Matt Clarke/McMaster University
Denise Catacutan, a graduate student at McMaster University, helped identify the new antibacterial compound.
Using artificial intelligence, researchers say they have found a new type of antibiotic that works against a particularly threatening and drug-resistant bacterium.
When they tested the antibiotic on the skin of mice experimentally infected with the superbug, it checked the bacteria’s growth, suggesting the method could be used to create suitable antibiotics to fight other drug-resistant pathogens. medications.
The researchers also tested the antibiotic against 41 different strains of antibiotic-resistant bacteria. Acinetobacter baumannii. The drug worked on all of them, although it needs to be further refined and tested in human clinical trials before it can be used in patients.
Additionally, the compound identified by the AI worked in a way that only blocked the problematic pathogen. It does not appear to kill the many other species of beneficial bacteria that live in the gut or on the skin, making it a rare and narrowly targeted agent.
If more antibiotics worked precisely, the researchers said, it could prevent the bacteria from becoming resistant in the first place.
The study was published in the journal Nature Chemical Biology.
“It’s incredibly promising,” said Dr. Cesar de la Fuente, assistant professor at the University of Pennsylvania’s Perlman School of Medicine, who also uses AI to find new treatments but was not involved in the new research.
De la Fuente says this kind of approach to finding new drugs is an emerging area that researchers have been testing since around 2018. It drastically reduces the time it takes to sift through thousands of promising compounds.
“I think AI, as we’ve seen, can be applied successfully in many areas, and I think drug discovery is sort of the next frontier.”
For the study, the researchers focused on the bacterium Actinetobacter baumanii. It hangs around hospitals and other health care facilities, clinging to surfaces like doorknobs and countertops. Because it’s able to scavenge bits of DNA from other organisms it comes into contact with, it can incorporate their best weapons: genes that help them resist the agents doctors use to treat them.
“It’s what we in the lab call an occupational pathogen,” said Jon Stokes, one of the researchers and assistant professor of biochemistry and biomedical sciences at McMaster University in Hamilton, Ont.
This species causes skin, blood or respiratory infections that are difficult to treat. The United States Centers for Disease Control and Prevention stated in 2019 that Acinetobacter baumanii the infections were “in dire need” of new types of antibiotics to treat them.
A recent study of hospitalized patients with Actinetobacter baumanii infections resistant even to powerful carbapenem antibiotics found that one in four patients died within a month of diagnosis.
For the new study, Stokes and the lab teamed up with researchers from MIT’s Broad Institute and Harvard. First, they used a technique called high-throughput drug screening to grow Acinetobacter baumanii in lab dishes and spent weeks exposing those colonies to more than 7,500 agents: drugs and active drug ingredients. They found 480 compounds that blocked the growth of bacteria.
They fed this information into a computer and used it to train an artificial intelligence algorithm.
“Once we’ve trained our model, what we can do is start showing this model brand new images of chemicals it’s never seen, right? And on based on what he had learned during the training, he would predict for us whether these molecules were antibacterial or not,” Stokes said.
They then sifted the model through more than 6,000 molecules, which Stokes said the AI was able to do in a matter of hours.
They narrowed the search down to 240 chemicals, which they tested in the lab. Lab tests helped them narrow down the list to nine of the bacteria’s best inhibitors. From there, they took a closer look at the structure of each, eliminating those they thought were dangerous or related to known antibiotics.
They ended up with a compound, called RS102895, which Stokes said was originally developed as a potential treatment for diabetes.
He says it seems to work in a completely new way, by preventing components of the bacteria from moving from inside the cell to its surface.
“It’s a rather interesting mechanism and one that’s not seen among clinical antibiotics as far as I know,” he said.
Additionally, he said, RS102895 — which the researchers renamed abaucin — only works on Actinetobacter baumanii.
Stokes says most antibiotics are broad-spectrum agents, working against many species of bacteria. Broad-spectrum antibiotics exert strong selection pressure on many types of bacteria, causing many to evolve rapidly and share genes that help them resist the drug and survive.
“With this molecule, because it only works very potently against Actinetobacter, it doesn’t impose this universal selective pressure, so it won’t spread resistance as quickly,” he said.