The statistical mechanics of complex signaling networks: nerve growth factor signaling

被引:170
作者
Brown, KS
Hill, CC
Calero, GA
Myers, CR
Lee, KH
Sethna, JP
Cerione, RA
机构
[1] Cornell Univ, LASSP, Dept Phys, Ithaca, NY 14853 USA
[2] Cornell Univ, Baker Lab, Dept Chem & Biol Chem, Ithaca, NY 14853 USA
[3] Cornell Theory Ctr, Ithaca, NY 14853 USA
[4] Cornell Univ, Sch Chem & Biomol Engn, Ithaca, NY 14853 USA
[5] Cornell Univ, Dept Mol Med, Ctr Vet Med, Ithaca, NY 14853 USA
关键词
D O I
10.1088/1478-3967/1/3/006
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The inherent complexity of cellular signaling networks and their importance to a wide range of cellular functions necessitates the development of modeling methods that can be applied toward making predictions and highlighting the appropriate experiments to test our understanding of how these systems are designed and function. We use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. A key difficulty with signaling models is that, while significant effort is being made to experimentally measure the rate constants for individual steps in these networks, many of the parameters required to describe their behavior remain unknown or at best represent estimates. To establish the usefulness of our approach, we have applied our methods toward modeling the nerve growth factor ( NGF)-induced differentiation of neuronal cells. In particular, we study the actions of NGF and mitogenic epidermal growth factor ( EGF) in rat pheochromocytoma (PC12) cells. Through a network of intermediate signaling proteins, each of these growth factors stimulates extracellular regulated kinase (Erk) phosphorylation with distinct dynamical profiles. Using our modeling approach, we are able to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems that we call 'sloppiness'.
引用
收藏
页码:184 / 195
页数:12
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