Insight into the effects of chiral isomers quinidine and quinine on CYP2D6 inhibition

Stereostructure-activity mechanism of cyproconazole by cytochrome P450 in rat liver microsomes: A combined experimental and computational study

Cyproconazole (CPZ), representing the chiral triazole fungicides, is widely used in the pharmaceutical and agricultural fields. To clarify its potential adverse effects on the generalized CYP-mediated processes within mammalian, a comparative experimental and computational approach was employed to investigate the CYP-mediated metabolism processes of CPZ stereoisomers in rat liver microsomes (RLMs). The depletion rate of CPZ stereoisomers in vitro incubation system with RLMs followed the order RR-> SS-> SR-> RS-CPZ. The results of kinetic assays were in line with the depletion rate results. Further inhibition assay confirmed the stereoselective metabolism of CPZ stereoisomers by different CYP isoforms. Molecular dynamics (MD) simulation revealed the stereoselective metabolism mechanism. Several hydrogen bonds and π-stacking restrict the position of CPZ isomers in the active cavity of CYPs so that the 4'-nitrogen on the triazole ring can bind closely to the heme of CYP, which results in the metabolism of CPZ isomers. By combining the computational and experimental approaches, the structure-activity relationship of CPZ and CYP was elucidated, and this method can be further applied to predict the degree of uncertainty in the process of xenobiotic biotransformation of triazole fungicides and serve as a basis for risk assessment.

Recent Advances in the Chemistry of Bioactive Compounds from Plants and Soil Microbes: a Review

Bioactive compounds derived from plants and microbial sources are required for the survival of the human race and groundbreaking research must continue in this line. Plants and microbes are the major sources of naturally occurring bioactive compounds for numerous biotechnological applications. Recent progress in the fields of bioactive compounds and soil chemistry in agriculture has since given man a lead to the discovery of potent drugs that combat both human and plant diseases. The soil provides the medium for the growth of medicinal plants, but its contamination greatly affects the quality of drugs, food crops, and other essential elements present in the plants which give strength to the body. This area has attracted the attention of scientists and the drug industry toward developing more potent drugs from medicinal plants grown in different soil. The studies of the effect of various parameters and the properties of soil such as; effect of heavy metals, pH, soil organic matter, and phytoremediation process have given a measure of some quality dependence of the soil producing secondary metabolites and soil containing microbes. The information provided will be useful in determine the action of microbes and their interaction with the soil and all true plants producing drugs. Some active compounds in plants and microbes, their properties, and applications have been described in this review. The soil microbes, activities and their interactions, effects of soil particle size, dispersibility and stability of microbes in the soil, and the future outlook for the development of novel active compounds have been reported.

Computational prediction of cytochrome P450 inhibition and induction

Cytochrome P450 (CYP) enzymes play an important role in the phase I metabolism of many xenobiotics. Most drug-drug interactions (DDIs) associated with CYP are caused by either CYP inhibition or induction. The early detection of potential DDIs is highly desirable in the pharmaceutical industry because DDIs can cause serious adverse events, which can lead to poor patient health and drug development failures. Recently, many computational studies predicting CYP inhibition and induction have been reported. The current computational modeling approaches for CYP metabolism are classified as ligand- and structure-based; various techniques, such as quantitative structure-activity relationships, machine learning, docking, and molecular dynamic simulation, are involved in both the approaches. Recently, combining these two approaches have resulted in improvements in the prediction accuracy of DDIs. In this review, we present important, recent developments in the computational prediction of the inhibition of four clinically crucial CYP isoforms (CYP1A2, 2C9, 2D6, and 3A4) and three nuclear receptors (aryl hydrocarbon receptor, constitutive androstane receptor, and pregnane X receptor) involved in the induction of CYP1A2, 2B6, and 3A4, respectively.

Drug-Drug Interactions Of Amiodarone And Quinidine On The Pharmacokinetics Of Eliglustat In Rats

Background

Eliglustat, a new oral substrate-reduction therapy, was recently approved as a first-line therapy for Gaucher's disease type 1 (GD1) patients.

Purpose

The purpose of the present study was to develop and validate a simple UPLC-MS/MS method for the measurement of plasma-eliglustat concentration and to investigate the effects of amiodarone and quinidine on eliglustat metabolism in rats.

Methods

Eighteen rats were randomly divided into three groups (n=6): control (0.5% CMC-Na, group A), amiodarone (60 mg/kg, group B), and quinidine (100 mg/kg, group C). Thirty minutes later, 10 mg/kg eliglustat was orally administered to each rat and concentrations of eliglustat in the rats determined by our UPLC-MS/MS method.

Results

Amiodarone and quinidine increased the main pharmacokinetic parameters (AUC0→_t, AUC_0→∞, and C_max) of eliglustat significantly and decreased clearance obviously.

Conclusion

Amiodarone and quinidine can elevate eliglustat exposure and have an inhibitory effect on eliglustat metabolism. Clearly, appropriate pharmacological studies of eliglustat in patients treated with amiodarone or quinidine should be done in future.

Systems Pharmacology for Investigation of the Mechanisms of Action of Traditional Chinese Medicine in Drug Discovery

As a traditional medical intervention in Asia and a complementary and alternative medicine in western countries, traditional Chinese medicine (TCM) has attracted global attention in the life science field. TCM provides extensive natural resources for medicinal compounds, and these resources are generally regarded as effective and safe for use in drug discovery. However, owing to the complexity of compounds and their related multiple targets of TCM, it remains difficult to dissect the mechanisms of action of herbal medicines at a holistic level. To solve the issue, in the review, we proposed a novel approach of systems pharmacology to identify the bioactive compounds, predict their related targets, and illustrate the molecular mechanisms of action of TCM. With a predominant focus on the mechanisms of actions of TCM, we also highlighted the application of the systems pharmacology approach for the prediction of drug combination and dynamic analysis, the synergistic effects of TCMs, formula dissection, and theory analysis. In summary, the systems pharmacology method contributes to understand the complex interactions among biological systems, drugs, and complex diseases from a network perspective. Consequently, systems pharmacology provides a novel approach to promote drug discovery in a precise manner and a systems level, thus facilitating the modernization of TCM.

Cytotoxic Trichothecene Macrolides Produced by the Endophytic Myrothecium roridum

Six new macrolides named myrothecines D-G (1-4), 16-hydroxymytoxin B (5), and 14'-dehydrovertisporin (6), including four 10,13-cyclotrichothecane derivatives, in addition to 12 known compounds (7-18), were isolated from three endophytic Myrothecium roridum, IFB-E008, IFB-E009, and IFB-E012. The isolated compounds were characterized by MS, NMR, CD, and single-crystal X-ray crystallography. The isolated macrolides exhibited an antiproliferation effect against chronic myeloid leukemia K562 and colorectal carcinoma SW1116 cell lines. Compounds 1-6 were cytotoxic, with IC₅₀ values ranging between 56 nM and 16 μM. Since slight structural changes led to obvious activity differences, the CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis) methods were then used to explore the 3D QSAR (three-dimensional quantitative structure-activity relationship) of these macrolides. The result showed that the steric, electrostatic, hydrophobic, and H-bond acceptor factors were involved in their cytotoxicity and provided an in-depth understanding of the structure-activity relationships of these metabolites.

Exploring the Chemical Space of Cytochrome P450 Inhibitors Using Integrated Physicochemical Parameters, Drug Efficiency Metrics and Decision Tree Models

The cytochrome P450s (CYPs) play a central role in the metabolism of various endogenous and exogenous compounds including drugs. CYPs are vulnerable to inhibition and induction which can lead to adverse drug reactions. Therefore, insights into the underlying mechanism of CYP450 inhibition and the estimation of overall CYP inhibitor properties might serve as valuable tools during the early phases of drug discovery. Herein, we present a large data set of inhibitors against five major metabolic CYPs (CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) for the evaluation of important physicochemical properties and ligand efficiency metrics to define property trends across various activity levels (active, efficient and inactive). Decision tree models for CYP inhibition were developed with an accuracy >90% for both the training set and 10-folds cross validation. Overall, molecular weight (MW), hydrogen bond acceptors/donors (HBA/HBD) and lipophilicity (clogP/logPo/w) represent important physicochemical descriptors for CYP450 inhibitors. However, highly efficient CYP inhibitors show mean MW, HBA, HBD and logP values between 294.18–482.40,5.0–8.2,1–7.29 and 1.68–2.57, respectively. Our results might help in optimization of toxicological profiles associated with new chemical entities (NCEs), through a better understanding of inhibitor properties leading to CYP-mediated interactions.

Cytochrome P450 Enzymes Involved in Metoprolol Metabolism and Use of Metoprolol as a CYP2D6 Phenotyping Probe Drug

Metoprolol is used for phenotyping of cytochrome P450 (CYP) 2D6, a CYP isoform considered not to be inducible by inducers of the CYP2C, CYP2B, and CYP3A families such as rifampicin. While assessing CYP2D6 activity under basal conditions and after pre-treatment with rifampicin in vivo, we surprisingly observed a drop in the metoprolol/α-OH-metoprolol clearance ratio, suggesting CYP2D6 induction. To study this problem, we performed in vitro investigations using HepaRG cells and primary human hepatocytes (before and after treatment with 20 μM rifampicin), human liver microsomes, and CYP3A4-overexpressing supersomes. While mRNA expression levels of CYP3A4 showed a 15- to 30-fold increase in both cell models, mRNA of CYP2D6 was not affected by rifampicin. 1'-OH-midazolam formation (reflecting CYP3A4 activity) increased by a factor of 5-8 in both cell models, while the formation of α-OH-metoprolol increased by a factor of 6 in HepaRG cells and of 1.4 in primary human hepatocytes. Inhibition studies using human liver microsomes showed that CYP3A4, 2B6, and 2C9 together contributed 19.0 ± 2.6% (mean ± 95%CI) to O-demethylation, 4.0 ± 0.7% to α-hydroxylation, and 7.6 ± 1.7% to N-dealkylation of metoprolol. In supersomes overexpressing CYP3A4, metoprolol was α-hydroxylated in a reaction inhibited by the CYP3A4-specific inhibitor ketoconazole, but not by the CYP2D6-specific inhibitor quinidine. We conclude that metoprolol is not exclusively metabolized by CYP2D6. CYP3A4, 2B6, and 2C9, which are inducible by rifampicin, contribute to α-hydroxylation, O-demethylation, and N-dealkylation of metoprolol. This contribution is larger after CYP induction by rifampicin but is too small to compromise the usability of metoprolol α-hydroxylation for CYP2D6 phenotyping.

In silico investigation by conceptual DFT and molecular docking of antitrypanosomal compounds for understanding cruzain inhibition

Current knowledge about Chagas disease, the potentially life-threatening illness caused by the protozoan parasite (Trypanosoma cruzi), has led to the development of new drugs and the understanding of their mode of action. The Conceptual Density-Functional Theory was applied to determine the active center sites of trypanocidal compounds, extended by the Molecular Docking analysis to identify the most favorable ligand conformation when bound to the active site of cruzain. Results such as CHELPG charges, Fukui function, MESP, and Molecular Docking analysis are reported and discussed in the present investigation. Whereas, a close agreement with experimental results was found to explain the possibility of studying the receptor-binding mode using these different axes.

Guanfu base A, an antiarrhythmic alkaloid of Aconitum coreanum, Is a CYP2D6 inhibitor of human, monkey, and dog isoforms

Guanfu base A (GFA) is a novel heterocyclic antiarrhythmic drug isolated from Aconitum coreanum (Lèvl.) rapaics and is currently in a phase IV clinical trial in China. However, no study has investigated the influence of GFA on cytochrome P450 (P450) drug metabolism. We characterized the potency and specificity of GFA CYP2D inhibition based on dextromethorphan O-demethylation, a CYP2D6 probe substrate of activity in human, mouse, rat, dog, and monkey liver microsomes. In addition, (+)-bufuralol 1'-hydroxylation was used as a CYP2D6 probe for the recombinant form (rCYP2D6), 2D1 (rCYP2D1), and 2D2 (rCYP2D2) activities. Results show that GFA is a potent noncompetitive inhibitor of CYP2D6, with inhibition constant Ki = 1.20 ± 0.33 μM in human liver microsomes (HLMs) and Ki = 0.37 ± 0.16 μM for the human recombinant form (rCYP2D6). GFA is also a potent competitive inhibitor of CYP2D in monkey (Ki = 0.38 ± 0.12 μM) and dog (Ki = 2.4 ± 1.3 μM) microsomes. However, GFA has no inhibitory activity on mouse or rat CYP2Ds. GFA did not exhibit any inhibition activity on human recombinant CYP1A2, 2A6, 2C8, 2C19, 3A4, or 3A5, but showed slight inhibition of 2B6 and 2E1. Preincubation of HLMs and rCYP2D6 resulted in the inactivation of the enzyme, which was attenuated by GFA or quinidine. Beagle dogs treated intravenously with dextromethorphan (2 mg/ml) after pretreatment with GFA injection showed reduced CYP2D metabolic activity, with the Cmax of dextrorphan being one-third that of the saline-treated group and area under the plasma concentration-time curve half that of the saline-treated group. This study suggests that GFA is a specific CYP2D6 inhibitor that might play a role in CYP2D6 medicated drug-drug interaction.

Insights on cytochrome p450 enzymes and inhibitors obtained through QSAR studies

The cytochrome P450 (CYP) superfamily of heme enzymes play an important role in the metabolism of a large number of endogenous and exogenous compounds, including most of the drugs currently on the market. Inhibitors of CYP enzymes have important roles in the treatment of several disease conditions such as numerous cancers and fungal infections in addition to their critical role in drug-drug interactions. Structure activity relationships (SAR), and three-dimensional quantitative structure activity relationships (3D-QSAR) represent important tools in understanding the interactions of the inhibitors with the active sites of the CYP enzymes. A comprehensive account of the QSAR studies on the major human CYPs 1A1, 1A2, 1B1, 2A6, 2B6, 2C9, 2C19, 2D6, 2E1, 3A4 and a few other CYPs are detailed in this review which will provide us with an insight into the individual/common characteristics of the active sites of these enzymes and the enzyme-inhibitor interactions.

Studies of new fused benzazepine as selective dopamine D3 receptor antagonists using 3D-QSAR, molecular docking and molecular dynamics

In recent years, great interest has been paid to the development of compounds with high selectivity for central dopamine (DA) D3 receptors, an interesting therapeutic target in the treatment of different neurological disorders. In the present work, based on a dataset of 110 collected benzazepine (BAZ) DA D3 antagonists with diverse kinds of structures, a variety of in silico modeling approaches, including comparative molecular field analysis (CoMFA), comparative similarity indices analysis (CoMSIA), homology modeling, molecular docking and molecular dynamics (MD) were carried out to reveal the requisite 3D structural features for activity. Our results show that both the receptor-based (Q(2) = 0.603, R(2) (ncv) = 0.829, R(2) (pre) = 0.690, SEE = 0.316, SEP = 0.406) and ligand-based 3D-QSAR models (Q(2) = 0.506, R(2) (ncv) =0.838, R(2) (pre) = 0.794, SEE = 0.316, SEP = 0.296) are reliable with proper predictive capacity. In addition, a combined analysis between the CoMFA, CoMSIA contour maps and MD results with a homology DA receptor model shows that: (1) ring-A, position-2 and R(3) substituent in ring-D are crucial in the design of antagonists with higher activity; (2) more bulky R(1) substituents (at position-2 of ring-A) of antagonists may well fit in the binding pocket; (3) hydrophobicity represented by MlogP is important for building satisfactory QSAR models; (4) key amino acids of the binding pocket are CYS101, ILE105, LEU106, VAL151, PHE175, PHE184, PRO254 and ALA251. To our best knowledge, this work is the first report on 3D-QSAR modeling of the new fused BAZs as DA D3 antagonists. These results might provide information for a better understanding of the mechanism of antagonism and thus be helpful in designing new potent DA D3 antagonists.

QSAR of cytochrome inhibitors

Cytochrome P450 (CYP450) enzymes are predominantly involved in the Phase I metabolism of xenobiotics. Metabolic inhibition and induction can give rise to clinically important drug-drug interactions. Metabolic stability is a prerequisite for sustaining the therapeutically relevant concentrations, and very often drug candidates are sacrificed due to poor metabolic profiles. Computational tools such as quantitative structure-activity relationships are widely used to study different metabolic end points successfully to accelerate the drug discovery process. There are a lot of computational studies on clinically important CYPs already reported in recent years. But other clinically significant families are to yet be explored computationally. Powerfulness of quantitative structure-activity relationship will drive computational chemists to develop new potent and selective inhibitors of different classes of CYPs for the treatment of different diseases with least drug-drug interactions. Furthermore, there is a need to enhance the accuracy, interpretability and confidence in the computational models in accelerating the drug discovery pathways.