Combination of docking,molecular dynamics and quantum mechanical calculations for metabolism prediction of 3,4-methylenedioxybenzoyl-2-thienylhydrazone |
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Authors: | Rodolpho C Braga Vinícius M Alves Carlos A M Fraga Eliezer J Barreiro Valéria de Oliveira Carolina H Andrade |
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Institution: | 1.Faculty of Pharmacy,Federal University of Goiás,Goiania,Brazil;2.LASSBio, Faculty of Pharmacy,Federal University of Rio de Janeiro,Rio de Janeiro,Brazil |
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Abstract: | In modern drug discovery process, ADME/Tox properties should be determined as early as possible in the test cascade to allow
a timely assessment of their property profiles. To help medicinal chemists in designing new compounds with improved pharmacokinetics,
the knowledge of the soft spot position or the site of metabolism (SOM) is needed. In silico methods based on docking, molecular
dynamics and quantum chemical calculations can bring us closer to understand drug metabolism and predict drug–drug interactions.
We report herein on a combined methodology to explore the site of metabolism prediction of a new cardioactive drug prototype,
LASSBio-294 (1), using MetaPrint2D to predict the most likely metabolites, combined with structure-based tools using docking, molecular
dynamics and quantum mechanical calculations to predict the binding of the substrate to CYP2C9 enzyme, to estimate the binding
free energy and to study the energy profiles for the oxidation of (1). Additionally, the computational study was correlated with a metabolic fingerprint profiling using LC-MS analysis. The results
obtained using the computational methods gave valuable information about the probable metabolites of (1) (qualitatively) and also about the important interactions of this lead compound with the amino acid residues of the active
site of CYP2C9. Moreover, using a combination of different levels of theory sheds light on the understanding of (1) metabolism by CYP2C9 and its mechanisms. The metabolic fingerprint profiling of (1) has shown that the metabolites founded in highest concentration in different species were metabolites M1, M2 and M3, whereas M8 was found to be a minor metabolite. Therefore, our computational study allowed a qualitative prediction for the metabolism
of (1). The approach presented here has afforded new opportunities to improve metabolite identification strategies, mediated by
not only CYP2C9 but also other CYP450 family enzymes. |
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