| Chapter title |
Measuring Protein-Protein Interactions Using Biacore.
|
|---|---|
| Chapter number | 17 |
| Book title |
Protein Chromatography
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-6412-3_17 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6410-9, 978-1-4939-6412-3
|
| Authors |
Paul Leonard, Stephen Hearty, Hui Ma, Richard O’Kennedy |
| Editors |
Dermot Walls, Sinéad T. Loughran |
| Abstract |
The use of optical biosensors for studying macromolecular interactions is gaining increasing popularity. In one study, 1514 papers that involved the application of biosensor data were identified for the year 2009 alone (Rich and Myszka, J Mol Recognit 24:892-914, 2011), the sheer volume and variety of which present a daunting task for the burgeoning biosensor user to accumulate and decipher. This chapter is designed to provide the reader with the tools necessary to prepare, design, and efficiently execute a kinetic experiment on Biacore. It is written to guide the Biacore user through basic theory, system maintenance, and assay setup while also offering some practical tips that we find useful for Biacore-based studies. Many kinetic-based screening assays require rigorous sample preparation and purification prior to analysis. To highlight these procedures, this protocol describes the kinetic characterization of single chain Fv (scFv) antibody fragments from crude bacterial lysates using an antibody affinity capture approach. Even though we specifically describe the capture of HA-tagged scFv antibody fragments to an anti-HA tag monoclonal antibody-immobilized surface prior to kinetic analysis, the same methodologies are universally applicable and can be used for practically any affinity pair and most Biacore systems. |
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Demographic breakdown
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|---|---|---|
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| Researcher | 27 | 20% |
| Student > Bachelor | 22 | 16% |
| Student > Master | 17 | 13% |
| Student > Doctoral Student | 7 | 5% |
| Other | 14 | 10% |
| Unknown | 17 | 13% |
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| Materials Science | 2 | 1% |
| Other | 4 | 3% |
| Unknown | 21 | 15% |