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Software predicted development of bacterial resistance
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A protein design algorithm may be able to predict antibiotic resistance in bacteria, according to data recently published in Proceedings of the National Academy of Sciences.
"For certain pathogens such as Staphylococcus and HIV, there are databases or libraries of resistance mutations," Bruce R. Donald, PhD, of the departments of computer science and biochemistry at Duke, told Infectious Disease News. "One might be able to predict what would happen in the future by looking up what had happened in the past.
"But for new drugs it is possible the pathogen will select mutations that have not been seen before. That is where protein design algorithms can be useful."
Researchers from Duke University and the University of Connecticut developed a program called OSPREY to identify DNA sequence changes that would block the effects of novel drugs. To measure the ability of their software, the teams compared resistance mutations that came from treating MRSA with experimental propargyl-linked antifolates with those predicted by OSPREY.
“If we can somehow predict how bacteria might respond to a particular drug ahead of time, we can change the drug, or plan for the next one, or rule out therapies that are unlikely to remain effective for long,” Pablo Gainza-Cirauqui, MS, a doctoral candidate at Duke University, said in a press release.
Using OSPREY’s algorithm, the researchers identified four single-nucleotide polymorphisms that would confer resistance to the dihydrofolate reductase enzymes targeted by the antifolates. More than half of the surviving MRSA colonies treated with the drug carried the predicted mutation, which had never been reported in previously published studies, reducing the treatment’s effectiveness by up to 58-fold.
Bruce R. Donald
“The fact that we actually found the new predicted mutations in bacteria is very exciting,” Donald said in the press release. “This gives us a window into the future to see what bacteria will do to evade drugs that we design before a drug is deployed.”
The OSPREY software is open source, and available for anyone to use. – Dave Muoio
Disclosure: The researchers report no relevant financial disclosures.
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