A new antibiotic able to fight against resistant bacteria.
Antibiotics have long been considered a miracle cure for bacterial infections. However, many pathogens have evolved to be resistant to antibiotics over time, and the search for new drugs is therefore becoming more urgent. Researchers from the University of Basel were part of an international team that used computer analysis to identify a new antibiotic and decipher its mode of action. Their research is an important step in creating powerful new drugs.
The WHO calls the growing number of antibiotic-resistant bacteria a “silent pandemic”. The situation is made worse by the fact that there have not been many new drugs introduced to the market over the past few decades. Even now, not all infections can be adequately treated and patients are still at risk of harm from routine procedures.
New active substances are urgently needed to stop the spread of antibiotic-resistant bacteria. A significant discovery was recently made by a team led by researchers from Northeastern University in Boston and Professor Sebastian Hiller from the Biozentrum at the University of Basel. The results of this research, which was part of the “AntiResist” project of the National Research Center (PRN), were recently published in Natural microbiology.
The researchers discovered the new antibiotic Dynobactin through a computer screening approach. This compound kills Gram-negative bacteria, which include many dangerous and resistant pathogens. “The search for antibiotics against this group of bacteria is far from trivial,” says Hiller. “They are well protected by their double membrane and therefore offer few attack possibilities. And over millions of years of evolution, bacteria have found many ways to make antibiotics harmless.
Just last year, Hiller’s team deciphered the mode of action of the newly discovered peptide antibiotic Darobactin. The knowledge acquired was incorporated into the process of selecting new compounds. The researchers used the fact that many bacteria produce antibiotic peptides to fight each other. And that these peptides, unlike natural substances, are encoded in the bacterial genome.
“The genes of these peptide antibiotics share a characteristic,” explains co-first author Dr. Seyed M. Modaresi. “According to this feature, the computer systematically screened the entire genome of those bacteria that produce such peptides. This is how we identified Dynobactin. In their study, the authors demonstrated that this new compound is extremely effective. Mice with life-threatening sepsis caused by resistant bacteria survived the severe infection by administering Dynobactin.
By combining different methods, the researchers were able to solve the structure as well as the mechanism of action of Dynobactin. This peptide blocks the bacterial membrane protein BamA, which plays an important role in the formation and maintenance of the outer protective bacterial envelope. “Dynobactin sticks to BamA from the outside like a plug and prevents it from doing its job. Thus, the bacteria die,” explains Modaresi. nevertheless has the same target on the bacterial surface. That, we did not expect at the start.
A boost for antibiotic research
At the molecular level, however, scientists have found that Dynobactin interacts with BamA differently than Darobactin does. By combining certain chemical characteristics of both, potential drugs could be further improved and optimized. This is an important step on the way to an effective drug. “Computerized screening will give a new impetus to identifying the antibiotics we urgently need,” says Hiller. “In the future, we want to expand our research and study more peptides for suitability as antimicrobial drugs.”
Reference: “Computational Identification of a Systemic Antibiotic for Gram-negative Bacteria” by Ryan D. Miller, Akira Iinishi, Seyed Majed Modaresi, Byung-Kuk Yoo, Thomas D. Curtis, Patrick J. Lariviere, Libang Liang, Sangkeun Son , Samantha Nicolau, Rachel Bargabos, Madeleine Morrissette, Michael F. Gates, Norman Pitt, Roman P. Jakob, Parthasarathi Rath, Timm Maier, Andrey G. Malyutin, Jens T. Kaiser, Samantha Niles, Blake Karavas, Meghan Ghiglieri, Sarah EJ Bowman, Douglas C. Rees, Sebastian Hiller and Kim Lewis Natural microbiology.
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