Exploration of enzyme-ligand interactions in CYP2D6 & 3A4 homology models and crystal structures using a novel computational approach

New crystal structures of human CYP2D6 and CYP3A4 have recently been reported, and in this study, we wanted to compare them with previously used homology models with respect to predictions of site of metabolism and ligand-enzyme interactions. The data set consisted of a family of synthetic opioid analgesics with the aim to cover both CYP2D6 and CYP3A4, as most of these compounds are metabolized by both isoforms. The program MetaSite was used for the site of metabolism predictions, and the results were validated by experimental assessment of the major metabolites formed with recombinant CYP450s. This was made on a selection of 14 compounds in the data set. The prediction rates for MetaSite were 79-100% except for the CYP3A4 homology model, which picked the correct site in half of the cases. Despite differences in orientation of some important amino acids in the active sites, the MetaSite-predicted sites were the same for the different structures, with the exception of the CYP3A4 homology model. Further exploration of interactions with ligands was done by docking substrates/inhibitors in the different structures with the docking program GLUE. To address the challenge in interpreting patterns of enzyme-ligand interactions for the large number of different docking poses, a new computational tool to handle the results from the dockings was developed, in which the output highlights the relative importance of amino acids in CYP450-substrate/inhibitor interactions. The method is based on calculations of the interaction energies for each pose with the surrounding amino acids. For the CYP3A4 structures, this method was compared with consensus principal component analysis (CPCA), a commonly used method for structural comparison to evaluate the usefulness of the new method. The results from the two methods were comparable with each other, and the highlighted amino acids resemble those that were identified to have a different orientation in the compared structures. The new method has clear advantages over CPCA in that it is far simpler to interpret and there is no need for protein alignment. The methodology enables structural comparison but also gives insights on important amino acid substrate/inhibitor interactions and can therefore be very useful when suggesting modifications of new chemical entities to improve their metabolic profiles.     

2D SMARTCyp reactivity-based site of metabolism prediction for major drug-metabolizing cytochrome P450 enzymes

Cytochrome P450 (CYP) 3A4, 2D6, 2C9, 2C19, and 1A2 are the most important drug-metabolizing enzymes in the human liver. Knowledge of which parts of a drug molecule are subject to metabolic reactions catalyzed by these enzymes is crucial for rational drug design to mitigate ADME/toxicity issues. SMARTCyp, a recently developed 2D ligand structure-based method, is able to predict site-specific metabolic reactivity of CYP3A4 and CYP2D6 substrates with an accuracy that rivals the best and more computationally demanding 3D structure-based methods. In this article, the SMARTCyp approach was extended to predict the metabolic hotspots for CYP2C9, CYP2C19, and CYP1A2 substrates. This was accomplished by taking into account the impact of a key substrate-receptor recognition feature of each enzyme as a correction term to the SMARTCyp reactivity. The corrected reactivity was then used to rank order the likely sites of CYP-mediated metabolic reactions. For 60 CYP1A2 substrates, the observed major sites of CYP1A2 catalyzed metabolic reactions were among the top-ranked 1, 2, and 3 positions in 67%, 80%, and 83% of the cases, respectively. The results were similar to those obtained by MetaSite and the reactivity + docking approach. For 70 CYP2C9 substrates, the observed sites of CYP2C9 metabolism were among the top-ranked 1, 2, and 3 positions in 66%, 86%, and 87% of the cases, respectively. These results were better than the corresponding results of StarDrop version 5.0, which were 61%, 73%, and 77%, respectively. For 36 compounds metabolized by CYP2C19, the observed sites of metabolism were found to be among the top-ranked 1, 2, and 3 sites in 78%, 89%, and 94% of the cases, respectively. The computational procedure was implemented as an extension to the program SMARTCyp 2.0. With the extension, the program can now predict the site of metabolism for all five major drug-metabolizing enzymes with an accuracy similar to or better than that achieved by the best 3D structure-based methods. Both the Java source code and the binary executable of the program are freely available to interested users.     

Regioselectivity prediction of CYP1A2-mediated phase I metabolism

A kinetic, reactivity-binding model has been proposed to predict the regioselectivity of substrates meditated by the CYP1A2 enzyme, which is responsible for the metabolism of planar-conjugated compounds such as caffeine. This model consists of a docking simulation for binding energy and a semiempirical molecular orbital calculation for activation energy. Possible binding modes of CYP1A2 substrates were first examined using automated docking based on the crystal structure of CYP1A2, and binding energy was calculated. Then, activation energies for CYP1A2-mediated metabolism reactions were calculated using the semiempirical molecular orbital calculation, AM1. Finally, the metabolic probability obtained from two energy terms, binding and activation energies, was used for predicting the most probable metabolic site. This model predicted 8 out of 12 substrates accurately as the primary preferred site among all possible metabolic sites, and the other four substrates were predicted into the secondary preferred site. This method can be applied for qualitative prediction of drug metabolism mediated by CYP1A2 and other CYP450 family enzymes, helping to develop drugs efficiently.     

Using a homology model of cytochrome P450 2D6 to predict substrate site of metabolism

CYP2D6 is an important enzyme that is involved in first pass metabolism and is responsible for metabolizing ~25% of currently marketed drugs. A homology model of CYP2D6 was built using X-ray structures of ligand-bound CYP2C5 complexes as templates. This homology model was used in docking studies to rationalize and predict the site of metabolism of known CYP2D6 substrates. While the homology model was generally found to be in good agreement with the recently solved apo (ligand-free) X-ray structure of CYP2D6, significant differences between the structures were observed in the B′ and F–G helical region. These structural differences are similar to those observed between ligand-free and ligand-bound structures of other CYPs and suggest that these conformational changes result from induced-fit adaptations upon ligand binding. By docking to the homology model using Glide, it was possible to identify the correct site of metabolism for a set of 16 CYP2D6 substrates 85% of the time when the 5 top scoring poses were examined. On the other hand, docking to the apo CYP2D6 X-ray structure led to a loss in accuracy in predicting the sites of metabolism for many of the CYP2D6 substrates considered in this study. These results demonstrate the importance of describing substrate-induced conformational changes that occur upon binding. The best results were obtained using Glide SP with van der Waals scaling set to 0.8 for both the receptor and ligand atoms. A discussion of putative binding modes that explain the distribution of metabolic sites for substrates, as well as a relationship between the number of metabolic sites and substrate size, are also presented. In addition, analysis of these binding modes enabled us to rationalize the typical hydroxylation and O-demethylation reactions catalyzed by CYP2D6 as well as the less common N-dealkylation.     

Drug disposition of chiral and achiral drug substrates metabolized by cytochrome P450 2D6 isozyme: case studies, analytical perspectives and developmental implications

The concepts of drug development have evolved over the last few decades. Although number of novel chemical entitities belonging to varied classes have made it to the market, the process of drug development is challenging, intertwined as it is with complexities and uncertainities. The intention of this article is to provide a comprehensive review of novel chemical entities (NCEs) that are substrates to cytochrome P450 (CYP) 2D6 isozyme. Topics covered in this review aim: (1) to provide a framework of the importance of CYP2D6 isozyme in the biotransformation of NCEs as stand-alones and/or in conjunction with other CYP isozymes; (2) to provide several case studies of drug disposition of important drug substrates, (3) to cover key analytical perspectives and key assay considerations to assess the role and involvement of CYP2D6, and (4) to elaborate some important considerations from the development point of view. Additionally, wherever applicable, special emphasis is provided on chiral drug substrates in the various subsections of the review.     

Characterization of the CYP3A4 active site by homology modeling

Human microsomal cytochrome P450s participate in drug metabolism and detoxification. Among them, CYP3A4 is the most important isoform for drug-drug interactions. To gain a better understanding of the active site, a homology model of CYP3A4 was constructed based on the crystallographic coordinates of mammalian CYP2C5. The putative active site is much larger than that of CYP2C5 and is divided into three parts (i.e. a proximal and two distal sites from the heme). Most residues reported to be important for ligand-binding are located in the active site of the model. Moreover, some inhibitors (paclitaxel etc.) docked into the model have complementary shapes to the pocket. Pharmacophore docking of 14 substrates was also performed using Ph4Dock of MOE. Calculated interaction energies showed a moderate correlation with the logarithm of apparent K(m) values. These results suggest that this model is reliable enough to be used in the design of compounds for removing undesirable CYP3A4 inhibition.     

Validation of higher-throughput high-performance liquid chromatography/atmospheric pressure chemical ionization tandem mass spectrometry assays to conduct cytochrome P450s CYP2D6 and CYP3A4 enzyme inhibition studies in human liver microsomes

In the early stage of drug discovery, thousands of new chemical entities (NCEs) may be screened before a single drug candidate can be identified for development. In order to accelerate the drug discovery process, we have developed higher-throughput enzyme assays to evaluate the inhibition of cytochrome P450 isoforms 2D6 (CYP2D6) and 3A4 (CYP3A4) in human liver microsomes. The assays are based on high-performance liquid chromatography/tandem mass spectrometry (LC/MS/MS) techniques. The analysis time for each sample was reduced from approximately 20 minutes for the conventional HPLC assay to 30 seconds for the LC/MS/MS assay. For both LC/MS/MS assays, the linearity (r(2) > 0.99), precision (%CV < 15%) and accuracy (% bias <15%) for both inter- and intraday validations were satisfactory. Since the implementation of the LC/MS/MS assays, our sample throughput has increased by over 40-fold.     

一种细胞色素P4502C8基因多态-CYP2C8.3的结构和功能

细胞色素P450超级家族在代谢众多的外源性化学物质方面发挥重要的作用.细胞色素P4502C8是人体肝脏中主要负责代谢抗癌药物紫杉醇的酶,它至少负责代谢5%的临床药物.细胞色素P450 2C8的基因多态性与用药个体化有着密切的关系.CYP2C8.3是常见的P450 2C8的基因多态之一,其发生了双点突变,分别是R139K...     

Synergistic use of compound properties and docking scores in neural network modeling of CYP2D6 binding: predicting affinity and conformational sampling

Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known active site. Docking scores for the active site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85+/-6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.     

Structural and functional insights into CYP2C8.3: A genetic polymorph of cytochrome P450 2C8

The cytochrome P450 (CYP) superfamily plays a key role in the oxidative metabolism of a wide range of exogenous chemicals. CYP2C8 is the principal enzyme responsible for the metabolism of the anti-cancer drug paclitaxel in the human liver, and carries out the oxidative metabolism of at least 5% of clinical drugs. Polymorphisms in CYP2C8 have been closely implicated in individualized medication. CYP2C8.3, a common polymorph of CYP2C8 with dual amino acid substitutions R139K and K399R, is found primarily in Caucasians. In this study, CYP2C8.3 and its wild type (WT) CYP2C8 were expressed in E. coli, and their purified proteins were characterized by UV-visible spectroscopy, mass spectrometry, and circular dichroism. Their thermal stability, substrate binding ability, and metabolic activity against paclitaxel were investigated. The electron transfer kinetics during paclitaxel metabolism by WT CYP2C8 or CYP2C8.3 was studied by stopped-flow kinetics. The results revealed that mutations in CYP2C8.3 did not greatly influence the heme active site or protein thermal stability and paclitaxel binding ability, but the metabolic activity against paclitaxel was significantly depressed to just 11% of that of WT CYP2C8. Electron transfer from CYP reductase to CYP2C8.3 was found to be significantly slower than that to WT CYP2C8 during catalysis, and this might be the main reason for the depressed metabolic activity. Since the polymorph CYP2C8.3 is defective in catalyzing substrates of CYP2C8 in vitro, it might be expected to have important clinical and pathophysiological consequences in homozygous individuals, and this study provides valuable information in this aspect.     

Prediction of cytochrome P450 3A4, 2D6, and 2C9 inhibitors and substrates by using support vector machines

Statistical learning methods have been used in developing filters for predicting inhibitors of two P450 isoenzymes, CYP3A4 and CYP2D6. This work explores the use of different statistical learning methods for predicting inhibitors of these enzymes and an additional P450 enzyme, CYP2C9, and the substrates of the three P450 isoenzymes. Two consensus support vector machine (CSVM) methods, "positive majority" (PM-CSVM) and "positive probability" (PP-CSVM), were used in this work. These methods were first tested for the prediction of inhibitors of CYP3A4 and CYP2D6 by using a significantly higher number of inhibitors and noninhibitors than that used in earlier studies. They were then applied to the prediction of inhibitors of CYP2C9 and substrates of the three enzymes. Both methods predict inhibitors of CYP3A4 and CYP2D6 at a similar level of accuracy as those of earlier studies. For classification of inhibitors of CYP2C9, the best CSVM method gives an accuracy of 88.9% for inhibitors and 96.3% for noninhibitors. The accuracies for classification of substrates and nonsubstrates of CYP3A4, CYP2D6, and CYP2C9 are 98.2 and 90.9%, 96.6 and 94.4%, and 85.7 and 98.8%, respectively. Both CSVM methods are potentially useful as filters for predicting inhibitors and substrates of P450 isoenzymes. These methods generally give better accuracies than single SVM classification systems, and the performance of the PP-CSVM method is slightly better than that of the PM-CSVM method.     

Homology modeling, binding site identification and docking in flavone hydroxylase CYP105P2 in Streptomyces peucetius ATCC 27952

Homology models of cytochrome P450 105P2 (CYP105P2) were constructed using four P450 structures, CYP105A1, CYP105, CYP165B3 and CYP107L1, as templates for the model building. Using Accelrys Discovery Studio 2.1 software, the lowest energy CYP105P2 model was then assessed for stereochemical quality and side-chain environment. Further active site optimization of the CYP105P2 model built using these templates was performed by molecular dynamics to generate the final CYP105P2 model. The substrates, flavone, flavanone, quercetin and naringenin, were docked into the model. The model-flavone complex was used to validate the active site architecture, and structurally and functionally important residues were identified by subsequent characterization of the secondary structure.     

Site of metabolism prediction on cytochrome P450 2C9: a knowledge-based docking approach

A novel structure-based approach for site of metabolism prediction has been developed. This knowledge-based method consists of three steps: (1) generation of possible metabolites, (2) docking the predicted metabolites to the CYP binding site and (3) selection of the most probable metabolites based on their complementarity to the binding site. As a proof of concept we evaluated our method by using MetabolExpert for metabolite generation and Glide for docking into the binding site of the CYP2C9 crystal structure. Our method could identify the correct metabolite among the three best-ranked compounds in 69% of the cases. The predictive power of our knowledge-based method was compared to that achieved by substrate docking and two alternative literature approaches.     

Simultaneous detection of single nucleotide polymorphisms and copy number variations in the CYP2D6 gene by multiplex polymerase chain reaction combined with capillary electrophoresis

CYP2D6 (cytochrome P450 2D6) is one of the most important enzymes involved in drug metabolism, and CYP2D6 gene variants may cause toxic effects of therapeutic drugs or treatment failure. In this research, a rapid and simple method for genotyping the most common mutant alleles in the Asian population (CYP2D6*1/*1, CYP2D6*1/*10, CYP2D6*10/*10, CYP2D6*1/*5, CYP2D6*5/*10, and CYP2D6*5/*5) was developed by allele-specific polymerase chain reaction (AS-PCR) combined with capillary electrophoresis (CE). We designed a second mismatch nucleotide next to the single nucleotide polymorphism (SNP) site in allele-specific primers to increase the difference in PCR amplification. Besides, we established simulation equations to predict the CYP2D6 genotypes by analyzing the DNA patterns in the CE chromatograms. The multiplex PCR combined with CE method was applied to test 50 patients, and all of the test results were compared with the DNA sequencing method, long-PCR method and real-time PCR method. The correlation of the analytical results between the proposed method and other methods were higher than 90%, and the proposed method is superior to other methods for being able to simultaneous detection of SNPs and copy number variations (CNV). Furthermore, we compared the plasma concentration of aripiprazole (a CYP2D6 substrate) and its major metabolites with the genotype of 25 patients. The results demonstrate the proposed genotyping method is effective for estimating the activity of the CYP2D6 enzyme and shows potential for application in personalized medicine. Similar approach can be applied to simultaneous detection of SNPs and CNVs of other genes.     

Rapid genotyping of CYP2D6, CYP2C19 and TPMT polymorphisms by primer extension reaction in a dipstick format

In recent years an increasing amount of interest has been directed at the study and routine testing of polymorphisms responsible for variations in drug metabolism. Most of the current methods involve either time-consuming electrophoresis steps or specialized and expensive equipment. In this context, we have developed a rapid, simple and robust method for genotyping of CYP2D6*3, CYP2D6*4, CYP2C19*2, CYP2C19*3 and TPMT*2 single nucleotide polymorphisms (SNP). Genomic DNA is isolated from whole blood and the segments that span the SNP of interest are amplified by PCR. The products are subjected directly (without purification) to two primer extension (PEXT) reactions (three cycles each) using normal and mutant primers in the presence of biotin-dUTP. The PEXT primers contain a (dA)₃₀ segment at the 5′ end. The PEXT products are detected visually by a dry-reagent dipstick-type assay in which the biotinylated extension products are captured from immobilized streptavidin on the test zone of the strip and detected by hybridization with oligo(dT)-functionalized gold nanoparticles. Patient samples (76 variants in total) were genotyped and the results were fully concordant with those obtained by direct DNA sequencing.