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Identification and in silico prediction of metabolites of tebufenozide derivatives by major human cytochrome P450 isoforms
Institution:1. Graduate School of Agriculture, Kyoto University, Kitashirakawa-oiwake-cho, Sakyo-ku, Kyoto 606-8502, Japan;2. Faculty of Engineering, Toyama Prefectural University, 5180, Kurokawa, Imizu-shi, Toyama 939-0398, Japan;1. Department of Medicinal Chemistry, Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, China;2. Department of Dermatology, Xiangya Hospital, Central South University, Changsha 410008, China;1. Center for Toxicogenomics and Human Health, NOVA Medical School/Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Lisbon, Portugal;2. LISBP, Université de Toulouse, CNRS, INRA, INSA, Toulouse, France
Abstract: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.
Keywords:CYP1A2  CYP2C9  CYP2C19  CYP2D6  CYP3A4  Tebufenozide derivatives metabolites  Docking simulation  Hydrogen atom abstraction energy  CYP"}  {"#name":"keyword"  "$":{"id":"k0055"}  "$$":[{"#name":"text"  "_":"cytochrome P450  QSAR"}  {"#name":"keyword"  "$":{"id":"k0065"}  "$$":[{"#name":"text"  "_":"quantitative structure-activity relationship  DFT"}  {"#name":"keyword"  "$":{"id":"k0075"}  "$$":[{"#name":"text"  "_":"density functional theory  NADPH"}  {"#name":"keyword"  "$":{"id":"k0085"}  "$$":[{"#name":"text"  "_":"β-nicotinamide adenine dinucleotide phosphate reduced tetrasodium salt  SOM"}  {"#name":"keyword"  "$":{"id":"k0095"}  "$$":[{"#name":"text"  "_":"sites of metabolism  retention time
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