Combination of docking, molecular dynamics and quantum mechanical calculations for metabolism prediction of 3,4-methylenedioxybenzoyl-2-thienylhydrazone

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.

Antihypertensive Drugs Metabolism: An Update to Pharmacokinetic Profiles and Computational Approaches

“…In one of the studies of the metabolism of a novel cardio active agent 3, 4 methylenedioxybenzoyl-2-phenyl hydrazine, known to improve the intracellular Ca +2 regulation, docking studies were used to predict the sites of metabolism (SOM) within the active site of CYP2C9, molecular dynamics (MD) simulations of docked complexes were performed to validate their stability and QM calculations were done to study the energy profiles for the oxidations [ 95 ]. This study demonstrated the ability of used computational approaches to provide reliable qualitative predictions of the novel cardio active agent metabolites produced by the action of the P450 enzyme CYP2C9.…”

ADME Profiling in Drug Discovery and a New Path Paved on Silica

“…The metabolism prediction combines mathematical models to predict whether the target compound could be a substrate of a specific enzyme in combination with metabolism site predictions. Usually, those initial predictions are followed by molecular docking simulations and quantum mechanics simulations due to the dependency of electronics structure from both substrate and enzyme in catalyzed reaction [113,114].…”

Quantum mechanics approaches to drug research in the era of structural chemogenomics

“…For some targets, the computational analysis is bound to go beyond docking and scoring: for example, understanding of potency, specificity and selectivity of covalent inhibitors and transition state analogs requires analysis of reaction paths and reactive intermediates. 23,24 In recent years, covalently acting drugs draw growing interest and attention, 25,26 making this an extremely important field of research, Finally, full characterization of drug candidates includes their interaction not only with their intended or unintended targets, but also with metabolizing most – enzymes importantly, cytochromes P450, 27,28 – i.e. requires tools for understanding of metabolic activation/degradation and formation of reactive metabolites.…”