An integrated strategy for rapid discovery and identification of the sequential piperine metabolites in rats using ultra high-performance liquid chromatography/high resolution mass spectrometery

Shang, Zhanpeng; Cai, Wei; Cao, Yanfeng; Wang, Fei; Wang, Zhibin; Lu, Jian‐Qiu; Zhang, Jiayu

doi:10.1016/j.jpba.2017.09.012

Cited by 37 publications

(17 citation statements)

References 22 publications

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“…Piperine (1-piperoyl piperidine), whose molecular weight corresponds to 285 g/mol, is an alkaloid present in many types of plants, such as Piper nigrum linn (black pepper), Zingiber officinale (ginger), Piper longum L. , Piper sarmentosum Roxb, and Dangzuo [1,2,3,4,5,6]. Piperine is not only used as a seasoning but also in various preparations of traditional medicine in India; it is also employed in the oldest medical science practiced since ancient time (Ayurveda) [7].…”

Section: Introductionmentioning

confidence: 99%

Experimental Approaches and Computational Modeling of Rat Serum Albumin and Its Interaction with Piperine

Zazeri

Povinelli

Lima

et al. 2019

IJMS

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The bioactive piperine (1-piperoyl piperidine) compound found in some pepper species (Piper nigrum linn and Piper sarmentosum Roxb) has been shown to have therapeutic properties and to be useful for well-being. The tests used to validate these properties were performed in vitro or with small rats. However, in all these assays, the molecular approach was absent. Although the first therapeutic trials relied on the use of rats, no proposal was mentioned either experimentally or computationally at the molecular level regarding the interaction between piperine and rat serum albumin (RSA). In the present study, several spectroscopic techniques were employed to characterize rat serum albumin and, aided by computational techniques, the protein modeling was proposed. From the spectroscopic results, it was possible to estimate the binding constant (3.9 × 104 M−1 at 288 K) using the Stern–Volmer model and the number of ligands (three) associated with the protein applying interaction density function model. The Gibbs free energy, an important thermodynamic parameter, was determined (−25 kJ/mol), indicating that the interaction was spontaneous. This important set of experimental results served to parameterize the computational simulations. The results of molecular docking and molecular dynamics matched appropriately made it possible to have detailed microenvironments of RSA accessed by piperine.

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Section: Introductionmentioning

confidence: 99%

Experimental Approaches and Computational Modeling of Rat Serum Albumin and Its Interaction with Piperine

Zazeri

Povinelli

Lima

et al. 2019

IJMS

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“…However, interpretation of the mass spectral data is laborious and time consuming. Recently, several methods have been developed for rapid analysis of mass data, such as high-resolution extracted ion chromatogram (HREIC) [16], mass defect filtering (MDF) [17], neutral loss filtering (NLF) [18], and diagnostic product ion (DPI) [19,20]. Among them, DPI is an easy-to-operate targeted data-mining vehicle to identify chemical components sharing similar scaffolds [19].…”

Section: Introductionmentioning

confidence: 99%

Targeted characterization of acylated compounds from Scrophulariae Radix using liquid chromatography coupled with Orbitrap mass spectrometry and diagnostic product ion‐based data analysis

Shang

Wang

et al. 2020

J of Separation Science

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Acylated compounds are often present in herbal medicines. In this study, a diagnostic product ion‐based strategy was established to comprehensively characterize acylated compounds in Scrophulariae Radix. After untargeted data acquisition using ultra‐high performance liquid chromatography coupled with Orbitrap mass spectrometry, the data were processed by three‐stage diagnostic product ions. First, diagnostic product ions corresponding to the acyl groups (cinnamoyl, p‐coumaroyl, feruloyl, and caffeoyl) were used to search 90 compounds. Second, these compounds were divided into three categories using diagnostic product ions for phenylethanoid glycosides, iridoid glycosides, and phenylpropanoids, respectively. Last, the linkage position of the acyl group to iridoid glycosides was discriminated via the third‐stage diagnostic product ions. As a result, 90 acylated compounds were characterized, and 37 of them were reported from Scrophulariae Radix for the first time.

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“…Accordingly, drug metabolism can be fully presented with high degrees of certainty even in situations where the corresponding reference standards are lacking. Thus, it is feasible to establish a comprehensive and integrated analytical workflow-interpretation sequence to obtain useful information from complex backgrounds [ 15 , 16 , 17 , 18 ]. Recently, efficient data-mining methods including isotope pattern filtering (IPF) [ 19 ], diagnostic product ion (DPI) [ 15 , 20 ], neutral loss filtering (NLF) [ 21 ], extracted ion chromatogram (EIC) [ 22 ], mass defect filter (MDF), and multiple mass defect filters (MMDFs) [ 23 ] have been successful applied to systematically profile the in vivo drug metabolism of drugs.…”

Section: Introductionmentioning

confidence: 99%

Rapid Screening and Identification of Daidzein Metabolites in Rats Based on UHPLC-LTQ-Orbitrap Mass Spectrometry Coupled with Data-Mining Technologies

Zhao

Shang

et al. 2018

Molecules

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Daidzein, the main bioactive soy isoflavone in Nature, has been found to possess many biological functions. It has been investigated in particular as a phytoestrogen owing to the similarity of its structure with that of the human hormone estrogen. Due to the lack of comprehensive studies on daidzein metabolism, further research is still required to clarify its in vivo metabolic fate and intermediate processes. In this study, an efficient strategy was established using UHPLC-LTQ-Orbitrap mass spectrometry to profile the metabolism of daidzein in rats. Meanwhile, multiple data-mining methods including high-resolution extracted ion chromatogram (HREIC), multiple mass defect filtering (MMDF), neutral loss fragment (NLF), and diagnostic product ion (DPI) were utilized to investigate daidzein metabolites from the HR-ESI-MS1 to ESI-MSn stage in both positive and negative ion modes. Consequently, 59 metabolites, including prototype compounds, were positively or tentatively elucidated based on reference standards, accurate mass measurements, mass fragmentation behaviors, chromatographic retention times, and corresponding calculated ClogP values. As a result, dehydration, hydrogenation, methylation, dimethylation, glucuronidation, glucosylation, sulfonation, ring-cleavage, and their composite reactions were ascertained to interpret its in vivo biotransformation. Overall, our results not only revealed the potential pharmacodynamics forms of daidzein, but also aid in establishing a practical strategy for rapid screening and identifying metabolites of natural compounds.

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An integrated strategy for rapid discovery and identification of the sequential piperine metabolites in rats using ultra high-performance liquid chromatography/high resolution mass spectrometery

Cited by 37 publications

References 22 publications

Experimental Approaches and Computational Modeling of Rat Serum Albumin and Its Interaction with Piperine

Experimental Approaches and Computational Modeling of Rat Serum Albumin and Its Interaction with Piperine

Targeted characterization of acylated compounds from Scrophulariae Radix using liquid chromatography coupled with Orbitrap mass spectrometry and diagnostic product ion‐based data analysis

Rapid Screening and Identification of Daidzein Metabolites in Rats Based on UHPLC-LTQ-Orbitrap Mass Spectrometry Coupled with Data-Mining Technologies

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