An interdisciplinary team of biochemists and computer scientists at the University of California, San Diego (UCSD), has developed a specialized software to explain how some proteins can play different roles in a wide range of cellular processes. This software approach was previously seen as unable to reveal these hidden conversations within cells. This computer model uses 70 differential equations to predict how some chemicals can affect the behavior of a protein. It helped them to discover that cells are using signals to communicate, like a phone carries information about conversations. This computer model could lead to new treatments for cancer and other diseases that involve failures in cell communication.
Let's start with a quote from Alexander Hoffmann, an assistant professor of chemistry and biochemistry at UCSD.
Our computational approach revealed how the same set of proteins produce physiologically different outputs in response to only subtly different inputs. This is the first step toward developing drugs that interfere with one of the pathological functions of the proteins, but leave the healthy functions intact. For example, many current cancer drugs dramatically reduce immune function. Computer modeling should make it possible to design anti-cancer drugs that do not weaken patients' immune systems.
Below is an illustration showing how "cells use the timing of signals to communicate, similar to the way a telephone wire carries information about conversations (Credit: Alexander Hoffmann, UCSD). Here is a link to a larger version.
So how was this computer model designed?
The computer model comprises 70 equations to account for the behavior of five proteins and three RNA molecules in the "NF-kappaB signaling pathway," which regulates genes involved in cancer, inflammation, immune function and cell death. Each equation takes into account a different parameter, such as how quickly a protein is synthesized, or how quickly it is degraded.
These proteins were chosen because the initial parameters of the models were easy to set, thanks to prior research. And, of course, the researchers compared their model's predictions with experimental results. Apparently, the computer model is working fine. Here is one example.
The model revealed why two natural chemicals have opposite physiological effects. When exposed to one of the chemicals, the proteins create positive feedback that lengthens the amount of time they are active. When exposed to the other chemical, they initiate negative feedback, which shuts them down rapidly.
Besides accurately predicting the behavior of living cells, how useful will be this computer model?
[The researchers] believe that the model has important practical applications, including guiding the design of better treatments for cancer and other diseases that involve failures in cell communication.
This research work has been published by Science under the name "Stimulus Specificity of Gene Expression Programs Determined by Temporal Control of IKK Activity" (Volume 309, Number 5742, Pages 1857-1861, September 16, 2005 Issue). Here is a link to the abstract.
Sources: Sherry Seethaler, University of California, San Diego, September 15, 2005; and various web sites
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