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Could predictive software defeat drug-resistant bacteria?

From reprogramming bacteria to self-destruct to eliminating movement of antibiotic resistance between cells, researchers continue to advance a campaign against "superbugs" such as methicillin-resistant Staphylococcus aureus (MRSA).

The latest weapon in that battle might be a computer algorithm known as K* (pronounced "K-star"), which is capable of predicting MRSA's next move, according to findings published yesterday in the Proceedings of the National Academy of Sciences.

Popular Science reports:

The team modeled mutations in an MRSA enzyme called dihydrofolate reductase [DHFR], 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.

The K* algorithm helped the researchers find DHFR mutation candidates that would be able to block new antibiotics. This knowledge could be incorporated into a drug-design strategy -- anticipating how bacteria would mutate to fight antibiotics, and designing antibiotics around those predicted mutations.

Study authors intend to provide their algorithm freely and publish the open-source software they devised, according to a Duke release.

Previously: Norway's strategy for fighting drug-resistant bacteria and Slate takes on the battle against bacteria

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