Algorithm Accelerates Search for New Antibiotics

Hosein Mohimani, assistant professor in Carnegie Mellon University's Computational Biology Department, said the research found "that the antibiotics produced by microbes are much more diverse than had been assumed." The results can aid the fight against antibiotic resistance.

Carnegie Mellon reported last week that team of American and Russian computer scientists has developed an algorithm that rapidly searches databases to identify novel variants of known antibiotics, which can aid the fight against antibiotic resistance, Byron Spice wrote in a release on the university's website.

The release explained that, in only a few hours, the VarQuest algorithm "identified 10 times more variants of peptidic natural products, or PNPs, than all previous PNP discovery efforts combined," as the team reported in the latest issue of the journal Nature Microbiology. It drastically reduces the time to conduct such a search, which previously might have taken hundreds of years of computation, said Hosein Mohimani, assistant professor in Carnegie Mellon University's Computational Biology Department.

"Our results show that the antibiotics produced by microbes are much more diverse than had been assumed," he added, saying VarQuest found more than a thousand variants of known antibiotics.

Mohimani and Pavel A. Pevzner, a professor of computer science at the University of California, San Diego, designed and headed the work with colleagues at St. Petersburg State University in Russia. The release says the U.S. National Institutes of Health and the Russian Science Foundation supported their research.

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