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Math Techniques Developed to Aid HIV Drug Discovery

Meghan Bellows-Peterson and Christodoulos Floudas (Frank Wojciechowski, Princeton Univ.)

Meghan Bellows-Peterson and Christodoulos Floudas have developed a way to use mathematical models for discovering new drugs. (Frank Wojciechowski, Princeton Univ.)

Researchers at Princeton University in New Jersey, and Johns Hopkins University School of Medicine in Baltimore, Maryland have developed mathematical methods for discovering new drugs for HIV and eventually for a range of diseases. Their results were published in a recent issue of Biophysical Journal.

The new methods forecast the effectiveness of potential medicines by computations of physical properties of their biological molecules. This process 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 researchers’ technique adapts concepts from optimization theory, a field of mathematics that focuses on calculating the best option among a number of choices. The process adds in ideas from computational biology, which is a synergy of mathematics, statistics, and computer science for biology research.

In applying the techniques to HIV, the Princeton team of engineering professor Christodoulos Floudas and doctoral student Meghan Bellows-Peterson (pictured right) searched for 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.

Floudas notes, however, that this mathematical approach has potential well beyond HIV. “The power of this is that it’s a general method,” says Floudas. “It has proven successful in finding potential peptides to fight HIV, but it should also be effective in searching for drugs for other diseases.”

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