MIT researchers have discovered a new class of antibiotics using artificial intelligence to treat infections caused by drug-resistant bacteria.
The researchers showed that these compounds could kill methicillin-resistant Staphylococcus aureus (MRSA) — a drug-resistant bacterium — that causes more than 10,000 deaths in the United States every year. It directly caused more than 100,000 deaths in 2019.
Use of AI in discovering new antibiotics
Researchers used a type of artificial intelligence (AI) known as deep learning to discover a new class of antibiotic candidates. A team at the laboratory of James Collins of the Broad Institute of the Massachusetts Institute of Technology (MIT) and Harvard University used deep learning to screen millions of compounds for antibiotic activity.
“The insight here was that we could see what was being learned by the models to make their predictions that certain molecules would make for good antibiotics,” James Collins, the Termeer Professor of Medical Engineering and Science in MIT’s Institute for Medical Engineering and Science (IMES) and one of the study’s authors, said. “Our work provides a framework that is time-efficient, resource-efficient, and mechanistically insightful, from a chemical-structure standpoint, in ways that we haven’t had to date.”
“Our work identifies a new class of antibiotics, one of the few in 60 years, that complements these other antibiotics,” he says.
Over the past several years, Collins and his colleagues in MIT’s Abdul Latif Jameel Clinic for Machine Learning in Health have been using deep learning to find new antibiotics. Their work has yielded potential drugs. These compounds were identified using deep learning models that sift through millions of other compounds, generating predictions of which ones may have strong antimicrobial activity.
Testing in mice showed that the new antibiotic compounds proved promising treatments for MRSA. The compounds also showed very low toxicity against human cells, making them good drug candidates.
MRSA, which infects more than 80,000 people in the U.S. every year, often causes skin infections or pneumonia. MRSA is a Gram-positive bacterium, with thicker cell walls.
Felix Wong, a postdoc at IMES and the Broad Institute of MIT and Harvard, said that the team has “pretty strong evidence that this new structural class is active against Gram-positive pathogens by selectively dissipating the proton motive force in bacteria.” He asserted that the molecules attack bacterial cell membranes selectively in a way that does not incur substantial damage in human cell membranes. They added that this new structural class of antibiotics is not toxic to human cells.
Antibiotic Resistance Crisis
AI’s use in discovering a new class of antibiotics can treat infections caused by drug-resistant bacteria. This could be a major win in the battle against antimicrobial resistance (AMR), which scientists and public health bodies around the world a global challenge have warned is the next great health crisis and a “silent pandemic”.
- WHO has estimated that some 4.9 million deaths annually are associated with AMR.
- A 2022 Lancet study found that in 2019, 1.27 million deaths – including 860,000 in Africa – were the direct result of drug-resistant bacterial infections.
- AMR is considered one of the top ten global public health threats to humanity in the 21st century.
Drug resistance, also known as AMR, occurs when bacteria, viruses, fungi, and parasites change over time and no longer respond to medicines.
Since the 1960s, bacteria and other microorganisms have become increasingly resistant to antimicrobial drugs, leading to more and more people dying. This is mainly due to the misuse and overuse of these drugs.
Having been introduced over 80 years ago, antibiotics revolutionized healthcare and saved millions of lives. However, the widespread use of these “wonder drugs” now poses a significant threat to the global health systems due to the spread of antibiotic-resistant bacteria.
This critical situation amounts to a silent pandemic. No new antibiotic classes have emerged for decades, since the ‘golden age’ of antibiotic discovery (1940s-1960s), leading to efficacy decline and antibiotic resistance ensued. This health emergency emphasizes the critical need for innovative solutions and new medicines.
