Literature DB >> 19834900

Experimental and computational tools useful for (re)construction of dynamic kinase-substrate networks.

Chris Soon Heng Tan1, Rune Linding.   

Abstract

The explosion of site- and context-specific in vivo phosphorylation events presents a potentially rich source of biological knowledge and calls for novel data analysis and modeling paradigms. Perhaps the most immediate challenge is delineating detected phosphorylation sites to their effector kinases. This is important for (re)constructing transient kinase-substrate interaction networks that are essential for mechanistic understanding of cellular behaviors and therapeutic intervention, but has largely eluded high-throughput protein-interaction studies due to their transient nature and strong dependencies on cellular context. Here, we surveyed some of the computational approaches developed to dissect phosphorylation data detected in systematic proteomic experiments and reviewed some experimental and computational approaches used to map phosphorylation sites to their effector kinases in efforts aimed at reconstructing biological signaling networks.

Mesh:

Substances:

Year:  2009        PMID: 19834900     DOI: 10.1002/pmic.200900266

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  6 in total

1.  Spatial phosphoprotein profiling reveals a compartmentalized extracellular signal-regulated kinase switch governing neurite growth and retraction.

Authors:  Yingchun Wang; Feng Yang; Yi Fu; Xiahe Huang; Wei Wang; Xinning Jiang; Marina A Gritsenko; Rui Zhao; Matthew E Monore; Olivier C Pertz; Samuel O Purvine; Daniel J Orton; Jon M Jacobs; David G Camp; Richard D Smith; Richard L Klemke
Journal:  J Biol Chem       Date:  2011-03-28       Impact factor: 5.157

2.  Systematic analysis of protein phosphorylation networks from phosphoproteomic data.

Authors:  Chunxia Song; Mingliang Ye; Zexian Liu; Han Cheng; Xinning Jiang; Guanghui Han; Zhou Songyang; Yexiong Tan; Hongyang Wang; Jian Ren; Yu Xue; Hanfa Zou
Journal:  Mol Cell Proteomics       Date:  2012-07-13       Impact factor: 5.911

3.  Combination of chemical genetics and phosphoproteomics for kinase signaling analysis enables confident identification of cellular downstream targets.

Authors:  Felix S Oppermann; Kathrin Grundner-Culemann; Chanchal Kumar; Oliver J Gruss; Prasad V Jallepalli; Henrik Daub
Journal:  Mol Cell Proteomics       Date:  2011-12-22       Impact factor: 5.911

4.  Structural Analysis of PTM Hotspots (SAPH-ire)--A Quantitative Informatics Method Enabling the Discovery of Novel Regulatory Elements in Protein Families.

Authors:  Henry M Dewhurst; Shilpa Choudhury; Matthew P Torres
Journal:  Mol Cell Proteomics       Date:  2015-06-12       Impact factor: 5.911

5.  Dynamic phosphorylation of HP1α regulates mitotic progression in human cells.

Authors:  Arindam Chakraborty; Kannanganattu V Prasanth; Supriya G Prasanth
Journal:  Nat Commun       Date:  2014-03-12       Impact factor: 14.919

6.  Elucidation of the evolutionary expansion of phosphorylation signaling networks using comparative phosphomotif analysis.

Authors:  Hisayoshi Yoshizaki; Shujiro Okuda
Journal:  BMC Genomics       Date:  2014-07-01       Impact factor: 3.969

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.