The novel antibiotic targets IBD, and AI predicted how it would work before scientists prove it

Researchers from McMaster University and the Massachusetts Institute of Technology (MIT) made two scientific breakthroughs at once. Not only did they discover the latest antibiotics targeting inflammatory bowel disease (IBD), they also managed to use a new type of AI to accurately predict how drugs work. To their knowledge, this is the first global for AI.

More in Journal Natural MicrobiologyThis discovery uncovers promising new treatment options for millions of people affected by Crohn's disease and other related conditions, and introduces important new applications of AI in drug discovery research.

“This work shows that, as far as AI-inducing agents are discovered, it still hurts the surface,” said Jon Stokes, assistant professor in the Department of Biochemistry and Biomedical Sciences at McMaster and lead investigator of the new study.

“The development of new drugs designed to target IBD has been quickly tracked thanks to the collaboration between human and generator AI.”

Antibiotics for IBD

Most of the antibiotics used in clinics today are “broad spectrum” drugs. This means wiping away good bacteria in addition to those that cause disease.

This can result in a type of bacteria that is invasive with invasive, resistant bacteria that migrate and colonize into the intestine, which can worsen the condition, like clones.

However, enterolin, a new antibiotic discovered in McMaster, is a “narrow spectrum” drug that spars the microbiota and attacks only certain groups of bugs that cause disease.

This means not only killing E. coli, but also reducing the chances of drug-resistant strains colonizing the intestines in the first place.

“This new drug is a very promising treatment candidate for the millions of patients living with IBD,” Stokes said. “We don't currently have treatments for these conditions, so developing something that could mean symptoms could help people experience a higher quality of life.”

How do drugs work? Ask AI

Until now, AI has been used as a tool to predict which molecules are likely to be treated, but in this study it was used to explain what researchers call “mechanism of action” (MOA), or what drugs attack disease.

“AI has accelerated the speed at which new drug candidates can explore the chemical space, but up until now, it has rarely alleviated the major bottlenecks of drug development that these new drug candidates understand what they are doing,” explains Stokes.

According to him, MOA research is essential for drug development. They help scientists to check safety, optimize doses, make modifications to improve efficacy, and uncover all-new drug targets. It also helps regulators determine whether a particular drug candidate is suitable for human use.

But they are also highly famous and slow.

Stokes says that thorough MOA research takes up to two years and costs around $2 million. However, using AI, his group did Enterolin in just six months, for just $60,000.

Indeed, after his lab discovered a new antibiotic, Stokes, who connected with colleagues at MIT's Computer Science and Artificial Intelligence Lab (CSAIL), saw whether any of their emerging machine learning platforms would help him quickly track his upcoming MOA research.

In just 100 seconds, he was given a prediction. His new drug attacked a microscopic protein complex called LOLCDE, which is essential for the survival of certain bacteria.

“Many use of AI in drug discovery has been about searching the chemical space, and identifying new molecules that could be active,” says Regina Barzilay, MIT's engineering professor and developer of AI models that made predictions.

“What we're showing here is that AI can provide a mechanical explanation, which is important for moving molecules through the development pipeline.”

Barzilay was recently listed as Time Magazine's most influential people on AI.

Stokes emphasizes that while predictions are intriguing, it is exactly that and a prediction. He still has to do traditional MOA research in the lab.

“We can't assume that these AI models are completely correct right now, but the concept of them being correct has stripped the speculation from our next step,” explains Stokes, a member of McMaster's Michael G. Degroote Institute for Infectious Disease Research Institute.

His team then began investigating Enterolin's MOA, led primarily by McMaster's graduate student Dennis Catactan, using MIT's predictions as a starting point.

Within just a few months it was clear that AI was actually right.

“We did all the standard MOA work-ups to verify the predictions to see if the experiment backs up AI. A Stokes Lab candidate. “Doing that in this way cuts a year and a half from our regular timeline.”

This allows Stokes to use AI to discover viable drug candidates, quickly track global drug discovery efforts, and determine how new drugs work. But if you ask him, he will tell you that – it was as it is – is merely a means of end.

“Drug resistance and our lack of new drugs are leaky faucets,” he says. “You can leave it for a while, but in the end there's a big problem. AI is my wrench. It's a tool to fix leaks before it gets flooded. It's really that. My only focus is taking new medications to patients who need them.

Stokes spin-out company Stokes spin-out company Stoked Bio has already approved enterolin from McMaster and is currently optimising it for human use.

The company is also testing modified versions of new antibiotics against other drug-resistant bacteria, such as Klebsiella, and early results are promising.

“The identification of enterolin highlights the notable science that appears in McMaster,” said Jeff Skinner, CEO of Stoked Bio. “We are proud to partner with the university by translating this breakthrough into actual therapy for our patients.”

If everything goes well, Stokes says the new drug will be ready for human testing within three years. His research team is eager to meet.

“It's surreal to work on translations like this,” says Kataktan. “The fact that what we discover in our lab might one day help patients is truly amazing and really reinforces the importance of our work.”