1
|
ElGamacy M, Riss M, Zhu H, Truffault V, Coles M. Mapping Local Conformational Landscapes of Proteins in Solution. Structure 2019; 27:853-865.e5. [PMID: 30930065 DOI: 10.1016/j.str.2019.03.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 10/05/2018] [Accepted: 03/07/2019] [Indexed: 01/19/2023]
Abstract
The ability of proteins to adopt multiple conformational states is essential to their function, and elucidating the details of such diversity under physiological conditions has been a major challenge. Here we present a generalized method for mapping protein population landscapes by NMR spectroscopy. Experimental NOESY spectra are directly compared with a set of expectation spectra back-calculated across an arbitrary conformational space. Signal decomposition of the experimental spectrum then directly yields the relative populations of local conformational microstates. In this way, averaged descriptions of conformation can be eliminated. As the method quantitatively compares experimental and expectation spectra, it inherently delivers an R factor expressing how well structural models explain the input data. We demonstrate that our method extracts sufficient information from a single 3D NOESY experiment to perform initial model building, refinement, and validation, thus offering a complete de novo structure determination protocol.
Collapse
Affiliation(s)
- Mohammad ElGamacy
- Department of Protein Evolution, Max Planck Institute for Developmental Biology, Max-Planck-Ring 5, 72076 Tübingen, Germany
| | - Michael Riss
- Department of Informatics, Technical University of Munich, Boltzmannstrasse 3, 85748 Garching, Germany
| | - Hongbo Zhu
- Department of Protein Evolution, Max Planck Institute for Developmental Biology, Max-Planck-Ring 5, 72076 Tübingen, Germany
| | - Vincent Truffault
- Department of Protein Evolution, Max Planck Institute for Developmental Biology, Max-Planck-Ring 5, 72076 Tübingen, Germany
| | - Murray Coles
- Department of Protein Evolution, Max Planck Institute for Developmental Biology, Max-Planck-Ring 5, 72076 Tübingen, Germany.
| |
Collapse
|
2
|
Forest T, Xu Q, Kuruvilla S, Vu H, Vlasakova K, Glaab WE, Hines C, Xun S. Magnetic Resonance and Ultrastructural Characterization of PEGylation-associated Vacuolation in Nonclinical Models. Toxicol Pathol 2017; 45:604-613. [PMID: 28673196 DOI: 10.1177/0192623317714068] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Conjugation with polyethylene glycol (PEG) is a strategy for improving the pharmaceutical properties of therapeutic proteins. In nonclinical studies of PEGylated compounds, microscopic tissue vacuolation is often observed, characterized ultrastructurally in this report by lysosomal distension. Although PEGylation-associated vacuolation appears to be of limited toxicologic concern when alternative therapies are limited, the risk-benefit considerations may be impacted by uncertainty about reversibility, lack of methods for monitoring PEG accumulation in vivo without biopsy, and the variability in tissues affected depending on species studied. We demonstrate the use of magnetic resonance spectroscopy (MRS) to measure PEG concentrations at multiple time points in vivo in the kidney with comparison to PEG concentrations ex vivo in body fluids and tissue extracts using nuclear magnetic resonance (NMR) spectroscopy. Furthermore, we demonstrate the use of these techniques to study distribution and elimination of PEG in a dog model of PEGylation-associated vacuolation. This report suggests that MRS could be further investigated as a feasible imaging-based method for monitoring PEG accumulation in a clinical setting in conjunction with NMR quantitation of PEG in plasma and urine.
Collapse
Affiliation(s)
- Thomas Forest
- Merck Research Laboratories, West Point, Pennsylvania, USA
| | - Qiuwei Xu
- Merck Research Laboratories, West Point, Pennsylvania, USA
| | - Sabu Kuruvilla
- Merck Research Laboratories, West Point, Pennsylvania, USA
| | - Heather Vu
- Merck Research Laboratories, West Point, Pennsylvania, USA
| | | | | | - Cathy Hines
- Merck Research Laboratories, West Point, Pennsylvania, USA
| | - Song Xun
- Merck Research Laboratories, West Point, Pennsylvania, USA
| |
Collapse
|
3
|
Puig-Castellví F, Alfonso I, Tauler R. Untargeted assignment and automatic integration of 1H NMR metabolomic datasets using a multivariate curve resolution approach. Anal Chim Acta 2017; 964:55-66. [PMID: 28351639 DOI: 10.1016/j.aca.2017.02.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2016] [Revised: 02/09/2017] [Accepted: 02/10/2017] [Indexed: 01/06/2023]
Abstract
In this article, we propose the use of the Multivariate Curve Resolution - Alternating Least Squares (MCR-ALS) chemometrics method to resolve the 1H NMR spectra and concentration of the individual metabolites in their mixtures in untargeted metabolomics studies. A decision tree-based strategy is presented to optimally select and implement spectra estimates and equality constraints during MCR-ALS optimization. The proposed method has been satisfactorily evaluated using different 1H NMR metabolomics datasets. In a first study, 1H NMR spectra of the metabolites in a simulated mixture were successfully recovered and assigned. In a second study, more than 30 metabolites were characterized and quantified from an experimental unknown mixture analyzed by 1H NMR. In this work, MCR-ALS is shown to be a convenient tool for metabolite investigation and sample screening using 1H NMR, and it opens a new path for performing metabolomics studies with this chemometric technique.
Collapse
Affiliation(s)
- Francesc Puig-Castellví
- Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - Ignacio Alfonso
- Department of Biological Chemistry and Molecular Modelling, Institute of Advanced Chemistry of Catalonia (IQAC-CSIC), Barcelona, Spain
| | - Romà Tauler
- Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain.
| |
Collapse
|
4
|
Giraudeau P, Tea I, Remaud GS, Akoka S. Reference and normalization methods: Essential tools for the intercomparison of NMR spectra. J Pharm Biomed Anal 2014; 93:3-16. [DOI: 10.1016/j.jpba.2013.07.020] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2013] [Revised: 07/12/2013] [Accepted: 07/15/2013] [Indexed: 12/17/2022]
|
5
|
Tiainen M, Soininen P, Laatikainen R. Quantitative Quantum Mechanical Spectral Analysis (qQMSA) of (1)H NMR spectra of complex mixtures and biofluids. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2014; 242:67-78. [PMID: 24607824 DOI: 10.1016/j.jmr.2014.02.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2013] [Revised: 12/24/2013] [Accepted: 02/06/2014] [Indexed: 05/24/2023]
Abstract
The quantitative interpretation of (1)H NMR spectra of mixtures like the biofluids is a demanding task due to spectral complexity and overlap. Complications may arise also from water suppression, T2-editing, protein interactions, relaxation differences of the species, experimental artifacts and, furthermore, the spectra may contain unknown components and macromolecular background which cannot be easily separated from baseline. In this work, tools and strategies for quantitative Quantum Mechanical Spectral Analysis (qQMSA) of (1)H NMR spectra from complex mixtures were developed and systematically assessed. In the present approach, the signals of well-defined, stoichiometric components are described by a QM model, while the background is described by a multiterm baseline function and the unknown signals using optimizable and adjustable lines, regular multiplets or any spectral structures which can be composed from spectral lines. Any prior knowledge available from the spectrum can also be added to the model. Fitting strategies for weak and strongly overlapping spectral systems were developed and assessed using two basic model systems, the metabolite mixtures without and with macromolecular (serum) background. The analyses show that if the spectra are measured in high-throughput manner, the consistent absolute quantification demands some calibration to compensate the different response factors of the protons and compounds. On the other hand, the results show that also the T2-edited spectra can be measured so that they obey well the QM rules. In general, qQMSA exploits and interprets the spectral information in maximal way taking full advantage from the QM properties of the spectra and, at the same time, offers chemical confidence which means that individual components can be identified with high confidence on the basis of their accurate spectral parameters.
Collapse
Affiliation(s)
- Mika Tiainen
- School of Pharmacy, University of Eastern Finland, P.O. Box 1627, FIN-70211 Kuopio, Finland
| | - Pasi Soininen
- School of Pharmacy, University of Eastern Finland, P.O. Box 1627, FIN-70211 Kuopio, Finland
| | - Reino Laatikainen
- School of Pharmacy, University of Eastern Finland, P.O. Box 1627, FIN-70211 Kuopio, Finland.
| |
Collapse
|
6
|
Thermal stability of water up to super-critical states: Application of the singular value decomposition and grund functions. J Mol Liq 2013. [DOI: 10.1016/j.molliq.2013.07.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
|
7
|
Hwang TL, Ronk M, Milne JE. Application of two-dimensional selective-TOCSY HMBC for structure elucidation of impurities in mixture without separation. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2013; 51:89-94. [PMID: 23233169 DOI: 10.1002/mrc.3912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2012] [Revised: 11/15/2012] [Accepted: 11/18/2012] [Indexed: 06/01/2023]
Abstract
In the pharmaceutical industry, regulatory expectations driven by patient safety considerations make structure elucidation of impurities at levels greater than 0.1% in the active pharmaceutical ingredient (API) of primary interest. Impurities can be generated from isomers in starting materials, or produced from different process steps toward the final API. Proton peaks belonging to different impurities could be potentially identified in the one-dimensional (1)H NMR spectrum, when evaluated in combination with two-dimensional (2-D) COSY and HSQC data. However, in 2-D HMBC data, correlation responses from different impurities may overlap with those from the major component, causing uncertainty of long-range proton to carbon correlations and quaternary carbon assignments. This observation prompts us to design the 2-D selective-TOCSY HMBC experiment to distinguish responses from different impurities in mixtures to obtain 2-D NMR data for each impurity, thus eliminating the use of a chromatographic isolation step to obtain material for NMR analysis. This methodology is demonstrated for structure elucidation of impurities ranging from 8.2% in the raw material to 0.4% in the API in this study, and would be particularly useful for industrial samples in which the solubility and availability of material are not an issue.
Collapse
Affiliation(s)
- Tsang-Lin Hwang
- Analytical Research and Development, Amgen Inc., Thousand Oaks, CA 91320, USA.
| | | | | |
Collapse
|
8
|
Pauli GF, Gödecke T, Jaki BU, Lankin DC. Quantitative 1H NMR. Development and potential of an analytical method: an update. JOURNAL OF NATURAL PRODUCTS 2012; 75:834-51. [PMID: 22482996 PMCID: PMC3384681 DOI: 10.1021/np200993k] [Citation(s) in RCA: 237] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Covering the literature from mid-2004 until the end of 2011, this review continues a previous literature overview on quantitative (1)H NMR (qHNMR) methodology and its applications in the analysis of natural products. Among the foremost advantages of qHNMR is its accurate function with external calibration, the lack of any requirement for identical reference materials, a high precision and accuracy when properly validated, and an ability to quantitate multiple analytes simultaneously. As a result of the inclusion of over 170 new references, this updated review summarizes a wealth of detailed experiential evidence and newly developed methodology that supports qHNMR as a valuable and unbiased analytical tool for natural product and other areas of research.
Collapse
Affiliation(s)
- Guido F Pauli
- Department of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois 60612, USA.
| | | | | | | |
Collapse
|
9
|
Zhu J, Sova P, Xu Q, Dombek KM, Xu EY, Vu H, Tu Z, Brem RB, Bumgarner RE, Schadt EE. Stitching together multiple data dimensions reveals interacting metabolomic and transcriptomic networks that modulate cell regulation. PLoS Biol 2012; 10:e1001301. [PMID: 22509135 PMCID: PMC3317911 DOI: 10.1371/journal.pbio.1001301] [Citation(s) in RCA: 134] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2011] [Accepted: 02/20/2012] [Indexed: 01/22/2023] Open
Abstract
DNA variation can be used as a systematic source of perturbation in segregating populations as a way to infer regulatory networks via the integration of large-scale, high-dimensional molecular profiling data. Cells employ multiple levels of regulation, including transcriptional and translational regulation, that drive core biological processes and enable cells to respond to genetic and environmental changes. Small-molecule metabolites are one category of critical cellular intermediates that can influence as well as be a target of cellular regulations. Because metabolites represent the direct output of protein-mediated cellular processes, endogenous metabolite concentrations can closely reflect cellular physiological states, especially when integrated with other molecular-profiling data. Here we develop and apply a network reconstruction approach that simultaneously integrates six different types of data: endogenous metabolite concentration, RNA expression, DNA variation, DNA–protein binding, protein–metabolite interaction, and protein–protein interaction data, to construct probabilistic causal networks that elucidate the complexity of cell regulation in a segregating yeast population. Because many of the metabolites are found to be under strong genetic control, we were able to employ a causal regulator detection algorithm to identify causal regulators of the resulting network that elucidated the mechanisms by which variations in their sequence affect gene expression and metabolite concentrations. We examined all four expression quantitative trait loci (eQTL) hot spots with colocalized metabolite QTLs, two of which recapitulated known biological processes, while the other two elucidated novel putative biological mechanisms for the eQTL hot spots. It is now possible to score variations in DNA across whole genomes, RNA levels and alternative isoforms, metabolite levels, protein levels and protein state information, protein–protein interactions, and protein–DNA interactions, in a comprehensive fashion in populations of individuals. Interactions among these molecular entities define the complex web of biological processes that give rise to all higher order phenotypes, including disease. The development of analytical approaches that simultaneously integrate different dimensions of data is essential if we are to extract the meaning from large-scale data to elucidate the complexity of living systems. Here, we use a novel Bayesian network reconstruction algorithm that simultaneously integrates DNA variation, RNA levels, metabolite levels, protein–protein interaction data, protein–DNA binding data, and protein–small-molecule interaction data to construct molecular networks in yeast. We demonstrate that these networks can be used to infer causal relationships among genes, enabling the identification of novel genes that modulate cellular regulation. We show that our network predictions either recapitulate known biology or can be prospectively validated, demonstrating a high degree of accuracy in the predicted network.
Collapse
Affiliation(s)
- Jun Zhu
- Sage Bionetworks, Seattle, Washington, United States of America
- * E-mail: (JZ); (EES)
| | - Pavel Sova
- Department of Microbiology, University of Washington, Seattle Washington, United States of America
| | - Qiuwei Xu
- Safety Assessment, Merck & Co., Inc., West Point, Pennsylvania, United States of America
| | - Kenneth M. Dombek
- Department of Microbiology, University of Washington, Seattle Washington, United States of America
| | - Ethan Y. Xu
- Safety Assessment, Merck & Co., Inc., West Point, Pennsylvania, United States of America
| | - Heather Vu
- Safety Assessment, Merck & Co., Inc., West Point, Pennsylvania, United States of America
| | - Zhidong Tu
- Molecular Profiling, Merck Research Laboratories, Boston, Massachusetts, United States of America
| | - Rachel B. Brem
- Department of Molecular and Cell Biology, University of California at Berkeley, Berkeley, California, United States of America
| | - Roger E. Bumgarner
- Department of Microbiology, University of Washington, Seattle Washington, United States of America
| | - Eric E. Schadt
- Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York City, New York, United States of America
- * E-mail: (JZ); (EES)
| |
Collapse
|
10
|
Soininen TH, Jukarainen N, Julkunen-Tiitto R, Karjalainen R, Vepsäläinen JJ. The combined use of constrained total-line-shape 1H NMR and LC–MS/MS for quantitative analysis of bioactive components in yellow onion. J Food Compost Anal 2012. [DOI: 10.1016/j.jfca.2011.09.001] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
|
11
|
Roberts AG, Yang J, Halpert JR, Nelson SD, Thummel KT, Atkins WM. The structural basis for homotropic and heterotropic cooperativity of midazolam metabolism by human cytochrome P450 3A4. Biochemistry 2011; 50:10804-18. [PMID: 21992114 DOI: 10.1021/bi200924t] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Human cytochrome P450 3A4 (CYP3A4) metabolizes a significant portion of clinically relevant drugs and often exhibits complex steady-state kinetics that can involve homotropic and heterotropic cooperativity between bound ligands. In previous studies, the hydroxylation of the sedative midazolam (MDZ) exhibited homotropic cooperativity via a decrease in the ratio of 1'-OH-MDZ to 4-OH-MDZ at higher drug concentrations. In this study, MDZ exhibited heterotropic cooperativity with the antiepileptic drug carbamazepine (CBZ) with characteristic decreases in the 1'-OH-MDZ to 4-OH-MDZ ratios. To unravel the structural basis of MDZ cooperativity, we probed MDZ and CBZ bound to CYP3A4 using longitudinal T(1) nuclear magnetic resonance (NMR) relaxation and molecular docking with AutoDock 4.2. The distances calculated from longitudinal T(1) NMR relaxation were used during simulated annealing to constrain the molecules to the substrate-free X-ray crystal structure of CYP3A4. These simulations revealed that either two MDZ molecules or an MDZ molecule and a CBZ molecule assume a stacked configuration within the CYP3A4 active site. In either case, the proton at position 4 of the MDZ molecule was closer to the heme than the protons of the 1'-CH(3) group. In contrast, molecular docking of a single molecule of MDZ revealed that the molecule was preferentially oriented with the 1'-CH(3) position closer to the heme than position 4. This study provides the first detailed molecular analysis of heterotropic and homotropic cooperativity of a human cytochrome P450 from an NMR-based model. Cooperativity of ligand binding through direct interaction between stacked molecules may represent a common motif for homotropic and heterotropic cooperativity.
Collapse
Affiliation(s)
- Arthur G Roberts
- Department of Pharmaceutical and Biomedical Sciences, University of Georgia, Athens, Georgia 30602, United States.
| | | | | | | | | | | |
Collapse
|
12
|
Xu Q, Vu H, Liu L, Wang TC, Schaefer WH. Metabolic profiles show specific mitochondrial toxicities in vitro in myotube cells. JOURNAL OF BIOMOLECULAR NMR 2011; 49:207-219. [PMID: 21359514 DOI: 10.1007/s10858-011-9482-8] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2010] [Accepted: 12/10/2010] [Indexed: 05/30/2023]
Abstract
Mitochondrial toxicity has been a serious concern, not only in preclinical drug development but also in clinical trials. In mitochondria, there are several distinct metabolic processes including fatty acid β-oxidation, the tricarboxylic acid (TCA) cycle, and oxidative phosphorylation (OXPHOS), and each process contains discrete but often intimately linked steps. Interruption in any one of those steps can cause mitochondrial dysfunction. Detection of inhibition to OXPHOS can be complicated in vivo because intermediate endogenous metabolites can be recycled in situ or circulated systemically for metabolism in other organs or tissues. Commonly used assays for evaluating mitochondrial function are often applied to ex vivo or in vitro samples; they include various enzymatic or protein assays, as well as functional assays such as measurement of oxygen consumption rate, membrane potential, or acidification rates. Metabolomics provides quantitative profiles of overall metabolic changes that can aid in the unraveling of explicit biochemical details of mitochondrial inhibition while providing a holistic view and heuristic understanding of cellular bioenergetics. In this paper, we showed the application of quantitative NMR metabolomics to in vitro myotube cells treated with mitochondrial toxicants, rotenone and antimycin A. The close coupling of the TCA cycle to the electron transfer chain (ETC) in OXPHOS enables specific diagnoses of inhibition to ETC complexes by discrete biochemical changes in the TCA cycle.
Collapse
Affiliation(s)
- Qiuwei Xu
- Merck Research Laboratories, 770 Sumneytown Pike, West Point, PA 19486, USA.
| | | | | | | | | |
Collapse
|
13
|
Recent Trends in Strategies and Methodologies for Metabonomics. CHINESE JOURNAL OF ANALYTICAL CHEMISTRY 2009. [DOI: 10.1016/s1872-2040(08)60081-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
|
14
|
Xu EY, Perlina A, Vu H, Troth SP, Brennan RJ, Aslamkhan AG, Xu Q. Integrated pathway analysis of rat urine metabolic profiles and kidney transcriptomic profiles to elucidate the systems toxicology of model nephrotoxicants. Chem Res Toxicol 2008; 21:1548-61. [PMID: 18656965 DOI: 10.1021/tx800061w] [Citation(s) in RCA: 65] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
In this study, approximately 40 endogenous metabolites were identified and quantified by (1)H NMR in urine samples from male rats dosed with two proximal tubule toxicants, cisplatin and gentamicin. The excreted amount of a majority of those metabolites in urine was found to be dose-dependent and exhibited a strong correlation with histopathology scores of overall proximal tubule damage. MetaCore pathway analysis software (GeneGo Inc.) was employed to identify nephrotoxicant-associated biochemical changes via an integrated quantitative analysis of both urine metabolomic and kidney transcriptomic profiles. Correlation analysis was applied to establish quantitative linkages between pairs of individual metabolite and gene transcript profiles in both cisplatin and gentamicin studies. This analysis revealed that cisplatin and gentamicin treatments were strongly linked to declines in mRNA transcripts for several luminal membrane transporters that handle each of the respective elevated urinary metabolites, such as glucose, amino acids, and monocarboxylic acids. The integrated pathway analysis performed on these studies indicates that cisplatin- or gentamicin-induced renal Fanconi-like syndromes manifested by glucosuria, hyperaminoaciduria, lactic aciduria, and ketonuria might be better explained by the reduction of functional proximal tubule transporters rather than by the perturbation of metabolic pathways inside kidney cells. Furthermore, this analysis suggests that renal transcription factors HNF1alpha, HNF1beta, and HIF-1 might be the central mediators of drug-induced kidney injury and adaptive response pathways.
Collapse
Affiliation(s)
- Ethan Yixun Xu
- Department of Safety Assessment, Merck Research Laboratories, West Point, Pennsylvania 19486, USA. ,
| | | | | | | | | | | | | |
Collapse
|
15
|
Van QN, Issaq HJ, Jiang Q, Li Q, Muschik GM, Waybright TJ, Lou H, Dean M, Uitto J, Veenstra TD. Comparison of 1D and 2D NMR Spectroscopy for Metabolic Profiling. J Proteome Res 2007; 7:630-9. [DOI: 10.1021/pr700594s] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Affiliation(s)
- Que N. Van
- Laboratory of Proteomics and Analytical Technologies, Advanced Technology Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, Department of Dermatology and Cutaneous Biology, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, and Laboratory of Genomic Diversity, National Cancer Institute at Frederick, Frederick, Maryland 21702
| | - Haleem J. Issaq
- Laboratory of Proteomics and Analytical Technologies, Advanced Technology Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, Department of Dermatology and Cutaneous Biology, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, and Laboratory of Genomic Diversity, National Cancer Institute at Frederick, Frederick, Maryland 21702
| | - Qiujie Jiang
- Laboratory of Proteomics and Analytical Technologies, Advanced Technology Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, Department of Dermatology and Cutaneous Biology, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, and Laboratory of Genomic Diversity, National Cancer Institute at Frederick, Frederick, Maryland 21702
| | - Qiaoli Li
- Laboratory of Proteomics and Analytical Technologies, Advanced Technology Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, Department of Dermatology and Cutaneous Biology, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, and Laboratory of Genomic Diversity, National Cancer Institute at Frederick, Frederick, Maryland 21702
| | - Gary M. Muschik
- Laboratory of Proteomics and Analytical Technologies, Advanced Technology Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, Department of Dermatology and Cutaneous Biology, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, and Laboratory of Genomic Diversity, National Cancer Institute at Frederick, Frederick, Maryland 21702
| | - Timothy J. Waybright
- Laboratory of Proteomics and Analytical Technologies, Advanced Technology Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, Department of Dermatology and Cutaneous Biology, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, and Laboratory of Genomic Diversity, National Cancer Institute at Frederick, Frederick, Maryland 21702
| | - Hong Lou
- Laboratory of Proteomics and Analytical Technologies, Advanced Technology Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, Department of Dermatology and Cutaneous Biology, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, and Laboratory of Genomic Diversity, National Cancer Institute at Frederick, Frederick, Maryland 21702
| | - Michael Dean
- Laboratory of Proteomics and Analytical Technologies, Advanced Technology Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, Department of Dermatology and Cutaneous Biology, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, and Laboratory of Genomic Diversity, National Cancer Institute at Frederick, Frederick, Maryland 21702
| | - Jouni Uitto
- Laboratory of Proteomics and Analytical Technologies, Advanced Technology Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, Department of Dermatology and Cutaneous Biology, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, and Laboratory of Genomic Diversity, National Cancer Institute at Frederick, Frederick, Maryland 21702
| | - Timothy D. Veenstra
- Laboratory of Proteomics and Analytical Technologies, Advanced Technology Program, SAIC-Frederick, Inc., National Cancer Institute at Frederick, Frederick, Maryland 21702, Department of Dermatology and Cutaneous Biology, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, and Laboratory of Genomic Diversity, National Cancer Institute at Frederick, Frederick, Maryland 21702
| |
Collapse
|