Homology Modeling of Rat and Human Cytochrome P450 2D (CYP2D) Isoforms and Computational Rationalization of Experimental Ligand-Binding Specificities

Venhorst, Jennifer; Laak, Antonius ter; Commandeur, Jan N. M.; Funae, Yoshihiko; Hiroi, Toyoko; Vermeulen, Nico

doi:10.1021/jm0209578

Cited by 108 publications

(87 citation statements)

References 39 publications

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“…We have used the latter molecular approach, combining experimental analysis of substrate binding with protein modeling, to study CYP2D6 active site-ligand interactions. This has helped us (Kirton et al, 2002;Paine et al, 2003;Flanagan et al, 2004;Kemp et al, 2004;McLaughlin et al, 2005) and others (Venhorst et al, 2003;Keizers et al, 2004Keizers et al, , 2005 to identify residues that play a key role in metabolism, and to determine the binding orientation and affinity of ligands in the active site (Kirton et al, 2002;Kemp et al, 2004). The recently determined crystal structure of CYP2D6 (Rowland et al, 2006) has confirmed the correctness of many of the features of the active site of our model of the enzyme.…”

supporting

confidence: 58%

In Silico Prediction of Drug Binding to Cyp2d6: Identification of a New Metabolite of Metoclopramide

Yu¹,

Paine²,

Maréchal³

et al. 2006

Drug Metab Dispos

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ABSTRACT:Patients with cancer often take many different classes of drugs to treat the effects of their malignancy and the side effects of treatment, as well as their comorbidities. The potential for drug-drug interactions that may affect the efficacy of anticancer treatment is high, and a major source of such interactions is competition for the drug-metabolizing enzymes, cytochromes P450 (P450s). We have examined a series of 20 drugs commonly prescribed to cancer patients to look for potential interactions via CYP2D6. We used a homology model of CYP2D6, together with molecular docking techniques, to perform an in silico screen for binding to CYP2D6. Experimental IC 50 values were determined for these compounds and compared with the model predictions to reveal a correlation with a regression coefficient of r 2 ‫؍‬ 0.61. Importantly, the docked conformation of the commonly prescribed antiemetic metoclopramide predicted a new site of metabolism that was further investigated through in vitro analysis with recombinant CYP2D6. An aromatic N-hydroxy metabolite of metoclopramide, consistent with predictions from our modeling studies, was identified by highperformance liquid chromatography/mass spectrometry. This metabolite was found to represent a major product of metabolism in human liver microsomes, and CYP2D6 was identified as the main P450 isoform responsible for catalyzing its formation. In view of the prevalence of interindividual variation in the CYP2D6 genotype and phenotype, we suggest that those experiencing adverse reactions with metoclopramide, e.g., extrapyramidal syndrome, are likely to have a particular CYP2D6 genotype/phenotype. This warrants further investigation.

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supporting

confidence: 58%

In Silico Prediction of Drug Binding to Cyp2d6: Identification of a New Metabolite of Metoclopramide

Yu¹,

Paine²,

Maréchal³

et al. 2006

Drug Metab Dispos

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Section: Structure-based Drug Designmentioning

confidence: 99%

“…1, IC 50 = 0.6 nM) was positioned into the extended binding cleft of renin (S3 to S2' subsites) making interactions with the hydrophobic cavity, which has not been previously explored. It is interestingly to note that pharmacokinetic properties and drug metabolism can also be examined and improved by exploring crystal structures of the human cytochrome P450 isoforms [17,18].The receptor-based approach is carried out in an iterative manner, proceeding via multiple computational and experimental paths until the development of an optimized lead compound having high affinity and selectivity, as well as optimized pharmacokinetic properties, as shown in Fig. (2).…”

mentioning

confidence: 99%

Structure-Based Drug Design Strategies in Medicinal Chemistry

Andricopulo¹,

Salum²,

Abraham

2009

CTMC

139

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A broad variety of medicinal chemistry approaches can be used for the identification of hits, generation of leads, as well as to accelerate the development of high quality drug candidates. Structure-based drug design (SBDD) methods are becoming increasingly powerful, versatile and more widely used. This review summarizes current developments in structure-based virtual screening and receptor-based pharmacophores, highlighting achievements as well as challenges, along with the value of structure-based lead optimization, with emphasis on recent examples of successful applications for the identification of novel active compounds.Keywords: Structure-based drug design, medicinal chemistry, virtual screening, QSAR, pharmacophores. STRUCTURE-BASED DRUG DESIGNThe performance of biochemical processes and cell mechanisms are dependent upon complex and multiple noncovalent intermolecular interactions between proteins and small-molecule modulators. The understanding of the structural and chemical binding properties of important drug targets in biologically relevant pathways allows the design of small molecules capable of regulating or modulating specific target functions in the body that are closely linked to human diseases and disorders, through multiple intermolecular interactions within a well-defined binding pocket [1][2][3][4]. In general, the identification of promising hits for further optimization is a major challenge faced by the both pharmaceutical and academic laboratories. Although the trial-anderror nature is inherent in drug research, rational concepts and modern computational methods have become widely employed for lead selection and optimization.The use of three-dimensional (3D) protein structure information in the development of new biologically active molecules, which is termed Structure-Based Drug Design (SBDD), is a well-established, successful and highly attarctive strategy used by academic and pharmaceutical research laboratories worldwide [3][4][5][6][7][8]. As a creative and knowledgedriven approach, an essential requirement for structure-based studies is a substantial understanding of the spatial and energetic aspects that affect the binding affinities of proteinligand complexes. Considering that the shape and chemical nature of the binding site of a specific target protein are known, and the possible intermolecular interactions between ligands and the protein within its active site have been identified, this qualified information can be directly employed for the identification of new ligands and the optimization of lead compounds. This opens new possibilities to boost the search for lead molecules and to limit the number of compounds that need to be evaluated experimentally.Hits can be identified through the docking of smallmolecule ligands (selected from databases of chemical structures) into protein active sites or by using receptorbased pharmacophore models. Furthermore, drug candidates can be designed de novo by improving the complementary binding properties of lead compounds and the r...

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“…Other possibilities for modeling studies include the move toward methods that do not require detailed ligand alignments (Balakin et al, 2004) and incorporate more information derived from determined protein structures and/or homology models. Improved homology models are also leading to more progress in molecular dynamics approaches in describing human P450 isoforms whose structure has not yet been determined (e.g., 2D6) (Venhorst et al, 2003;Kemp et al, 2004). One intriguing approach even uses 3D-QSAR to refine homology models before they are used for further docking to improve the ligand alignments (Evers et al, 2003).…”

Section: New Uses Of 3d-qsarmentioning

confidence: 99%

Three-Dimensional Quantitative Structure-Activity Relationship Analysis of Cytochromes P450: Effect of Incorporating Higher-Affinity Ligands and Potential New Applications

Locuson¹,

Wahlstrom²

2005

Drug Metab Dispos

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ABSTRACT:Recently, two new classes of reversible inhibitors, the benzbromarones (BZBRs) and the N-3 substituted phenobarbitals (PBs), were used to study the active site characteristics of CYP2C9 and 2C19, respectively. Since these ligands are some of the first CYP2C ligands to extend into the low nanomolar K i range (K i < 100 nM), they were subjected to three-dimensional quantitative structureactivity relationship (3D-QSAR) analysis. Given that BZBRs or the PB ligands bind very tightly, it can be assumed that these structures complement the binding pocket(s) for these enzymes. Thus, the resulting models should output a 3D arrangement of interaction sites predicted to be important for near optimal binding to the CYP2C9 and CYP2C19 enzymes. These predicted interaction regions may then improve the ability to predict drug-drug interactions. The resulting models generated from these new high affinity ligands are discussed, as are novel uses of 3D-QSAR and molecular modeling techniques that may be useful in the study of cytochromes P450 specifically.In ligand-based molecular modeling, knowledge accumulated from experimentation is used to build and test potential models for predicting ligand-protein interactions and hence drug-drug interactions, the sites of drug metabolism, toxicity, and other parameters. Recently, CYP2C9 and CYP2C19 inhibitors with 1 to 2 orders of magnitude lower K i values than previously characterized compounds have been reported (Suzuki et al., 2002;Locuson et al., 2003). These new inhibitors should help expand various models for CYP2C metabolism. Several groups have published 3D quantitative structure-activity relationship analysis (3D-QSAR) models for P450s, including multiple models for CYP2C9. Therefore, it is relevant to address how the newer, more potent inhibitors, which fit the same alignment rules used previously, have altered existing QSAR models for CYP2C9 and, in some cases, provided distinctions between the chemical properties that appear to define inhibitors of CYP2C9 and CYP2C19. Finally, new applications of 3D-QSAR modeling and how it may enhance P450 metabolism research is discussed. What Can High Affinity Ligands of P450s Tell Us?The pursuit for, and study of, high affinity P450 ligands remains an important endeavor. High affinity ligands for each P450 enzyme can help define the enzyme in the form of a pharmacophore, improving the identification of drug leads with the highest potential for drugdrug interactions based on their structure. In practice, this is a lofty goal because determining drug interaction potential in any quantitative manner requires an accurate, universal binding model that can predict any compound's affinity for a given enzyme. Establishing such a model, however, can be difficult because: 1) models used for prediction can only be based on what is currently known, and 2) P450s display complex binding behavior and conformational flexibility. Investigators may have the ability to screen new drugs for their drug interaction potential with the use of selective su...

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Homology Modeling of Rat and Human Cytochrome P450 2D (CYP2D) Isoforms and Computational Rationalization of Experimental Ligand-Binding Specificities

Cited by 108 publications

References 39 publications

In Silico Prediction of Drug Binding to Cyp2d6: Identification of a New Metabolite of Metoclopramide

In Silico Prediction of Drug Binding to Cyp2d6: Identification of a New Metabolite of Metoclopramide

Structure-Based Drug Design Strategies in Medicinal Chemistry

Three-Dimensional Quantitative Structure-Activity Relationship Analysis of Cytochromes P450: Effect of Incorporating Higher-Affinity Ligands and Potential New Applications

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