Reseachers use statistical analysis to discover weakness in HIV/AIDS strain.
The research adds weight to a provocative hypothesis—that an HIV vaccine should avoid a broadside attack and instead home in on a few targets. Indeed, there is a rare group of patients who naturally control HIV without medication, and these “elite controllers” most often assail the virus at precisely this vulnerable area.
The study was conducted at the Ragon Institute, a joint enterprise of Massachusetts General Hospital, the Massachusetts Institute of Technology and Harvard University. The institute was founded in 2009 to convene diverse groups of scientists to work on HIV/AIDS and other diseases.
To find the vulnerable sectors in HIV, Drs. Chakraborty and Dahirel reached back to a statistical method called random matrix theory, which has also been used to analyze the behavior of stocks. While stock market sectors are already well defined, the Ragon researchers didn’t necessarily know what viral sectors they were looking for. Moreover, they wanted to take a fresh look at the virus.
So they defined the sectors purely mathematically, using random matrix theory to sift through most of HIV’s genetic code for correlated mutations, without reference to previously known functions or structures of HIV. The segment that could tolerate the fewest multiple mutations was dubbed sector 3 on an HIV protein known as Gag.
Dr. Walker’s team found that even immune systems that fail to control HIV often attack sector 3, but they tend to devote only a fraction of their resources against it, while wasting their main assault on parts of the virus that easily mutate to evade the attack. That suggested what the study’s authors consider the paper’s most important hypothesis: A vaccine shouldn’t elicit a scattershot attack, but surgical strikes against sector 3 and similarly low-mutating regions of HIV.
Ah, why am I not surprised?
Math is the backbone to explaining how real world applications work, so utilizing it to find a vaccine or cure for the HIV strain yield results scientists never expected to see.