Amelia Nathania Dong , Nafees Ahemad , Yan Pan , Uma Devi Palanisamy , Chin Eng Ong
{"title":"Interactions of coumarin and amine ligands with six cytochrome P450 2D6 allelic variants: Molecular docking","authors":"Amelia Nathania Dong , Nafees Ahemad , Yan Pan , Uma Devi Palanisamy , Chin Eng Ong","doi":"10.1016/j.comtox.2023.100284","DOIUrl":null,"url":null,"abstract":"<div><p>Human CYP2D6 contributes extensively to the biotransformation of important therapeutic drugs. CYP2D6 substrate and inhibitor specificity may be affected by genetic polymorphism. This study aimed to characterize interactions of three typical ligands, 3-cyano-7-ethoxycoumarin, fluoxetine and terbinafine with six CYP2D6 variants using molecular docking simulations. The compounds were docked individually to the CYP2D6 models based on published crystal structure (PDB code: 3TBG). All ligands bound within the active site pocket near the heme. Binding involved residues found in critical secondary structures that formed the active site boundary: B-C loop, F helix, F-G loop, β-1 strands and I helix. Twenty-five amino acids were involved in the binding, and all were located in the known substrate recognition sites. Hydrophobic bonds involving phenylalanine (Phe120, Phe384) dominated CEC binding whereas electrostatic bonds between the protonated nitrogen with acidic residues (Glu216, Glu222, Asp301) dominated in binding of fluoxetine and terbinafine. Collectively, the subtle structural changes in the active site and substrate access channels induced by the mutations in the variants contributed to differential ligand docking poses. This study has provided insights into important molecular properties for CYP2D6 catalysis and inhibition, and formed basis for further exploration of structural determinants for potency and specificity of CYP2D6 ligands.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Toxicology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468111323000257","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Human CYP2D6 contributes extensively to the biotransformation of important therapeutic drugs. CYP2D6 substrate and inhibitor specificity may be affected by genetic polymorphism. This study aimed to characterize interactions of three typical ligands, 3-cyano-7-ethoxycoumarin, fluoxetine and terbinafine with six CYP2D6 variants using molecular docking simulations. The compounds were docked individually to the CYP2D6 models based on published crystal structure (PDB code: 3TBG). All ligands bound within the active site pocket near the heme. Binding involved residues found in critical secondary structures that formed the active site boundary: B-C loop, F helix, F-G loop, β-1 strands and I helix. Twenty-five amino acids were involved in the binding, and all were located in the known substrate recognition sites. Hydrophobic bonds involving phenylalanine (Phe120, Phe384) dominated CEC binding whereas electrostatic bonds between the protonated nitrogen with acidic residues (Glu216, Glu222, Asp301) dominated in binding of fluoxetine and terbinafine. Collectively, the subtle structural changes in the active site and substrate access channels induced by the mutations in the variants contributed to differential ligand docking poses. This study has provided insights into important molecular properties for CYP2D6 catalysis and inhibition, and formed basis for further exploration of structural determinants for potency and specificity of CYP2D6 ligands.
期刊介绍:
Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs