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Simultaneous Quantification of Protein Binding Kinetics in Whole Cells with Surface Plasmon Resonance Imaging and Edge Deformation Tracking

Most drugs work by binding to receptors on the cell surface. Quantification of binding kinetics between drug and membrane protein is an essential step in drug discovery. Current methods for measuring binding kinetics involve extracting the membrane protein and labeling, and both have issues. Surface...

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Autores principales: Jing, Wenwen, Hunt, Ashley, Tao, Nongjian, Zhang, Fenni, Wang, Shaopeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7558147/
https://www.ncbi.nlm.nih.gov/pubmed/32971834
http://dx.doi.org/10.3390/membranes10090247
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author Jing, Wenwen
Hunt, Ashley
Tao, Nongjian
Zhang, Fenni
Wang, Shaopeng
author_facet Jing, Wenwen
Hunt, Ashley
Tao, Nongjian
Zhang, Fenni
Wang, Shaopeng
author_sort Jing, Wenwen
collection PubMed
description Most drugs work by binding to receptors on the cell surface. Quantification of binding kinetics between drug and membrane protein is an essential step in drug discovery. Current methods for measuring binding kinetics involve extracting the membrane protein and labeling, and both have issues. Surface plasmon resonance (SPR) imaging has been demonstrated for quantification of protein binding to cells with single-cell resolution, but it only senses the bottom of the cell and the signal diminishes with the molecule size. We have discovered that ligand binding to the cell surface is accompanied by a small cell membrane deformation, which can be used to measure the binding kinetics by tracking the cell edge deformation. Here, we report the first integration of SPR imaging and cell edge tracking methods in a single device, and we use lectin interaction as a model system to demonstrate the capability of the device. The integration enables the simultaneous collection of complementary information provided by both methods. Edge tracking provides the advantage of small molecule binding detection capability, while the SPR signal scales with the ligand mass and can quantify membrane protein density. The kinetic constants from the two methods were cross-validated and found to be in agreement at the single-cell level. The variation of observed rate constant between the two methods is about 0.009 s(−1), which is about the same level as the cell-to-cell variations. This result confirms that both methods can be used to measure whole-cell binding kinetics, and the integration improves the reliability and capability of the measurement.
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spelling pubmed-75581472020-10-29 Simultaneous Quantification of Protein Binding Kinetics in Whole Cells with Surface Plasmon Resonance Imaging and Edge Deformation Tracking Jing, Wenwen Hunt, Ashley Tao, Nongjian Zhang, Fenni Wang, Shaopeng Membranes (Basel) Article Most drugs work by binding to receptors on the cell surface. Quantification of binding kinetics between drug and membrane protein is an essential step in drug discovery. Current methods for measuring binding kinetics involve extracting the membrane protein and labeling, and both have issues. Surface plasmon resonance (SPR) imaging has been demonstrated for quantification of protein binding to cells with single-cell resolution, but it only senses the bottom of the cell and the signal diminishes with the molecule size. We have discovered that ligand binding to the cell surface is accompanied by a small cell membrane deformation, which can be used to measure the binding kinetics by tracking the cell edge deformation. Here, we report the first integration of SPR imaging and cell edge tracking methods in a single device, and we use lectin interaction as a model system to demonstrate the capability of the device. The integration enables the simultaneous collection of complementary information provided by both methods. Edge tracking provides the advantage of small molecule binding detection capability, while the SPR signal scales with the ligand mass and can quantify membrane protein density. The kinetic constants from the two methods were cross-validated and found to be in agreement at the single-cell level. The variation of observed rate constant between the two methods is about 0.009 s(−1), which is about the same level as the cell-to-cell variations. This result confirms that both methods can be used to measure whole-cell binding kinetics, and the integration improves the reliability and capability of the measurement. MDPI 2020-09-22 /pmc/articles/PMC7558147/ /pubmed/32971834 http://dx.doi.org/10.3390/membranes10090247 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jing, Wenwen
Hunt, Ashley
Tao, Nongjian
Zhang, Fenni
Wang, Shaopeng
Simultaneous Quantification of Protein Binding Kinetics in Whole Cells with Surface Plasmon Resonance Imaging and Edge Deformation Tracking
title Simultaneous Quantification of Protein Binding Kinetics in Whole Cells with Surface Plasmon Resonance Imaging and Edge Deformation Tracking
title_full Simultaneous Quantification of Protein Binding Kinetics in Whole Cells with Surface Plasmon Resonance Imaging and Edge Deformation Tracking
title_fullStr Simultaneous Quantification of Protein Binding Kinetics in Whole Cells with Surface Plasmon Resonance Imaging and Edge Deformation Tracking
title_full_unstemmed Simultaneous Quantification of Protein Binding Kinetics in Whole Cells with Surface Plasmon Resonance Imaging and Edge Deformation Tracking
title_short Simultaneous Quantification of Protein Binding Kinetics in Whole Cells with Surface Plasmon Resonance Imaging and Edge Deformation Tracking
title_sort simultaneous quantification of protein binding kinetics in whole cells with surface plasmon resonance imaging and edge deformation tracking
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7558147/
https://www.ncbi.nlm.nih.gov/pubmed/32971834
http://dx.doi.org/10.3390/membranes10090247
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