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Sci. Signal., 27 March 2012
Vol. 5, Issue 217, p. ra25
[DOI: 10.1126/scisignal.2002469]

RESEARCH ARTICLES

Editor's Summary

Computing TOR Regulation
Without effective genetic or specific pharmacological tools, it can be challenging to dissect regulatory mechanisms in complex, interconnected pathways. Dalle Pezze et al. combined computational modeling with biochemical analysis to test specific regulatory mechanisms of the mammalian target of rapamycin (mTOR) pathway, in particular the regulation of mTOR complex mTORC2, which has important functions in controlling cell growth. After identifying key network components that could be experimentally monitored to explicitly test specific network structures, they compared the experimental data to the modeled networks to rule out previously suggested regulatory mechanisms and postulated the existence of a previously unknown pathway. Their results led to the proposal of a distinct phosphoinositide 3-kinase–dependent pathway from the insulin receptor to mTORC2 that is independent of various components that participate in the activation of mTORC1 and thus should open new areas of research into mTOR signaling and could provide direction for developing selective regulators of mTORC1 and mTORC2 signaling.

Citation: P. Dalle Pezze, A. G. Sonntag, A. Thien, M. T. Prentzell, M. Gödel, S. Fischer, E. Neumann-Haefelin, T. B. Huber, R. Baumeister, D. P. Shanley, K. Thedieck, A Dynamic Network Model of mTOR Signaling Reveals TSC-Independent mTORC2 Regulation. Sci. Signal. 5, ra25 (2012).

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THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:
Insulin Signaling in Type 2 Diabetes: EXPERIMENTAL AND MODELING ANALYSES REVEAL MECHANISMS OF INSULIN RESISTANCE IN HUMAN ADIPOCYTES.
C. Brannmark, E. Nyman, S. Fagerholm, L. Bergenholm, E.-M. Ekstrand, G. Cedersund, and P. Stralfors (2013)
J. Biol. Chem. 288, 9867-9880
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Comment on "A Dynamic Network Model of mTOR Signaling Reveals TSC-Independent mTORC2 Regulation": Building a Model of the mTOR Signaling Network with a Potentially Faulty Tool.
B. D. Manning (2012)
Science Signaling 5, lc3
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Response to Comment on "A Dynamic Network Model of mTOR Signaling Reveals TSC-Independent mTORC2 Regulation": Building a Model of the mTOR Signaling Network with a Potentially Faulty Tool.
P. Dalle Pezze, A. G. Sonntag, D. P. Shanley, and K. Thedieck (2012)
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Computational Approaches for Analyzing Information Flow in Biological Networks.
B. Kholodenko, M. B. Yaffe, and W. Kolch (2012)
Science Signaling 5, re1
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Deconvolution of mTORC2 "in Silico".
D. C. Fingar and K. Inoki (2012)
Science Signaling 5, pe12
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