The Stereoselective Sulfate Conjugation of 4′‐Methoxyfenoterol Stereoisomers by Sulfotransferase Enzymes

Iyer, Lalitha; Ramamoorthy, Anuradha; Rutkowska, Ewelina; Furimsky, Anna; Tang, Liang; Catz, Paul; Green, Carol E.; Jóźwiak, Krzysztof; Wainer, Irving W.

doi:10.1002/chir.22072

Cited by 5 publications

(4 citation statements)

References 15 publications

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“…Second, the docking results were also investigated based on three-dimensional pharmacophore features such as hydrogen bonds, hydrophobic contacts, or aromatic areas. To the best of our knowledge, this approach has rarely been applied to SULT docking studies because primarily hydrogen bonds have been considered to evaluate docked ligand conformations (26,(67)(68)(69). Due to the nature of the active site of SULT1E1 (a barrel-like structure lined with lipophilic and/or aromatic amino acids), the consideration of hydrophobic areas and aromatic contacts bears advantages as shown by the predictive power of the presented in silico model for ligands of SULT1E1.…”

Section: Discussionmentioning

confidence: 99%

“…Based on the enzyme structure, computational studies have investigated the mechanism of inhibition of SULT1E1 by nucleotides (25) and stereoselectivity of sulfonation via docking (26), analyzed the sulfonation reaction using QM/MM methods (27), and utilized molecular docking to predict ligand binding (28). Here, we report on a novel approach of computer-based metabolism prediction for human SULT1E1.…”

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confidence: 99%

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In Silico Prediction of Human Sulfotransferase 1E1 Activity Guided by Pharmacophores from Molecular Dynamics Simulations

Rakers

Schumacher

Meinl

et al. 2016

Journal of Biological Chemistry

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Acting during phase II metabolism, sulfotransferases (SULTs) serve detoxification by transforming a broad spectrum of compounds from pharmaceutical, nutritional, or environmental sources into more easily excretable metabolites. However, SULT activity has also been shown to promote formation of reactive metabolites that may have genotoxic effects. SULT subtype 1E1 (SULT1E1) was identified as a key player in estrogen homeostasis, which is involved in many physiological processes and the pathogenesis of breast and endometrial cancer. The development of an in silico prediction model for SULT1E1 ligands would therefore support the development of metabolically inert drugs and help to assess health risks related to hormonal imbalances. Here, we report on a novel approach to develop a model that enables prediction of substrates and inhibitors of SULT1E1. Molecular dynamics simulations were performed to investigate enzyme flexibility and sample protein conformations. Pharmacophores were developed that served as a cornerstone of the model, and machine learning techniques were applied for prediction refinement. The prediction model was used to screen the DrugBank (a database of experimental and approved drugs): 28% of the predicted hits were reported in literature as ligands of SULT1E1. From the remaining hits, a selection of nine molecules was subjected to biochemical assay validation and experimental results were in accordance with the in silico prediction of SULT1E1 inhibitors and substrates, thus affirming our prediction hypotheses.Metabolism plays an important role in drug discovery and appropriate metabolic profiles of new drug candidates should be taken into consideration during the process of drug development. Acting in phase I metabolism, the enzyme family of cytochrome P450 is estimated to transform about 75% of marketed drugs (1) and numerous in silico approaches for the prediction of cytochrome P450-mediated metabolism have emerged to date (2, 3). Although the majority of metabolism prediction studies focuses on phase I, the significance of phase II metabolism is generally underestimated (4) and to this day, computer-based models for the prediction of phase II metabolism remain scarce (5).Among the predominant phase II enzyme families are the soluble sulfotransferases that form a gene superfamily termed SULT. These enzymes regulate the sulfonation of smaller molecules such as endogenous hormones, neurotransmitters, and xenobiotic substances from pharmaceutical, nutritional, or environmental sources. Based on sequence similarity, functional human SULTs are divided into two main families (SULT1 and SULT2) and further into subfamilies that exhibit individual, but somewhat overlapping substrate specificities (6). Influencing the level of female sex hormones (estrogens), SULT subtype 1E1 (SULT1E1) shows a specific substrate preference for physiological estrogenic compounds (K m ϭ 5 nM for estradiol (7)) and has been extensively investigated in experimental studies.In general, sulfonation reactions in which a sulfona...

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

In Silico Prediction of Human Sulfotransferase 1E1 Activity Guided by Pharmacophores from Molecular Dynamics Simulations

Rakers

Schumacher

Meinl

et al. 2016

Journal of Biological Chemistry

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“…Conformations with highest binding energies were selected for QM/MM calculations (at B3LYP/6-311 + G(d,p)//AMBER level) for estimating the reaction barriers. Distances between catechol oxygen atoms to be methylated and sulfur atom of S-adenosyl-L-methionine (2.95 −3.10 Å) and the O C S angle (160)(161)(162)(163)(164)(165)(166)(167)(168)(169)(170) were constrained for selection of starting geometries form the MD trajectories.…”

Section: Simulations To Understand Regioselectivity In Comt-mediated Methylationsmentioning

confidence: 99%

“…Iyer et al worked on the regioselective and stereospecific phenolic sulfonation of 4′‐methoxyfenoterol (MF), a potential candidate for the treatment of congestive heart failure . Experimental results showed that sulfonation of MF is stereoselective.…”

Section: Prediction Of Phase II (Ugt and Non‐ugt) Drug Metabolismmentioning

confidence: 99%

Recent advances in the prediction of non‐CYP450‐mediated drug metabolism

Dixit

Lal

Agrawal

2017

WIREs Comput Mol Sci

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Computational models of drug metabolism prediction have focused mainly on cytochrome P450 enzymes, because drug–drug interactions, reactive metabolite formation, hepatotoxicity, idiosyncratic adverse drug interactions, and/or loss of efficacy of many drugs were the results of interactions with CYP450s. Metabolic regioselectivity and isoform specificity prediction models for CYP450‐catalyzed reactions have reached approximately 95% accuracy. Thus, a new drug candidate is less likely to show unexpected metabolic profile due to metabolism via CYP450 pathways. For such candidates, secondary metabolic Phase I and II enzymes are likely to play an expected (or unexpected) role in drug metabolism. The importance of flavin monooxygenases (FMOs), aldehyde and alcohol dehydrogenase, monoamine oxidase from the Phase I and UDP‐glucuronosyltransferase (UGT), sulfotransferase, glutathione S‐transferase, and methyltransferase from Phase II has increased and United States Food and Drug Administration guidelines on NDA have specific recommendations for in vitro and in vivo testing against these enzymes. Thus, there is an urgent requirement of reliable predictive models for drug metabolism catalyzed by these enzymes. In this review, we have classified drug metabolism prediction models (site of metabolism, isoform specificity, and kinetic parameter) for these enzymes into Phase I and II. When such models are unavailable, we discuss the Quantitative Structure Activity Relationship (QSAR), pharmacophore, docking, dynamics, and reactivity studies performed for the prediction of substrates and inhibitors. Recently published models for FMO and UGT are discussed. The need for comprehensive, widely applicable, sequential primary and secondary metabolite prediction is highlighted. Potential difficulties and future prospectives in the development of such models are discussed. WIREs Comput Mol Sci 2017, 7:e1323. doi: 10.1002/wcms.1323 This article is categorized under: Structure and Mechanism > Reaction Mechanisms and Catalysis Computer and Information Science > Chemoinformatics Software > Molecular Modeling

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fRMSDchiral: A novel algorithm to represent differences between positions of stereoisomers in complex with dissymmetric binding site

Urniaż

Rutkowska

Płazińska

et al. 2014

Journal of Chromatography B

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The Stereoselective Sulfate Conjugation of 4′‐Methoxyfenoterol Stereoisomers by Sulfotransferase Enzymes

Cited by 5 publications

References 15 publications

In Silico Prediction of Human Sulfotransferase 1E1 Activity Guided by Pharmacophores from Molecular Dynamics Simulations

In Silico Prediction of Human Sulfotransferase 1E1 Activity Guided by Pharmacophores from Molecular Dynamics Simulations

Recent advances in the prediction of non‐CYP450‐mediated drug metabolism

fRMSDchiral: A novel algorithm to represent differences between positions of stereoisomers in complex with dissymmetric binding site

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