Structural and mechanistic divergence in LL-37, HNP-1, and Magainin-2: An integrated computational and biophysical...

Escalating antimicrobial resistance necessitates the development of alternative therapeutics that circumvent conventional enzymatic and efflux-based defence systems. Antimicrobial peptides (AMPs) represent a compelling class of innate immune effectors, however, their clinical translation is hindered by incomplete mechanistic understanding of how structural organization and conformational dynamics shape antimicrobial function. In this study, we performed an integrated comparative analysis of three mechanistically representative AMPs-LL-37, HNP-1, and magainin-2-to resolve how maturation pathways, fold topology, amphipathic architecture, and dynamic target engagement govern antimicrobial action. Consensus secondary-structure prediction, AlphaFold2/PEP-FOLD modelling, and physicochemical profiling revealed three distinct structural signatures. LL-37 exhibited a flexible disorder-to-helix transition enabling adaptive, curvature-driven membrane dissolution, HNP-1 adopted a rigid cysteine-stabilized β-sheet that promotes lipid clustering and entropic inhibition of membrane-associated enzymes, and magainin-2 formed a stable amphipathic α-helix optimized for toroidal pore initiation. Machine-learning classification corroborated strong antimicrobial likelihood for HNP-1 and magainin-2, with LL-37 displaying context-dependent activation. Protein-peptide docking and normal-mode elastic network modelling further demonstrated the possibility of LL-37 allosterically dampening conformational cycling of the MexB efflux pump, HNP-1 restricting catalytic-loop mobility in LpxC, and magainin-2 enhancing correlated β-barrel breathing in OprF to promote pore formation. These findings delineate three mechanistically distinct antimicrobial strategies-adaptive membrane dissolution, rigid pore-stacking inhibition, and dynamic pore initiation-linked directly to peptide structural organization. This framework provides a rational basis for mechanism-guided AMP optimization and the engineering of next-generation membrane-active therapeutics with reduced resistance susceptibility.