such as "Introduction", "Conclusion"..etc
ago, scientists began reducing the physics of the universe into a few,
key laws described by a handful of parameters. Such simple descriptions
have remained elusive for complex biological systems – until now.
University biophysicist Ilya Nemenman has identified parameters for
several biochemical networks that distill the entire behavior of these
systems into simple equivalent dynamics. The discovery may hold the
potential to streamline the development of drugs and diagnostic tools,
by simplifying the research models.
The resulting paper, now available online, will be published in the March issue of Physical Biology.
appears that the details of the complexity of these biological systems
don't matter, as long as some aggregate property, which we've
calculated, remains the same," says Nemenman, associate professor of
physics and biology. He conducted the analysis with Golan Bel and Brian
Munsky of the Los Alamos National Laboratory.
'A beautiful result'
simplicity of the discovery makes it "a beautiful result," Nemenman
says. "We hope that this theoretical finding will also have practical
He cites the air molecules moving about his
office: "All of the crazy interactions of these molecules hitting each
other boils down to a simple behavior: An ideal gas law. You could take
the painstaking route of studying the dynamics of every molecule, or
you could simply measure the temperature, volume and pressure of the
air in the room. The second method is clearly easier, and it gives you
just as much information."
Nemenman wanted to find similar
parameters for the incredibly complex dynamics of cellular networks,
involving hundreds, or even thousands, of variables among different
interacting molecules. Among the key questions: What determines which
features in these networks are relevant? And if they have simple
equivalent dynamics, did nature choose to make them so complex in order
to fulfill a specific biological function? Or is the unnecessary
complexity a "fossil record" of the evolutionary heritage?
A KPR scheme
the Physical Biology paper, Nemenman and co-authors investigated these
questions in the context of a kinetic proofreading (KPR) scheme.
is the mechanism a cell uses for optimal quality control as it makes
protein. KPR was predicted during the 1970s and it applies to most
cellular assembly processes. It involves hundreds of steps, and each
step may have different parameters.
A key aggregate rate
and his colleagues wondered if the KPR scheme could be described more
simply. "Our calculations confirmed that there is, in fact, a key
aggregate rate," he says. "The whole behavior of the system boils down
to just one parameter."
That means that, instead of
painstakingly testing or measuring every rate in the process, you can
predict the error and completion rate of a system by looking at a
single aggregate parameter.
Charted on a graph, the aggregate
behavior appears as a straight line amid a tangle of curving ones. "The
larger and more complex the system gets, the more the aggregate
behavior is visible," Nemenman says. "The completion time gets simpler
and simpler as the system size goes up."
In addition to the
KPR scheme, the paper reports similar results for other biochemical
kinetics networks, including a reversible linear pathway and a general
multi-step completion process.
is now collaborating with Emory theoretical biologist Rustom Antia, to
see if the discovery can shed light on the processes of immune cells.
In particular, they are interested in the malfunction of certain immune
receptors involved in most allergic reactions.
"We may be
able to simplify the model for these immune receptors from about 3,000
steps to three steps," Nemenman says. "You wouldn't need a
supercomputer to test different chemical compounds on the receptors,
because you don't need to simulate every single step – just the
Just as the discovery of an ideal gas law led to
the creation of engines and automobiles, Nemenman believes that such
simple biochemical aggregates could drive advancements in health.
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