Targeting ESKAPE pathogens with AI-designed antimicrobial peptide - Abstract: The increasing prevalence of ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) poses a critical global health threat, particularly with the emergence of resistance to last-resort antibiotics such as vancomycin, colistin, and carbapenems. This situation underscores the urgent need for innovative therapeutic strategies. Antimicrobial peptides (AMPs) have emerged as promising alternatives to conventional antibiotics, yet their clinical development has been hindered by challenges such as cytotoxicity, instability, and high production costs. Our previous work identified a short synthetic peptide, RR, effective against MRSA, but limited in activity against Gram-negative bacteria. To address this, we developed optimized derivatives, RR4 and its D-enantiomer, D- RR4, which showed superior potency against Gram-negative and Gram-positive pathogens and demonstrated effectiveness under challenging physiological conditions such as high salt concentrations and acidic pH. D-RR4 also exhibited superior protection in animal models of infection. However, pharmacokinetic challenges persist, necessitating further optimization. This project aims to integrate artificial intelligence (AI), machine learning, chemical approaches, and computational tools to optimize these peptides for combating ESKAPE infections. Our three specific aims are: 1) To optimize peptide potency and safety through AI-guided structure-based sequence screening, improving pharmacokinetics and minimizing toxicity; 2) To evaluate the in vivo efficacy of optimized peptides in systemic animal models, including septicemic peritonitis and VRE rat endocarditis models; 3) To assess bactericidal efficacy and wound healing in a biofilm-infected diabetic pressure ulcer model. These studies aim to advance novel antimicrobial peptide therapies, offering new treatment options for antibiotic- resistant infections, and potentially revolutionizing the management of ESKAPE pathogens.
