State-of-the-art tools for computational site of metabolism predictions: comparative analysis, mechanistical insights, and future applications

In drug design, it is crucial to have reliable information on how a chemical entity behaves in the presence of metabolizing enzymes. This requires substantial experimental efforts. Consequently, being able to predict the likely site/s of metabolism in any compound, synthesized or virtual, would be highly beneficial and time efficient. In this work, six different methodologies for predictions of the site of metabolism (SOM) have been compared and validated using structurally diverse data sets of drug-like molecules with well-established metabolic pattern in CYP3A4, CYP2C9, or both. Three of the methods predict the SOM based on the ligand's chemical structure, two additional methods use structural information of the enzymes, and the sixth method combines structure and ligand similarity and reactivity. The SOM is correctly predicted in 50 to 90% of the cases, depending on method and enzyme, which is an encouraging rate. We also discuss the underlying mechanisms of cytochrome P450 metabolism in the light of the results from this comparison.     

Structure-based site of metabolism prediction for cytochrome P450 2D6

Realistic representation of protein flexibility in biomolecular simulations remains an unsolved fundamental problem and is an active area of research. The high flexibility of the cytochrome P450 2D6 (CYP2D6) active site represents a challenge for accurate prediction of the preferred binding mode and site of metabolism (SOM) for compounds metabolized by this important enzyme. To account for this flexibility, we generated a large ensemble of unbiased CYP2D6 conformations, to which small molecule substrates were docked to predict their experimentally observed SOM. SOM predictivity was investigated as a function of the number of protein structures, the scoring function, the SOM-heme cutoff distance used to distinguish metabolic sites, and intrinsic reactivity. Good SOM predictions for CYP2D6 require information from the protein. A critical parameter is the distance between the heme iron and the candidate site of metabolism. The best predictions were achieved with cutoff distances consistent with the chemistry relevant to CYP2D6 metabolism. Combination of the new ensemble-based docking method with estimated intrinsic reactivities of substrate sites considerably improved the predictivity of the model. Testing on an independent set of substrates yielded area under curve values as high as 0.93, validating our new approach.     

Computational predictions of the site of metabolism of cytochrome P450 2D6 substrates: comparative analysis,molecular docking,bioactivation and toxicological implications

Cytochrome P450 2D6 (CYP2D6) is a polymorphic enzyme responsible for metabolizing approximately 25% of all drugs. CYP2D6 is highly expressed in the brain and plays a role as the major CYP in the metabolism of numerous brain-penetrant drugs, including antipsychotics and antidepressants. CYP2D6 activity and inhibition have been associated with numerous undesirable effects in patients, such as bioactivation, drug-associated suicidality and prolongation of the QTc interval. Several in silico tools have been developed in recent years to assist safety assessment scientists in predicting the structural identity of CYP2D6-derived metabolites. The first goal of this study was to perform a comparative evaluation on the ability of four commonly used in silico tools (MetaSite, StarDrop, SMARTCyp and RS-WebPredictor) to correctly predict the CYP2D6-derived site of metabolism (SOM) for 141 compounds, including 10 derived from the Genentech small molecule library. The second goal was to evaluate if a bioactivation prediction model, based on an indicator of chemical reactivity (E_LUMO–E_HOMO) and electrostatic potential, could correctly predict five representative compounds known to be bioactivated by CYP2D6. Such a model would be of great utility in safety assessment since unforeseen toxicities of CYP2D6 substrates may in part be due to bioactivation mechanisms. The third and final goal was to investigate whether molecular docking, using the crystal structure of human CYP2D6, had the potential to compliment or improve the results obtained from the four SOM in silico programs.     

CYP2C9 structure-metabolism relationships: substrates, inhibitors, and metabolites

The cytochrome P450 (CYP) family is composed of monooxygenases, which mediate the metabolism of xenobiotics and endogenous compounds. The characterization of the interactions between these enzymes and candidate drugs is an important part of the drug discovery process. CYP2C9, one isoform of the CYPs, mediates the oxidation of several important drugs. The aim of this work is to investigate the possibility to study inhibition and substrate interactions with CYP2C9, using docking and the site of metabolism predictions. The model compounds used for the study were the COX-2 inhibitor celecoxib and a series of 13 analogues known to be metabolized by CYP2C9. The results obtained using the two methods gave valuable information about important interactions of inhibitors and substrates with CYP2C9. The two methods could be used to predict the site of metabolism and to determine the productive docking pose for each compound. These predictions were verified by metabolite identification using LC/MS/MS after incubation with recombinant CYP2C9.     

Computational methods and tools to predict cytochrome P450 metabolism for drug discovery

In this review, we present important, recent developments in the computational prediction of cytochrome P450 (CYP) metabolism in the context of drug discovery. We discuss in silico models for the various aspects of CYP metabolism prediction, including CYP substrate and inhibitor predictors, site of metabolism predictors (i.e., metabolically labile sites within potential substrates) and metabolite structure predictors. We summarize the different approaches taken by these models, such as rule‐based methods, machine learning, data mining, quantum chemical methods, molecular interaction fields, and docking. We highlight the scope and limitations of each method and discuss future implications for the field of metabolism prediction in drug discovery.     

Computational models for predicting interactions with cytochrome p450 enzyme

Cytochrome p450 (CYP) enzymes are predominantly involved in Phase 1 metabolism of xenobiotics. As only 6 isoenzymes are responsible for approximately 90 % of known oxidative drug metabolism, a number of frequently prescribed drugs share the CYP-mediated metabolic pathways. Competing for a single enzyme by the co-administered therapeutic agents can substantially alter the plasma concentration and clearance of the agents. Furthermore, many drugs are known to inhibit certain p450 enzymes which they are not substrates for. Because some drug-drug interactions could cause serious adverse events leading to a costly failure of drug development, early detection of potential drug-drug interactions is highly desirable. The ultimate goal is to be able to predict the CYP specificity and the interactions for a novel compound from its chemical structure. Current computational modeling approaches, such as two-dimensional and three-dimensional quantitative structure-activity relationship (QSAR), pharmacophore mapping and machine learning methods have resulted in statistically valid predictions. Homology models have been often combined with 3D-QSAR models to impose additional steric restrictions and/or to identify the interaction site on the proteins. This article summarizes the available models, methods, and key findings for CYP1A2, 2A6, 2C9, 2D6 and 3A4 isoenzymes.     

细胞色素P450与外源物的相互作用研究进展

细胞色素P450酶是一种多功能酶系,它既参与外源物的生物转化,也与内源性物质的代谢有关,并且作为肝细胞药物代谢的主要酶系参与药物毒性的代谢灭活。由于P450酶结构、功能和基因调控的多样性,自其发现以来,该酶系的研究一直是毒理学研究中的一个热点。本文综述了P450与药物代谢相关的主要亚型及其与药物的相互作用,探讨了P450酶与外源物代谢之间的相互作用机制。     

Characterization of CYP2C Induction in Cryopreserved Human Hepatocytes and Its Application in the Prediction of the Clinical Consequences of the Induction

CYP2C enzymes play key roles in drug metabolism, and clinical drug-drug interactions caused by CYP2C induction have been reported. The aim of this study was to establish a method to predict the potency of CYP2C inductions considering the mechanism. We first investigated the relations of CYP2C induction with CYP3A4 or CYP2B6 induction in human hepatocytes after 48-h exposure with 19 inducers. The fold-induction values of CYP2C8 and CYP2C9 were well correlated with those of CYP3A4, whereas the inducers were separated into 2 groups showing different correlations with CYP2B6 induction for CYP2C8 and CYP2C9 induction. In the regression models established, the fold-induction values of CYP2C8 and CYP2C9 were well expressed as the functions of those of CYP3A4 and CYP2B6, while no such obvious correlation was observed for CYP2C19 induction. These results suggest that CYP2Cs are not simply coinduced with CYP3A4 and that CYP2C8 and CYP2C9 inductions are regulated by both pregnane X receptor and constitutive androstane receptor with different contributions. Finally, simple correlations were proposed using the experimental E_max values obtained and plasma concentrations of CYP2C9 substrates from the literature, and positive correlations were observed. These data provide methods to estimate the clinical impact of CYP2C9 induction from in vitro data.     

Prediction of human drug metabolizing enzyme induction

New chemical entities are routinely screened in vitro and in vivo for their ability to induce cytochrome P450s (CYP), other drug-metabolizing enzymes and possibly transporters in an attempt to more accurately predict clinical parameters such as drug-drug interactions and clearance in humans. Some of these potential therapeutic agents can cause induction of the metabolism of another molecule or auto-induction thereby increasing their own metabolism and elimination, as well as potentially any molecules metabolized by the same enzyme(s). Key CYPs in the 1A, 2B, 2C, and 3A families have all been shown to be inducible. It would be clearly advantageous to know the potential for a compound to induce drug metabolizing enzymes or transporters prior to clinical development, and many in vitro systems have been developed for this purpose. Newer computational technologies are also being applied in order to attempt to predict induction from the molecular structure alone before a molecule is even synthesized or tested. This review will cover the various in vitro and in silico methods developed for prediction of key inducers of CYPs and other proteins, as well as the limitations of such technologies and applications in the future.     

The use of gene knockout mice to unravel the mechanisms of toxicity and chemical carcinogenesis

Metabolism of toxins and carcinogens is carried out by large groups of xenobiotic-metabolizing enzymes. These enzymes are generally considered to be required for elimination of xenobiotics such as drugs, dietary chemicals and environmental pollutants, and to be required for chemical toxicity and carcinogenicity. An important role for these enzymes in metabolism of endogenous chemicals has not been established. Mouse lines in which the genes encoding several xenobiotic-metabolizing enzymes were knocked out were produced and are being used to determine the role of metabolism in carcinogenesis, and acute and chronic toxicities in vivo. Mouse lines lacking the P450s CYP1A1, CYP1A2, CYP1B1 and CYP2E1, microsomal epoxide hydrolase (mEH), NADPH:quinone oxidoreductase and the glutathione S-transferase P1 have no deleterious phenotypes, indicating that these enzymes are not required for mammalian development and physiological homeostasis. However, when challenged with toxins and carcinogens, they respond differently from their wild-type (WT) counterparts. For example, mice lacking CYP1A2 and CYP2E1 are totally resistant to acetaminophen-induced hepatotoxicity. Mice lacking CYP1B1 or mEH are less responsive to tumorigenesis by 7,12-dimethybenz[a]anthracene. However, CYP1A2-null mice do not significantly differ from WT mice in their response to the hepatocarcinogen 4-aminobiphenyl. These and other studies indicate that the xenobiotic-metabolism null mice are of great value in the study of the mechanisms of chemical injury.     

CYP450酶内源性生物标志物的研究进展

CYP450酶广泛参与药物的I相代谢过程,CYP450酶活性受到基因、性别、年龄、疾病等多种因素的影响,CYP450酶活性直接影响经CYP450酶代谢药物的体内代谢过程.测定CYP450酶活性有助于了解药物在体内的代谢情况,预测药物疗效和不良反应.测定CYP450酶活性的方法主要有外源性探针药物法和内源性生物标志物法,...     

细胞色素P450酶参与动物体内代谢的研究与展望

细胞色素P450酶(Cytochrome P450 enzymes,CYP450)通过其活性部位的Fe3+使底物得到O2 中的一个氧原子并伴随着得失电子来进一步实现化合物的氧化过程.其家族成员CYP3A4 在治疗抗COVID-19 的化学药物中能介导利托那韦(Ritonvir)与洛匹那韦(Lopinavir)的代谢来达...     

PreMetabo: An in silico phase I and II drug metabolism prediction platform

This study aimed to develop a drug metabolism prediction platform using knowledge-based prediction models. Site of Metabolism (SOM) prediction models for four cytochrome P450 (CYP) subtypes were developed along with uridine 5′-diphosphoglucuronosyltransferase (UGT) and sulfotransferase (SULT) substrate classification models. The SOM substrate for a certain CYP was determined using the sum of the activation energy required for the reaction at the reaction site of the substrate and the binding energy of the substrate to the CYP enzyme. Activation energy was calculated using the EaMEAD model and binding energy was calculated by docking simulation. Phase II prediction models were developed to predict whether a molecule is the substrate of a certain phase II conjugate protein, i.e., UGT or SULT. Using SOM prediction models, the predictability of the major metabolite in the top-3 was obtained as 72.5–84.5% for four CYPs, respectively. For internal validation, the accuracy of the UGT and SULT substrate classification model was obtained as 93.94% and 80.68%, respectively. Additionally, for external validation, the accuracy of the UGT substrate classification model was obtained as 81% in the case of 11 FDA-approved drugs. PreMetabo is implemented in a web environment and is available at https://premetabo.bmdrc.kr/.     

Complementary DNA cloning, functional expression and characterization of a novel cytochrome P450, CYP2D50, from equine liver

Members of the CYP2D family constitute only about 2-4% of total hepatic CYP450s, however, they are responsible for the metabolism of 20-25% of commonly prescribed therapeutic compounds. CYP2D enzymes have been identified in a number of different species. However, vast differences in the metabolic activity of these enzymes have been well documented. In the horse, the presence of a member of the CYP2D family has been suggested from studies with equine liver microsomes, however its presence has not been definitively proven. In this study a cDNA encoding a novel CYP2D enzyme (CYP2D50) was cloned from equine liver and expressed in a baculovirus expression system. The nucleotide sequence of CYP2D50 was highly homologous to that of human CYP2D6 and therefore the activity of the enzyme was characterized using dextromethorphan and debrisoquine, two isoform selective substrates for the human orthologue. CYP2D50 displayed optimal catalytic activity with dextromethorphan using molar ratios of CYP2D50 to NADPH CYP450 reductase of 1:15. Although CYP2D50 and CYP2D6 shared significant sequence homology, there were striking differences in the catalytic activity between the two enzymes. CYP2D50 dextromethorphan-O-demethylase activity was nearly 180-fold slower than the human counterpart, CYP2D6. Similarly, rates of formation of 4-hydroxydebrisoquine activity were 50-fold slower for CYP2D50 compared to CYP2D6. The results of this study demonstrate substantial interspecies variability in metabolism of substrates by CYP2D orthologues in the horse and human and support the need to fully characterize this enzyme system in equids.     

食物对细胞色素P450药物代谢酶的影响

细胞色素P450酶系在大多数内源性和外源性分子的生物氧化过程中发挥重要的作用,尤其在药物代谢方面。CYP450酶个体差异大,除了遗传因素的影响外,食物等外界因素也可能影响其活性或表达,从而影响经酶代谢药物的疗效和不良反应。故本文就食物因素对细胞色素P450酶影响的相关研究进行综述。     

去氢厄弗酚在小鼠肝微粒体中代谢产物及CYP450酶亚型的鉴定

目的建立去氢厄弗酚(DHE)小鼠体外肝微粒体孵育方法,鉴定DHE在小鼠肝微粒体中的代谢产物及参与DHE代谢的CYP450酶亚型。方法采用UPLC-Q-TOF-MS/MS分析鉴定DHE在体外肝微粒体共温孵后的代谢产物,筛选7种CYP450酶亚型,并通过特异性化学抑制剂法,鉴别参与DHE代谢的主要CYP450酶亚型。结果在体外肝微粒体共温孵后,检测到4个代谢产物;所筛选的7种CYP450酶亚型中,CYP1A2、CYP2C8和CYP2D2对DHE体外肝微粒体代谢的参与度较高。结论在肝脏中,有多种代谢酶亚型参与DHE的代谢,表明DHE在临床上不易与其他药物产生相互作用。     

MetaSite: understanding metabolism in human cytochromes from the perspective of the chemist

Identification of metabolic biotransformations can significantly affect the drug discovery process. Since bioavailability, activity, toxicity, distribution, and final elimination all depend on metabolic biotransformations, it would be extremely advantageous if this information could be produced early in the discovery phase. Once obtained, this information can help chemists to judge whether a potential candidate should be eliminated from the pipeline or modified to improve chemical stability or safety of new compounds. The use of in silico methods to predict the site of metabolism in phase I cytochrome-mediated reactions is a starting point in any metabolic pathway prediction. This paper presents a new method, specifically designed for chemists, that provides the cytochrome involved and the site of metabolism for any human cytochrome P450 (CYP) mediated reaction acting on new substrates. The methodology can be applied automatically to all the cytochromes for which 3D structure is known and can be used by chemists to detect positions that should be protected in order to avoid metabolic degradation or to check the suitability of a new scaffold or prodrug. The fully automated procedure is also a valuable new tool in early ADME-Tox assays (absorption, distribution, metabolism, and excretion toxicity assays), where drug safety and metabolic profile patterns must be evaluated as soon, and as early, as possible.     

Novel functionalized 5-(phenoxymethyl)-1,3-dioxane analogs exhibiting cytochrome P450 inhibition: a patent evaluation WO2015048311 (A1)

Cytochrome P450’s (CYP’s) constitute a diverse group of over 500 monooxygenase hemoproteins, catalyzing transformations that involve xenobiotic metabolism, steroidogenesis and other metabolic processes. Over-production of the steroid hormone cortisol is implicated in the progression of diseases such as diabetes, heart failure and hypertension, stroke, Cushing’s syndrome, obesity and renal failure, among others. The biosynthesis of cortisol involves a cascade of cholesterol metabolizing reactions regulated through three major CYP proteins: 17α?hydroxylase-C17/20-lyase (CYP17), 21-hydroxylase (CYP21), and 11β-hydroxylase (CYP11B1). Excess activities of these enzymes are linked to the progression of malignancies including prostate, breast, ovarian, and uterine cancers. A series of novel functionalized dioxane analogs have been developed and recently patented as CYP17, CYP21, and CYP11B1 inhibitors, which lead to the modulation of cortisol production as a method for treating, delaying, slowing, and inhibiting the implicated diseases. The findings disclosed in this patent have been analyzed and compared with the literature data on inhibitors of CYP17, CYP21, and CYP11B1. The compiled data provide insight into the novel functionality of the compounds described in the patent. In this regard, an objective opinion on the effectiveness and novel biochemistry of these compounds in comparison to current CYP inhibitors used in the treatment of cortisol-related diseases is presented in this paper.     

Regioselective hydroxylation of steroid hormones by human cytochromes P450

This article reviews in vitro metabolic activities [including Michaelis constants (K_m), maximal velocities (V_max) and V_max/K_m] and drug–steroid interactions [such as induction and cooperativity (activation)] of cytochromes P450 (P450 or CYP) in human tissues, including liver and adrenal gland, for 14 kinds of endogenous steroid compounds, including allopregnanolone, cholesterol, cortisol, cortisone, dehydroepiandrosterone, estradiol, estrone, pregnenolone, progesterone, testosterone and bile acids (cholic acid). First, we considered the drug-metabolizing P450s. 6β-Hydroxylation of many steroids, including cortisol, cortisone, progesterone and testosterone, was catalyzed primarily by CYP3A4. CYP1A2 and CYP3A4, respectively, are likely the major hepatic enzymes responsible for 2-/4-hydroxylation and 16α-hydroxylation of estradiol and estrone, steroids that can contribute to breast cancer risk. In contrast, CYP1A1 and CYP1B1 predominantly metabolized estrone and estradiol to 2- and 4-catechol estrogens, which are endogenous ultimate carcinogens if formed in the breast. Some metabolic activities of CYP3A4, including dehydroepiandrosterone 7β-/16α-hydroxylation, estrone 2-hydroxylation and testosterone 6β-hydroxylation, were higher than those for polymorphically expressed CYP3A5. Next, we considered typical steroidogenic P450s. CYP17A1, CYP19A1 and CYP27A1 catalyzed steroid synthesis, including hydroxylation at 17α, 19 and 27 positions, respectively. However, it was difficult to predict which hepatic drug-metabolizing P450 or steroidogenic P450 will be mainly responsible for metabolizing each steroid hormone in vivo based on these results. Further research is required on the metabolism of steroid hormones by various P450s and on prediction of their relative contributions to in vivo metabolism. The findings collected here provide fundamental and useful information on the metabolism of steroid compounds.