Synthetic antibiotic could help turn the tide against drug-resistant pathogens

A new antibiotic synthesized at Rockefeller University and derived from computer models of bacterial gene products appears to neutralize even drug-resistant bacteria. The compound called Silagine works well in mice and uses a new mechanism to attack MRSA. C difference.and some other deadly pathogens, according to a published study Science.

The results show that a new generation of antibiotics can be obtained from computer models. “It’s not just a great new molecule, it’s a validation of a new approach to drug discovery,” says Sean F. Brady of Rockefeller. “This work is an example of computational biology, genetic sequencing and synthetic chemistry coming together to unlock the secrets of bacterial evolution.”

Act on the infinities of bacterial warfare

Bacteria have spent billions of years developing unique ways to kill each other, so it’s perhaps not surprising that many of our most powerful antibiotics are derived from bacteria themselves. With the exception of penicillin and a few other essential substances derived from fungi, most antibiotics were first weaponized by bacteria to fight other bacteria.

“Ages of evolution have given bacteria unique ways to engage in combat and kill other bacteria before their enemies develop resistance,” says Professor Evnin and Brady, director of the Laboratory of Genetically Engineered Small Molecules. The discovery of antibiotics was once largely made up of scientists. streptomyces or bacillus in the lab and bottling up its secrets to cure human diseases.

But with the rise of antibiotic-resistant bacteria, new active compounds are urgently needed – and easy-to-use bacteria may be running out. However, numerous antibiotics lurk in stubborn bacterial genomes that are difficult or impossible to study in the laboratory. “Many antibiotics come from bacteria, but most bacteria cannot be grown in a lab,” says Brady. “It appears that most antibiotics are probably running out. »

An alternative method advocated by the Brady lab for the past fifteen years is to find antibacterial genes in soil and grow them in lab-friendly bacteria. But even this strategy has its limits. Most antibiotics are derived from genetic sequences enclosed in bacterial gene clusters called biosynthetic gene clusters, which act as a unit to collectively encode a number of proteins. However, these clusters are often inaccessible with current technologies.

“Bacteria are complex, and just because we can sequence a gene doesn’t mean we know how to make the bacteria work to produce proteins,” says Brady. “There are thousands of uncharacterized gene clusters and we’ve never figured out how to activate some of them.”

A new pool of antibiotics

Frustrated by the inability to unlock so many bacterial gene groups, Brady and his colleagues turned to algorithms. By breaking down genetic instructions into a DNA sequence, modern algorithms can predict the structure of antibiotic-like compounds that a bacterium with those sequences would produce. Organic chemists can then take this data and synthesize the predicted structure in the lab.

It’s not always a perfect guess. “The molecule we finally get is what these genes would produce in nature most likely, but not necessarily,” Brady says. “We’re not worried if it’s not completely true – we just need the synthetic molecule close enough to act in the same way as the naturally occurring compound.”

Postdoctoral partners Zonggiang Wang and Bimal Koirala from the Brady lab began by searching a large genetic sequence database for promising bacterial genes that had not been studied before, which are thought to be involved in killing other bacteria. In this context, the “cilium” gene cluster, which has not yet been discovered, attracted attention with its proximity to other genes involved in antibiotic production. The researchers duly fed their respective sequences into an algorithm that came up with a handful of compounds likely to generate it. A compound appropriately called silagsin has been shown to be an active antibiotic.

Cilagicin reliably killed Gram-positive bacteria in the lab, did not damage human cells, and (when chemically optimized for use in animals) successfully treated bacterial infections in mice. Of particular interest, silagen was potent against several drug-resistant bacteria, and even when threatened against bacteria that had been specifically cultured to resist silage, the synthetic compound prevailed.

Brady, Wang, Koirala and colleagues determined that silagin works by binding two molecules, C55-P and C55-PP, both of which help protect bacterial cell walls. Existing antibiotics such as bacitracin bind to one of these two molecules, but not both, and bacteria can often resist these drugs by attaching a cell wall to the remaining molecule. The team suspects that silagen’s ability to separate the two molecules may create an insurmountable barrier that prevents resistance.

Silagisin is still a long way from human trials. In follow-up studies, the Brady lab will perform further synthesis to optimize the compound and test it against a wider variety of pathogens in animal models to determine which diseases it might be most effective in treating.

However, beyond silagine’s clinical implications, the study demonstrates an evolutionary method that researchers can use to discover and develop new antibiotics. “This study is a great example of what can be found hidden in a gene cluster,” Brady says. “We now believe we can unlock a large number of new natural compounds through this strategy, which we hope will provide an exciting new pool of drug candidates.”

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