Overcoming LPS-mediated resistance in gram-negative pathogens: a review of LL-37 analogs and computational design...

The increasing incidence of antimicrobial resistance (AMR) in Gram-negative bacteria has become a significant global health issue, driven primarily by the structural and adaptive characteristics of lipopolysaccharide (LPS) in the outer membrane. As a robust permeability barrier, LPS limits the entry of various antimicrobial agents; furthermore, adaptive alterations to the chemical configuration of lipid A and related compounds augment bacterial resistance to both conventional antibiotics and host defense peptides. The human cathelicidin LL-37, a prominent endogenous antimicrobial peptide, has attracted considerable interest for its potent antibacterial activity, high affinity for LPS, membrane-disrupting capabilities, and immunomodulatory functions. However, the direct therapeutic application of LL-37 is constrained by stability, toxicity, and cost-related challenges. Extensive research has focused on developing structurally diverse LL-37 analogs to overcome these limitations. Through rational sequence engineering, truncation, residue substitution, cyclization, and amphipathic optimization, researchers aim to augment antibacterial efficacy while minimizing host toxicity. This review comprehensively encapsulates the molecular diversity of LL-37 analogs and examines their structure-activity relationships (SAR), with a focus on charge distribution, helicity, hydrophobicity, selectivity, and LPS-binding efficiency. Special attention is given to analogs engineered to circumvent LPS-mediated resistance in multidrug-resistant Gram-negative pathogens. Moreover, we highlight recent progress in computational techniques-such as structure prediction, molecular docking, molecular dynamics (MD) simulations, and artificial intelligence-assisted design that facilitate the identification of critical interaction hotspots and expedite peptide optimization. A previously unrecognized computational gap is also noted: five of nine clinically relevant LL-37 analogs have never been the subject of a molecular dynamics simulation study, and none of the analogs has been targeted to gram negative outer membrane model containing lipopolysaccharide. This gap limits the mechanistic understanding of LL-37 based design strategies against Gram-negative bacteria. Ultimately, integrating molecular diversity with computational engineering establishes a solid foundation for developing next-generation LL-37-derived therapeutics characterized by enhanced stability, safety, and efficacy in the global effort to combat antibiotic resistance. To address these limitations we propose a conceptual computational pipeline, including sequence generation, physicochemical screening, structure prediction, molecular docking, and MD simulation, for prospective next-generation LL-37 analog development.