18 February 2009—A computer program may eventually hold the key in the never-ending struggle between evolving bacteria and the drugs we use to kill them.
Researchers from Duke University have designed software that can simulate modifications to an enzyme used to make a common antibiotic. Mutating genes that produce the enzyme will make for slightly different variants of the drug. The researchers say this technique could eventually be used to design new variants of existing antibiotics to which bacteria have built up resistance. The results were detailed this week in the Proceedings of the National Academy of Sciences .
The study is a good first step in ”either developing cheaper methods of making antibiotics or developing slightly different antibiotics,” says George Makhatadze, professor of biology, chemistry, and chemical biology at Rensselaer Polytechnic Institute, in Troy, N.Y., who is not affiliated with the study.
New antibiotics are sorely needed because of bacteria’s growing resistance to older drugs. According to the U.S. Food and Drug Administration, about 70 percent of infection-causing bacteria found in hospitals are resistant to at least one common antibiotic. And doctors at the University of Texas Medical School estimated in the January 2009 New England Journal of Medicine that in 2003, more than half of the staph infections found in hospitals were resistant to multiple antibiotics. But designing new antibiotics is difficult. The enzymes that are involved in making the drugs are very specific, so introducing a small mutation can completely change the resulting drug’s function.
The Duke computer program helps because it quickly sorts through all the many possible mutations that could alter an enzyme and then predicts which mutations would yield an enzyme most likely to produce an antibiotic effective against a drug-resistant bacterial strain. The resulting antibiotics would still need to be tested against the bacteria.
The software relies on what’s called an epsilon approximation algorithm, a type of function that yields solutions guaranteed to be within a certain percentage of the optimal solution. That percentage can be controlled by the user to produce more or less precise results. The Duke team redesigned enzymes so that they were guaranteed to be within 97 percent of an ideal model.
Bruce Donald, who led the Duke team, says their work is akin to changing one step in an assembly line. ”If you think of the enzyme as a machine that takes in square parts and punches holes in them, we want to change the enzyme so that it will take in star-shaped parts and punch holes in them,” he says.
However, the enzyme’s end product isn’t the whole story, points out Arieh Warshel, chemistry and biochemistry professor at the University of Southern California. He says that it is also important to consider the rate at which the enzyme produces a drug, which is typically slower in redesigned enzymes. This problem is not unique to the Duke study but rather inherent in computer-aided enzyme-design programs, he adds.
Donald acknowledges that improving the algorithm to increase the rate of reaction would be an interesting goal, but he does not think that it is the sole measure of success. Julie Mitchell, assistant professor of biochemistry and mathematics at the University of Wisconsin, agrees with Donald and says there is often a trade-off between speed and specificity. Mitchell likens the enzyme to a key: It can be a master key that opens every door, a key that opens a suite of doors, or a key that opens one door. The more specific the key is, the longer it will take to open a door.
The next step, says Donald, is improving the algorithm and working with enzymes that make different types of antibiotics. He says they have started working with the enzymes that make vancomycin. Vancomycin is the antibiotic of last resort for the bacteria that causes staph infections. The bacteria has developed resistance to several other antibiotics and has been of particular concern in hospitals.
About the Author
Monica Heger is a writer based in New York City. She wrote about the use of unmanned aerial vehicles in combating Somali pirates in the February 2009 issue of IEEE Spectrum .