The immune system responds to disease-causing microbes called pathogens by making antibodies to destroy the invaders. Vaccines also trigger this infection-fighting ability by stimulating the production of antibodies. But developing an effective vaccine is time-consuming and costly, in part because scientists have a hard time predicting how pathogens and antibodies will interact.
Now, biochemist Robert Woods, Ph.D., of the University of Georgia in Athens has developed a computer simulation model that can be used to predict such interactions. The new tool may help scientists create customized vaccines that protect against a wide range of infections.
Most antibodies that protect us from bacterial infections work by reacting with carbohydrate, or "sugar," chains located on a microbe's cell surface. Sugar chains are complicated, bendy structures that often flop about, making it difficult for scientists to see the sites where antibodies grip. As a result, despite best efforts, vaccines sometimes don’t recognize a given pathogen, or they may react with an unintended target, like a healthy human cell.
In a recent study, Woods tried to predict why antibodies to two very similar bacteria don’t cross-react, despite the fact that the pathogens’ cell surfaces differ only by a single sugar molecule. Woods’ computer model revealed that the extra sugar on one of the bacterial coats caused the carbohydrate chain that it is part of to curl up like a corkscrew, which is easily recognized by an antibody. The uncurled sugar chain on the other microbe goes unseen by that antibody.
Woods plans to use his model to simulate interactions with other microbial menaces, such as the bacterium that causes meningitis.
This page last reviewed on
8/9/2018 5:28 PM
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