Functional influence of human CYP2D6 allelic variations: P34S, E418K, S486T, and R296C

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.

Determination of novel CYP2D6 haplotype using the targeted sequencing followed by the long-read sequencing and the functional characterization in the Japanese population

Next-generation sequencing (NGS) has identified variations in cytochrome P450 (CYP) 2D6 associated with drug responses. However, determination of novel haplotypes is difficult because of the short reads generated by NGS. We aimed to identify novel CYP2D6 variants in the Japanese population and predict the CYP2D6 phenotype based on in vitro metabolic studies. Using a targeted NGS panel (PKSeq), 990 Japanese genomes were sequenced, and then novel CYP2D6 haplotypes were determined. K_m, V_max, and intrinsic clearance (V_max/K_m) of N-desmethyl-tamoxifen 4-hydroxylation were calculated by in vitro metabolic studies using cDNA-expressed CYP2D6 proteins. After determination of the CYP2D6 diplotypes, phenotypes of the individuals were predicted based on the in vitro metabolic activities. Targeted NGS identified 14 CYP2D6 variants not registered in the Pharmacogene Variation Consortium (PharmVar) database. Ten novel haplotypes were registered as CYP2D6*128 to *137 alleles in the PharmVar database. Based on the V_max/K_m value of each allele, *128, *129, *130, *131, *132, and *133 were predicted to be nonfunctional alleles. According to the results of the present study, six normal metabolizers (NM) and one intermediate (IM) metabolizers were designated as IM and poor metabolizers (PM), respectively. Our findings provide important insights into novel haplotypes and haplotypes of CYP2D6 and the effects on in vitro metabolic activities.

Analysis of the Deleterious Single-Nucleotide Polymorphisms Associated With Antidepressant Efficacy in Major Depressive Disorder

Major depressive disorder (MDD) is a serious mental disease with negative effects on both mental and physical health of the patient. Currently, antidepressants are among the major ways to ease or treat MDD. However, the existing antidepressants have limited efficacy in treating MDD, with a large fraction of patients either responding inadequately or differently to antidepressants during the treatment. Pharmacogenetics studies have found that the genetic features of some genes are associated with the antidepressant efficacy. In order to obtain a better understanding on the relationship between the genetic factors and antidepressant treatment response, we compiled a list of 233 single-nucleotide polymorphisms (SNPs) significantly associated with the antidepressant efficacy in treating MDD. Of the 13 non-synonymous SNPs in the list, three (rs1065852, rs3810651, and rs117986340) may influence the structures and function of the corresponding proteins. Besides, the influence of rs1065852 on the structure of CYP2D6 was further investigated via molecular dynamics simulations. Our results showed that compared to the native CYP2D6 the flexibility of the F-G loop was reduced in the mutant. As a portion of the substrate access channel, the lower flexibility of F-G loop may reduce the ability of the substrates to enter the channel, which may be the reason for the lower enzyme activity of mutant. This study may help us to understand the impact of genetic variation on antidepressant efficacy and provide clues for developing new antidepressants.

CYP2D6 genotyping analysis and functional characterization of novel allelic variants in a Ni-Vanuatu and Kenyan population by assessing dextromethorphan O-demethylation activity

While CYP2D6 allele and phenotype frequencies have been extensively studied, currently, very little ethnically specific data is available regarding the East African and South Pacific region, including Kenya and Vanuatu. The absence of information regarding gene polymorphisms and their resulting clinical effects in these populations may hinder treatment strategies and patient outcome. Given the scarceness of CYP2D6 related data in these populations, the purpose of this study was to perform a pharmacogenomic analysis of the Kenyan and Ni-Vanuatu population and ultimately characterize the enzymatic properties of eight novel CYP2D6 variant proteins expressed in 293FT cells in vitro using dextromethorphan as a substrate. Our study revealed a prevalence of functional alleles in both populations a low frequency for decreased function defining genotypes in the Ni-Vanuatu population, with approximately 36% of our Kenyan subjects presenting substrate-dependent decreased function alleles. Additionally, 6 variants (P171L, G306R, V402L, K1, K2, and K3) showed significantly reduced intrinsic clearance compared to wild-type CYP2D6.1. Our findings aid in efforts to bridge the gap between pharmacogenomic analysis and clinical application, by providing useful information in the development of ethnic-specific strategies as well as stressing the importance of population-specific genotyping when conducting multi-regional clinical trials and designing therapeutic strategies.

Genetic Polymorphisms and In Silico Mutagenesis Analyses of CYP2C9, CYP2D6, and CYPOR Genes in the Pakistani Population

Diverse distributions of pharmacogenetically relevant variants of highly polymorphic CYP2C9, CYP2D6 and CYPOR genes are responsible for some varied drug responses observed across human populations. There is limited data available regarding the pharmacogenetic polymorphisms and frequency distributions of major allele variants in the Pakistani population. The present in silico mutagenesis study conducted on genotype pharmacogenetic variants and comparative analysis with a global population aims to extend the currently limited pharmacogenetic available evidence for the indigenous Pakistani population. Extracted genomic DNA from 244 healthy individuals' venous blood samples were amplified for distinct variant loci in the CYP2C9, CYP2D6 and CYPOR genes. Two-way sequencing results were compared with standard PubMed data and sequence variant loci confirmed by Chromas. This study revealed significant variations in CYP2C9 (rs1799853, rs1057910 and rs72558189), CYP2D6 (rs16947 and rs1135840), and CYPOR (rs1057868, rs781919285 and rs562750402) variants in intraethnic and interethnic frequency distributions. In silico mutagenesis and three-dimensional protein structural alignment analysis approaches clearly exposed the possible varied impact of rare CYPOR (rs781919285 and rs562750402) single nucleotide polymorphisms (SNPs) and confirmed that the influences of CYP2C9 and CYP2D6 variants are consistent with what was found in earlier studies. This investigation highlighted the need to study pharmacogenetic relevance loci and documentation since evidence could be utilized to elucidate genetic backgrounds of drug metabolism, and provide a basis for future pharmacogenomic studies and adequate dose adjustments in Pakistani and global populations.

Molecular Dynamics Simulations Reveal Structural Differences among Allelic Variants of Membrane-Anchored Cytochrome P450 2D6

Cytochrome P450 2D6 (CYP2D6) is an enzyme that is involved in the metabolism of roughly 25% of all marketed drugs and therefore belongs to the most important enzymes in drug metabolism. CYP2D6 features a high degree of genetic polymorphism that can significantly affect the metabolic activity of an individual. In extreme cases, structural changes at the level of single amino acids can either increase its enzymatic activity abolishing the drug therapeutic effect or completely disable the enzyme and elevate drug plasma level potentially leading to adverse effects. In this study, starting from the crystal structure, we built a full-length membrane-anchored all-atom model of the wild-type CYP2D6 as well as five of its variants differing in the enzymatic activity. We validated our models with available experimental data and compared their structural properties with molecular dynamics simulations. The main focus of this study was to identify differences that could mechanistically explain the altered activity of the variants and improve our understanding of their functioning. We observed differences in the opening frequencies and minimal diameters of tunnels that connect the buried active site to the surrounding solvent environment. The variants CYP2D6*4 and CYP2D6*10 associated with missing or decreased activity showed less frequent opening of the tunnels compared to the wild-type. Both CYP2D6*10 and CYP2D6*17 showed a deprivation of an important ligand tunnel suggesting a feasible reason for their altered substrate specificity. Next, the altered fold at the N-terminal anchor region and the decreased active site volume caused by the amino acid mutations of the CYP2D6*4 variant offer an explanation for the absence of its metabolic activity. The mutations in CYP2D6*53 contributed to a significant enlargement of an important ligand tunnel and an extension of the active site cavity. This could explain the altered metabolic profile as well as the enhanced metabolic rates of this particular variant supporting its designation as a possible cause for the ultrarapid metabolizer phenotype. We believe these novel structural insights could advance the fields of personalized medicine and enzyme engineering. Furthermore, they could aid in guiding laboratory as well as computational experiments in the future.

Functional characterization of 50 CYP2D6 allelic variants by assessing primaquine 5-hydroxylation

Cytochrome P450 2D6 (CYP2D6) is responsible for the metabolic activation of primaquine, an antimalarial drug. CYP2D6 is genetically polymorphic, and these polymorphisms are associated with interindividual variations observed in the therapeutic efficacy of primaquine. To further understand this association, we performed in vitro enzymatic analyses of the wild-type CYP2D6.1 and 49 CYP2D6 allelic variants, which were expressed in 293FT cells, using primaquine as a substrate. The concentrations of CYP2D6 variant holoenzymes were measured by using carbon monoxide (CO)-reduced difference spectroscopy, and the wild type and 27 variants showed a peak at 450 nm. The kinetic parameters K_m, V_max, and intrinsic clearance (V_max/K_m) of primaquine 5-hydroxylation were characterized. The kinetic parameters of the wild type and 16 variants were measured, but the values for the remaining 33 variants could not be determined because of low metabolite concentrations. Among the variants, six (i.e., CYP2D6.17, .18, .35, .39, .53, and .70) showed significantly reduced intrinsic clearance compared with that of CYP2D6.1. Three-dimensional structural modeling analysis was performed to elucidate the mechanism of changes in the kinetics of CYP2D6 variants. Our findings provide insights into the allele-specific activity of CYP2D6 for primaquine, which could be clinically useful for malaria treatment and eradication efforts.

CYP2D6 Allelic Variants *34, *17-2, *17-3, and *53 and a Thr309Ala Mutant Display Altered Kinetics and NADPH Coupling in Metabolism of Bufuralol and Dextromethorphan and Altered Susceptibility to Inactivation by SCH 66712

Metabolic phenotype can be affected by multiple factors, including allelic variation and interactions with inhibitors. Human CYP2D6 is responsible for approximately 20% of cytochrome P450-mediated drug metabolism but consists of more than 100 known variants; several variants are commonly found in the population, whereas others are quite rare. Four CYP2D6 allelic variants-three with a series of mutations distal to the active site (*34, *17-2, *17-3) and one ultra-metabolizer with mutations near the active site (*53), along with reference *1 and an active site mutant of *1 (Thr309Ala)-were expressed, purified, and studied for interactions with the typical substrates dextromethorphan and bufuralol and the inactivator SCH 66712. We found that *34, *17-2, and *17-3 displayed reduced enzyme activity and NADPH coupling while producing the same metabolites as *1, suggesting a possible role for Arg296 in NADPH coupling. A higher-activity variant, *53, displayed similar NADPH coupling to *1 but was less susceptible to inactivation by SCH 66712. The Thr309Ala mutant showed similar activity to that of *1 but with greatly reduced NADPH coupling. Overall, these results suggest that kinetic and metabolic analysis of individual CYP2D6 variants is required to understand their possible contributions to variable drug response and the complexity of personalized medicine.

DL-ADR: a novel deep learning model for classifying genomic variants into adverse drug reactions

Background

Genomic variations are associated with the metabolism and the occurrence of adverse reactions of many therapeutic agents. The polymorphisms on over 2000 locations of cytochrome P450 enzymes (CYP) due to many factors such as ethnicity, mutations, and inheritance attribute to the diversity of response and side effects of various drugs. The associations of the single nucleotide polymorphisms (SNPs), the internal pharmacokinetic patterns and the vulnerability of specific adverse reactions become one of the research interests of pharmacogenomics. The conventional genomewide association studies (GWAS) mainly focuses on the relation of single or multiple SNPs to a specific risk factors which are a one-to-many relation. However, there are no robust methods to establish a many-to-many network which can combine the direct and indirect associations between multiple SNPs and a serial of events (e.g. adverse reactions, metabolic patterns, prognostic factors etc.). In this paper, we present a novel deep learning model based on generative stochastic networks and hidden Markov chain to classify the observed samples with SNPs on five loci of two genes (CYP2D6 and CYP1A2) respectively to the vulnerable population of 14 types of adverse reactions.

Methods

A supervised deep learning model is proposed in this study. The revised generative stochastic networks (GSN) model with transited by the hidden Markov chain is used. The data of the training set are collected from clinical observation. The training set is composed of 83 observations of blood samples with the genotypes respectively on CYP2D6*2, *10, *14 and CYP1A2*1C, *1 F. The samples are genotyped by the polymerase chain reaction (PCR) method. A hidden Markov chain is used as the transition operator to simulate the probabilistic distribution. The model can perform learning at lower cost compared to the conventional maximal likelihood method because the transition distribution is conditional on the previous state of the hidden Markov chain. A least square loss (LASSO) algorithm and a k-Nearest Neighbors (kNN) algorithm are used as the baselines for comparison and to evaluate the performance of our proposed deep learning model.

Results

There are 53 adverse reactions reported during the observation. They are assigned to 14 categories. In the comparison of classification accuracy, the deep learning model shows superiority over the LASSO and kNN model with a rate over 80 %. In the comparison of reliability, the deep learning model shows the best stability among the three models.

Conclusions

Machine learning provides a new method to explore the complex associations among genomic variations and multiple events in pharmacogenomics studies. The new deep learning algorithm is capable of classifying various SNPs to the corresponding adverse reactions. We expect that as more genomic variations are added as features and more observations are made, the deep learning model can improve its performance and can act as a black-box but reliable verifier for other GWAS studies.

Evaluating the impact of missenses mutations in CYP2D6*7 and CYP2D6*14A: does it compromise tamoxifen metabolism?

CYP2D6 is a high polymorphic enzyme from P450, responsible for metabolizing almost 25% of drugs. The distribution of different mutations among CYP2D6 alleles has been associated with poor, intermediate, extensive and ultra-metabolizers.

AIM

To evaluate how missenses mutations in CYP2D6*7 and CYP2D6*14A poor metabolizer alleles affect CYP2D6 stability and function.

MATERIALS & METHODS

CYPalleles database was used to collect polymorphisms data present in 105 alleles. We selected only poor metabolizers alleles that presented exclusively missenses mutations. They were analyzed through seven algorithms to predict the impact on CYP2D6 structure and function.

RESULTS

H324P, the unique mutation in CYP2D6*7, has high impact in enzyme function due to its occurrence between two alpha-helixes involved in active site dynamics. G169R, a mutation that occurs only in CYP2D6*14A, leads to the gain of solvent accessibility and severe protein destabilization.

CONCLUSION

Our in silico analysis showed that missenses mutations in CYP2D6*7 and CYP2D6*14A cause CYP2D6 dysfunction.

Expression and Characterization of Truncated Recombinant Human Cytochrome P450 2J2

The human cytochrome P450 2J2 catalyzes an epoxygenase reaction to oxidize various fatty acids including arachidonic acid. In this study, three recombinant enzyme constructs of P450 2J2 were heterologously expressed in Escherichia coli and their P450 proteins were successfully purified using a Ni(2+)-NTA affinity column. Deletion of 34 amino acid residues in N-terminus of P450 2J2 enzyme (2J2-D) produced the soluble enzyme located in the cytosolic fraction. The enzymatic analysis of this truncated protein indicated the typical spectral characteristics and functional properties of P450 2J2 enzyme. P450 2J2-D enzymes from soluble fraction catalyzed the oxidation reaction of terfenadine to the hydroxylated product. However, P450 2J2-D enzymes from membrane fraction did not support the P450 oxidation reaction although it displayed the characteristic CO-binding spectrum of P450. Our finding of these features in the N-terminal modified P450 2J2 enzyme could help understand the biological functions and the metabolic roles of P450 2J2 enzyme and make the crystallographic analysis of the P450 2J2 structure feasible for future studies.

Development of mice exhibiting hepatic microsomal activity of human CYP3A4 comparable to that in human liver microsomes by intravenous administration of an adenovirus vector expressing human CYP3A4

Cytochrome P450 3A4 (CYP3A4) plays a crucial role in the pharmacokinetic and safety profiles of drugs. However, it is difficult to properly predict the pharmacokinetics and hepatotoxicity of drugs in humans using data from experimental animals, because the catalytic activities of CYP3A4 and other drug-metabolizing enzymes differ between human and animal organs. In order to easily generate an animal model for proper evaluation of human CYP3A4-mediated drug metabolism, we developed a human CYP3A4-expressing adenovirus (Ad) vector based on our novel Ad vector exhibiting significantly lower hepatotoxicity (Ad-E4-122aT-hCYP3A4). Intravenous administration of Ad-E4-122aT-hCYP3A4 at a dose of 2 × 10(11) virus particles/mouse produced a mouse exhibiting human CYP3A4 activity at a level similar to that in the human liver, as shown in the dexamethasone metabolic experiment using liver microsomes. The area under the curve (AUC) of 6βOHD was 2.7-fold higher in the Ad-E4-122aT-hCYP3A4-administered mice, compared with the mice receiving a control Ad vector. This Ad vector-expressing human CYP3A4 would thus be a powerful tool for evaluating human CYP3A4-mediated drug metabolism in the livers of experimental animals.