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

Effect of chlorpyrifos-exposure on the expression levels of CYP genes in Daphnia magna and examination of a possibility that an up-regulated clan 3 CYP, CYP360A8, reacts with pesticides

Daphnia magna is a test organism used for ecological risk assessments of pesticides, but little is known about the expression levels of cytochrome P450s (CYP)s and their changes after pesticide exposure in the less than 24-h-olds used for ecotoxicity tests. In this study, D. magna juveniles were exposed to 0.2 μg/L of chlorpyrifos under the conditions for acute immobilization test as specified by the OECD test guideline for 24 h, and then the gene expression was compared between the control and chlorpyrifos-exposure groups by RNA-sequencing analysis, with a focus on CYP genes. Among 38 CYP genes expressed in the control group, seven were significantly up-regulated while two were significantly down-regulated in the chlorpyrifos-exposure group. Although the sublethal concentration of chlorpyrifos did not change their expression levels so drastically (0.8 < fold change < 2.6), CY360A8 of D. magna (DmCYP360A8), which had been proposed to be responsible for metabolism of xenobiotics, was abundantly expressed in controls yet up-regulated by chlorpyrifos. Therefore, homology modeling of DmCYP360A8 was performed based on the amino acid sequence, and then molecular docking simulations with the insecticides that were indicated to be metabolized by CYPs in D. magna were conducted. The results indicated that DmCYP360A8 could contribute to the metabolism of diazinon and chlorfenapyr but not chlorpyrifos. These findings suggest that chlorpyrifos is probably detoxified by other CYP(s) including up-regulated and/or constitutively expressed one(s).

Identification of key amino acid residues toward improving the catalytic activity and substrate specificity of plant-derived cytochrome P450 monooxygenases CYP716A subfamily enzyme for triterpenoid production in Saccharomyces cerevisiae

Triterpenoids constitute a group of specialized plant metabolites with wide structural diversity and high therapeutic value for human health. Cytochrome P450 monooxygenases (CYP) are a family of enzymes important for generating the structural diversity of triterpenoids by catalyzing the site-specific oxidization of the triterpene backbone. The CYP716 enzyme family has been isolated from various plant families as triterpenoid oxidases; however, their experimental crystal structures are not yet available and the detailed catalytic mechanism remains elusive. Here, we address this challenge by integrating bioinformatics approaches with data from other CYP families. Medicago truncatula CYP716A12, the first functionally characterized CYP716A subfamily enzyme, was chosen as the model for this study. We performed homology modeling, structural alignment, in silico site-directed mutagenesis, and molecular docking analysis to search and screen key amino acid residues relevant to the catalytic activity and substrate specificity of the CYP716A subfamily enzyme in triterpenoid biosynthesis. An in vivo functional analysis using engineered yeast that endogenously produced plant-derived triterpenes was performed to elucidate the results. When the amino acids in the signature region and substrate recognition sites (SRSs) were substituted, the product profile of CYP716A12 was modified. We identified amino acid residues that control the substrate contraction of the enzyme (D292) and engineered the enzyme to improve its catalytic activity and substrate specificity (D122, I212, and Q358) for triterpenoid biosynthesis. In addition, we demonstrated the versatility of this strategy by changing the properties of key residues in SRSs to improve the catalytic activity of Arabidopsis thaliana CYP716A1 (S356) and CYP716A2 (M206, F210) at C-28 on the triterpene backbone. This research has the potential to help in the production of desired triterpenoids in engineered yeast by increasing the catalytic activity and substrate specificity of plant CYP716A subfamily enzymes.

CYP2C8-Mediated Formation of a Human Disproportionate Metabolite of the Selective NaV1.7 Inhibitor DS-1971a, a Mixed Cytochrome P450 and Aldehyde Oxidase Substrate

Predicting human disproportionate metabolites is difficult, especially when drugs undergo species-specific metabolism mediated by cytochrome P450s (P450s) and/or non-P450 enzymes. This study assessed human metabolites of DS-1971a, a potent Na_v1.7-selective blocker, by performing human mass balance studies and characterizing DS-1971a metabolites, in accordance with the Metabolites in Safety Testing (MIST) guidance. In addition, we investigated the mechanism by which the major human disproportionate metabolite (M1) was formed. After oral administration of radiolabeled DS-1971a, the major metabolites in human plasma were P450-mediated monoxidized metabolites M1 and M2 with area under the curve ratios of 27% and 10% of total drug-related exposure, respectively; the minor metabolites were dioxidized metabolites produced by aldehyde oxidase and P450s. By comparing exposure levels of M1 and M2 between humans and safety assessment animals, M1 but not M2 was found to be a human disproportionate metabolite, requiring further characterization under the MIST guidance. Incubation studies with human liver microsomes indicated that CYP2C8 was responsible for the formation of M1. Docking simulation indicated that, in the formation of M1 and M2, there would be hydrogen bonding and/or electrostatic interactions between the pyrimidine and sulfonamide moieties of DS-1971a and amino acid residues Ser100, Ile102, Ile106, Thr107, and Asn217 in CYP2C8, and that the cyclohexane ring of DS-1971a would be located near the heme iron of CYP2C8. These results clearly indicate that M1 is the predominant metabolite in humans and a human disproportionate metabolite due to species-specific differences in metabolism. Significance Statement This report is the first to show a human disproportionate metabolite generated by CYP2C8-mediated primary metabolism. We clearly demonstrate that DS-1971a, a mixed aldehyde oxidase and cytochrome P450 substrate, was predominantly metabolized by CYP2C8 to form M1, a human disproportionate metabolite. Species differences in the formation of M1 highlight the regio- and stereoselective metabolism by CYP2C8, and the proposed interaction between DS-1971a and CYP2C8 provides new knowledge of CYP2C8-mediated metabolism of cyclohexane-containing substrates.

Feature importance of machine learning prediction models shows structurally active part and important physicochemical features in drug design

The objective of this study was to obtain the indicators of physicochemical parameters and structurally active sites to design new chemical entities with desirable pharmacokinetic profiles by investigating the process by which machine learning prediction models arrive at their decisions, which are called explainable artificial intelligence. First, we developed the prediction models for metabolic stability, CYP inhibition, and P-gp and BCRP substrate recognition using 265 physicochemical parameters for designing the molecular structures. Four important parameters, including the well-known indicator h_logD, are common in some in vitro studies; as such, these can be used to optimize compounds simultaneously to address multiple pharmacokinetic concerns. Next, we developed machine learning models that had been programmed to show structurally active sites. Many types of machine learning models were developed using the results of in vitro metabolic stability study of around 30000 in-house compounds. The metabolic sites of in-house compounds predicted using some prediction models matched experimentally identified metabolically active sites, with a ratio of number of metabolic sites (predicted/actual) of over 90%. These models can be applied to several screening projects. These two approaches can be employed for obtaining lead compounds with desirable pharmacokinetic profiles efficiently.

Predicting drug metabolism and pharmacokinetics features of in-house compounds by a hybrid machine-learning model

We constructed machine learning-based pharmacokinetic prediction models with very high performance. The models were trained on 26138 and 16613 compounds involved in metabolic stability and cytochrome P450 inhibition, respectively. Because the compound features largely differed between the publicly available and in-house compounds, the models learned on the public data could not predict the in-house compounds, suggesting that outside of a certain applicability domain (AD), the prediction results are unreliable and can mislead the design of novel compounds. To exclude the uncertain prediction results, we constructed another machine learning model that determines whether the newly designed compound is inside or outside the AD. The AD was evaluated multi-dimensionally with some explanatory variables: The structural similarities and the probability obtained from the pharmacokinetic prediction model. The accuracy of predicting metabolic stability was 79.9% on the test set, increasing significantly to 93.6% after excluding the low-reliability compounds. The model properly classified the reliability of the compounds. After learning on the in-house compounds, the reliability model classified almost all (90%) of the public compounds as low reliability, indicating that the AD was properly determined by the model.

Structure-Based Site of Metabolism (SOM) Prediction of Ligand for CYP3A4 Enzyme: Comparison of Glide XP and Induced Fit Docking (IFD)

Metabolism is one of the prime reasons where most of drugs fail to accomplish their clinical trials. The enzyme CYP3A4, which belongs to the superfamily of cytochrome P450 enzymes (CYP), helps in the metabolism of a large number of drugs in the body. The enzyme CYP3A4 catalyzes oxidative chemical processes and shows a very broad range of ligand specificity. The understanding of the compound’s structure where oxidation would take place is crucial for the successful modification of molecules to avoid unwanted metabolism and to increase its bioavailability. For this reason, it is required to know the site of metabolism (SOM) of the compounds, where compounds undergo enzymatic oxidation. It can be identified by predicting the accessibility of the substrate’s atom toward oxygenated Fe atom of heme in a CYP protein. The CYP3A4 enzyme is highly flexible and can take significantly different conformations depending on the ligand with which it is being bound. To predict the accessibility of substrate atoms to the heme iron, conventional protein-rigid docking methods failed due to the high flexibility of the CYP3A4 protein. Herein, we demonstrated and compared the ability of the Glide extra precision (XP) and Induced Fit docking (IFD) tool of Schrodinger software suite to reproduce the binding mode of co-crystallized ligands into six X-ray crystallographic structures. We extend our studies toward the prediction of SOM for compounds whose experimental SOM is reported but the ligand-enzyme complex crystal structure is not available in the Protein Data Bank (PDB). The quality and accuracy of Glide XP and IFD was determined by calculating RMSD of docked ligands over the corresponding co-crystallized bound ligand and by measuring the distance between the SOM of the ligand and Fe atom of heme. It was observed that IFD reproduces the exact binding mode of available co-crystallized structures and correctly predicted the SOM of experimentally reported compounds. Our approach using IFD with multiple conformer structures of CYP3A4 will be one of the effective methods for SOM prediction.

Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors

The Cytochrome P450 family of heme-containing proteins plays a major role in catalyzing phase I metabolic reactions, and the CYP3A4 subtype is responsible for the metabolism of many currently marketed drugs. Additionally, CYP3A4 has an inherent affinity for a broad spectrum of structurally diverse chemical entities, often leading to drug-drug interactions mediated by the inhibition or induction of the metabolic enzyme. The current study explores the binding of selected highly efficient CYP3A4 inhibitors by docking and molecular dynamics (MD) simulation protocols and their binding free energy calculated using the WaterSwap method. The results indicate the importance of binding pocket residues including Phe57, Arg105, Arg106, Ser119, Arg212, Phe213, Thr309, Ser312, Ala370, Arg372, Glu374, Gly481 and Leu483 for interaction with CYP3A4 inhibitors. The residue-wise decomposition of the binding free energy from the WaterSwap method revealed the importance of binding site residues Arg106 and Arg372 in the stabilization of all the selected CYP3A4-inhibitor complexes. The WaterSwap binding energies were further complemented with the MM(GB/PB)SA results and it was observed that the binding energies calculated by both methods do not differ significantly. Overall, our results could guide towards the use of multiple computational approaches to achieve a better understanding of CYP3A4 inhibition, subsequently leading to the design of highly specific and efficient new chemical entities with suitable ADMETox properties and reduced side effects.

The relationship between pharmacokinetic parameters of carbamazepine and therapeutic response in epileptic patients

INTRODUCTION

The prescribed dose and carbamazepine plasma concentration to achieve the optimal therapeutic efficacy are highly variable from one patient to the other. Our study aimed to determine whether biological parameters may be used as plasma markers that can individually adjust the carbamazepine dose necessary to optimize therapeutic efficacy.

MATERIAL AND METHODS

Ninety-four epileptic patients under carbamazepine monotherapy and who have never used combination therapy were recruited from the consecutive admissions at the Department of Neurology "CHU Sahloul" of Sousse Central Hospital in Tunisia from February 2010 to April 2011. The patients were monitored for epilepsy for three years on average. Carbamazepine and 10,11-epoxide-carbamazepine concentrations were analyzed through high-performance liquid chromatography. Simultaneously, therapeutic efficacy was assessed through the annual number of seizures in each patient.

RESULTS

Our results showed the absence of any significant correlations between specific dose (mg/kg/day), carbamazepine plasma concentrations and therapeutic efficacy (r = 0.0025, p = 0.30; r = 0.1584, p = 0.38 respectively), whereas both plasma 10,11-epoxide-carbamazepine concentration and 10,11-epoxide-carbamazepine to plasma carbamazepine ratio were closely correlated with therapeutic efficacy (r = 0.34, p = 0.03; r = 0.45, p = 0.008 respectively). The optimum therapeutic response was observed among patients who simultaneously had a plasma concentration of 0.8 μg/ml of metabolite and 5.5 μg/ml of carbamazepine.

CONCLUSIONS

The results suggest that plasma levels of both carbamazepine and of 10,11-epoxide-carbamazepine must be set to achieve an optimum therapeutic response.

A Triazinone Derivative Inhibits HIV-1 Replication by Interfering with Reverse Transcriptase Activity

A novel HIV-1 inhibitor, 6-(tert-butyl)-4-phenyl-4-(trifluoromethyl)-1H,3H-1,3,5-triazin-2-one (compound 1), was identified from a compound library screened for the ability to inhibit HIV-1 replication. EC₅₀ values of compound 1 were found to range from 107.9 to 145.4 nm against primary HIV-1 clinical isolates. In in vitro assays, HIV-1 reverse transcriptase (RT) activity was inhibited by compound 1 with an EC₅₀ of 4.3 μm. An assay for resistance to compound 1 selected a variant of HIV-1 with a RT mutation (RT^L100I ); this frequently identified mutation confers mild resistance to non-nucleoside RT inhibitors (NNRTIs). A recombinant HIV-1 bearing RT^L100I exhibited a 41-fold greater resistance to compound 1 than the wild-type virus. Compound 1 was also effective against HIV-1 with RT^K103N , one of the major mutations that confers substantial resistance to NNRTIs. Computer-assisted docking simulations indicated that compound 1 binds to the RT NNRTI binding pocket in a manner similar to that of efavirenz; however, the putative compound 1 binding site is located further from RT^K103 than that of efavirenz. Compound 1 is a novel NNRTI with a unique drug-resistance profile.

Inhibition of cytochrome P450 3A by acetoxylated analogues of resveratrol in in vitro and in silico models

Many dietary compounds, including resveratrol, are potent inhibitors of CYP3A4. Here we examined the potential to predict inhibition capacity of dietary polyphenolics using an in silico and in vitro approaches and synthetic model compounds. Mono, di, and tri-acetoxy resveratrol were synthesized, a cell line of human intestine origin and microsomes from rat liver served to determine their in vitro inhibition of CYP3A4, and compared to that of resveratrol. Docking simulation served to predict the affinity of the synthetic model compounds to the enzyme. Modelling of the enzyme’s binding site revealed three types of interaction: hydrophobic, electrostatic and H-bonding. The simulation revealed that each of the examined acetylations of resveratrol led to the loss of important interactions of all types. Tri-acetoxy resveratrol was the weakest inhibitor in vitro despite being the more lipophilic and having the highest affinity for the binding site. The simulation demonstrated exclusion of all interactions between tri-acetoxy resveratrol and the heme due to distal binding, highlighting the complexity of the CYP3A4 binding site, which may allow simultaneous accommodation of two molecules. Finally, the use of computational modelling may serve as a quick predictive tool to identify potential harmful interactions between dietary compounds and prescribed drugs.

Use of In Vitro and Predictive In Silico Models to Study the Inhibition of Cytochrome P4503A by Stilbenes

CYP3A4 is recognized as the main enzyme involved in the metabolism of drugs and xenobiotics in the human body and its inhibition may lead to undesirable consequences. Stilbenes, including resveratrol, belong to a group of dietary health-promoting compounds that also act as inhibitors of CYP3A4. The aim of this study was to examine the use of computer modeling of enzyme-ligand interactions to analyze and predict the inhibition of structurally related compounds. To this end, an aldehyde group was attached to resveratrol and the interactions of CYP3A4 with resveratrol, its aldehyde analogue (RA) and a known synthetic inhibitor were studied and compared in two biological models. Specifically, the metabolism of testosterone was examined in a human intestine cell line (Caco-2/TC7) and in rat liver microsomes (RLM). The results demonstrated a weak inhibitory effect of RA on CYP3A4, as compared to resveratrol itself, in both biological models. Human CYP3A4 was more susceptible to inhibition than the commonly used model isozyme from rat. Modeling of the binding site of CYP3A4 revealed a combination of three types of interactions: hydrophobic interactions, electrostatic interactions and hydrogen bonds. A docking simulation revealed that the RA lacked an important binding feature, as compared to resveratrol, and that that difference may be responsible for its lower level of affinity for CYP3A4. Software analysis of binding affinity may serve as a predictive tool for designing new therapeutic compounds in terms of inhibition of CYP3A4 and help to reveal the biochemical nature of the interactions of dietary compounds, herbal compounds and drugs whose metabolism is mediated by this enzyme.

Molecular dynamics and density functional studies on the metabolic selectivity of antipsychotic thioridazine by cytochrome P450 2D6: Connection with crystallographic and metabolic results

CYP2D6, a cytochrome P450 isoform, significantly contributes to the metabolism of many clinically important drugs. Thioridazine (THD) is one of the phenothiazine-type antipsychotics, which exhibit dopamine D2 antagonistic activity. THD shows characteristic metabolic profiles compared to other phenothiazine-type antipsychotics such as chlorpromazine. The sulfur atom attached to the phenothiazine ring is preferentially oxidized mainly by CYP2D6, that is, the 2-sulfoxide is a major metabolite, and interestingly this metabolite shows more potent activity against dopamine D2 receptors than THD. On the other hand, the formation of this metabolite causes many serious problems for its clinical use. Wójcikowski et al. (Drug Metab. Dispos. 2006, 34, 471) reported a kinetic study of THD formed by CYP2D6. Recently, Wang et al. (J. Biol. Chem. 2012, 287, 10834 and J. Biol. Chem. 2015, 290, 5092) revealed the crystallographic structure of THD with CYP2D6. In the current study, the binding and reaction mechanisms at the atomic and electronic levels were computationally examined based on the assumption as to whether or not the different crystallographic binding poses correspond to the different metabolites. The binding and oxidative reaction steps in the whole metabolic process were investigated using molecular dynamics and density functional theory calculations, respectively. The current study demonstrated the essential importance of the orientation of the substrate in the reaction center of CYP2D6 for the metabolic reaction.

Pi-pi Stacking Mediated Cooperative Mechanism for Human Cytochrome P450 3A4

Human Cytochrome P450 3A4 (CYP3A4) is an important member of the cytochrome P450 superfamily with responsibility for metabolizing ~50% of clinical drugs. Experimental evidence showed that CYP3A4 can adopt multiple substrates in its active site to form a cooperative binding model, accelerating substrate metabolism efficiency. In the current study, we constructed both normal and cooperative binding models of human CYP3A4 with antifungal drug ketoconazoles (KLN). Molecular dynamics simulation and free energy calculation were then carried out to study the cooperative binding mechanism. Our simulation showed that the second KLN in the cooperative binding model had a positive impact on the first one binding in the active site by two significant pi-pi stacking interactions. The first one was formed by Phe215, functioning to position the first KLN in a favorable orientation in the active site for further metabolism reactions. The second one was contributed by Phe304. This pi-pi stacking was enhanced in the cooperative binding model by the parallel conformation between the aromatic rings in Phe304 and the dioxolan moiety of the first KLN. These findings can provide an atomic insight into the cooperative binding in CYP3A4, revealing a novel pi-pi stacking mechanism for drug-drug interactions.

Mechanism of drug-drug interactions mediated by human cytochrome P450 CYP3A4 monomer

Using Nanodiscs, we quantitate the heterotropic interaction between two different drugs mediated by monomeric CYP3A4 incorporated into a nativelike membrane environment. The mechanism of this interaction is deciphered by global analysis of multiple-turnover experiments performed under identical conditions using the pure substrates progesterone (PGS) and carbamazepine (CBZ) and their mixtures. Activation of CBZ epoxidation and simultaneous inhibition of PGS hydroxylation are measured and quantitated through differences in their respective affinities for both a remote allosteric site and the productive catalytic site near the heme iron. Preferred binding of PGS at the allosteric site and a stronger preference for CBZ binding at the productive site give rise to a nontrivial drug-drug interaction. Molecular dynamics simulations indicate functionally important conformational changes caused by PGS binding at the allosteric site and by two CBZ molecules positioned inside the substrate binding pocket. Structural changes involving Phe-213, Phe-219, and Phe-241 are thought to be responsible for the observed synergetic effects and positive allosteric interactions between these two substrates. Such a mechanism is likely of general relevance to the mutual heterotropic effects caused by biologically active compounds that exhibit different patterns of interaction with the distinct allosteric and productive sites of CYP3A4, as well as other xenobiotic metabolizing cytochromes P450 that are also involved in drug-drug interactions. Importantly, this work demonstrates that a monomeric CYP3A4 can display the full spectrum of activation and cooperative effects that are observed in hepatic membranes.

A multiscale approach to modelling drug metabolism by membrane-bound cytochrome P450 enzymes

Cytochrome P450 enzymes are found in all life forms. P450s play an important role in drug metabolism, and have potential uses as biocatalysts. Human P450s are membrane-bound proteins. However, the interactions between P450s and their membrane environment are not well-understood. To date, all P450 crystal structures have been obtained from engineered proteins, from which the transmembrane helix was absent. A significant number of computational studies have been performed on P450s, but the majority of these have been performed on the solubilised forms of P450s. Here we present a multiscale approach for modelling P450s, spanning from coarse-grained and atomistic molecular dynamics simulations to reaction modelling using hybrid quantum mechanics/molecular mechanics (QM/MM) methods. To our knowledge, this is the first application of such an integrated multiscale approach to modelling of a membrane-bound enzyme. We have applied this protocol to a key human P450 involved in drug metabolism: CYP3A4. A biologically realistic model of CYP3A4, complete with its transmembrane helix and a membrane, has been constructed and characterised. The dynamics of this complex have been studied, and the oxidation of the anticoagulant R-warfarin has been modelled in the active site. Calculations have also been performed on the soluble form of the enzyme in aqueous solution. Important differences are observed between the membrane and solution systems, most notably for the gating residues and channels that control access to the active site. The protocol that we describe here is applicable to other membrane-bound enzymes.

Biochemical analysis of a multifunctional cytochrome P450 (CYP51) enzyme required for synthesis of antimicrobial triterpenes in plants

Members of the cytochromes P450 superfamily (P450s) catalyze a huge variety of oxidation reactions in microbes and higher organisms. Most P450 families are highly divergent, but in contrast the cytochrome P450 14α-sterol demethylase (CYP51) family is one of the most ancient and conserved, catalyzing sterol 14α-demethylase reactions required for essential sterol synthesis across the fungal, animal, and plant kingdoms. Oats (Avena spp.) produce antimicrobial compounds, avenacins, that provide protection against disease. Avenacins are synthesized from the simple triterpene, β-amyrin. Previously we identified a gene encoding a member of the CYP51 family of cytochromes P450, AsCyp51H10 (also known as Saponin-deficient 2, Sad2), that is required for avenacin synthesis in a forward screen for avenacin-deficient oat mutants. sad2 mutants accumulate β-amyrin, suggesting that they are blocked early in the pathway. Here, using a transient plant expression system, we show that AsCYP51H10 is a multifunctional P450 capable of modifying both the C and D rings of the pentacyclic triterpene scaffold to give 12,13β-epoxy-3β,16β-dihydroxy-oleanane (12,13β-epoxy-16β-hydroxy-β-amyrin). Molecular modeling and docking experiments indicate that C16 hydroxylation is likely to precede C12,13 epoxidation. Our computational modeling, in combination with analysis of a suite of sad2 mutants, provides insights into the unusual catalytic behavior of AsCYP51H10 and its active site mutants. Fungal bioassays show that the C12,13 epoxy group is an important determinant of antifungal activity. Accordingly, the oat AsCYP51H10 enzyme has been recruited from primary metabolism and has acquired a different function compared to other characterized members of the plant CYP51 family--as a multifunctional stereo- and regio-specific hydroxylase in plant specialized metabolism.