Archive for the ‘Modeling & Simulation’ Category


By Kevin Jiang, University of Chicago Medicine

Just 12 molecules of water cause the long post-activation recovery period required by potassium ion channels before they can function again. Using molecular simulations that modeled a potassium channel and its immediate cellular environment, atom for atom, University of Chicago scientists have revealed this new mechanism in the function of a nearly universal biological structure, with implications ranging from fundamental biology to the design of pharmaceuticals. Their findings were published online July 28 in Nature.

“Our research clarifies the nature of this previously mysterious inactivation state. This gives us better understanding of fundamental biology and should improve the rational design of drugs, which often target the inactivated state of channels” said Benoît Roux, PhD, professor of biochemistry and molecular biology at the University of Chicago and senior fellow at the Computation Institute.

Potassium channels, present in the cells of virtually living organisms, are core components in bioelectricity generation and cellular communication. Required for functions such as neural firing and muscle contraction, they serve as common targets in pharmaceutical development.


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Forest of synthetic pyramidal dendrites grown using Cajal's laws of neuronal branching (Wikimedia Commons)

Forest of synthetic pyramidal dendrites grown using Cajal’s laws of neuronal branching (Wikimedia Commons)

Trauma surgeons know how to fix gunshot wounds, lacerations and broken bones. It’s what comes afterwards that really worries them. Even after the initial injury is treated, patients are at risk for secondary issues such as infection, sepsis and organ failure. While the biological pathways involved in these processes have been well studied and characterized, effective interventions to reliably stop the dangerous cascade have yet to be discovered.

“It was very frustrating for me to not have the drugs and tools necessary to fix what I thought was actually going wrong with those patients,” said trauma surgeon and CI senior fellow Gary An, in his University of Chicago Alumni Weekend UnCommon Core talk. “Often we know what will happen, but we have no way to stop it.”

The current fashionable approach to such intractable problems in medicine and other fields is Big Data, where answers hiding in massive datasets will be uncovered by advanced analytic methods. But quoting Admiral Ackbar, An warned the audience that this approach alone “is a trap,” generating a multitude of correlations and hypotheses that don’t always translate into real world applications.

“What it wants to appeal to is magic…if you can get enough data and a big powerful computer, an answer will magically appear,” said An, an associate professor of surgery at University of Chicago Medicine. “That’s fine if you want to diagnose or characterize. But if we want to engineer interventions to be able to manipulate systems, we need to have presumptions of mechanistic causality; we need to be able to test hypotheses.”


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