It is widely known that genetic mutations cause disease. What are largely unknown are the mechanisms by which these mutations wreak havoc at the molecular level, giving rise to clinically observable symptoms in patients. Now a new study using bioinformatics, led by scientists at the Buck Institute for Age Research, reports the ability to predict the molecular cause of many inherited genetic diseases. These predictions involve tens of thousands of genetic disease-causing mutations and have led to the creation of a web-based tool available to academic researchers who study disease. The research is due to be published online in the February 9, 2010 edition of Human Mutation.
"We now have a quantitative model of function using bioinformatic methods that can predict things like the stability of the protein and how its stability is disrupted when a mutation occurs," said Buck Institute faculty member Sean Mooney, PhD, who led the research team. "Traditionally people have used a very time consuming process based on evolutionary information about protein structure to predict molecular activity," Mooney said, "I think we're the first group to really quantitatively describe the universe of molecular functions that cause human genetic disease."
The research was done in the contexts of inherited single gene diseases, complex diseases such as cardiovascular and developmental disorders and mutations in cancerous tumors. The study focused on amino acid substitutions (AAS), which are genetically driven changes in proteins that can give rise to disease, and utilized a series of complex mathematical algorithms to predict activity stemming from the mutations.
As a first step, researchers used available databases of known sites of protein function and built mathematical algorithms to predict new sites of protein function said Mooney. They then applied the algorithms to proteins that have disease-associated mutations assigned to them and loo
|Contact: Kris Rebillot|
Buck Institute for Age Research