MIT Researchers' Computer Model Pinpoints Multiple Genes In Disease Process

The computer model called NetworKIN pores through existing research data to pinpoint protein networks that control cellular function.
Researchers at the Massachusetts Institute of Technology have developed a computational model to study how enzymes regulate proteins, a step on the path to discovering proteins' part in diseases such as cancer.

The university announced Tuesday that the findings will be on Friday's cover of Cell. Researchers at the Samuel Lunenfeld Research Institute of Mount Sinai Hospital in Canada and the European Molecular Biology Laboratory in Germany developed the model, called NetworKIN, which pores through existing research data to pinpoint protein networks that control cellular function.

Michael Yaffe, MIT associate professor of biology and biological engineering, a member of MIT's Center for Cancer Research, and one of the paper's authors, said in a statement that NetworKIN allows researchers to map the information.

The model focuses on enzymes, called kinases, which are involved in cell signaling pathways, including DNA repair, MIT said in a statement. Kinases add a phosphate group to a protein for instruction. Yaffe said that 30% to 50% of the proteins in a cell are phosphorylated at any given time. Mass spectrometry allows scientists to figure out where phosphorylation occurs, but scientists lacked the means to figure out which kinases act on each site, Yaffe said.

"It's a huge bottleneck," said Yaffe, who also is affiliated with the Broad Institute of MIT and Harvard, and Beth Israel Deaconess Medical Center. "We're getting thousands of phosphorylation sites, but we don't know which kinase phosphorylated them, so we don't know what pathway to put them in."

Researchers used two existing computer programs that can analyze amino acid sequences of phosphorylation sites and predict which group of kinases is most likely to bind to it and cause phosphorylation. Then they developed a computational model to analyze databases of information about signaling pathways and protein interactions. The program also mines the text of published articles and abstracts for reported protein-kinase interactions.

By combining two sources of information, the computational model can develop a detailed network that would be very difficult to create by manually examining the available data, MIT researchers explained.

"The sequence gets us into the ballpark, but it's all of this contextual information that helps us figure out specifically which kinases are acting on which sites," Yaffe said.

Rune Linding, a postdoctoral fellow with joint appointments through the CCR and Mount Sinai, said the network-wide view allows scientists to more easily target multiple aberrant genes. "In the future, complex human diseases will be treated by targeting multiple genes," he said in a statement.

Funding for the project came from the European Commission FP6 Programme, the Danish Research Council for the Natural Sciences, the Lundbeck Foundation, Genome Canada, and the National Institutes of Health. Other authors of the paper include Gerald Ostheimer, a postdoctoral fellow in biological engineering; Marcel van Vugt, a postdoctoral fellow at the Center for Cancer Research; and Leona Samson, director of the Center for Environmental Health Sciences and professor of biology and biological engineering, all from MIT.