Stay up to date with notifications from The Independent

Notifications can be managed in browser preferences.

Scientists use AI to discover new antibiotic against deadly hospital superbug

‘AI methods afford us the opportunity to vastly increase the rate at which we discover new antibiotics’

Vishwam Sankaran
Friday 26 May 2023 06:08 BST
Comments
Related video: Strep Throat is Becoming Antibiotic-Resistant

Your support helps us to tell the story

From reproductive rights to climate change to Big Tech, The Independent is on the ground when the story is developing. Whether it's investigating the financials of Elon Musk's pro-Trump PAC or producing our latest documentary, 'The A Word', which shines a light on the American women fighting for reproductive rights, we know how important it is to parse out the facts from the messaging.

At such a critical moment in US history, we need reporters on the ground. Your donation allows us to keep sending journalists to speak to both sides of the story.

The Independent is trusted by Americans across the entire political spectrum. And unlike many other quality news outlets, we choose not to lock Americans out of our reporting and analysis with paywalls. We believe quality journalism should be available to everyone, paid for by those who can afford it.

Your support makes all the difference.

Scientists have discovered a new antibiotic using artificial intelligence that could be used against deadly hospital-bourne, treatment-resistant infections.

The process developed by the researchers, including those from McMaster University in Canada, could pave the way for discovering new antibiotics to treat many other challenging bacteria.

In the study, published in the journal Nature Chemical Biology, scientists sought to urgently develop new drugs to treat Acinetobacter baumannii – classified as one of the world’s most dangerous drug-resistant bacteria, according to the WHO.

The bacterium is known to cause pneumonia, meningitis, and infect wounds – all of which may also lead to death.

It has been found in hospital settings, where it lingers on surfaces for long periods.

Previous studies have also found that the pathogen is able to pick up antibiotic-resistance genes from other bacteria.

However, developing new antibiotics against A baumannii using conventional chemical screening trials has been challenging since traditional methods are time-consuming and costly.

In the new study, scientists used AI to predict previously unknown classes of antibacterial molecules and identified a new compound that they have named abaucin.

Using AI algorithms, researchers have been able to assess hundreds of millions, possibly billions, of molecules with antibacterial properties.

“This work validates the benefits of machine learning in the search for new antibiotics,” study lead author Jonathan Stokes said in a statement.

“Using AI, we can rapidly explore vast regions of chemical space, significantly increasing the chances of discovering fundamentally new antibacterial molecules,” Dr Stokes said.

Scientists believe the new compound abaucin is promising as it only targets A baumannii.

Since most antibiotics have a broad spectrum activity affecting all bacteria, they may disrupt the body’s helpful gut bacteria and open the door to serious infections, including by the deadly C difficile.

Targeting A baumannii with the new drug could make it less likely to rapidly develop drug resistance and help create new precise and effective treatments, researchers say.

“We know algorithmic models work, now it’s a matter of widely adopting these methods to discover new antibiotics more efficiently and less expensively,” James J Collin, another author of the study, said.

“AI methods afford us the opportunity to vastly increase the rate at which we discover new antibiotics, and we can do it at a reduced cost. This is an important avenue of exploration for new antibiotic drugs,” Dr Stokes added.

Join our commenting forum

Join thought-provoking conversations, follow other Independent readers and see their replies

Comments

Thank you for registering

Please refresh the page or navigate to another page on the site to be automatically logged inPlease refresh your browser to be logged in