Novel approach to predicting P450-mediated drug metabolism: development of a combined protein and pharmacophore model for CYP2D6

Evaluation of designed ligands by a multiple screening method: application to glycogen phosphorylase inhibitors constructed with a variety of approaches

Glycogen phosphorylase (GP) is an important enzyme that regulates blood glucose level and a key therapeutic target for the treatment of type II diabetes. In this study, a number of potential GP inhibitors are designed with a variety of computational approaches. They include the applications of MCSS, LUDI and CoMFA to identify additional fragments that can be attached to existing lead molecules; the use of 2D and 3D similarity-based QSAR models (HQSAR and SMGNN) and of the LUDI program to identify novel molecules that may bind to the glucose binding site. The designed ligands are evaluated by a multiple screening method, which is a combination of commercial and in-house ligand-receptor binding affinity prediction programs used in a previous study (So and Karplus, J. Comp.-Aid. Mol. Des., 13 (1999), 243-258). Each method is used at an appropriate point in the screening, as determined by both the accuracy of the calculations and the computational cost. A comparison of the strengths and weaknesses of the ligand design approaches is made.

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.

Competitive CYP2C9 inhibitors: enzyme inhibition studies, protein homology modeling, and three-dimensional quantitative structure-activity relationship analysis

This study describes the generation of a three-dimensional quantitative structure activity relationship (3D-QSAR) model for 29 structurally diverse, competitive CYP2C9 inhibitors defined experimentally from an initial data set of 73 compounds. In parallel, a homology model for CYP2C9 using the rabbit CYP2C5 coordinates was built. For molecules with a known interaction mode with CYP2C9, this homology model, in combination with the docking program GOLD, was used to select conformers to use in the 3D-QSAR analysis. The remaining molecules were docked, and the GRID interaction energies for all conformers proposed by GOLD were calculated. This was followed by a principal component analysis (PCA) of the GRID energies for all conformers of all compounds. Based on the similarity in the PCA plot to the inhibitors with a known interaction mode, the conformer to be used in the 3D-QSAR analysis was selected. The compounds were randomly divided into two groups, the training data set (n = 21) to build the model and the external validation set (n = 8). The PLS (partial least-squares) analysis of the interaction energies against the K(i) values generated a model with r(2) = 0.947 and a cross-validation of q(2) = 0.730. The model was able to predict the entire external data set within 0.5 log units of the experimental K(i) values. The amino acids in the active site showed complementary features to the grid interaction energies in the 3D-QSAR model and were also in agreement with mutagenesis studies.

Computational toxicology and the generation of mechanistic hypotheses: gamma-butyrolactone

In this study, we use SAR approaches in an attempt to elucidate the action of gamma-butyrolactone (GBL), an illicit drug and a dietary supplement, that can cause coma and deaths in humans while exhibiting low systemic toxicity towards rodents. The lack of systemic toxicity of GBL and of its metabolite(s) was also predicted by validated SAR models. In fact using diverse SAR models, the only significant SAR prediction was that GBL had the potential for inhibiting human cytochrome P4502D6 (CYP2D6). However, inhibition of that isozyme is not necessarily associated with toxicity. It is suggested that GBL users also abuse other substances. When GBL inhibits CYP2D6 this may prevent the CYP2D6-mediated detoxification of other toxicants simultaneously consumed by the GBL user.

Application of in silico approaches to predicting drug--drug interactions

In an environment driven to find the next blockbuster drug, failure years into a project should not be an option. Recent studies have shown that poor absorption, distribution, metabolism, and excretion (ADME), and the related properties of toxicity and pharmacokinetics are responsible for a large proportion of failures. One way to understand and potentially predict molecules likely to be successful in humans as drugs from an ADME point of view is to use simulations. Such simulations may include simple rule-based approaches, structure--activity relationships, three-dimensional quantitative structure--activity relationships (3D-QSAR), and pharmacophores. All of these represent useful tools in understanding metabolism by the cytochromes P450, predicting drug--drug interactions (DDIs), and other pharmacokinetic parameters. The present paper briefly reviews the application of some computational tools applied to predicting DDIs and will provide the reader with an idea of their utility.

Variable cytochrome P450 2D6 expression and metabolism of codeine and other opioid prodrugs: implications for the Australian anaesthetist

Codeine is a popular opioid prodrug dependent on the activity of the specific cytochrome P450 enzyme 2D6 (CYP2D6). This enzyme catalyses the production of the potent analgesic metabolite morphine, but genetic studies have demonstrated that individuals from different ethnic groups exhibit considerable variability in the functional capacities of their expressed CYP2D6 enzymes, and pharmacological studies have shown many commonly prescribed drugs can reduce the action of CYP2D6 enzymes. These findings have significant clinical implications for the rational prescription of effective analgesia, especially in a multicultural country like Australia.

High-throughput screening in drug metabolism and pharmacokinetic support of drug discovery

The application of rapid methods currently used for screening discovery drug candidates for metabolism and pharmacokinetic characteristics is discussed. General considerations are given for screening in this context, including the criteria for good screens, the use of counterscreens, the proper sequencing of screens, ambiguity in the interpretation of results, strategies for false positives and negatives, and the special difficulties encountered in drug metabolism and pharmacokinetic screening. Detailed descriptions of the present status of screening are provided for absorption potential, blood-brain barrier penetration, inhibition and induction of cytochrome P450, pharmacokinetics, biotransformation, and computer modeling. Although none of the systems currently employed for drug metabolism and pharmacokinetic screening can be considered truly high-throughput, several of them are rapid enough to be a practical part of the screening paradigm for modern, fast-moving discovery programs.

Progress in predicting human ADME parameters in silico

Understanding the development of a scientific approach is a valuable exercise in gauging the potential directions the process could take in the future. The relatively short history of applying computational methods to absorption, distribution, metabolism and excretion (ADME) can be split into defined periods. The first began in the 1960s and continued through the 1970s with the work of Corwin Hansch et al. Their models utilized small sets of in vivo ADME data. The second era from the 1980s through 1990s witnessed the widespread incorporation of in vitro approaches as surrogates of in vivo ADME studies. These approaches fostered the initiation and increase in interpretable computational ADME models available in the literature. The third era is the present were there are many literature data sets derived from in vitro data for absorption, drug-drug interactions (DDI), drug transporters and efflux pumps [P-glycoprotein (P-gp), MRP], intrinsic clearance and brain penetration, which can theoretically be used to predict the situation in vivo in humans. Combinatorial synthesis, high throughput screening and computational approaches have emerged as a result of continual pressure on pharmaceutical companies to accelerate drug discovery while decreasing drug development costs. The goal has become to reduce the drop-out rate of drug candidates in the latter, most expensive stages of drug development. This is accomplished by increasing the failure rate of candidate compounds in the preclinical stages and increasing the speed of nomination of likely clinical candidates. The industry now understands the reasons for clinical failure other than efficacy are mainly related to pharmacokinetics and toxicity. The late 1990s saw significant company investment in ADME and drug safety departments to assess properties such as metabolic stability, cytochrome P-450 inhibition, absorption and genotoxicity earlier in the drug discovery paradigm. The next logical step in this process is the evaluation of higher throughput data to determine if computational (in silico) models can be constructed and validated from it. Such models would allow an exponential increase in the number of compounds screened virtually for ADME parameters. A number of researchers have started to utilize in silico, in vitro and in vivo approaches in parallel to address intestinal permeability and cytochrome P-450-mediated DDI. This review will assess how computational approaches for ADME parameters have evolved and how they are likely to progress.

Regioselective hydroxylation of debrisoquine by cytochrome P4502D6: implications for active site modelling

1. Debrisoquine, a prototypic probe substrate for human cytochrome P4502D6 (CYP2D6), is hydroxylated at the alicyclic C4-position by this enzyme. Phenolic metabolites of debrisoquine (5-, 6-, 7- and 8-hydroxydebrisoquine) have also been reported as in vivo metabolites, but the role of CYP2D6 in their formation is unclear. 2. As part of studies to develop a predictive model of the active site of CYP2D6 using pharmacophore and homology modelling techniques, it became important to determine the precise regioselective hydroxylation of debrisoquine by CYP2D6. 3. Data from studies with human liver microsomes and yeast microsomes containing cDNA-derived CYP2D6 demonstrated unequivocally that debrisoquine was hydroxylated by CYP2D6 at each aromatic site in the molecule, as well as at the alicyclic 4-position. The four phenolic metabolites amounted to > 60% of the total identified products and the pattern of regioselective hydroxylation (4-HD > 7-HD > 6-HD > 8-HD > 5-HD) was similar in both in vitro systems. 4. A pharmacophore model for CYP2D6 indicated that while the hydroxylation of debrisoquine at alternative positions could arise from the substrate adopting multiple binding orientations, the energy constraints for the aromatic hydroxylations were unfavourable. An alternative proposal involving essentially a single binding orientation and a mechanism of hydroxylation based on benzylic radical spin delocalization could satisfactorily rationalize all the hydroxylations of debrisoquine. 5. This latter proposal demonstrates the need to consider the mechanism of oxidation as well as the spatial orientation of the substrate in the development of a predictive model of the active site of CYP2D6.

Molecular cloning, expression, and characterization of CYP2D17 from cynomolgus monkey liver

The cynomolgus monkey is a species used in drug-safety evaluation and biotransformation studies by the pharmaceutical industry. Relatively little is known, however, about the catalytic activities and specificities of cytochromes P450 (CYP) in this species. As a first step in characterizing monkey CYPs, a cDNA was cloned by reverse-transcriptase PCR from cynomolgus monkey liver mRNA using oligonucleotide primers based on the human CYP2D6 sequence. The full-length cDNA (called CYP2D17) encoded a 497-amino-acid protein that is 93% identical to human CYP2D6 and 90% identical to marmoset CYP2D19. The CYP2D17 cDNA was cloned into a baculovirus expression vector, and microsomes prepared from CYP2D17-infected insect cells were used to determine the catalytic properties of the recombinant enzyme. The recombinant CYP2D17 results were compared to data generated with monkey liver microsomes, human liver microsomes, and recombinant CYP2D6 and demonstrated catalytic similarity using probe substrates and inhibitors. Recombinant CYP2D17 catalyzed the oxidation of bufuralol to 1'-hydroxybufuralol and dextromethorphan to dextrorphan, reactions shown to be mediated by CYP2D6 in humans; the apparent K(m) values for bufuralol and dextromethorphan were 1 and 0.8 microM, respectively. Moreover, both of these reactions were more strongly inhibited by quinidine than by quinine. A more complete understanding of the substrate specificities and activities of monkey CYPs will be advantageous in delineating species differences in metabolite profiles and metabolic activation of new chemical entities in the pharmaceutical industry.