Prior to the UCSD team's findings, which are published in the September 16 issue of the journal Science, many scientists expressed doubts that a computational approach could represent the intricate mechanisms through which cells respond to outside signals. However, the researchers report that their computer model accurately predicts particular behaviors of living cells. They also 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
"Our computational approach revealed how the same set of proteins produce physiologically different outputs in response to only subtly different inputs," explained Alexander Hoffmann, an assistant professor of chemistry and biochemistry, who led the team. "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."
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.
The researchers chose the NF-kappaB proteins because there is a wide body of prior research that they were able to draw on to set the initial parame
Contact: Sherry Seethaler
University of California - San Diego