Researchers from Stanford Medicine and McMaster University have developed an AI model called SyntheMol that can design entirely new molecules, including potential antibiotics. This model has generated six novel drugs aimed at killing resistant strains of Acinetobacter baumannii, one of the leading pathogens responsible for antibacterial resistance-related deaths.
SyntheMol was trained on a library of “molecular building blocks” and chemical reactions. They included data on which chemicals currently work against Acinetobacter baumannii as a guideline. According to Stanford, the model “generated around 25,000 possible antibiotics and the recipes to make them in less than nine hours.”
Initially, SyntheMol was a bit too imaginative, creating compounds that couldn’t feasibly exist, so researchers added guardrails. The results were much more realistic. To ensure the bacteria wouldn’t become resistant to these new recipes, researchers filtered out compounds that were similar to currently effective antibiotics.
“Now we have not just entirely new molecules, but also explicit instructions for how to make those molecules,” Zou said.
Researchers narrowed down SyntheMol’s suggested compounds for viability. Chemical company was able to create 58 compounds in a lab. Six were able to kill a resistant strain of the bacteria when tested, and two have moved forward to testing stages in mice.
The new compounds also showed promise in fighting other infectious bacteria that can become antibiotic-resistant, including E. coli, MRSA, and those that can cause meningitis and pneumonia.
The researchers are currently tweaking SyntheMol and working with other teams to see if the model can also be used for discovering possible heart disease drugs.
