Researchers have developed a peptide named CIT8 using machine learning to combat Acinetobacter baumannii, a pathogen classified by the WHO as a critical priority threat. The peptide consists of a 13-amino acid chain identified by an algorithm from a database of over 14,000 antimicrobial compounds. Initial research focused on Staphylococcus aureus before the discovery of its efficacy against A. baumannii.
In laboratory tests, CIT8 reduced bacterial counts to undetectable levels in under 15 minutes at a concentration of 20 mcg/ml, outperforming the reserve antibiotic polymyxin B. The peptide functions by damaging the bacterial cell membrane, causing a loss of electrical potential and the leakage of ATP. Computer modeling confirmed that specific amino acid substitutions strengthened the peptide's helical structure.
The study also demonstrated that CIT8 enhances the effectiveness of meropenem, an antibiotic that previously lost potency against resistant strains. By compromising the outer membrane, the peptide allows the antibiotic to reach its targets more effectively. Laboratory trials showed no toxicity to human skin or kidney cells at concentrations 32 times higher than the therapeutic dose.
A modified version, CIT8-D, showed stronger inhibition of bacterial biofilms but exhibited a narrower safety window. Researchers are now preparing to evaluate the stability of the peptide in biological fluids and its performance in living organisms. Preclinical trials are required to confirm the safety and efficacy of the treatment for human use.
