Login Register Cart 0
Generic placeholder image

Current Pharmaceutical Analysis

Editor-in-Chief

ISSN (Print): 1573-4129
ISSN (Online): 1875-676X

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Protein Species of Origin Determination By NMR Relaxometry

Author(s): Gregory K. Webster*

Volume 19, Issue 9, 2023

Published on: 07 November, 2023

Page: [687 - 694] Pages: 8

DOI: 10.2174/0115734129246067230921050607

Price: $65

Abstract

Aims: The aim of this project was to develop a QC friendly and efficient method of protein species of origin identification to replace more costly mass spectrometric based methods currently being used for this testing.

Background: NMR relaxation measurements with proteins in aqueous solutions exploit the fast chemical exchange between water and exposed NH and OH protons of amino acid side chains in the folded protein structure unique to each biologic drug. Implementation of this technique has led to routine testing for authentication and forensics of biopharmaceuticals, determination of moisture content in lyophilized protein formulations and aggregation of proteins in solution. For small molecule applications, TD-NMR can detect if solvents are received neat or tainted with moisture, impurities, or denaturants.

Objective: The objective of this study was to evaluate the ability of NMR Relaxation measurements to differentiate between sources of Albumin proteins as a rapid QC test. Evaluation of differences in molecular mobility between components in a solution as reflected in the longitudinal (T1) and transverse (T2) relaxation times of protons demonstrate that NMR relaxation techniques can distinguish between different albumin sources of origin.

Methods: Representative albumin proteins from differing sources of origin were studied. Using bovine serum albumin (BSA) as the target species of origin, NMR relaxation techniques as well as chemometric modeling were used to evaluate the use of this technique for protein source of origin identification.

Results: NMR Relaxation using benchtop instrumentation showed that the bovine albumin species of origin can be distinguished from porcine, chicken egg white and sheep sources of origin. Goat albumin selectivity remained questionable and BSA cannot be distinguished from human or rabbit sources of origin within the representative variability.

T2 transverse relaxation results were significantly more discriminating for protein source identification than the T1 longitudinal relaxation result by itself. The T1 longitudinal relaxation result did not contribute significantly to this investigation. However, fusing the T1 data with the T2 transverse relaxation results and using larger data sets merit further evaluation in the hope of achieving additional selectivity.

Conclusion: While additional lots are needed for more definitive results, this preliminary evaluation of using NMR Relaxation demonstrated the capability for the source of origin species discrimination and identification using benchtop NMR instrumentation.

« Previous Next »
Graphical Abstract

[1]
Flores, D.W.M.; Colnago, L.A.; Ferreira, M.D.; Spoto, M.H.F. Prediction of Orange juice sensorial attributes from intact fruits by TD-NMR. Microchem. J., 2016, 128, 113-117.
[http://dx.doi.org/10.1016/j.microc.2016.04.009]
[2]
Yildiz, E.; Guner, S.; Sumnu, G.; Sahin, S.; Oztop, M.H. Monitoring the effects of ingredients and baking methods on quality of gluten-free cakes by time-domain (TD) NMR relaxometry. Food Bioprocess Technol., 2018, 11(10), 1923-1933.
[http://dx.doi.org/10.1007/s11947-018-2152-z]
[3]
Rodríguez-Alonso, E.; Vergeldt, F.J.; van der Goot, A.J. TD-NMR to understand water-binding food properties. Magn. Reson. Chem., 2019, 57(9), 603-606.
[http://dx.doi.org/10.1002/mrc.4815]
[4]
Mulas, G.; Roggio, T.; Uzzau, S.; Anedda, R. A new magnetic resonance imaging approach for discriminating Sardinian sheep milk cheese made from heat-treated or raw milk. J. Dairy Sci., 2013, 96(12), 7393-7403.
[http://dx.doi.org/10.3168/jds.2013-6607] [PMID: 24119804]
[5]
Dekkers, B.L.; de Kort, D.W.; Grabowska, K.J.; Tian, B.; Van As, H.; van der Goot, A.J. A combined rheology and time domain NMR approach for determining water distributions in protein blends. Food Hydrocoll., 2016, 60, 525-532.
[http://dx.doi.org/10.1016/j.foodhyd.2016.04.020]
[6]
Todt, H.; Guthausen, G.; Burk, W.; Schmalbein, D.; Kamlowski, A. Water/moisture and fat analysis by time-domain NMR. Food Chem., 2006, 96(3), 436-440.
[http://dx.doi.org/10.1016/j.foodchem.2005.04.032]
[7]
Osheter, T.; Linder, C.; Wiesman, Z. Time Domain (TD) Proton NMR analysis of the oxidative safety and quality of lipid-rich foods. Biosensors, 2022, 12(4), 230.
[http://dx.doi.org/10.3390/bios12040230] [PMID: 35448290]
[8]
Cobo, M.F.; Deublein, E.J.; Haber, A.; Kwamen, R.; Nimbalkar, M.; Decker, F. TD-NMR in quality control: Standard applications.Modern Magnetic Resonance; Webb, G., Ed.; Springer: Cham, 2018.
[http://dx.doi.org/10.1007/978-3-319-28388-3_12]
[9]
Guthausen, G.; Todt, H.; Burk, W.; Schmalbein, D.; Kamlowski, A. Time-Domain NMR in Quality Control: More Advanced Methods.Modern Magnetic Resonance; Webb, G.A., Ed.; Springer: Dordrecht, 2008.
[http://dx.doi.org/10.1007/1-4020-3910-7_195]
[10]
Hills, B.P.; Takacs, S.F.; Belton, P.S. The effects of proteins on the proton N.M.R. transverse relaxation time of water. Mol. Phys., 1989, 67(4), 919-937.
[http://dx.doi.org/10.1080/00268978900101541]
[11]
Akhunzada, Z.; Wu, Y.; Haby, T.; Jayawickrama, D.; McGeorge, G.; La Colla, M.; Bernstein, J.; Semones, M.; Abraham, A. Analysis of biopharmaceutical formulations by time domain nuclear magnetic resonance (TD-NMR) spectroscopy: A potential method for detection of counterfeit biologic pharmaceuticals. J. Pharm. Sci., 2021, 110(7), 2765-2770.
[http://dx.doi.org/10.1016/j.xphs.2021.03.011] [PMID: 33745914]
[12]
Semones, M.; Bernstein, J.; La Colla, M.; Graham-Coco, W.; Webster, G.K.; Doherty, S.J.; Yang, C.; Anantharaman, S. Portable Time-Domain NMR: A rapid method for detecting changes in complex pharmaceutical materials and formulations. Pittsburgh Conference, 2022.
[13]
Taraban, M.B.; DePaz, R.A.; Lobo, B.; Yu, Y.B. Use of water proton NMR to characterize protein aggregates: Gauging the response and sensitivity. Anal. Chem., 2019, 91(6), 4107-4115.
[http://dx.doi.org/10.1021/acs.analchem.8b05733] [PMID: 30767509]
[14]
Indrawati, L.; Stroshine, R.L.; Narsimhan, G. Low-field NMR: A Tool for studying protein aggregation. J. Sci. Food Agric., 2007, 87(12), 2207-2216.
[http://dx.doi.org/10.1002/jsfa.2914]
[15]
Stueber, D.; Jehle, S. Quantitative component analysis of solid mixtures by analyzing time domain 1h and 19f t1 saturation recovery curves (qSRC). J. Pharm. Sci., 2017, 106(7), 1828-1838.
[http://dx.doi.org/10.1016/j.xphs.2017.03.034] [PMID: 28412399]
[16]
Metz, H.; Mäder, K. Benchtop-NMR and MRI : A new analytical tool in drug delivery research. Int. J. Pharm., 2008, 364(2), 170-175.
[http://dx.doi.org/10.1016/j.ijpharm.2008.09.033] [PMID: 18930126]
[17]
Masiewicz, E.; Ashcroft, G.P.; Boddie, D.; Dundas, S.R.; Kruk, D.; Broche, L.M. Towards applying NMR relaxometry as a diagnostic tool for bone and soft tissue sarcomas: A pilot study. Sci. Rep., 2020, 10(1), 14207.
[http://dx.doi.org/10.1038/s41598-020-71067-x] [PMID: 32848198]
[18]
Abraham, A.; Elkassabany, O.; Krause, M.E.; Ott, A. A nondestructive and noninvasive method to determine water content in lyophilized proteins using low-field time-domain NMR. Magn. Reson. Chem., 2019, 57(10), 873-877.
[http://dx.doi.org/10.1002/mrc.4864] [PMID: 30861192]
[19]
Rohman, A.; Windarsih, A.; Erwanto, Y.; Zakaria, Z. Review on analytical methods for analysis of porcine gelatine in food and pharmaceutical products for halal authentication. Trends Food Sci. Technol., 2020, 101, 122-132.
[http://dx.doi.org/10.1016/j.tifs.2020.05.008]
[20]
Eryılmaz, H.S.; Işık, B.Ş.; Demircan, E.; Memeli, Z.; Çapanoğlu, E.; Erdil, D.N. Origin determination and differentiation of gelatin species of bovine, porcine, and piscine through analytical methods. Turk. J. Agricul. Food. Sci. Technol., 2017, 5(5), 507-517.
[http://dx.doi.org/10.24925/turjaf.v5i5.507-517.1077]
[21]
Mureșan, C.I.; Cornea-Cipcigan, M.; Suharoschi, R.; Erler, S.; Mărgăoan, R. Honey botanical origin and honey-specific protein pattern: Characterization of some european honeys. Lebensm. Wiss. Technol., 2022, 154, 112883.
[http://dx.doi.org/10.1016/j.lwt.2021.112883]
[22]
Grundy, H.H.; Reece, P.; Buckley, M.; Solazzo, C.M.; Dowle, A.A.; Ashford, D.; Charlton, A.J.; Wadsley, M.K.; Collins, M.J. A mass spectrometry method for the determination of the species of origin of gelatine in foods and pharmaceutical products. Food Chem., 2016, 190, 276-284.
[http://dx.doi.org/10.1016/j.foodchem.2015.05.054] [PMID: 26212971]
[23]
Grundy, H.H. Determination of species origin of gelatine in foods.FoodIntegrity Handbook: A guide to food authenticity issues and analytical solutions; Morin, J-F.; Lees, M., Eds.; Eurofins Analytics France, 2018.
[http://dx.doi.org/10.32741/fihb.21.gelatine]
[24]
Monakhova, Y.B.; Holzgrabe, U.; Diehl, B.W.K. Current role and future perspectives of multivariate (chemometric) methods in NMR spectroscopic analysis of pharmaceutical products. J. Pharm. Biomed. Anal., 2018, 147, 580-589.
[http://dx.doi.org/10.1016/j.jpba.2017.05.034] [PMID: 28583765]
[25]
Ramos, P.F.O.; de Toledo, I.B.; Nogueira, C.M.; Novotny, E.H.; Vieira, A.J.M.; Azeredo, R.B.V. Low field 1H NMR relaxometry and multivariate data analysis in crude oil viscosity prediction. Chemom. Intell. Lab. Syst., 2009, 99(2), 121-126.
[http://dx.doi.org/10.1016/j.chemolab.2009.08.001]
[26]
Muhammad, A.; Azeredo, R.B.V. 1H NMR spectroscopy and low-field relaxometry for predicting viscosity and API gravity of Brazilian crude oils : A comparative study. Fuel, 2014, 130, 126-134.
[http://dx.doi.org/10.1016/j.fuel.2014.04.026]
[27]
Santos, P.M.; Amais, R.S.; Colnago, L.A.; Rinnan, Å.; Monteiro, M.R. Time Domain-NMR combined with chemometrics analysis: An alternative tool for monitoring diesel fuel quality. Energy Fuels, 2015, 29(4), 2299-2303.
[http://dx.doi.org/10.1021/acs.energyfuels.5b00017]
[28]
Guillemant, J.; Lacoue-Nègre, M.; Berlioz-Barbier, A.; de Oliveira, L.P.; Albrieux, F.; Joly, J.F.; Duponchel, L. Evaluating the benefits of data fusion and PARAFAC for the chemometric analysis of FT-ICR MS data sets from gas oil samples. Energy Fuels, 2020, 34(7), 8195-8205.
[http://dx.doi.org/10.1021/acs.energyfuels.0c01104]
[29]
Olson, D.L.; Norcross, J.A.; O’Neil-Johnson, M.; Molitor, P.F.; Detlefsen, D.J.; Wilson, A.G.; Peck, T.L. Microflow NMR: Concepts and Capabilities. Anal. Chem., 2004, 76(10), 2966-2974.
[http://dx.doi.org/10.1021/ac035426l] [PMID: 15144211]
[30]
Torres, A.M.; Price, W.S. Common problems and artifacts encountered in solution-state NMR experiments. Concepts Magn. Reson. Part A Bridg. Educ. Res., 2016, 45A(2), e21387.
[http://dx.doi.org/10.1002/cmr.a.21387]
[31]
Chi, L.; Huang, M.; Pfaff, A.R.; Huang, J.; Gerald, R.E., II; Woelk, K. Capillary-tube package devices for the quantitative performance evaluation of nuclear magnetic resonance spectrometers and pulse sequences. Rev. Sci. Instrum., 2018, 89(12), 123115.
[http://dx.doi.org/10.1063/1.5052374] [PMID: 30599605]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy