Scientists used artificial intelligence to identify a new antibiotic that might be useful to fight a deadly drug-resistant bacteria commonly found in hospitals and medical offices. The study has just been published in the journal Nature Chemical Biology. The newly discovered drug – Abaucin is a narrow-spectrum antibiotic that is effective against Acinetobacter baumannii, a superbug that is resistant to many antibiotics. Abaucin works by inhibiting the transport of lipoproteins, which are essential for the growth and survival of bacteria. It has now also been shown to be safe in animal studies

Abaucin was developed by a team of researchers led by James J. Collins at the MIT Jameel Clinic and Jonathan Stokes at McMaster University. The team used an artificial intelligence algorithm to screen thousands of compounds for potential antibiotic activity. Abaucin was one of the compounds that was identified by the algorithm.

Abaucin works by inhibiting lipoprotein transport, which is essential for bacterial growth. It is a narrow-spectrum antibiotic, which means that it is only effective against a few types of bacteria. This makes it less likely to cause resistance to develop. Abaucin is still in the early stages of development, but it has the potential to be a valuable new tool for treating infections caused by Acinetobacter baumannii.

“There’s a lot of trepidation around AI and I genuinely understand it,” said Jonathan Stokes, lead author on the paper and an assistant professor of biomedicine and biochemistry at at McMaster University in Ontario, Canada. “When I think about AI in general, I think of these models as things that are just going to help us do the thing we’re going to do better.“

According to a report by USA Today, Stokes teamed up with researchers from the Broad Institute of MIT and Harvard to screen for potential antibiotics to use on Acinetobacter baumannii, a superbug that can cause infections in the blood, urinary tract and lungs. This bacteria usually invades hospitals and healthcare settings, infecting vulnerable patients on breathing machines, in intensive care units and undergoing operations.

This type of bacteria, resistant to the potent antibiotic carbapenem, infected 8,500 in hospitals and killed 700 in 2017, according to the Centers for Disease Control and Prevention.

Stokes said the lab team developed AI models to predict which ones would have the highest likelihood of antimicrobial activity, narrowing the field to 240 drugs or active ingredients. Researchers then narrowed the field again through testing before discovering a molecule RS102895, renamed abaucin, that appeared to be potent against the superbug.

“It’s important to remember right when we’re trying to develop a drug, it doesn’t just have to kill the bacterium,” Stokes said. “It also has to be well tolerated in humans and it has to get to the infection site and stay at the infection site long enough to elicit an effect.”

Researchers said they can screen a much larger volume of potential drugs by using machine-learning techniques. The study said while existing high-throughput screening can evaluate a few million drugs or chemical ingredients at once, algorithms developed from machine learning can assess “hundreds of millions to billions” of drug molecules.

There are other examples of AI being used to develop new drugs:

– –  Exscientia is a pharmaceutical company that uses AI to design new drugs. The company has developed several drugs that are now in clinical trials, including a drug for Alzheimer’s disease and a drug for cancer.
– –  Insilico Medicine is another pharmaceutical company that uses AI to develop new drugs. The company has developed several drugs that are now in preclinical trials, including a drug for Parkinson’s disease and a drug for HIV.
– –  Atomwise is a company that uses AI to design new drugs for infectious diseases. It has developed several drugs that are now in preclinical trials, including a drug for malaria and a drug for tuberculosis.
– –  BenevolentAI is a company that uses AI to develop new drugs for rare diseases. It has developed several drugs that are also now in preclinical trials, including a drug for Duchenne muscular dystrophy and a drug for cystic fibrosis.

These are just a few examples of the many companies that are using AI to develop new drugs. AI has the potential to revolutionize the drug discovery process, and it could help to develop new treatments for a wide range of diseases.