Finding the low hanging fruit in Antibiotics.

A new CMU algorithm can help thwart antibiotic resistance

Antibiotic resistance represents a modern medical challenge as big-gun drugs become less effective, and even ineffective, against deadly bacterial ...

From article, (Antibiotic resistance represents a modern medical challenge as big-gun drugs become less effective, and even ineffective, against deadly bacterial infections.

In response, Carnegie Mellon University, the University of California San Diego and St. Petersburg State University in Russia combined forces to develop a biological search engine — an algorithm named VarQuest — to expand the arsenal of non-resistant antibiotics with new discoveries.

Microbes throughout nature produce such antibiotic compounds to kill competing organisms. PNPs, in particular, have been used to create the most powerful antibiotics in medicine, including such drugs as vancomycin and daptomycin. But their effectiveness has diminished due to resistance, which involves bacteria changing or mutating to survive exposure to such drugs.

 As it turns out, more than 200 researchers over the years have produced “a gigantic amount of data — a billion possible data points — that could serve as molecular fingerprints of potentially new antibiotic medications,” said Mr. Mohimani, who holds a Ph.D. in computational biology.

But those variants remained well hidden in the data.

With VarQuest, the team was able to pre-process databases to enable the Google-like search that discovered 1,000 variants of the 100 known PNP compounds. Such variants can involve differences of only a few extra atoms of hydrogen and carbon — enough to thwart bacterial resistance, he said. 

The major natural antibiotic compounds were discovered long ago and represented “the low-hanging fruit.” Finding new ones has become more costly and time-consuming. 

“Five or six years ago,” Mr. Mohimani said, “researchers in the community of antibiotic discovery realized they have to coordinate their efforts to make sure that they are not doing redundant work, and at the same time, sharing valuable data collected from different parts of the earth.” 

As a result, the new social network of scientists shares databases that include “fingerprints of molecules” of variants that the new algorithm found — a process that would have taken hundreds of years of computation to discover under previous methods.

Consider the entire Library of Congress disorganized with books randomly stacked and no way to find any specific one. In that context, VarQuest essentially organized and indexed the entire library in a matter of hours.

In a word of caution, Mr. Mohimani said, turning these variants into safe, effective drugs still can take a decade or longer, given the high costs of drug development and testing, and U.S. Food and Drug Administration requirements. 

Still, VarQuest “is going to play the same role in the field of natural products that a Google search would play for users.”)

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