high-throughput use in lead optimization projects. Availability: RS-WebPredictor is accessible for free use at http://reccr.chem.rpi.edu/Software/RS-WebPredictor/ Contact: brenec@rpi.edu

A novel lab-on-a-chip nanotree enzyme reactor is demonstrated for the detection of acetylcholine. The reactors are intended for use in the RISFET (regional ion sensitive field effect transistor) nanosensor, and are constructed from gold-tipped branched nanorod structures grown on SiN(x)-covered wafers. Two different reactors are shown: one with simple, one-dimensional nanorods and one with branched nanorod structures (nanotrees). Significantly higher enzymatic activity is found for the nanotree reactors than for the nanorod reactors, most likely due to the increased gold surface area and thereby higher enzyme binding capacity. A theoretical calculation is included to show how the enzyme kinetics and hence the sensitivity can be influenced and increased by the control of electrical fields in relation to the active sites of enzymes in an electronic biosensor. The possible effects of electrical fields employed in the RISFET on the function of acetylcholine esterase is investigated using quantum chemical methods, which show that the small electric field strengths used are unlikely to affect enzyme kinetics. Acetylcholine esterase activity is determined using choline oxidase and peroxidase by measuring the amount of choline formed using the chemiluminescent luminol reaction.