Chapter title |
Fluorescence anisotropy-based salt-titration approach to characterize protein-nucleic Acid interactions.
|
---|---|
Chapter number | 23 |
Book title |
RNA Remodeling Proteins
|
Published in |
Methods in molecular biology, January 2015
|
DOI | 10.1007/978-1-4939-2214-7_23 |
Pubmed ID | |
Book ISBNs |
978-1-4939-2213-0, 978-1-4939-2214-7
|
Authors |
Rye-McCurdy T, Rouzina I, Musier-Forsyth K, Tiffiny Rye-McCurdy, Ioulia Rouzina, Karin Musier-Forsyth |
Abstract |
Many proteins bind nucleic acids (NA) via cationic residues that interact electrostatically with the anionic phosphate backbone of RNA or DNA. These electrostatic interactions are often insensitive to NA sequence and structure, but confer strong salt dependence to the binding interactions. In contrast, salt-independent non-electrostatic contacts reflect more specific binding interactions. Proteins with multiple cationic NA-binding domains connected by flexible linkers, such as the HIV-1 Gag polyprotein, may bind different NA molecules in distinct ways. For example, Gag binding to the Psi-packaging signal of the HIV-1 RNA genome optimizes the specific non-electrostatic binding component of this protein-RNA interaction. In contrast, Gag binding to a non-psi RNA optimizes the electrostatic interactions at the expense of specific contacts. Here, we describe a fluorescence anisotropy-based salt-titration approach that allows complete characterization of both electrostatic and non-electrostatic binding components for any protein-NA complex in a quantitative manner within a single assay. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 10 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 5 | 50% |
Student > Bachelor | 2 | 20% |
Student > Ph. D. Student | 2 | 20% |
Unknown | 1 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 4 | 40% |
Agricultural and Biological Sciences | 2 | 20% |
Immunology and Microbiology | 1 | 10% |
Chemistry | 1 | 10% |
Unknown | 2 | 20% |