Using mathematical concepts, Princeton researchers have developed a method of discovering new drugs for a range of diseases by calculating which physical properties of biological molecules may predict their effectiveness as medicines.
The technique already has identified several potential new drugs that were shown to be effective for fighting strains of HIV by researchers at Johns Hopkins University.
"The power of this is that it's a general method," said Princeton chemical and biological engineering professor Christodoulos Floudas, who led the research team. "It has proven successful in finding potential peptides to fight HIV, but it should also be effective in searching for drugs for other diseases."
Floudas, the Stephen C. Macaleer '63 Professor in Engineering and Applied Science, and Princeton engineering doctoral student Meghan Bellows-Peterson collaborated on the study with researchers at the Johns Hopkins University School of Medicine. Their findings were reported in the Nov. 17, 2010, issue of Biophysical Journal.
The researchers' technique combines concepts from optimization theory, a field of mathematics that focuses on calculating the best option among a number of choices, with those of computational biology, which combines mathematics, statistics and computer science for biology research.
In the case of HIV, the challenge for the Princeton team was to find peptides -- the small chains of biologically active amino acids that are the basic building blocks of proteins -- that could stop the virus from infecting human cells.
"The Princeton researchers have a very sophisticated way of selecting peptides that will fit a particular binding site on an HIV virus," said collaborator Robert Siliciano, a professor of medicine at Johns Hopkins and a 1974 Princeton graduate, who specializes in the treatment of HIV. "It narrows the possibilities, and may reduce the amount of time and resources it takes
|Contact: Chris Emery|
Princeton University, Engineering School