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"Researchers ... have made two scientific breakthroughs at once: they not only discovered a brand-new antibiotic that targets inflammatory bowel diseases (IBD), but also successfully used a new type of AI to predict exactly how the drug works. To their knowledge, this is a global first for the AI. ...
Most antibiotics used in clinics today are "broad-spectrum" drugs, meaning they wipe out good bacteria in addition to those that cause disease ...
But enterololin, the new antibiotic discovered ... is a "narrow-spectrum" drug, meaning it spares the microbiome and attacks only a specific group of disease-causing bugs—in this case, a family of bacteria called Enterobacteriaceae, which happens to include E. coli. ...
thorough MOA [mechanism of action] study can take up to two years and cost around $2 million; however, using AI, his group did enterololin's in just six months and for just $60,000. ...
In just 100 seconds, he was given a prediction: his new drug attacked a microscopic protein complex called LolCDE, which is essential to the survival of certain bacteria. ..."
"... DiffDock, a generative AI model ...
DiffDock was designed to predict how small molecules fit into the binding pockets of proteins, a notoriously difficult problem in structural biology. Traditional docking algorithms search through possible orientations using scoring rules, often producing noisy results. DiffDock instead frames docking as a probabilistic reasoning problem: a diffusion model iteratively refines guesses until it converges on the most likely binding mode.
“In just a couple of minutes, the model predicted that enterololin binds to a protein complex called LolCDE, which is essential for transporting lipoproteins in certain bacteria,” ...
put that prediction to the test. Using DiffDock predictions as an experimental GPS, they first evolved enterololin-resistant mutants of E. coli in the lab, which revealed that changes in the mutant’s DNA mapped to lolCDE, precisely where DiffDock had predicted enterololin to bind.
They also performed RNA sequencing to see which bacterial genes switched on or off when exposed to the drug,
as well as used CRISPR to selectively knock down expression of the expected target. These laboratory experiments all revealed disruptions in pathways tied to lipoprotein transport, exactly what DiffDock had predicted. ..."
From the abstract:
"Current clinical antibiotics are largely broad-spectrum agents that can alter the gut microbiome and promote colonization by Enterobacteriaceae, which are often drug resistant. This includes adherent-invasive Escherichia coli (AIEC), particularly in patients with inflammatory bowel disease, in which dysbiosis creates a niche for this pathogen to colonize. There is an urgent and unmet need for novel narrow-spectrum and microbiome-sparing antibiotics.
Here we screened 10,747 bioactive small molecules for antibacterial activity against AIEC and discovered enterololin, an antibacterial compound with targeted activity against Enterobacteriaceae species. Enterololin could overcome intrinsic and acquired resistance mechanisms in clinical isolates when combined with a subinhibitory concentration of SPR741, a polymyxin B analogue used here to increase outer membrane permeability in Gram-negative bacteria.
Molecular substructure- and deep learning-guided mechanism-of-action investigations revealed that enterololin perturbs lipoprotein trafficking through a mechanism involving the LolCDE complex, laboratory-evolved resistant mutants predominantly mapped to lolC and lolE, with an in vitro frequency of resistance of ~10−8 to 10−7.
Enterololin showed low mammalian cytotoxicity (HEK293 half-maximal inhibitory concentration ~100 µg ml−1) and suppressed AIEC infection in mouse models when administered in combination with SPR741, while largely preserving the overall microbiome composition.
This study highlights the utility of deep learning methods for predicting molecular interactions and identifies a promising Enterobacteriaceae-specific antibacterial candidate for further development."
Researchers discover new antibiotic for IBD — and AI correctly predicts how it works (original news release) "McMaster researchers have discovered an antibiotic that targets inflammatory bowel diseases like Crohn’s. Then, in a first, they used cutting-edge AI to determine how it would work."
AI maps how a new antibiotic targets gut bacteria (original news release) "MIT CSAIL and McMaster researchers used a generative AI model to reveal how a narrow-spectrum antibiotic attacks disease-causing bacteria, speeding up a process that normally takes years."
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