System level dynamics of post-translational modifications.
Attempts to characterize cellular behaviors with static, univariate measurements cannot fully capture biological complexity and lead to an inadequate interpretation of cellular processes. Significant biological insight can be gleaned by considering the contribution of dynamic protein post-translational modifications (PTMs) utilizing systems-level quantitative analysis. High-resolution mass spectrometry coupled with computational modeling of dynamic signal-response relationships is a powerful tool to reveal PTM-mediated regulatory networks. Recent advances using this approach have defined network kinetics of growth factor signaling pathways, identified systems level responses to cytotoxic perturbations, elucidated kinase-substrate relationships, and unraveled the dynamics of PTM cross-talk. Innovations in multiplex measurement capacity, PTM annotation accuracy, and computational integration of datasets promise enhanced resolution of dynamic PTM networks and further insight into biological intricacies.
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Aaron S
AS
Gajadhar
Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: fwhite@mit.edu.
Forest M
FM
White
D000818:Animals; D006801:Humans; D013058:Mass Spectrometry; D010766:Phosphorylation; D011499:Protein Processing, Post-Translational; D011506:Proteins / Q000737:chemistry / Q000378:metabolism*; D015398:Signal Transduction
D011506:Proteins