To Fight Drug-Resistant MRSA, Algorithm Predicts Bacteria's Future Mutations

MRSA This colorized scanning electron micrograph depicts a grouping of methicillin resistant Staphylococcus aureus (MRSA) bacteria. CDC via Wikimedia Commons

Success in chess is all about anticipation -- you have to plan your moves by guessing what your opponent will do. Now scientists are taking a page from Bobby Fischer's book to fight a wily foe: drug-resistant staph bacteria, which stymies drug therapies with its swift mutation strategy. Researchers led by Bruce Donald, a professor of computer science and biochemistry at Duke University, are using a computer algorithm to predict MRSA's next move.

Some bacteria, including MRSA (methicillin-resistant Staphylococcus aureus), evolve mutations to change the shape of the active site of their enzymes, which is what antibiotics are after. The algorithm, called K* (pronounced K-star), tries to anticipate those changes.

The team modeled mutations in an MRSA enzyme called dihydrofolate reductase, which is targeted by several drugs. Almost every living thing has a version of DHFR, because it helps turn folic acid into thymidine, the "T" among the DNA nucleotides.

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Technology, Rebecca Boyle, algorithms, antibiotic-resistant bacteria, antibiotics, drug-resistance, drugs, enzymes, mrsa, mutations, staphylococcus aureus

When the team studied the mutant enzymes, they realized their structures were one reason why they were able to evade antibiotics, according to a Duke news release.

Donald's team has also studied using the K* algorithm to diagnose cancer and to design enzymes that could improve antibiotics' efficacy.

[PhysOrg]