AI Helps Scientists Discover New Antibiotics After 60 Years
The advent of artificial intelligence in recent years has led to significant scientific discoveries and advancements, some of which include drug discovery and development, astronomy and space exploration, material science, and even neuroscience and brain research. The use of AI as a rather powerful tool for scientific research has not only revolutionized some scientific fields but also revitalized them. One such case is the new antibiotics, which are the first discovery in the field in the past 60 years, made by AI technology.
Namely, the use of AI proved to be a massive game changer when it comes to medicine, and the technology has now helped researchers develop a new antibiotic for a drug-resistant staphylococcus aureus (MRSA) bacterium.
The insight AI learning models provided to the researchers regarding predictions about certain molecules and their use in antibiotics seems far more valuable.
This new compound is now capable of eradicating a drug-resistant bacteria responsible for killing thousands of people worldwide each year, and it has the potential to become a turning point in the fight against antibiotic resistance. Still, this doesn’t mean that the current research into bacteriophages is therapy for combating multidrug-resistant bacteria.
Interestingly enough, AI antibiotics are the first new discovery in the field of antibiotics, which faces numerous challenges that contribute to its near-stagnation. Some of these challenges are completely scientific because bacteria are capable of rapidly developing resistance to known antibiotics, and this resistance typically spreads faster than the development of new antibiotics.
The AI pinpointed antibiotic compounds that are capable of effectively combating the targeted microbes with minimal harm to the human body.
Difficulties in discovering new compounds and our limited understanding of bacterial complexity are also contributing factors.
But perhaps the biggest discovery is the one overshadowed by media headlines about the new AI antibiotic. The insight AI learning models provided to the researchers regarding predictions about certain molecules and their use in antibiotics seems far more valuable, as it provided a more time and resource-efficient framework that was previously unavailable to the researchers.
To paraphrase, in this case, the AI provided both the fish and the fishing lessons to researchers, completely revitalizing the research and development of new antibiotics.
The team behind this extensively enlarged deep learning model provided an expanded dataset on approximately 39,000 compounds, which were evaluated for their antibiotic activity against MRSA in order to create the training data.
Not only that, but both the resulting data and details regarding chemical structures were also input into the model, and three additional deep-learning AI models were introduced to the research and trained to assess not only the antibiotic compounds’ effectiveness but also their toxicity on three distinct types of human cells.
By cross-referencing the toxicity data predictions with the previously determined antimicrobial activity, the AI pinpointed antibiotic compounds that are capable of effectively combating the targeted microbes with minimal harm to the human body.
This new compound is now capable of eradicating a drug-resistant bacteria responsible for killing thousands of people worldwide each year.
The creation of training data alone required scanning of 12 million commercially available compounds, which artificial intelligence sorted into five different classes that exhibited predicted antibiotic activity against MRSA based on the chemical substructure.
As a result, the researchers acquired 280 of the resulting compounds for testing against MRSA in laboratory testing, with two promising AI antibiotic candidates from the same class already being identified. Further experiments on mice showed that both MRSA skin and MRSA systematic infections were reduced by a factor of 10. Apparently, a new dawn breaks over antibiotics research.
Source: EurekaAlert!
