TY - JOUR
T1 - Information theoretical quantification of cooperativity in signalling complexes
AU - Lenaerts, Tom
AU - Ferkinghoff-Borg, Jesper
AU - Schymkowitz, Joost
AU - Rousseau, Frederic
PY - 2009
Y1 - 2009
N2 - Background: Intra-cellular information exchange, propelled by cascades of interacting signalling
proteins, is essential for the proper functioning and survival of cells. Now that the interactome of
several organisms is being mapped and several structural mechanisms of cooperativity at the
molecular level in proteins have been elucidated, the formalization of this fundamental quantity, i.e.
information, in these very diverse biological contexts becomes feasible.
Results: We show here that Shannon's mutual information quantifies information in biological
system and more specifically the cooperativity inherent to the assembly of macromolecular
complexes. We show how protein complexes can be considered as particular instances of noisy
communication channels. Further we show, using a portion of the p27 regulatory pathway, how
classical equilibrium thermodynamic quantities such as binding affinities and chemical potentials can
be used to quantify information exchange but also to determine engineering properties such as
channel noise and channel capacity. As such, this information measure identifies and quantifies
those protein concentrations that render the biochemical system most effective in switching
between the active and inactive state of the intracellular process.
Conclusion: The proposed framework provides a new and original approach to analyse the effects
of cooperativity in the assembly of macromolecular complexes. It shows the conditions, provided
by the protein concentrations, for which a particular system acts most effectively, i.e. exchanges
the most information. As such this framework opens the possibility of grasping biological qualities
such as system sensitivity, robustness or plasticity directly in terms of their effect on information
exchange. Although these parameters might also be derived using classical thermodynamic
parameters, a recasting of biological signalling in terms of information exchange offers an alternative
framework for visualising network cooperativity that might in some cases be more intuitive.
AB - Background: Intra-cellular information exchange, propelled by cascades of interacting signalling
proteins, is essential for the proper functioning and survival of cells. Now that the interactome of
several organisms is being mapped and several structural mechanisms of cooperativity at the
molecular level in proteins have been elucidated, the formalization of this fundamental quantity, i.e.
information, in these very diverse biological contexts becomes feasible.
Results: We show here that Shannon's mutual information quantifies information in biological
system and more specifically the cooperativity inherent to the assembly of macromolecular
complexes. We show how protein complexes can be considered as particular instances of noisy
communication channels. Further we show, using a portion of the p27 regulatory pathway, how
classical equilibrium thermodynamic quantities such as binding affinities and chemical potentials can
be used to quantify information exchange but also to determine engineering properties such as
channel noise and channel capacity. As such, this information measure identifies and quantifies
those protein concentrations that render the biochemical system most effective in switching
between the active and inactive state of the intracellular process.
Conclusion: The proposed framework provides a new and original approach to analyse the effects
of cooperativity in the assembly of macromolecular complexes. It shows the conditions, provided
by the protein concentrations, for which a particular system acts most effectively, i.e. exchanges
the most information. As such this framework opens the possibility of grasping biological qualities
such as system sensitivity, robustness or plasticity directly in terms of their effect on information
exchange. Although these parameters might also be derived using classical thermodynamic
parameters, a recasting of biological signalling in terms of information exchange offers an alternative
framework for visualising network cooperativity that might in some cases be more intuitive.
U2 - 10.1186/1752-0509-3-9
DO - 10.1186/1752-0509-3-9
M3 - Journal article
C2 - 19149897
SN - 1752-0509
VL - 3
SP - 9
JO - BMC Systems Biology
JF - BMC Systems Biology
ER -