Absolute quantification of multidrug resistance-associated protein 2 (MRP2/ABCC2) using liquid chromatography tandem mass spectrometry

Li, Na; Nemirovskiy, Olga V.; Zhang, Yiqun; Yuan, Haodan; Mo, Jingping; Ji, Chengjie; Zhang, Bo; Brayman, Timothy G.; Lepsy, Christopher; Heath, Timothy G.; Lai, Yurong

doi:10.1016/j.ab.2008.05.032

Cited by 61 publications

(85 citation statements)

References 29 publications

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“…The limitations of this approach include the need for high end instruments and potential loss of protein mapping coverage due to low abundance of membrane protein expression. As mentioned above, upfront sample enrichment and use of nano-flow LC instead of regular LC could improve protein mapping coverage as well as peptide detection sensitivity (18,23).…”

Section: Empirical Experimental Tools For the Selection Of Quantitatimentioning

confidence: 99%

“…The peptides for quantification are easily detectable in an instrument representing the highest responding peptides for the target protein (17). The selection can be accomplished through the use of either empirical experimental tools in a high-resolution mass spectrometry analysis (18), such as time of flight (TOF) and Orbitrap, or in silico predictive tools (7,19) as discussed below. Protein digestion to release peptides can be achieved by a protease reaction with biological samples.…”

Section: Selection Of Surrogate Target Peptides For Protein Quantificmentioning

confidence: 99%

“…It is critical that the high-quality MS/MS spectra are collected for the peptides of interest since it is inevitable for the peptides to co-elute with others especially for a complex sample such as tissue lysate. Target protein enrichment or purification would achieve the best peptides coverage for the target proteins (18), and the fast acquisition rate is a key as the possibility of detecting a specific peptide goes up with the total number of spectra that one can collect within each cycle. For this reason, many instrument vendors strive to improve the acquisition rate with promising results.…”

Section: Empirical Experimental Tools For the Selection Of Quantitatimentioning

confidence: 99%

“…Among the several proteases available for the reaction, trypsin is an ideal initial choice as it often produces fragments that are amenable to detection by MS in terms of size and amino acid composition. In one early study (18), multidrug resistance-associated protein 2 (MRP2), was immunoprecipitated and separated by sodium dodecyl sulfate (SDS) polyacrylamide gel electrophoresis, followed by in-gel digestion. Then, nano-electrospray ionization (nano-ESI) quadrupole TOF (Q-TOF) was utilized to select the target proteotypic peptide with the best detection sensitivity (18).…”

Section: Selection Of Surrogate Target Peptides For Protein Quantificmentioning

confidence: 99%

“…In one early study (18), multidrug resistance-associated protein 2 (MRP2), was immunoprecipitated and separated by sodium dodecyl sulfate (SDS) polyacrylamide gel electrophoresis, followed by in-gel digestion. Then, nano-electrospray ionization (nano-ESI) quadrupole TOF (Q-TOF) was utilized to select the target proteotypic peptide with the best detection sensitivity (18). On the other hand, understanding of the specific protease cleavage sites can facilitate the probability of de novo sequencing for a given protein, to predict the peptides that would result from protease digestion of the protein through an in silico digestion.…”

Section: Selection Of Surrogate Target Peptides For Protein Quantificmentioning

confidence: 99%

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Quantitative Targeted Proteomics for Membrane Transporter Proteins: Method and Application

Qiu

Zhang

Lai

2014

AAPS J

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Abstract. Although global proteomics has shown promise for discovery of many new proteins, biomarkers, protein modifications, and polymorphisms, targeted proteomics is emerging in the proteomics research field as a complement to untargeted shotgun proteomics, particularly when a determined set of low-abundance functional proteins need to be measured. The function and expression of proteins related to drug absorption, distribution, metabolism, and excretion (ADME) such as cytochrome P450 enzymes and membrane transporters are of great interest in biopharmaceutical research. Since the variation in ADME-related protein expression is known to be a major complicating factor encountered during in vitro-in vivo and in vivo-in vivo extrapolations (IVIVE), the accurate quantification of the ADME proteins in complex biological systems becomes a fundamental element in establishing IVIVE for pharmacokinetic predictions. In this review, we provide an overview of relevant methodologies followed by a summary of recent applications encompassing mass spectrometry-based targeted quantifications of membrane transporters.KEY WORDS: drug absorption, distribution, metabolism, and excretion (ADME); drug transporters; in vitro-in vivo and in vivo-in vivo extrapolations (IVIVE); LC-MS/MS; quantitative targeted proteomics.

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Section: Empirical Experimental Tools For the Selection Of Quantitatimentioning

confidence: 99%

Section: Selection Of Surrogate Target Peptides For Protein Quantificmentioning

confidence: 99%

Section: Empirical Experimental Tools For the Selection Of Quantitatimentioning

confidence: 99%

Section: Selection Of Surrogate Target Peptides For Protein Quantificmentioning

confidence: 99%

Section: Selection Of Surrogate Target Peptides For Protein Quantificmentioning

confidence: 99%

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Quantitative Targeted Proteomics for Membrane Transporter Proteins: Method and Application

Qiu

Zhang

Lai

2014

AAPS J

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Absolute abundance and function of intestinal drug transporters: a prerequisite for fully mechanistic in vitro–in vivo extrapolation of oral drug absorption

Harwood

Neuhoff

Carlson

et al. 2012

Biopharm & Drug Disp

102

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The use of whole body physiological-based pharmacokinetic (PBPK) models linked with in vitro-in vivo extrapolation (IVIVE) of kinetic parameters from laboratory experiments, has become embedded within many of the pharmaceutical industry and is used even as part of regulatory submissions. These include the influence of transporter proteins on drug disposition, a subject for which we have witnessed an increasing awareness. A combination of the development of high-powered analytical techniques and antibody-based technology, together with a realization that an understanding of absolute transporter protein abundances together with activity can potentially enhance the modelling of transporter kinetics by PBPK-IVIVE link models. This review summarizes the mechanistic approaches to integrate suitable non-biased in vitro transporter kinetic data relevant to the intestine (i.e. 'intrinsic' K i , 'intrinsic' K m ), by in vitro system modelling for these kinetic inputs with the advantages of, and challenges for, generating these data for input into PBPK models. This step is considered as a prerequisite for mechanistic modelling of the oral absorption for drugs that are substrates for transporters. Various approaches are provided to integrate intestinal transporter expression into PBPK models with a perspective on the incorporation of the absolute abundance/activity of transporters to enhance the predictive power of the models. We define the key intestinal tissue and functional expression-based scaling factors required. The objective is to use these for facilitating the extrapolation from in vitro intestinal transporter assays to the in vivo system, using absolute quantification methodologies. The models could be used to elucidate the complex relationship and relative importance of metabolizing enzymes and transporters in drug disposition and toxicity.

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Quantitative assessment of the contribution of sodium‐dependent taurocholate co‐transporting polypeptide (NTCP) to the hepatic uptake of rosuvastatin, pitavastatin and fluvastatin

Qiu

Rotter

et al. 2013

Biopharm & Drug Disp

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Hepatic uptake transport is often the rate-determining step in the systemic clearance of drugs. The ability to predict uptake clearance and to determine the contribution of individual transporters to overall hepatic uptake is therefore critical in assessing the potential pharmacokinetic and pharmacodynamic variability associated with drug-drug interactions and pharmacogenetics. The present study revisited the interaction of statin drugs, including pitavastatin, fluvastatin and rosuvastatin, with the sodium-dependent taurocholate co-transporting polypeptide (NTCP) using gene transfected cell models. In addition, the uptake clearance and the contribution of NTCP to the overall hepatic uptake were assessed using in vitro hepatocyte models. Then NTCP protein expression was measured by a targeted proteomics transporter quantification method to confirm the presence and stability of NTCP expression in suspended and cultured hepatocyte models. It was concluded that NTCP-mediated uptake contributed significantly to active hepatic uptake in hepatocyte models for all three statins. However, the contribution of NTCP-mediated uptake to the overall active hepatic uptake was compound-dependent and varied from about 24% to 45%. Understanding the contribution of individual transporter proteins to the overall hepatic uptake and its functional variability when other active hepatic uptake pathways are interrupted could improve the current prediction practice used to assess the pharmacokinetic variability due to drug-drug interactions, pharmacogenetics and physiopathological conditions in humans.

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Absolute quantification of multidrug resistance-associated protein 2 (MRP2/ABCC2) using liquid chromatography tandem mass spectrometry

Cited by 61 publications

References 29 publications

Quantitative Targeted Proteomics for Membrane Transporter Proteins: Method and Application

Quantitative Targeted Proteomics for Membrane Transporter Proteins: Method and Application

Absolute abundance and function of intestinal drug transporters: a prerequisite for fully mechanistic in vitro–in vivo extrapolation of oral drug absorption

Quantitative assessment of the contribution of sodium‐dependent taurocholate co‐transporting polypeptide (NTCP) to the hepatic uptake of rosuvastatin, pitavastatin and fluvastatin

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