Prediction of cytochrome P450 mediated metabolism

Investigation of in silico studies for cytochrome P450 isoforms specificity

Cytochrome P450 (CYP450) enzymes comprise a highly diverse superfamily of heme-thiolate proteins that responsible for catalyzing over 90 % of enzymatic reactions associated with xenobiotic metabolism in humans. Accurately predicting whether chemicals are substrates or inhibitors of different CYP450 isoforms can aid in pre-selecting hit compounds for the drug discovery process, chemical toxicology studies, and patients treatment planning. In this work, we investigated in silico studies on CYP450s specificity over past twenty years, categorizing these studies into structure-based and ligand-based approaches. Subsequently, we utilized 100 of the most frequently prescribed drugs to test eleven machine learning-based prediction models which were published between 2015 and 2024. We analyzed various aspects of the evaluated models, such as their datasets, algorithms, and performance. This will give readers with a comprehensive overview of these prediction models and help them choose the most suitable one to do prediction. We also provide our insights for future research trend in both structure-based and ligand-based approaches in this field.

Prediction of Cytochrome P450 Substrates Using the Explainable Multitask Deep Learning Models

Cytochromes P450 (P450s or CYPs) are the most important phase I metabolic enzymes in the human body and are responsible for metabolizing ∼75% of the clinically used drugs. P450-mediated metabolism is also closely associated with the formation of toxic metabolites and drug-drug interactions. Therefore, it is of high importance to predict if a compound is the substrate of a given P450 in the early stage of drug development. In this study, we built the multitask learning models to simultaneously predict the substrates of five major drug-metabolizing P450 enzymes, namely, CYP3A4, 2C9, 2C19, 2D6, and 1A2, based on the collected substrate data sets. Compared to the single-task model and conventional machine learning models, the multitask fingerprints and graph neural networks model achieved superior performance with the average AUC values of 90.8% on the test set. Notably, the multitask model demonstrated its good performance on the small amount of substrate data sets such as CYP1A2, 2C9, and 2C19. In addition, the Shapley additive explanation and the attention mechanism were used to reveal specific substructures associated with P450 substrates, which were further confirmed and complemented by the substructure mining tool and the literature.

Effect of Lipid Bilayer Anchoring on the Conformational Properties of the Cytochrome P450 2D6 Binding Site

Human cytochrome P450 (CYP) proteins metabolize 75% of small-molecule pharmaceuticals, which makes structure-based modeling of CYP metabolism and inhibition, bolstered by the current availability of X-ray crystal structures of CYP globular catalytic domains, an attractive prospect. Accounting for this broad metabolic capacity is a combination of the existence of multiple different CYP proteins and the capacity of a single CYP protein to metabolize multiple different small molecules. It is thought that structural plasticity and flexibility contribute to this latter property; therefore, incorporating diverse conformational states of a particular CYP is likely an important consideration in structure-based CYP metabolism and inhibition modeling. While all-atom explicit-solvent molecular dynamics simulations can be used to generate conformational ensembles under biologically relevant conditions, existing CYP crystal structures are of the globular domain only, whereas human CYPs contain N-terminal transmembrane and linker peptides that anchor the globular catalytic domain to the endoplasmic reticulum. To determine whether this can cause significant differences in the sampled binding site conformations, microsecond scale all-atom explicit-solvent molecular dynamics simulations of the CYP2D6 globular domain in an aqueous environment were compared with those of the full-length protein anchored in a POPC lipid bilayer. While bilayer-anchoring damped some structural fluctuations in the globular domain relative to the aqueous simulations, none of the affected residues included binding site pocket residues. Furthermore, clustering of molecular dynamics snapshots based on either pairwise binding site pocket RMSD or volume differences demonstrated a lack of separation of snapshots from the two simulation conditions into different clusters. These results suggest the substantially simpler and computationally cheaper aqueous simulation approach can be used to generate a relevant conformational ensemble of the CYP2D6 binding site for structure-based metabolism and inhibition modeling.

Deuterium Editing of Small Molecules: A Case Study on Antitumor Activity of 1,4-Benzodiazepine-2,5-dione Derivatives

Substituting hydrogen with deuterium in drug molecules is an appealing bioisosteric strategy for the generation of novel chemical entities in drug development. Optimizing lead compounds through deuteration has proven to be challenging and unpredictable, particularly for compounds with multiple metabolic sites. This study presents the pioneering achievement of substituting up to 19 hydrogen atoms with deuterium on 1,4-benzodiazepine-2,5-dione derivatives, shedding light on the structure-metabolism relationship and the impact of multiple deuterations on drug-like properties. Notably, the deuterated compound 3f exhibited remarkable antitumor activity in vivo and demonstrated favorable drug-like properties as a drug candidate.

Predictive Modelling in pharmacokinetics: from in-silico simulations to personalized medicine

INTRODUCTION

Pharmacokinetic parameters assessment is a critical aspect of drug discovery and development, yet challenges persist due to limited training data. Despite advancements in machine learning and in-silico predictions, scarcity of data hampers accurate prediction of drug candidates' pharmacokinetic properties.

AREAS COVERED

The study highlights current developments in human pharmacokinetic prediction, talks about attempts to apply synthetic approaches for molecular design, and searches several databases, including Scopus, PubMed, Web of Science, and Google Scholar. The article stresses importance of rigorous analysis of machine learning model performance in assessing progress and explores molecular modeling (MM) techniques, descriptors, and mathematical approaches. Transitioning to clinical drug development, article highlights AI (Artificial Intelligence) based computer models optimizing trial design, patient selection, dosing strategies, and biomarker identification. In-silico models, including molecular interactomes and virtual patients, predict drug performance across diverse profiles, underlining the need to align model results with clinical studies for reliability. Specialized training for human specialists in navigating predictive models is deemed critical. Pharmacogenomics, integral to personalized medicine, utilizes predictive modeling to anticipate patient responses, contributing to more efficient healthcare system. Challenges in realizing potential of predictive modeling, including ethical considerations and data privacy concerns, are acknowledged.

EXPERT OPINION

AI models are crucial in drug development, optimizing trials, patient selection, dosing, and biomarker identification and hold promise for streamlining clinical investigations.

Water Exchange from the Buried Binding Sites of Cytochrome P450 Enzymes 1A2, 2D6, and 3A4 Correlates with Conformational Fluctuations

Human cytochrome P450 enzymes (CYPs) are critical for the metabolism of small-molecule pharmaceuticals (drugs). As such, the prediction of drug metabolism by and drug inhibition of CYP activity is an important component of the drug discovery and design process. Relative to the availability of a wide range of experimental atomic-resolution CYP structures, the development of structure-based CYP activity models has been limited. To better characterize the role of CYP conformational fluctuations in CYP activity, we perform multiple microsecond-scale all-atom explicit-solvent molecular dynamics (MD) simulations on three CYP isoforms, 1A2, 2D6, and 3A4, which together account for the majority of CYP-mediated drug metabolism. The MD simulations employ a variety of positional restraints, ranging from keeping all CYP atoms close to their experimentally determined coordinates to allowing full flexibility. We find that, with full flexibility, large fluctuations in the CYP binding sites correlate with efficient water exchange from these buried binding sites. This is especially true for 1A2, which, when restrained to its crystallographic conformation, is unable to exchange water between the binding site and bulk solvent. These findings imply that, in addition to crystal structures, a representative ensemble of conformational states ought to be included when developing structure-based CYP activity models.

Prediction of Sites of Metabolism of CYP3A4 Substrates Utilizing Docking-Derived Geometric Features

Cytochrome P450 3A4 (CYP3A4) is one of the major drug-metabolizing enzymes in the human body and is responsible for the metabolism of ∼50% of clinically used drugs. Therefore, the identification of the compound's sites of metabolism (SOMs) mediated by CYP3A4 is of utmost importance in the early stage of drug discovery and development. Herein, docking-based approaches incorporating geometric features were used for SOMs prediction of CYP3A4 substrates. The cross-docking poses of a relatively large data set containing 474 substrates were analyzed in depth, and a widely observed geometric pattern called the close proximity of SOMs was derived from the poses. On the basis of the close proximity, several structure-based models have been constructed, which demonstrated better performance than those structure-based models using the criterion of Fe-SOM distance. For further improving the prediction performance, the structure-based models were also combined with the well-known ligand-based model SMARTCyp. One combined model exhibited good performance on the SOMs prediction of an external substrate set containing kinase inhibitors, PROTACs, approved drugs, and some lead compounds.

Twenty-four hours of Thiamethoxam: In vivo and molecular dynamics simulation study on the toxicokinetic and underlying mechanisms in quails (Coturnix japonica)

Neonicotinoids is the most widely used insecticide, its contamination has led to sustained bird population declines. However, the toxicokinetic and underlying mechanisms of neonicotinoid toxicity in birds are largely unknown. Thiamethoxam (TMX), as a representative neonicotinoid insecticide, is now widely detected in most environmental medium and animal bodies. In this study, 5 mg/kg body weight TMX (potential environmental intake level) were orally administrated to male Japanese quails (Coturnix japonica). We found a rapid absorption, distribution, metabolism and elimination of TMX in quails in a period of 24 h, with the main metabolite, clothianidin (CLO), being extensively distributed and rapidly eliminated from tissues as well. The maximum plasm concentration of CLO was consistent with wild birds. Metabolomics analysis and followed determination of liver enzymes mRNA expression indicated the rapid metabolism was mediated mainly by CYPs and GSTs that involved riboflavin metabolism and glutathione metabolism pathways upon TMX exposure. Molecular dynamic simulation showed the strongest binding interaction in quail CYP2H1-TMX and CYP3A12-CLO complexes among a set of CYPs-substrate. The present study elucidated toxicokinetic and underlying metabolic mechanisms of TMX in quails at environmentally-relevant concentration, the findings would facilitate the understanding of potential risks of TMX and its metabolites to birds.

Enantioselective Metabolic Mechanism and Metabolism Pathway of Pydiflumetofen in Rat Liver Microsomes: In Vitro and In Silico Study

Pydiflumetofen (PYD) has been used worldwide. However, the enantioselective fate of PYD within mammals is not clear. Thus, the enantioselective metabolism and its potential mechanisms of PYD were explored via in vitro and in silico. Consistent results were observed between metabolism and enzyme kinetics experiments, with S-PYD metabolizing faster than R-PYD in rat liver microsomes. Moreover, CYP3A1 and carboxylesterase 1 were found to be major enzymes participating in the metabolism of PYD. Based on the computational results, S-PYD bound with CYP3A1 and carboxylesterase 1 more tightly with lower binding free energy than R-PYD, explaining the mechanism of enantioselective metabolism. Nine phase I metabolites of PYD were identified, and metabolic pathways of PYD were speculated. This study is the first to clarify the metabolism of PYD in mammals, and further research to evaluate the toxicological implications of these metabolites will help in assessing the risk of PYD.

Modulating effect of DL-kavain on the mutagenicity and carcinogenicity induced by doxorubicin in Drosophila melanogaster

Kavain, kavalactone, present in Piper methysticum exhibits anticonvulsive, analgesic, anxiolytic, antiepileptic, antithrombotic, anti-inflammatory and antioxidant properties. Given its importance, the aim of the present study was to assess (1) the mutagenic and carcinogenicity of kavain administered alone and (2) the antimutagenic and anticarcinogenic potential when administered simultaneously with the chemotherapeutic drug doxorubicin (DXR) using the Somatic Mutation and Recombination Test (SMART) and Epithelial Tumor Test (ETT) using Drosophila melanogaster as a model system. Third-stage larvae from a standard (ST) and high metabolic bioactivation (HB) crosses were treated with different kavain concentrations (32, 64 or 128 μg/ml), alone or in conjunction with DXR (0.125 mg/ml). In ST descendants, kavain produced no significant mutagenic or recombinogenic effects. In the HB cross, mutagenic activity was observed at kavain concentrations of 64 and 128 μg/ml. In the DXR and kavain co-treatment, a modulating effect of the DXR-mediated mutagenic response dependent upon the concentration was detected in both crosses. In ETT, no marked carcinogenic or anticarcinogenic activity was noted for kavain. However, when kavain was combined with DXR synergistic induction of tumors by the chemotherapeutic drug occurred indicating that kavain enhanced the carcinogenic action of DXR.

Mutagenicity risk prediction of PAH and derivative mixtures by in silico simulations oriented from CYP compound I-mediated metabolic activation

PAHs and their derivatives are the main sources of mutagenicity and carcinogenicity in airborne particular matter and cause serious public health and environmental problems. Risk assessment is challenging due to the mixed nature and deficiency of toxicity data of most PAHs and their derivatives. Cytochrome P450 enzymes (CYPs) play important roles in PAH-induced carcinogenicity via metabolic activation, and CYP conformations with compound I structures strongly influence metabolic sites and metabolite species. In this study, complexes of BaP with CYP1A1, CYP1B1 or CYP2C19 compound I were successfully simulated by QM/MM methods and verified by metabolic clearance, and the mutagenicity of chemicals was then predicted by the BaP-7,8-epoxide-related metabolic conformation fitness (MCF) approach, which was validated by Ames tests, showing satisfying accuracy (R² = 0.46-0.66). Furthermore, a prediction model of the mutagenicity risk of PAH and derivative mixtures was established based on the relative potential factor (RPF) approach and the RPF calculated from the mathematical relationship between the minimum MCF (MCF_min) and RPF, which was successfully validated by the mutagenesis of PAH and derivative mixture mimic-simulating PM2.5 samples collected in eastern China. This study provides fast reliable tools for assessing risk of the complex components of environmental PAHs and their derivatives.

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.

Effects of paeoniflorin on the activities and mRNA expression of rat CYP1A2, CYP2C11 and CYP3A1 enzymes in vivo

Paeoniflorin is the major constituent in extracts of the paeony root, the purpose of the present study was to assess the effects of paeoniflorin on the activities and mRNA expression of the rat hepatic drug-metabolizing enzymes cytochrome P450 (CYP1A2), CYP2C11 and CYP3A1 in vivo.Sprague-Dawley (SD) male rats were treated with paeoniflorin at the dosage of 25, 50 and 100 mg/kg or 0.9% sodium chloride solution by intragastric administration for 7 days, then were given probe drugs phenacetin (CYP1A2), tolbutamide (CYP2C11), or midazolam (CYP3A1) orally on the eighth day. Blood samples were collected at various times, and the plasma concentrations of the probe drugs were estimated with ultra-high-performance liquid chromatography. The mRNA expression levels of rat hepatic CYP1A2, CYP2C11 and CYP3A1 were analysed with real-time PCR.The pharmacokinetic results indicated that paeoniflorin inhibits the activities of CYP1A2, CYP2C11 and CYP3A1 in vivo. The effect was most pronounced on CYP3A1, according to the United States Food and Drug Administration classification of inhibitors of CYP3A, it reached the category of moderate inhibition. The mRNA expression levels of 3 CYP enzymes were also tended to be inhibited.We conclude that paeoniflorin can inhibit the activities of CYP1A2, CYP2C11 and CYP3A1 in vivo, which may affect the metabolism of drugs that are primarily dependent on these pathways.

Metabolic activation mechanism of 2,2',3,3',6,6'-hexachlorobiphenyl (PCB136) by cytochrome P450 2B6: A QM/MM approach

Cytochrome P450 enzymes (CYPs) play an essential role in the bio-transformation of polychlorinated biphenyls (PCBs). The present work implemented quantum mechanic/molecular mechanic methods (QM/MM) and density functional theory (DFT) to study the metabolic activation of 2,2',3,3',6,6'-hexachlorobiphenyl (PCB136) catalyzed by CYP2B6. Electrophilic additions at the C^α and C^β positions generate different active intermediates. The electrophilic addition energy barrier of C^β is 10.9 kcal/mol higher than that of C^α, and C^α is the preferred site for the electrophilic addition reaction. Based on the previous experimental studies, this work investigated the mechanism of converting active intermediates into OH-PCB136, which has high toxicity in a non-enzymatic environment. Structural analysis via the electrostatic and noncovalent interactions indicates that Phe108, Ile114, Phe115, Phe206, Phe297, Ala298, Leu363, Val367, TIP32475 and TIP32667 play crucial roles in substrate recognition and metabolism. The analysis suggests that the halogen-π interactions are important factors for the metabolism of CYP2B6 to halogenated environmental pollutants. This work improved the understanding of the metabolism and activation process of chiral PCBs, and can be used as a guide to improve the microbial degradation efficiency of PCB136.

Frequent occurrence of triclosan hydroxylation in mammals: A combined theoretical and experimental investigation

Triclosan (TCS) is a widespread antimicrobial agent with many adverse health risks. Its hepatoxicity invariably points to the activation of constitutive androstane receptor (CAR), which regulates cytochrome P450 (CYP) genes that are critical for oxidative metabolism. Here, we provide the theoretical and experimental evidences showing that metabolic activation of TCS frequently occurs through aromatic hydroxylation in mammals. CYP-mediated oxidation was predicted to take place at each aromatic C‒H bond. Molecular docking and in vitro approaches reveal oxidative reaction could be efficiently catalyzed by CAR-regulated CYP2B6 enzyme. Parallel reaction monitoring (PRM) high-resolution mass spectrometry was utilized to identify and profile TCS oxidative metabolites in paired mouse liver, bile, feces, plasma and urine. We found multiple hydroxylated isomers including the products generated via the NIH shift of chlorine, as well as their subsequent conjugates. These metabolites showed isomer-specific retention in mice. Glucuronide conjugates are more readily excreted than the sulfates. Moreover, for the first time, isomeric hydroxylated metabolites were detected in the urine and stool of human subjects used TCS-contained household and personal care products. Collectively, these findings suggest that hydroxylation is an important, yet often underestimated element that worth considering to fully evaluate the biological fates and health risks of TCS.

Assessment of CYP2C9 Structural Models for Site of Metabolism Prediction

Structure-based prediction of a compound's potential sites of metabolism (SOMs) mediated by cytochromes P450 (CYPs) is highly advantageous in the early stage of drug discovery. However, the accuracy of the SOMs prediction can be influenced by several factors. CYP2C9 is one of the major drug-metabolizing enzymes in humans and is responsible for the metabolism of ∼13 % of clinically used drugs. In this study, we systematically evaluated the effects of protein crystal structure models, scoring functions, heme forms, conserved active-site water molecules, and protein flexibility on SOMs prediction of CYP2C9 substrates. Our results demonstrated that, on average, ChemScore and GlideScore outperformed four other scoring functions: Vina, GoldScore, ChemPLP, and ASP. The performance of the crystal structure models with pentacoordinated heme was generally superior to that of the hexacoordinated iron-oxo heme (referred to as Compound I) models. Inclusion of the conserved active-site water molecule improved the prediction accuracy of GlideScore, but reduced the accuracy of ChemScore. In addition, the effect of the conserved water on SOMs prediction was found to be dependent on the receptor model and the substrate. We further found that one of snapshots from molecular dynamics simulations on the apo form can improve the prediction accuracy when compared to the crystal structural model.

Identification of structural properties influencing the metabolism of polycyclic aromatic hydrocarbons by cytochrome P450 1A1

Cytochrome P450 1A1 (CYP1A1) has served as a known metabolic enzyme that mediates the carcinogenesis of polycyclic aromatic hydrocarbons (PAHs). However, the structural mechanism involved in the metabolic capacity remains unclear. In this study, thirty-three calculated properties representing the physicochemical and electronic properties of PAH and PAH-CYP1A1 interactions were utilized to identify the key structural properties that affect metabolic processes, including binding ability, metabolic clearance, and mutagenicity, using a quantitative structure-activity relationship (QSAR) strategy combined with docking methods, QM/MM calculations and ab initio calculations. van der Waals interactions (glide vdw) appeared to be important for PAH binding to CYP1A1 and were mainly affected by the molecular weight and hydrophobic structures of PAHs. Interaction features between PAHs and heme, including the distance between iron and carbons of PAHs (Fe_C_min) and heme vdw, coordinately influence the metabolic clearance of PAHs. Furthermore, the electronic properties (ESP neg variance) appeared to be critical for the mutagenicity of PAHs by CYP1A1 through influencing epoxide metabolite formation. The QSAR models with these key properties provide a new perspective on the structural mechanism of PAH metabolism and provide a useful in silico tool for screening, classifying and predicting PAHs for their metabolism-related toxicities and risk assessment in the environment.

Preclinical Pharmacokinetics, Tissue Distribution and Primary Safety Evaluation of a Novel Curcumin Analogue H10 Suspension, a Potential 17β Hydroxysteroid Dehydrogenase Type 3 Inhibitor

17β Hydroxysteroid dehydrogenase type 3 (17β-HSD3) is the key enzyme in the biosynthesis of testosterone, which is an attractive therapeutic target for prostate cancer (PCa). H10, a novel curcumin analogue, was identified as a potential 17β-HSD3 inhibitor. The pharmacokinetic study of H10 in rats were performed by intraperitoneal (i.p.), intravenous (i.v.) and oral (p.o.) administration. In addition, the inhibitory effects of H10 against liver CYP3A4 were investigated in vitro using human liver microsomes (HLMs). The acute and chronic toxicological characteristics were characterized using single-dose and 30 d administration. All the mice were alive after i.p. H10 with dose of no more than 100 mg/kg which are nearly the maximum solubility in acute toxicity test. The pharmacokinetic characteristics of H10 fitted with linear dynamics model after single dose. Furthermore, H10 could bioaccumulate in testis, which was the target organ of 17β-HSD3 inhibitor. H10 distributed highest in spleen, and then in liver both after single and multiple i.p. administration. Moreover, H10 showed weak inhibition towards liver CYP3A4, and did not cause significant changes in aspartate transaminase (AST) and alanine transaminase (ALT) levels after treated with H10 for continuously 30 d. Taken together, these preclinical characteristics laid the foundation for further clinical studies of H10.

Deciphering Reaction Determinants of Altered-Activity CYP2D6 Variants by Well-Tempered Metadynamics Simulation and QM/MM Calculations

The xenobiotic metabolizing enzyme CYP2D6 is the P450 cytochrome family member with the highest rate of polymorphism. This causes changes in the enzyme activity and specificity, which can ultimately lead to adverse reactions during drug treatment. To avoid or lower CYP-related toxicity risks, prediction of the most likely positions within a molecule where a metabolic reaction might occur is paramount. In order to obtain accurate predictions, it is crucial to understand all phenomena within the active site of the enzyme that contribute to an efficient substrate recognition and the subsequent catalytic reaction together with their relative weight within the overall thermodynamic context. This study aims to define the weight of the driving forces upon the C-H bond activation within CYP2D6 wild-type and a clinically relevant allelic variant with increased activity (CYP2D6*53) featuring two amino acid mutations in close vicinity of the heme. First, we investigated the steric and electrostatic complementarity of the substrate bufuralol using well-tempered metadynamics simulations with the aim to obtain the free energy profiles for each site of metabolism (SoM) within the different active sites. Second, the stereoelectronic complementarity was determined for each SoM within the two different active-site environments. Relying on the well-tempered metadynamics simulation energy profiles of each SoM, we identified the binding mode that was closest to the preferred transition-state geometry for efficient C-H bond activation. The binding modes were then used as starting structures for the quantum mechanics/molecular mechanics calculations performed to quantify the corresponding activation barriers. Our results show the relevance of the steric component in orienting the SoM in an energetically accessible position toward the heme. However, the corresponding intrinsic reactivity and electronic complementarity within the active site must be accurately evaluated in order to obtain a meaningful reaction prediction, from which the predominant SoM can be determined. The F120I mutation lowered the activation barrier for the major site and one of the minor SoMs. However, it had an impact neither on the CYP2D6 enantioselectivity preference of the oxidation reaction nor on the stereoselectivity from the substrate point of view.

Comparative Dynamics and Functional Mechanisms of the CYP17A1 Tunnels Regulated by Ligand Binding

As an important member of cytochrome P450 (CYP) enzymes, CYP17A1 is a dual-function monooxygenase with a critical role in the synthesis of many human steroid hormones, making it an attractive therapeutic target. The emerging structural information about CYP17A1 and the growing number of inhibitors for these enzymes call for a systematic strategy to delineate and classify mechanisms of ligand transport through tunnels that control catalytic activity. In this work, we applied an integrated computational strategy to different CYP17A1 systems with a panel of ligands to systematically study at the atomic level the mechanism of ligand-binding and tunneling dynamics. Atomistic simulations and binding free energy computations identify the dynamics of dominant tunnels and characterize energetic properties of critical residues responsible for ligand binding. The common transporting pathways including S, 3, and 2c tunnels were identified in CYP17A1 binding systems, while the 2c tunnel is a newly formed pathway upon ligand binding. We employed and integrated several computational approaches including the analysis of functional motions and sequence conservation, atomistic modeling of dynamic residue interaction networks, and perturbation response scanning analysis to dissect ligand tunneling mechanisms. The results revealed the hinge-binding and sliding motions as main functional modes of the tunnel dynamic, and a group of mediating residues as key regulators of tunnel conformational dynamics and allosteric communications. We have also examined and quantified the mutational effects on the tunnel composition, conformational dynamics, and long-range allosteric behavior. The results of this investigation are fully consistent with the experimental data, providing novel rationale to the experiments and offering valuable insights into the relationships between the structure and function of the channel networks and a robust atomistic model of activation mechanisms and allosteric interactions in CYP enzymes.

SMARTCyp 3.0: enhanced cytochrome P450 site-of-metabolism prediction server

MOTIVATION

Cytochromes P450 are the most important class of drug metabolizing enzymes. Prediction of drug metabolism is important in development of new drugs, to understand and reduce adverse drug reactions and to reduce animal testing.

RESULTS

SMARTCyp 3.0 is an updated version of our previous web server for prediction of site-of-metabolism for Cytochrome P450-mediated metabolism, now in Python 3 with increased structural coverage and new features. The SMARTCyp program is a first principle-based method using density functional theory determined activation energies for more than 250 molecules to identify the most likely site-of-metabolism. New features include a similarity measure between the query molecule and the model fragment, a new graphical interface and additional parameters expanding the structural coverage of the SMARTCyp program.

AVAILABILITY AND IMPLEMENTATION

The SMARTCyp server is freely available for use on the web at smartcyp.sund.ku.dk.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

In-Silico Modeling in Drug Metabolism and Interaction: Current Strategies of Lead Discovery

BACKGROUND

Drug metabolism is a complex mechanism of human body systems to detoxify foreign particles, chemicals, and drugs through bio alterations. It involves many biochemical reactions carried out by invivo enzyme systems present in the liver, kidney, intestine, lungs, and plasma. After drug administration, it crosses several biological membranes to reach into the target site for binding and produces the therapeutic response. After that, it may undergo detoxification and excretion to get rid of the biological systems. Most of the drugs and its metabolites are excreted through kidney via urination. Some drugs and their metabolites enter into intestinal mucosa and excrete through feces. Few of the drugs enter into hepatic circulation where they go into the intestinal tract. The drug leaves the liver via the bile duct and is excreted through feces. Therefore, the study of total methodology of drug biotransformation and interactions with various targets is costly.

METHODS

To minimize time and cost, in-silico algorithms have been utilized for lead-like drug discovery. Insilico modeling is the process where a computer model with a suitable algorithm is developed to perform a controlled experiment. It involves the combination of both in-vivo and in-vitro experimentation with virtual trials, eliminating the non-significant variables from a large number of variable parameters. Whereas, the major challenge for the experimenter is the selection and validation of the preferred model, as well as precise simulation in real physiological status.

RESULTS

The present review discussed the application of in-silico models to predict absorption, distribution, metabolism, and excretion (ADME) properties of drug molecules and also access the net rate of metabolism of a compound.

CONCLUSION

It helps with the identification of enzyme isoforms; which are likely to metabolize a compound, as well as the concentration dependence of metabolism and the identification of expected metabolites. In terms of drug-drug interactions (DDIs), models have been described for the inhibition of metabolism of one compound by another, and for the compound-dependent induction of drug-metabolizing enzymes.

Interpretation of Drug Interaction Using Systemic and Local Tissue Exposure Changes

Systemic exposure of a drug is generally associated with its pharmacodynamic (PD) effect (e.g., efficacy and toxicity). In this regard, the change in area under the plasma concentration-time curve (AUC) of a drug, representing its systemic exposure, has been mainly considered in evaluation of drug-drug interactions (DDIs). Besides the systemic exposure, the drug concentration in the tissues has emerged as a factor to alter the PD effects. In this review, the status of systemic exposure, and/or tissue exposure changes in DDIs, were discussed based on the recent reports dealing with transporters and/or metabolic enzymes mediating DDIs. Particularly, the tissue concentration in the intestine, liver and kidney were referred to as important factors of PK-based DDIs.

Identification and in silico prediction of metabolites of tebufenozide derivatives by major human cytochrome P450 isoforms

Cytochrome P450 (CYP) enzymes constitute a superfamily of heme-containing monooxygenases. CYPs are involved in the metabolism of many chemicals such as drugs and agrochemicals. Therefore, examining the metabolic reactions by each CYP isoform is important to elucidate their substrate recognition mechanisms. The clarification of these mechanisms may be useful not only for the development of new drugs and agrochemicals, but also for risk assessment of chemicals. In our previous study, we identified the metabolites of tebufenozide, an insect growth regulator, formed by two human CYP isoforms: CYP3A4 and CYP2C19. The accessibility of each site of tebufenozide to the reaction center of CYP enzymes and the susceptibility of each hydrogen atom for metabolism by CYP enzymes were evaluated by a docking simulation and hydrogen atom abstraction energy estimation at the density functional theory level, respectively. In this study, the same in silico prediction method was applied to the metabolites of tebufenozide derivatives by major human CYPs (CYP1A2, 2C9, 2C19, 2D6, and 3A4). In addition, the production rate of the metabolites by CYP3A4 was quantitively analyzed by frequency based on docking simulation and hydrogen atom abstraction energy using the classical QSAR approach. Then, the obtained QSAR model was applied to predict the sites of metabolism and the metabolite production order by each CYP isoform.

Biomimetic Oxidation of Benzofurans with Hydrogen Peroxide Catalyzed by Mn(III) Porphyrins

The modelling of metabolic activation of the benzofuran nucleus is important to obtain eco-sustainable degradation methods and to understand the related mechanisms. The present work reports the catalytic oxidation of benzofuran, 2-methylbenzofuran, and 3-methylbenzofuran by hydrogen peroxide, at room temperature, in the presence of different Mn(III) porphyrins as models of cytochrome P450 enzymes. Conversions above 95% were attained for all the substrates. The key step is the formation of epoxides, which undergo different reaction pathways depending on factors, such as the position of the methyl group and the reaction and work-up conditions used.

Potential Anti-Cancer Flavonoids Isolated From Caesalpinia bonduc Young Twigs and Leaves: Molecular Docking and In Silico Studies

Tyrosine kinase (TK), vascular endothelial growth factor (VEGF), and matrix metalloproteinases (MMP) are important cancer therapeutic target proteins. Based on reported anti-cancer and cytotoxic activities of Caesalpinia bonduc, this study isolated phytochemicals from young twigs and leaves of C bonduc and identified the interaction between them and cancer target proteins (TK, VEGF, and MMP) in silico. AutoDock Vina, iGEMDOCK, and analysis of pharmacokinetic and pharmacodynamic properties of the isolated bioactives as therapeutic molecules were performed. Seven phytochemicals (7-hydroxy-4′-methoxy-3,11-dehydrohomoisoflavanone, 4,4′-dihydroxy-2’-methoxy-chalcone, 7,4′-dihydroxy-3,11-dehydrohomoisoflavanone, luteolin, quercetin-3-methyl, kaempferol-3-O-β-d-xylopyranoside and kaempferol-3-O-α-l-rhamnopyranosyl-(1 → 2)-β-D-xylopyranoside) were isolated. Molecular docking analysis showed that the phytochemicals displayed strong interactions with the proteins compared with their respective drug inhibitors. Pharmacokinetic and pharmacodynamic properties of the compounds were promising suggesting that they can be developed as putative lead compounds for developing new anti-cancer drugs.

Absorption of 1-Dicysteinethioacetal-5-Hydroxymethylfurfural in Rats and Its Effect on Oxidative Stress and Gut Microbiota

The absorption of a 5-hydroxymethylfurfural (HMF)-cysteine adduct, 1-dicysteinethioacetal-5-hydroxymethylfurfural (DCH), and its effect on antioxidant activity and gut microbiota were investigated. Results indicated that DCH is more easily absorbed in rats than HMF. Serum DCH concentrations were 15-38-fold of HMF concentrations from 30 to 180 min after intragastrical administration at the level of 100 mg/kg of body weight, and 2.7-4.5% of absorbed DCH was converted to HMF. The malondialdehyde content in the plasma, heart, liver, and kidneys significantly increased after drug (100 mg/kg of bw) administration for 1 week, suggesting that HMF and DCH were oxidative-stress-inducing agents, instead of antioxidant agents, in rats. HMF and DCH also modulated gut microbiota. HMF promoted the growth of Lactobacillus, Tyzzerella, Enterobacter, and Streptococcus. DCH increased the ratio of Firmicutes/ Bacteroidetes and promoted the growth of Akkermansia, Shigella, and Escherichia while inhibiting the growth of Lactobacillus.

Mammalian Cells Engineered To Produce New Steroids

Steroids can be difficult to modify through traditional organic synthesis methods, but many enzymes regio- and stereoselectively process a wide variety of steroid substrates. We tested whether steroid-modifying enzymes could make novel steroids from non-native substrates. Numerous genes encoding steroid-modifying enzymes, including some bacterial enzymes, were expressed in mammalian cells by transient transfection and found to be active. We made three unusual steroids by stable expression, in HEK293 cells, of the 7α-hydroxylase CYP7B1, which was selected because of its high native product yield. These cells made 7α,17α-dihydroxypregnenolone and 7β,17α-dihydroxypregnenolone from 17α-hydroxypregnenolone and produced 11α,16α-dihydroxyprogesterone from 16α-hydroxyprogesterone. The last two products were the result of CYP7B1-catalyzed hydroxylation at previously unobserved sites. A Rosetta docking model of CYP7B1 suggested that these substrates' D-ring hydroxy groups might prevent them from binding in the same way as the native substrates, bringing different carbon atoms close to the active ferryl oxygen atom. This new approach could potentially use other enzymes and substrates to produce many novel steroids for drug candidate testing.

Structure-Based Drug Design for Cytochrome P450 Family 1 Inhibitors

Cytochromes P450 are a class of metalloproteins which are responsible for electron transfer in a wide spectrum of reactions including metabolic biotransformation of endogenous and exogenous substrates. The superfamily of cytochromes P450 consists of families and subfamilies which are characterized by a specific structure and substrate specificity. Cytochromes P450 family 1 (CYP1s) play a distinctive role in the metabolism of drugs and chemical procarcinogens. In recent decades, these hemoproteins have been intensively studied with the use of computational methods which have been recently developed remarkably to be used in the process of drug design by the virtual screening of compounds in order to find agents with desired properties. Moreover, the molecular modeling of proteins and ligand docking to their active sites provide an insight into the mechanism of enzyme action and enable us to predict the sites of drug metabolism. The review presents the current status of knowledge about the use of the computational approach in studies of ligand-enzyme interactions for CYP1s. Research on the metabolism of substrates and inhibitors of CYP1s and on the selectivity of their action is particularly valuable from the viewpoint of cancer chemoprevention, chemotherapy, and drug-drug interactions.

In silico prediction of potential chemical reactions mediated by human enzymes

Background

Administered drugs are often converted into an ineffective or activated form by enzymes in our body. Conventional in silico prediction approaches focused on therapeutically important enzymes such as CYP450. However, there are more than thousands of different cellular enzymes that potentially convert administered drug into other forms.

Result

We developed an in silico model to predict which of human enzymes including metabolic enzymes as well as CYP450 family can catalyze a given chemical compound. The prediction is based on the chemical and physical similarity between known enzyme substrates and a query chemical compound. Our in silico model was developed using multiple linear regression and the model showed high performance (AUC = 0.896) despite of the large number of enzymes. When evaluated on a test dataset, it also showed significantly high performance (AUC = 0.746). Interestingly, evaluation with literature data showed that our model can be used to predict not only enzymatic reactions but also drug conversion and enzyme inhibition.

Conclusion

Our model was able to predict enzymatic reactions of a query molecule with a high accuracy. This may foster to discover new metabolic routes and to accelerate the computational development of drug candidates by enabling the prediction of the potential conversion of administered drugs into active or inactive forms.

Using chemical bond-based method to predict site of metabolism for five biotransformations mediated by CYP 3A4, 2D6, and 2C9

Although it has been proposed for decades to predict site of metabolism (SOM) by in silico methods, identifying SOM correctly remains an unsolved fundamental problem and is an active area of research. In our prior works, we proposed a chemical bond-based approach to construction of SOM prediction models by integrating chemical bond descriptors and drug-metabolizing enzymes data. Although it has been evaluated with both 10-fold cross-validation and independent validation, we believe comparisons between this method and prior methods using publicly accessible external datasets are indispensable and more desirable. In the current study, based on chemical bond-based method, metabolism data released by Sheridan et al. and Zaretzki et al. was utilized to establish metabolite prediction models for CYP450 3A4, 2D6, and 2C9. Five major reaction types were involved, including Aliphatic C-hydroxylation, Aromatic C-hydroxylation, N-dealkylation, O-dealkylation, and S-Oxidation. Consequently, all our five models showed impressive performance on predicting SOMs, with accuracy and area under curve exceeded 0.940 and 0.953, respectively. Compared to prior works, our models were better than SOMP both in "SOM-scale" and "molecule-scale". In conclusion, comparisons between chemical-bond based method and prior works were conducted for the first time, which demonstrated that chemical-bond based method is better than or at least comparable to prior works.

Metabolic map of osthole and its effect on lipids

1. Osthole, a coumarin compound from plants, is a promising agent for the treatment of metabolic diseases, including hyperglycemia, fatty liver, and cancers. Studies indicate that the peroxisome proliferator-activated receptors (PPAR) α and γ are involved in the pharmacological effects of osthole. The in vitro and in vivo metabolism of osthole and its biological activity are not completely understood. 2. In this study, ultra-performance chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-QTOFMS)-based metabolomics was used to determine the metabolic pathway of osthole and its influence on the levels of endogenous metabolites. Forty-one osthole metabolites, including 23 novel metabolites, were identified and structurally elucidated from its metabolism in vitro and in vivo. Recombinant cytochrome P450s (CYPs) screening showed that CYP3A4 and CYP3A5 were the primary enzymes contributing to osthole metabolism. 3. More importantly, osthole was able to decrease the levels of lysophosphatidylethanolamine (LPE) and lysophosphatidylcholine (LPC) in the plasma, which explains in part its modulatory effects on metabolic diseases. 4. This study gives the insights about the metabolic pathways of osthole in vivo, including hydroxylation, glucuronidation, and sulfation. Furthermore, the levels of the lipids regulated by osthole indicated its potential effects on adipogenesis. These data contribute to the understanding of the disposition and pharmacological activity of osthole in vivo.

Decreased expression of hepatic cytochrome P450 1A2 (CYP1A2) in a chronic intermittent hypoxia mouse model

Background

Hepatic cytochrome P450 (CYP) isoforms, CYP1A2, is one of important enzymes for many drugs metabolism. Studies have confirmed that sustained hypoxia can influence the expression of hepatic CYP, including CYP1A2. The impact of chronic intermittent hypoxia (CIH), a marked characteristic of sleep apnea, on CYP1A2 remains unclear. The aim of the present study was to evaluate the effect of CIH on the expression of hepatic CYP1A2 in a mouse model with sleep apnea.

Methods

Twenty four old male (6-8 weeks) C57BL/6J mice (n=12 in each group) were randomly assigned to either normoxia group or CIH group. Mice in CIH group underwent 12 weeks intermittent hypoxia exposure. The different gene expression of hepatic CYP1A2 between two groups was analyzed by quantity real-time polymerase chain reaction. The protein levels of hepatic CYP1A2 in each group were observed by using western blotting and immunohistochemistry.

Results

After 12 weeks of exposure to intermittent hypoxia, the expression of hepatic CYP1A2, at the mRNA and protein levels was decreased more significantly in the CIH group than the normoxia group (P<0.01).

Conclusions

CIH contributes to inhibiting the expression of hepatic CYP1A2. This implies that the dosage of drugs metabolized by CYP1A2, should be adjusted in patients with sleep apnea.

Integral estimation of xenobiotics’ toxicity with regard to their metabolism in human organism

Toxicity and severe adverse effects are the primary cause of drug-candidate failures at the late stages of preclinical and clinical trials. Since most xenobiotics undergo biotransformations, their interaction with human organism reveals the effects produced by parent compounds and all metabolites. To increase the chances of successful drug development, estimation of the entire toxicity for drug substance and its metabolites is necessary for filtering out the potentially toxic compounds. We proposed the computational approach to the integral evaluation of xenobiotics’ toxicity based on the structural formula of the drug-like compound. In the framework of this study, the consensus QSAR model was developed based on the analysis of over 3000 compounds with information about their rat acute toxicity for intravenous route of administration. Four different numerical methods, estimating the integral toxicity, were proposed, and their comparative performance was studied using the external evaluation set consisting of 37 structures of drugs and 200 their metabolites. It was shown that, on the average, the best correspondence between the predicted and published data is obtained using the method that takes into account the estimated characteristics for both the parent compound and its most toxic metabolite.

Synthesis, biological evaluation and docking studies of trans-stilbene methylthio derivatives as cytochromes P450 family 1 inhibitors

Cytochromes P450 family 1 (CYP1) are responsible for the metabolism of procarcinogens, for example polycyclic aromatic hydrocarbons and aromatic and heterocyclic amines. The inhibition of CYP1 activity is examined in terms of chemoprevention and cancer chemotherapy. We designed and synthesized a series of trans-stilbene derivatives possessing a combination of methoxy and methylthio functional groups attached in different positions to the trans-stilbene skeleton. We determined the effects of synthesized compounds on the activities of human recombinant CYP1A1, CYP1A2 and CYP1B1 and, to explain the variation of inhibitory potency of methoxystilbene derivatives and their methylthio analogues, we employed computational analysis. The compounds were docked to CYP1A1, CYP1A2 and CYP1B1 binding sites with the use of Accelrys Discovery Studio 4.0 by the CDOCKER procedure. For CYP1A2 and CYP1B1, values of scoring functions correlated well with inhibitory potency of stilbene derivatives. All compounds were relatively poor inhibitors of CYP1A2 that possess the most narrow and flat enzyme cavity among CYP1s. For the most active CYP1A1 inhibitor, 2-methoxy-4'-methylthio-trans-stilbene, a high number of molecular interactions was observed, although the interaction energies were not distinctive.

Design of Radioiodinated Pharmaceuticals: Structural Features Affecting Metabolic Stability towards in Vivo Deiodination

Radioiodinated pharmaceuticals are convenient tracers for clinical and research investigations because of the relatively long half-lives of radioactive iodine isotopes (i.e., 123I, 124I, and 131I) and the ease of their chemical insertion. Their application in radionuclide imaging and therapy may, however, be hampered by poor in vivo stability of the C-I bond. After an overview of the use of iodine in biology and nuclear medicine, we present here a survey of the catabolic pathways for iodinated xenobiotics, including their biodistribution, accumulation, and biostability. We summarize successful rational improvements in the biostability and conclude with general guidelines for the design of stable radioiodinated pharmaceuticals. It appears to be necessary to consider the whole molecule, rather than the radioiodinated fragment alone. Iodine radionuclides are generally retained in vivo on sp2 carbon atoms in iodoarenes and iodovinyl moieties, but not in iodinated heterocycles or on sp3 carbon atoms. Iodoarene substituents also have an influence, with increased in vivo deiodination in the cases of iodophenols and iodoanilines, whereas methoxylation and difluorination improve biostability.

Alignment-Based Prediction of Sites of Metabolism

Prediction of metabolically labile atom positions in a molecule (sites of metabolism) is a key component of the simulation of xenobiotic metabolism as a whole, providing crucial information for the development of safe and effective drugs. In 2008, an exploratory study was published in which sites of metabolism were derived based on molecular shape- and chemical feature-based alignment to a molecule whose site of metabolism (SoM) had been determined by experiments. We present a detailed analysis of the breadth of applicability of alignment-based SoM prediction, including transfer of the approach from a structure- to ligand-based method and extension of the applicability of the models from cytochrome P450 2C9 to all cytochrome P450 isozymes involved in drug metabolism. We evaluate the effect of molecular similarity of the query and reference molecules on the ability of this approach to accurately predict SoMs. In addition, we combine the alignment-based method with a leading chemical reactivity model to take reactivity into account. The combined model yielded superior performance in comparison to the alignment-based approach and the reactivity models with an average area under the receiver operating characteristic curve of 0.85 in cross-validation experiments. In particular, early enrichment was improved, as evidenced by higher BEDROC scores (mean BEDROC = 0.59 for α = 20.0, mean BEDROC = 0.73 for α = 80.5).