Modeling the active sites of cytochrome P450s and glutathione S-transferases, two of the most important biotransformation enzymes

Polymorphisms in the human cytochrome P450 and arylamine N-acetyltransferase: susceptibility to head and neck cancers

The occurrence of head and neck cancer (HNC) is associated with smoking and alcohol drinking. Tobacco smoking exposes smokers to a series of carcinogenic chemicals. Cytochrome P450 enzymes (CYP450s), such as CYP1A1, CYP1B1, and CYP2D6, usually metabolize carcinogens to their inactive derivatives, but they occasionally convert the chemicals to more potent carcinogens. In addition, via CYP450 (CYP2E1) oxidase, alcohol is metabolized to acetaldehyde, a highly toxic compound, which plays an important role in carcinogenesis. Furthermore, two N-acetyltransferase isozymes (NATs), NAT1 and NAT2, are polymorphic and catalyze both N-acetylation and O-acetylation of aromatic and heterocyclic amine carcinogens. Genetic polymorphisms are associated with a number of enzymes involved in the metabolism of carcinogens important in the induction of HNC. It has been suggested that such polymorphisms may be linked to cancer susceptibility. In this paper, we select four cytochrome P450 enzymes (CYP1A1, CYP1BA1, CYP2D6, and CYP2E1), and two N-acetyltransferase isozymes (NAT1 and NAT2) in order to summarize and analyze findings from the literature related to HNC risk by focusing on (i) the interaction between these genes and the environment, (ii) the impact of genetic defect on protein activity and/or expression, and (iii) the eventual involvement of race in such associations.

Structure-based CoMFA as a predictive model - CYP2C9 inhibitors as a test case

In this study, we tried to establish a general scheme to create a model that could predict the affinity of small compounds to their target proteins. This scheme consists of a search for ligand-binding sites on a protein, a generation of bound conformations (poses) of ligands in each of the sites by docking, identifications of the correct poses of each ligand by consensus scoring and MM-PBSA analysis, and a construction of a CoMFA model with the obtained poses to predict the affinity of the ligands. By using a crystal structure of CYP 2C9 and the twenty known CYP inhibitors as a test case, we obtained a CoMFA model with a good statistics, which suggested that the classification of the binding sites as well as the predicted bound poses of the ligands should be reasonable enough. The scheme described here would give a method to predict the affinity of small compounds with a reasonable accuracy, which is expected to heighten the value of computational chemistry in the drug design process.

Predicting drug metabolism--an evaluation of the expert system METEOR

The paper begins with a discussion of the goals of metabolic predictions in early drug research, and some difficulties toward this objective, mainly the various substrate and product selectivities characteristic of drug metabolism. The major in silico approaches to predict drug metabolism are then classified and summarized. A discrimination is, thus, made between 'local' and 'global' systems. In its second part, an evaluation of METEOR, a rule-based expert system used to predict the metabolism of drugs and other xenobiotics, is reported. The published metabolic data of ten substrates were used in this evaluation, the overall results being discussed in terms of correct vs. disputable (i.e., false-positive and false-negative) predictions. The predictions for four representative substrates are presented in detail (Figs. 1-4), illustrating the interest of such an evaluation in identifying where and how predictive rules can be improved.

Comparative molecular field analysis and QSAR on substrates binding to cytochrome P450 2D6

In this study, we utilized comparative molecular field analysis (CoMFA) to gain a better understanding of the steric and electrostatic features of the cytochrome p450 2D6 (CYP2D6) active site. The training set consists of 24 substrates with reported K(M) values from liver microsomal CYP2D6 spanning an activity range of almost three log units. The low energy conformers were fit by root mean square (RMS) to minaprine at the site of metabolism and to the protonated nitrogen. In this manner, we constructed two CoMFA models, one model with a distance constraint and another without. The model with the distance parameter (non-cross-validated R(2)=0.99) was approximately equal to the CoMFA without a distance parameter (non-cross-validated R(2)=0.98). Validation of our CoMFA was accomplished by predicting the K(M) values of 15 diverse CYP2D6 substrates not in the original training set resulting in a predictive R(2)=0.62. Finally, we also pursued correlations of pK(a) and log P with CYP2D6 substrate K(M) in an effort to investigate other physicochemical properties.

Modeling and molecular dynamics of glutamine transaminase K/cysteine conjugate beta-lyase

The homodimeric, pyridoxal 5'-phosphate (PLP)-dependent enzyme glutamine transaminase K/cysteine conjugate beta-lyase (GTK/beta-lyase) has been implicated in the bioactivation of chemopreventive compounds. This paper describes the first homology model of rat renal GTK/beta-lyase and its active site residues, deduced from molecular dynamics (MD) simulations of the binding mode of 13 structurally diverse cysteine S-conjugates and amino acids after Amber-parametrization of PLP. Comparison with Thermus thermophilus aspartate aminotransferase (tAAT) and Trypanosoma cruzi tyrosine aminotransferase (tTAT), used as templates for modeling GTK/beta-lyase, showed that the PLP-binding site of GTK/beta-lyase is highly conserved. Binding of the ligand alpha-carboxylate-group occurred via the conserved residues Arg(432) and Asn(219), and Asn(50) and Gly(70). Two pockets accommodated the various ligand side chains. A small pocket, located directly above PLP, was of a highly hydrophobic and aromatic character. A larger pocket, formed partly by the substrate access channel, was more hydrophilic and notably involved the salt bridge partners Glu(54) and Arg(99*) (* denotes the other subunit). Ligand-binding residues included Leu(51), Phe(71), Tyr(135), Phe(373) and Phe(312*), and pi-stacking interactions were often observed. Tyr(135) and Asn(50) were prominent in hydrogen bonding with the sulfur-atom of cysteine S-conjugates. The observed binding mode of the ligands corresponded well with their experimentally determined inhibitory potency toward GTK/beta-lyase. The current homology model thus provides a starting point for further validation of the role of active site residues in ligand-binding by means of mutagenesis studies. Ultimately, insight in the binding of ligands to GTK/beta-lyase may result in the rational design of new ligands and selective inhibitors.

Chemoinformatics and Drug Discovery

This article reviews current achievements in the field of chemoinformatics and their impact on modern drug discovery processes. The main data mining approaches used in cheminformatics, such as descriptor computations, structural similarity matrices, and classification algorithms, are outlined. The applications of cheminformatics in drug discovery, such as compound selection, virtual library generation, virtual high throughput screening, HTS data mining, and in silico ADMET are discussed. At the conclusion, future directions of chemoinformatics are suggested.

Pharmacophore modeling of cytochromes P450

Understanding the binding of ligands in the active site of a membrane-bound protein is difficult in the absence of a crystal structure. When these proteins are the enzymes involved in drug metabolism, it leaves little option but to use site-directed mutagenesis and in vitro studies to provide critical information relating to determinants of binding affinity. Pharmacophore models and three-dimensional quantitative structure-activity relationships have been used either alone or in combination with protein homology models to provide this information for cytochrome P450s. At present, their application has been directed to the major enzymes but this may escalate in future as more in vitro data are generated for other P450s. The following review outlines the methodologies and models as well as future prospects for applying these technologies to P450s in the hope that future drugs will be selected with increased metabolic stability and fewer incidences of undesirable drug-drug interactions.

Combined three-dimensional quantitative structure-activity relationship analysis of cytochrome P450 2B6 substrates and protein homology modeling

Understanding the basis of the substrate specificity of cytochrome P450 2B6 (CYP2B6) is important for determining the role of this enzyme in drug metabolism and for predicting new substrates. Pharmacophores were generated for 16 structurally diverse CYP2B6 substrates with Catalyst after overlapping the reaction sites. Two pharmacophores were determined for the CYP2B6 binding site. Both include two hydrophobes and one hydrogen bond acceptor. The three-dimensional structure of CYP2B6 was then modeled based on the crystal structure of CYP2C5. Benzyloxyresorufin and 7-ethoxy-4-trifluoromethylcoumarin, the two lowest K(m) substrates in the training set, were then docked in the active site of CYP2B6. The pharmacophores were combined with the CYP2B6 model by comparing the docking results and the mapping of the two substrates with the pharmacophores. The results indicated that the active site of CYP2B6 complements the pharmacophores. The pharmacophores and the CYP2B6 model were used in conjunction to predict the K(m) values of substrates in a test set of five compounds and yielded satisfactory predictions for benzphetamine, cinnarizine, bupropion, and verapamil but not lidocaine. The CYP2B6 model, the pharmacophores, and the combination of the model with these pharmacophores provide insight into the interactions of CYP2B6 with substrates. The pharmacophores may be used as queries to search a database to predict new substrates for CYP2B6 when the reaction site is known (N- or O-dealkylation). For C-hydroxylation, the CYP2B6 model is helpful in evaluating the possible reaction sites in order for the pharmacophores to predict corresponding K(m) values.

Influence of phenylalanine-481 substitutions on the catalytic activity of cytochrome P450 2D6

Homology models of the active site of cytochrome P450 2D6 (CYP2D6) have identified phenylalanine 481 (Phe(481)) as a putative ligand-binding residue, its aromatic side chain being potentially capable of participating in pi-pi interactions with the benzene ring of ligands. We have tested this hypothesis by replacing Phe(481) with tyrosine (Phe(481)-->Tyr), a conservative substitution, and with leucine (Phe(481)-->Leu) or glycine (Phe(481)-->Gly), two non-aromatic residues, and have compared the properties of the wild-type and mutant enzymes in microsomes prepared from yeast cells expressing the appropriate cDNA-derived protein. The Phe(481)-->Tyr substitution did not alter the kinetics [K(m) (microM) and V(max) (pmol/min per pmol) respectively] of oxidation of S-metoprolol (27; 4.60), debrisoquine (46; 2.46) or dextromethorphan (2; 8.43) relative to the respective wild-type values [S-metoprolol (26; 3.48), debrisoquine (51; 3.20) and dextromethorphan (2; 8.16)]. The binding capacities [K(s) (microM)] of a range of CYP2D6 ligands to the Phe(481)-->Tyr enzyme (S-metoprolol, 22.8; debrisoquine, 12.5; dextromethorphan, 2.3; quinidine, 0.13) were also similar to those for the wild-type enzyme (S-metoprolol, 10.9; debrisoquine, 8.9; dextromethorphan, 3.1; quinidine, 0.10). In contrast, the Phe(481)-->Leu and Phe(481)-->Gly substitutions increased significantly (3-16-fold) the K(m) values of oxidation of the three substrates [S-metoprolol (120-124 microM), debrisoquine (152-184 microM) and dextromethorphan (20-31 microM)]. Similarly, the K(s) values of the ligands to Phe(481)-->Leu and Phe(481)-->Gly mutants were also increased 3 to 10-fold (S-metoprolol, 33.2-41.9 microM; debrisoquine, 85-90 microM; dextromethorphan, 15.7-18.8 microM; quinidine 0.35-0.53 microM). However, contrary to a recent proposal that Phe(481) has the dominant role in the binding of substrates that undergo CYP2D6-mediated N-dealkylation routes of metabolism, the Phe(481)-->Gly substitution did not substantially decrease the capacity of the enzyme to N-deisopropylate metoprolol (wild-type, 1.12 pmol/min per pmol of P450; Phe(481)-->Gly, 0.71), whereas an Asp(301)-->Gly substitution decreased the N-dealkylation reaction by 95% of the wild-type rate. Overall, our results are consistent with the proposal that Phe(481) is a ligand-binding residue in the active site of CYP2D6 and that the residue interacts with ligands via a pi-pi interaction between its phenyl ring and the aromatic moiety of the ligand. However, the relative importance of Phe(481) in binding is ligand-dependent; furthermore, its importance is secondary to that of Asp(301). Finally, contrary to predictions of a recent homology model, Phe(481) does not seem to have a primary role in CYP2D6-mediated N-dealkylation.

Theoretical investigation of substrate specificity for cytochromes P450 IA2, P450 IID6 and P450 IIIA4

Three-dimensional models of the cytochromes P450 IA2, P450 IID6 and P450 IIIA4 were built by means of comparative modeling using the X-ray crystallographic structures of P450 CAM, P450 BM-3, P450 TERP and P450 ERYF as templates. The three cytochromes were analyzed both in their intrinsic structural features and in their interaction properties with fifty specific and non-specific substrates. Substrate/enzyme complexes were obtained by means of both automated rigid and flexible body docking. The comparative analysis of the three cytochromes and the selected substrates, in their free and bound forms, allowed for the building of semi-quantitative models of substrate specificity based on both molecular and intermolecular interaction descriptors. The results of this study provide new insights into the molecular determinants of substrate specificity for the three different eukaryotic P450 isozymes and constitute a useful tool for predicting the specificity of new compounds.

Genetic polymorphisms of human N-acetyltransferase, cytochrome P450, glutathione-S-transferase, and epoxide hydrolase enzymes: relevance to xenobiotic metabolism and toxicity

In this review, an overview is presented of the current knowledge of genetic polymorphisms of four of the most important enzyme families involved in the metabolism of xenobiotics, that is, the N-acetyltransferase (NAT), cytochrome P450 (P450), glutathione-S-transferase (GST), and microsomal epoxide hydrolase (mEH) enzymes. The emphasis is on two main topics, the molecular genetics of the polymorphisms and the consequences for xenobiotic metabolism and toxicity. Studies are described in which wild-type and mutant alleles of biotransformation enzymes have been expressed in heterologous systems to study the molecular genetics and the metabolism and pharmacological or toxicological effects of xenobiotics. Furthermore, studies are described that have investigated the effects of genetic polymorphisms of biotransformation enzymes on the metabolism of drugs in humans and on the metabolism of genotoxic compounds in vivo as well. The effects of the polymorphisms are highly dependent on the enzyme systems involved and the compounds being metabolized. Several polymorphisms are described that also clearly influence the metabolism and effects of drugs and toxic compounds, in vivo in humans. Future perspectives in studies on genetic polymorphisms of biotransformation enzymes are also discussed. It is concluded that genetic polymorphisms of biotransformation enzymes are in a number of cases a major factor involved in the interindividual variability in xenobiotic metabolism and toxicity. This may lead to interindividual variability in efficacy of drugs and disease susceptibility.