Next-Generation Antimicrobial Peptide for Biofilm-Associated Infections: Engineering, Biomaterial Delivery and AI-Assisted Discovery

Antimicrobial peptides (AMPs) are increasingly regarded as next-generation antimi-crobial agents because of their broad-spectrum activity, rapid killing, antibiofilm po-tential, immunomodulatory properties, and mechanisms of action that differ from those of many conventional antibiotics. Most AMPs are short, cationic, and amphipathic molecules that interact with negatively charged microbial envelopes. However, their biological activities extend beyond membrane disruption and include intracellular targeting, immune modulation, endotoxin neutralization, and interference with biofilm formation. Despite these advantages, the clinical translation of AMPs remains limited by proteolytic instability, hemolysis or cytotoxicity, poor pharmacokinetics, salt and serum sensitivity, production costs, and delivery challenges. The AMP field is now shifting from natural peptide discovery toward integrated engineering pipelines that combine rational peptide modification, biomaterial-based delivery, high-throughput screening, and artificial in-telligence/machine learning (AI/ML). Chemical and structural modifications, including D-amino acid substitution, cyclization, lipidation, PEGylation, terminal amidation, hy-drocarbon stapling, hybridization, sequence truncation, metal coordination and immo-bilization onto biomaterials, are being used to improve stability, potency, selectivity, antibiofilm activity, and tissue localization. In parallel, AI/ML approaches now enable the large-scale mining of microbiomes, extinct proteomes, venom-derived sequences, and de novo peptide sequence space. Recent predictive, generative, and optimization-based AI/ML approaches now accelerate AMP discovery by mining large biological datasets, identifying cryptic antimicrobial sequences, generating de novo peptide candidates, and optimizing multiple properties, including potency, selectivity, stability, toxicity, and synthesizability. This focused review summarizes recent advances in AMP research, highlights engineering strategies used to endow AMPs with improved biological and pharmacological properties and discusses how AI/ML is reshaping antimicrobial peptide discovery in the context of antimicrobial resistance.