Chris Adami, professor of microbiology and molecular genetics at Michigan State University, found that, in patients who have never taken medications to treat HIV, the virus’ proteins don’t evolve. However, patients who were on anti-viral drugs saw their viral proteins evolve quickly, and in a very particular way.
Using information about the protein sequences of patients who are taking anti-viral medications, Adami and Aditi Gupta, coauthor and postdoctoral researcher at Rutgers Medical School, found that continued exposure to drugs limits the changes to the viral proteins, making continued evolution more difficult.
“You think of evolution as always finding a way. But we found instead that when an organism must adapt quickly, the fast way to adapt may doom your long-term adaptive potential,” Adami says.
A protein’s structure can be thought of as a set of beads connected with ties. To change, either the beads or the ties must change. The team found that when a protein needs to adapt quickly, it does so by introducing new ties and rearranging the existing ones, as opposed to just changing the beads. However, the new ties eventually “tie down” the protein, making further changes all the more difficult. If tied down sufficiently, the protein’s evolution must drastically slow down.
By studying the evolution of a particular viral protein for ten years, the team was able to observe precisely how the protein changes. “We show that HIV has successfully adapted to stronger and stronger medications over the years,” Gupta says. “It takes a lot of money and time to develop new and better drugs, yet the virus can evolve drug-resistance in a matter of months, if not weeks.”
HIV evolution might be the answer to addressing the problem of drug-resistance and to increase the longevity of available drugs, Adami adds.
“We may one day be able to introduce new drugs strategically to purposefully tie down the protein. Thus, research on slowing down evolution may become as important as finding out how to accelerate evolution,” he says.
The paper appears in PLOS Genetics.
Source: Michigan State University
This article was originally published on futurity.org.