Design principles of mammalian signaling networks : emergent properties at modular and global scales

This thesis utilizes modeling approaches rooted in statistical physics and physical chemistry to investigate several aspects of cellular signal transduction at both the modular and global levels. Design principles of biological networks and cell signaling processes pertinent to disease progression emerge from these studies. It is my hope that knowledge of these principles may provide new mechanistic insights and conceptual frameworks for thinking about therapeutic intervention into diseases such as cancer and diabetes that arise from aberrant signaling. Areas of interest have emphasized the role of scaffold proteins in protein kinase cascades, modeling relevant biophysical processes related to T cell activation, design principles of signal transduction focusing on multisite phosphorylation, quantifying the notion of signal duration and the time scale dependence of signal detection, and entropy based models of network architecture inferred from proteomics data. These problems are detailed below. The assembly of multiple signaling proteins into a complex by a scaffold protein guides many cellular decisions. Despite recent advances, the overarching principles that govern scaffold function are not well understood. We carried out a computational study using kinetic Monte Carlo simulations to understand how spatial localization of kinases on a scaffold may regulate signaling under different physiological condition. Our studies identify regulatory properties of scaffold proteins that allow them to both amplify and attenuate incoming signals in different biological contexts. In a further, supplementary study, simulations also indicate that a major effect that scaffolds exert on the dynamics of cell signaling is to control how the activation of protein kinases is distributed over time[2].

Department dc:contributor.department

Massachusetts Institute of Technology. Biological Engineering Division.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2008

Author dc:creator

• Locasale, Jason W

Advisor dc:contributor.advisor

• Arup K. Chakraborty.

• Biological Engineering Division.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/44862

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/44862