Prediction of sites of metabolism in a substrate molecule, instanced by carbamazepine oxidation by CYP3A4

In drug discovery process, improvement of ADME/Tox properties of lead compounds including metabolic stability is critically important. Cytochrome P450 (CYP) is one of the major metabolizing enzymes and the prediction of sites of metabolism (SOM) on the given lead compounds is key information to modify the compounds to be more stable against metabolism. There are two factors essentially important in SOM prediction. First is accessibility of each substrate atom to the oxygenated Fe atom of heme in a CYP protein, and the other is the oxidative reactivity of each substrate atom. To predict accessibility of substrate atoms to the heme iron, conventional protein-rigid docking simulations have been applied. However, the docking simulations without consideration of protein flexibility often lead to incorrect answers in the case of very flexible proteins such as CYP3A4. In this study, we demonstrated an approach utilizing molecular dynamics (MD) simulation for SOM prediction in which multiple MD runs were executed using different initial structures. We applied this strategy to CYP3A4 and carbamazepine (CBZ) complex. Through 10 ns MD simulations started from five different CYP3A4-CBZ complex models, our approach correctly predicted SOM observed in experiments. The experimentally known epoxidized sites of CBZ by CYP3A4 were successfully predicted as the most accessible sites to the heme iron that was judged from a numerical analysis of calculated ΔG(binding) and the frequency of appearance. In contrast, the predictions using protein-rigid docking methods hardly provided the correct SOM due to protein flexibility or inaccuracy of the scoring functions. Our strategy using MD simulation with multiple initial structures will be one of the reliable methods for SOM prediction.     

Progress in cytochrome P450 active site modeling

Models capable of predicting the possible involvement of cytochromes P450 in the metabolism of drugs or drug candidates are important tools in drug discovery and development. Ideally, functional information would be obtained from crystal structures of all the cytochromes P450 of interest. Initially, only crystal structures of distantly related bacterial cytochromes P450 were available-comparative modeling techniques were used to bridge the gap and produce structural models of human cytochromes P450, and thereby obtain some useful functional information. A significant step forward in the reliability of these models came four years ago with the first crystal structure of a mammalian cytochrome P450, rabbit CYP2C5, followed by the structures of two human enzymes, CYP2C8 and CYP2C9, and a second rabbit enzyme, CYP2B4. The evolution of a CYP2D6 model, leading to the validation of the model as an in silico tool for predicting binding and metabolism, is presented as a case study.     

Essential requirements for substrate binding affinity and selectivity toward human CYP2 family enzymes

A detailed analysis of substrate selectivity within the cytochrome P450 2 (CYP2) family is reported. From a consideration of specific interactions between drug substrates for human CYP2 family enzymes and the putative active sites of CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, and CYP2E1, it is likely that the number and disposition of hydrogen bond donor/acceptors and aromatic rings within the various P450 substrate molecules determines their enzyme selectivity and binding affinity, together with directing their preferred routes of metabolism by the CYP2 enzymes concerned. Although many aliphatic residues are present in most P450 active sites, it would appear that their main contribution centers around hydrophobic interactions and desolvation processes accompanying substrate binding. Molecular modeling studies based on the recent CYP2C5 crystal structure appear to show close agreement with site-directed mutagenesis experiments and with information on substrate metabolism and selectivity within the CYP2 family.     

Structural and functional insights into polymorphic enzymes of cytochrome P450 2C8

The cytochrome P450 (CYP) superfamily plays a key role in the oxidative metabolism of a wide range of drugs and exogenous chemicals. CYP2C8 is the principal enzyme responsible for the metabolism of the anti-cancer drug paclitaxel in the human liver. Nearly all previous works about polymorphic variants of CYP2C8 were focused on unpurified proteins, either cells or human liver microsomes; therefore their structure–function relationships were unclear. In this study, two polymorphic enzymes of CYP2C8 (CYP2C8.4 (I264M) and CYP2C8 P404A) were expressed in E. coli and purified. Metabolic activities of paclitaxel by the two purified polymorphic enzymes were observed. The activity of CYP2C8.4 was 25% and CYP2C8 P404A was 30% of that of WT CYP2C8, respectively. Their structure–function relationships were systematically investigated for the first time. Paclitaxel binding ability of CYP2C8.4 increased about two times while CYP2C8 P404A decreased about two times than that of WT CYP2C8. The two polymorphic mutant sites of I264 and P404, located far from active site and substrate binding sites, significantly affect heme and/or substrate binding. This study indicated that two important nonsubstrate recognition site (SRS) residues of CYP2C8 are closely related to heme binding and/or substrate binding. This discovery could be valuable for explaining clinically individual differences in the metabolism of drugs and provides instructed information for individualized medication.     

Transfer learning for cytochrome P450 isozyme selectivity prediction

In the drug discovery process, the metabolic fate of drugs is crucially important to prevent drug-drug interactions. Therefore, P450 isozyme selectivity prediction is an important task for screening drugs of appropriate metabolism profiles. Recently, large-scale activity data of five P450 isozymes (CYP1A2 CYP2C9, CYP3A4, CYP2D6, and CYP2C19) have been obtained using quantitative high-throughput screening with a bioluminescence assay. Although some isozymes share similar selectivities, conventional supervised learning algorithms independently learn a prediction model from each P450 isozyme. They are unable to exploit the other P450 isozyme activity data to improve the predictive performance of each P450 isozyme's selectivity. To address this issue, we apply transfer learning that uses activity data of the other isozymes to learn a prediction model from multiple P450 isozymes. After using the large-scale P450 isozyme selectivity dataset for five P450 isozymes, we evaluate the model's predictive performance. Experimental results show that, overall, our algorithm outperforms conventional supervised learning algorithms such as support vector machine (SVM), Weighted k-nearest neighbor classifier, Bagging, Adaboost, and latent semantic indexing (LSI). Moreover, our results show that the predictive performance of our algorithm is improved by exploiting the multiple P450 isozyme activity data in the learning process. Our algorithm can be an effective tool for P450 selectivity prediction for new chemical entities using multiple P450 isozyme activity data.     

Combination of docking,molecular dynamics and quantum mechanical calculations for metabolism prediction of 3,4-methylenedioxybenzoyl-2-thienylhydrazone

In modern drug discovery process, ADME/Tox properties should be determined as early as possible in the test cascade to allow a timely assessment of their property profiles. To help medicinal chemists in designing new compounds with improved pharmacokinetics, the knowledge of the soft spot position or the site of metabolism (SOM) is needed. In silico methods based on docking, molecular dynamics and quantum chemical calculations can bring us closer to understand drug metabolism and predict drug–drug interactions. We report herein on a combined methodology to explore the site of metabolism prediction of a new cardioactive drug prototype, LASSBio-294 (1), using MetaPrint2D to predict the most likely metabolites, combined with structure-based tools using docking, molecular dynamics and quantum mechanical calculations to predict the binding of the substrate to CYP2C9 enzyme, to estimate the binding free energy and to study the energy profiles for the oxidation of (1). Additionally, the computational study was correlated with a metabolic fingerprint profiling using LC-MS analysis. The results obtained using the computational methods gave valuable information about the probable metabolites of (1) (qualitatively) and also about the important interactions of this lead compound with the amino acid residues of the active site of CYP2C9. Moreover, using a combination of different levels of theory sheds light on the understanding of (1) metabolism by CYP2C9 and its mechanisms. The metabolic fingerprint profiling of (1) has shown that the metabolites founded in highest concentration in different species were metabolites M1, M2 and M3, whereas M8 was found to be a minor metabolite. Therefore, our computational study allowed a qualitative prediction for the metabolism of (1). The approach presented here has afforded new opportunities to improve metabolite identification strategies, mediated by not only CYP2C9 but also other CYP450 family enzymes.     

细胞色素P450基因多态性与药物代谢研究进展

细胞色素P450（cytochrome P450,CYP450）在人体药物代谢过程中起着非常重要的作用并参与代谢80%以上的临床药物。由于CYP450在不同种族和不同人群中存在基因多态性,从而造成药物反应的个体差异,一度成为药物基因组学研究的热点。通过查阅国外相关文献,综述了近年来关于CYP1A2、CYP2C9、CYP2C19、CYP2D6和CYP3A4五种主要的药物代谢酶的基因多态性和药物代谢的研究进展,为临床指导个体化用药、避免药物不良反应和新药研发提供科学参考依据。     

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

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

Comparative cytochrome P450 proteomics in the livers of immunodeficient mice using 18O stable isotope labeling

Quantitative changes in cytochrome P450 (CYP) proteins involved in drug metabolism as a consequence of drug treatment are important parameters in predicting the fates and pharmacological consequences of xenobiotics and drugs. In this study we undertook comparative P450 proteomics using liver from control and 1,4-bis-2-(3,5-dichloropyridyloxybenzene) (TCPOBOP)-dosed mice. The method involved separation of microsomal proteins by SDS-PAGE, trypsin digestion, and postdigest 18O/16O labeling followed by nano-LC-MS/MS for peptide identification and LC-MS for relative quantification. Seventeen P450 proteins were identified from mouse liver of which 16 yielded data sufficient for relative quantification. All the P450s detected were unambiguously identified except the highly homologous CYP2A4/2A5. With the exception of CYP2A12, -2D10, and -2F2, the levels of all the P450s quantified were affected by treatment with TCPOBOP (3 mg/kg). CYP1A2, -2A4/5, -2B10, -2B20, -2C29, -2C37, -2C38, -3A11, and -39A1 were up-regulated, and CYP2C40, -2E1, -3A41, and -27A1 down-regulated. The response of CYP2B20 to stimulation has not been distinguished previously from that of CYP2B10 because of the poor discrimination between these two proteins (they share 87% sequence identity). Differential response to chemical stimulation by closely related members of the CYP2C subfamily was also observed.     

The influence of cytochrome P450 pharmacogenetics on disposition of common antidepressant and antipsychotic medications

Since the identification of all the major drug-metabolising cytochrome P450 (CYP) enzymes and their major gene variants, pharmacogenetics has had a major impact on psychotherapeutic drug therapy. CYP enzymes are responsible for the metabolism of most clinically used drugs. Individual variability in CYP activity is an important reason for drug therapy failure. Variability in CYP activity may be caused by various factors, including endogenous factors such as age, gender and morbidity as well as exogenous factors such as co-medication, food components and smoking habit. However, polymorphisms, present in most CYP genes, are responsible for a substantial part of this variability. Although CYP genotyping has been shown to predict the majority of aberrant phenotypes, it is currently rarely performed in clinical practice.     

Mutation probability of cytochrome P450 based on a genetic algorithm and support vector machine

The support vector machine (SVM), an effective statistical learning method, has been widely used in mutation prediction. Two factors, i.e., feature selection and parameter setting, have shown great influence on the efficiency and accuracy of SVM classification. In this study, according to the principles of a genetic algorithm (GA) and SVM, we developed a GA-SVM program and applied it to human cytochrome P450s (CYP450s), which are important monooxygenases in phase I drug metabolism. The program optimizes features and parameters simultaneously, and hence fewer features are used and the overall prediction accuracy is improved. We focus on the mutation of non-synonymous single nucleotide polymorphisms (nsSNPs) in protein sequences that appear to exhibit significant influences on drug metabolism. The final predictive model has a quite satisfactory performance, with the prediction accuracy of 61% and cross-validation accuracy of 73%. The results indicate that the GA-SVM program is a powerful tool in optimizing mutation predictive models of nsSNPs of human CYP450s.     

Drugs impact on CYP-450 enzyme family: A pharmacogenetical study of response variation

Pharmacogenetics is the study of genetic basis in the individual response to drugs. A thorough knowledge of this will lead to a future where tailor-made drugs, suiting an individual, can be used. Scandinavian countries have been known for wide usage of pharmacogenetics and the most widely used application is for genotyping CYP2D6 in treating psychiatric illness. The CYP-450 enzyme, a super family of microsomal drug-metabolizing enzymes, is the most important of enzymes that catalyzes phase-I drug metabolism reaction. CYP2D6 is a member of this family and it has been most intensively studied and the best example of pharmacogenetics variation in drug metabolism. Neuro-transmitter and drug acting CNS viz. codeine, dextromethorphan, metoprolol and tryptyline etc. are well metabolized by this enzyme. Thus, CYP2D6 is one of the most important and responsible enzymes which regulates bioavailability and metabolism of drug. Presently 75 alleles of CYP2D6 have been described which are responsible for variance of metabolism and toxicity of drugs. Thus, by determining variance of CYP2D6 using molecular approaches viz., PCR, real-time PCR, DNA micro-array and molecular docking can determine the adverse effects, drug toxicity, bioavailability and therapeutic potential of new drug.     

Targeting cytochrome P450 enzymes: a new approach in anti-cancer drug development

Cytochrome P450s (CYPs) represent a large class of heme-containing enzymes that catalyze the metabolism of multitudes of substrates both endogenous and exogenous. Until recently, however, CYPs have been largely overlooked in cancer drug development, acknowledged only for their role in phase I metabolism of chemotherapeutics. The first successful strategy targeting CYP enzymes in cancer therapy was the development of potent inhibitors of CYP19 (aromatase) for the treatment of breast cancer. Aromatase inhibitors ushered in a new era in hormone ablation therapy for estrogen dependent cancers, and have paved the way for similar strategies (i.e., inhibition of CYP17) that combat androgen dependent prostate cancer. Identification of CYPs involved in the inactivation of anti-cancer metabolites of vitamin D(3) and vitamin A has triggered development of agents that target these enzymes as well. The discovery of the over-expression of exogenous metabolizing CYPs, such as CYP1B1, in cancer cells has roused interest in the development of inhibitors for chemoprevention and of prodrugs designed to be activated by CYPs only in cancer cells. Finally, the expression of CYPs within tumors has been utilized in the development of bioreductive molecules that are activated by CYPs only under hypoxic conditions. This review offers the first comprehensive analysis of strategies in drug development that either inhibit or exploit CYP enzymes for the treatment of cancer.     

微生物细胞色素P450与胆固醇的生物代谢

细胞色素P450(CYP450)是一类含亚铁血红素的单加氧酶,广泛存在于各类生物体内,参与多种外源物质的代谢和内源物质的转化,如甾类激素、胆汁酸、胆固醇等的代谢。胆固醇是一种环戊烷多氢菲的衍生物,也是人类重要的脂类物质和许多特殊生物活性物质的前体之一,当其过量时会导致高胆固醇血症、动脉粥样硬化、静脉血栓生成等,对机体产生不利的影响。微生物CYP450酶可催化胆固醇的生物代谢,特别是其中的CYP125酶是胆固醇分解代谢起始的关键酶,可用作调节胆固醇代谢的药物靶标。     

Specific human CYP 450 isoform metabolism of a pentachlorobiphenyl (PCB-IUPAC# 101)

Polychlorinated biphenyl IUPAC# 101-PCB 101 (chlorination pattern-2,2',4',5,5') is a common, persistent non-coplanar PCB congener found in the ambient environment but information related to its metabolism in humans is lacking. Previous studies indicate PCB 101 is rapidly metabolized in mammals through CYP 2B and 3A family enzymes. Recently, PCB metabolism through a 2A family isoform in hamsters was also reported. To specifically identify the human CYP 450 isoforms responsible for PCB 101 metabolism, we compared human microsome metabolism to metabolism using several specific recombinant human CYP isoforms. These data characterized selective and extensive metabolism by human CYP 2A6. The product formed was the 4-hydroxy-PCB 101 metabolite (4-hydroxy-2,2',4',5,5') and was the only major metabolite observed in the recombinant and human microsome investigation. This is important information for predicting human specific toxicokinetics of PCBs.     

Development of a whole-cell screening system for evaluation of the human CYP1A2-mediated metabolism

Cytochrome P450 1A2 (CYP1A2) is an important member of cytochrome P450 involved in drug metabolism. In this study, a cell line, Huh7-1A2-I-E, with high expression level of CYP1A2 is established based on Huh7 cells. To achieve this, we constructed a recombinant lentiviral vector, pLenti-1A2-I-E, containing a single promoter encoding CYP1A2 followed by an internal ribosome entry site (IRES) to permit the translation of enhanced green fluorescence protein (EGFP). Such a design has greatly facilitated the selection of stable cell lines because the translations of CYP1A2 and EGFP proteins would be based on a single bi-cistronic mRNA. The Huh7-1A2-I-E cells were evaluated as a cell-based model for identification of CYP1A2 inhibitors and for studies of cytotoxicity resulted from CYP-mediated drug metabolism. Treatment of Huh7-1A2-I-E cells and the Huh7-E control cells with aflatoxin B1 showed that cells with CYP1A2 expression are much more sensitive to aflatoxin B1 and the cellular toxicity of aflatoxin B1 in Huh7-1A2-I-E cells could be prevented by furafylline, a CYP1A2 inhibitor. A collection of approximately 200 drugs were screened using this system and results indicate that for most drugs the metabolism by CYP1A2 is unlikely to have made a major contribution to the in vitro cytotoxicity except for thimerosal and evoxine. Several previously unidentified CYP1A2 inhibitors such as evoxine and berberine were also identified in this study.     

Characterization of Phase I and Phase II hepatic drug metabolism activities in a panel of human liver preparations.

The role of drug metabolism in drug discovery (lead compound selection) and the traditional role of identifying the enzymes involved in biotransformation pathways (reaction phenotyping) have both relied heavily on the availability and use of a human liver bank. The assessment of drug metabolizing enzyme activity and variability in a series of individual human livers is essential when characterizing the enzymes involved in metabolic pathways (i.e. correlation analysis). In this regard, a human liver bank of 21 samples (14 males, six females, and one unknown) was characterized with respect to the activity of several important drug metabolizing enzymes. The total CYP450 content of the livers ranged from 0.06 to 0.46 nmol/mg microsomal protein. The fold variations found in specific enzyme contents were as follows: CYP1A2 (3x), CYP2A6 (21x), CYP2C9 (8x), CYP2C19 (175x), CYP2D6 (18x), CYP2E1 (5x), CYP3A4 (18x), FMO (2.5x), UDPGT (4x), NAT (7x), COMT (5x), ST (5x), TPMT (3x), and GST (2.5x). In general, the fold variation of the Phase II enzymes was lower compared with the Phase I enzymes, with the exceptions of CYP1A2, CYP2E1, and FMO. Similar data were reviewed from other established liver banks and compared with regard to the relative variability observed in drug metabolizing capacities found in this study.     

Use of electrospray ionization liquid chromatography-mass spectrometry to study the role of CYP2D^ in the in vitro metabolism of 5-hydroxytryptamine receptor antagonists

An electrospray ionization liquid chromatographic-mass spectrometric (ESI-LC-MS) method has been developed to study the involvement of the cytochrome P450 isoenzyme CYP2D6 in the in vitro metabolism of the indole containing 5-hydroxytryptamine (5-HT₃) receptor antagonists tropisetron, ondansetron and dolasetron in human liver microsomes. Compounds were eluted using linear gradients of acetonitrile-20 mM ammonium acetate, solvent A, (10:90, v/v) (ph 6.0) and solvent B, (60:40, v/v) (pH 6.0) and a Nucleosil C₄ column. Microsomal incubations were analysed using selected ion monitoring of the molecular ion of parent drug and the molecular ion of hydroxylated metabolites. The involvement of CYP2D6 in drug metabolism was assessed by inhibition studies using quinidine (5 μM), a specific inhibitor of human CYP2D6, as well as by incubating compounds with microsomes prepared from celss transfected with cDNA encoding human CYP2D6. Results showed that the oxidation of all three compounds involved CYP2D6, but only that of tropisetron was inhibited by over 90% in the presence of quinidine. The present method can be applied to pre-clinical compounds, at an early stage of drug discovery, to assess the involvement of CYP2D6 in their metabolism and to screen for those compounds where CYP2D6 is the only isoenzyme implicated in the formation of major metabolites.     

A quantitative high-throughput 96-well plate fluorescence assay for mechanism-based inactivators of cytochromes P450 exemplified using CYP2B6

Mechanism-based inactivators such as bergamottin are useful chemical tools for identifying the functions of specific active-site amino acid residues in the reactions catalyzed by cytochromes P450 (CYPs or P450s), which are responsible for the metabolism of a wide variety of drugs and endogenous substrates. In clinical settings, mechanism-based inactivation of P450s involved in xenobiotic metabolism has the potential to lead to adverse drug-drug interactions, and assays to identify and characterize drug candidates as P450 inactivators are important in drug discovery and development. Here we present a quantitative high-throughput protocol for investigating cytochrome P450 mechanism-based inactivators; we use the example of CYP2B6 and bergamottin to illustrate the finer points of this protocol. This protocol details the adaptation of a 7-ethoxytrifluoromethyl coumarin O-deethylation fluorescence activity assay to a 96-well microtiter plate format and uses a plate reader to detect the fluorescence of the product. Compared with previous methods, this protocol requires less P450 and takes significantly less time while greatly increasing throughput. The protocol as written takes ～2 h to complete. The principles and procedures outlined in this protocol can be easily adapted to other inactivators, P450 isoforms, substrates and plate readers.     

Machine learning-driven identification of drugs inhibiting cytochrome P450 2C9

Cytochrome P450 2C9 (CYP2C9) is a major drug-metabolizing enzyme that represents 20% of the hepatic CYPs and is responsible for the metabolism of 15% of drugs. A general concern in drug discovery is to avoid the inhibition of CYP leading to toxic drug accumulation and adverse drug–drug interactions. However, the prediction of CYP inhibition remains challenging due to its complexity. We developed an original machine learning approach for the prediction of drug-like molecules inhibiting CYP2C9. We created new predictive models by integrating CYP2C9 protein structure and dynamics knowledge, an original selection of physicochemical properties of CYP2C9 inhibitors, and machine learning modeling. We tested the machine learning models on publicly available data and demonstrated that our models successfully predicted CYP2C9 inhibitors with an accuracy, sensitivity and specificity of approximately 80%. We experimentally validated the developed approach and provided the first identification of the drugs vatalanib, piriqualone, ticagrelor and cloperidone as strong inhibitors of CYP2C9 with IC values <18 μM and sertindole, asapiprant, duvelisib and dasatinib as moderate inhibitors with IC50 values between 40 and 85 μM. Vatalanib was identified as the strongest inhibitor with an IC50 value of 0.067 μM. Metabolism assays allowed the characterization of specific metabolites of abemaciclib, cloperidone, vatalanib and tarafenacin produced by CYP2C9. The obtained results demonstrate that such a strategy could improve the prediction of drug-drug interactions in clinical practice and could be utilized to prioritize drug candidates in drug discovery pipelines.