| Chapter title |
Identification of Direct Kinase Substrates via Kinase Assay-Linked Phosphoproteomics.
|
|---|---|
| Chapter number | 18 |
| Book title |
Phospho-Proteomics
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3049-4_18 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3048-7, 978-1-4939-3049-4
|
| Authors |
Liang Xue, Justine V. Arrington, W. Andy Tao |
| Editors |
Louise von Stechow |
| Abstract |
Protein phosphorylation plays an essential role in the regulation of various cellular functions. Dysregulation of phosphorylation is implicated in the pathogenesis of certain cancers, diabetes, cardiovascular diseases, and central nervous system disorders. As a result, protein kinases have become potential drug targets for treating a wide variety of diseases. Identification of kinase substrates is vital not only for dissecting signaling pathways, but also for understanding disease pathologies and identifying novel therapeutic targets. However, identification of bona fide kinase substrates has remained challenging, necessitating the development of new methods and techniques. The kinase assay linked phosphoproteomics (KALIP) approach integrates in vitro kinase assays with global phosphoproteomics experiments to identify the direct substrates of protein kinases. This strategy has demonstrated outstanding sensitivity and a low false-positive rate for kinase substrate screening. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 4% |
| France | 1 | 4% |
| Unknown | 24 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor > Associate Professor | 4 | 15% |
| Student > Ph. D. Student | 4 | 15% |
| Professor | 3 | 12% |
| Researcher | 3 | 12% |
| Student > Master | 2 | 8% |
| Other | 1 | 4% |
| Unknown | 9 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 19% |
| Agricultural and Biological Sciences | 4 | 15% |
| Chemistry | 3 | 12% |
| Computer Science | 2 | 8% |
| Chemical Engineering | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 9 | 35% |