Blocked Bacteria: Researchers discover a new target against tuberculosis

Laura Gödl and Lina Riegler-Berket, together with a team led by Monika Oberer, have discovered a new target for attacking tuberculosis. Photo: University of Graz/Leljak.

Researchers at the University of Graz have deciphered the structure of an enzyme that enables “dormant” tuberculosis bacteria to survive. For the first time, they have now identified a compound that disrupts the bacteria’s fat metabolism in this state. These discoveries could pave the way for shorter and more effective therapies against the infectious disease.

Each year, more than one million people worldwide die from tuberculosis — the infectious disease that claims more lives than any other. Treatment lasts at least six months and often fails because patients discontinue the lengthy antibiotic regimen, leading to dangerous resistances. The bacteria are particularly difficult to treat when they “hide” in granulomas. “Granulomas are tiny protective capsules formed by our immune system when it cannot completely eliminate pathogens. Inside them, the bacteria retreat and enter a kind of dormant state. In this hideout, they are hard for drugs to reach,” explains molecular biologist Lina Riegler-Berket.

Blocked in their sleep

This is precisely where a current study comes in: The research team at the University of Graz, together with international partners and the biotech company Innophore, has identified an enzyme that tuberculosis bacteria need for their fat metabolism during this resting phase. “In addition, we have discovered a drug candidate that blocks this enzyme while the bacteria are in their ‘sleeping’ state. This small step subsequently disrupts the entire fat metabolism of the bacterium, thereby reducing its ability to survive,” says Riegler-Berket. The research findings could form the basis for revising existing antibiotics, with the goal of shortening treatment durations in the future.

Artificial intelligence as a key factor

A decisive role in the study was played by the collaboration with the company Innophore. The firm, a spin-off from the University of Graz, used AI-based analyses to investigate the similarities between the bacterial enzyme and its human counterpart. This made it possible to rule out early on that potential compounds would cause unwanted side effects in humans. “AI can help us filter from billions of possible molecular structures those that might fit best — a step that significantly accelerates our research,” the scientist explains.

Publication:

M. tuberculosis meets European Lead Factory – Identification and structural characterization of novel Rv0183 inhibitors using X-ray crystallography. Riegler-Berket, Lina and Gödl, Laura et al. Disease and Therapeutics. 1 (2025): 100002. DOI: 10.1016/j.dist.2025.100002

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