Most antibiotics target metabolically active bacteria, but with artificial intelligence, researchers can efficiently screen compounds that are lethal to dormant microbes.

These compounds can kill methicillin-resistant Staphylococcus aureus (MRSA), a bacterium that causes deadly infections.

SMART researchers find the enzyne RlmN, which directly senses chemical and environmental stresses, can be targeted in drug development.

SMART researchers combine rifaximin and clarithromycin to effectively restore the latter drug's efficacy.

The machine-learning algorithm identified a compound that kills Acinetobacter baumannii, a bacterium that lurks in many hospital settings.

Developed at SMART, the therapy stimulates the host immune system to more effectively clear bacterial infections and accelerate infected wound healing.

Study finds computer models that predict molecular interactions need improvement before they can help identify drug mechanisms of action.

Using this diagnostic, doctors could avoid prescribing antibiotics in cases where they won’t be effective.

Mixing drugs into oil-based gels could offer relief for children and adults who have trouble swallowing pills.

Microbes that safely break down antibiotics could prevent opportunistic infections and reduce the spread of antibiotic resistance.