Proteome-Mining and Chemical Activation of Hidden Bioactive Fragments as Antimicrobial Assemblies

Proteolytic processing of precursor proteins liberates
bioactive
fragments, yet the systematic discovery of such peptides remains challenging.
Here, we establish a fragment-mining strategy that combines in silico
prediction with chemical tailoring to generate self-assembling antimicrobial
peptides directly from protein sequences, including previously unannotated
proteins. Self-assembly proved integral to activity: amphiphilic modification
promoted nanonet formation and efficient bacterial membrane disruption,
while rational glycosylation reprogrammed physicochemical properties
to confer selectivity for bacterial phosphatidylglycerol over mammalian
phosphatidylcholine, thereby broadening the therapeutic window. The
optimized peptide, C16-KA6-Glc, displayed broad-spectrum
bactericidal activity, superior biofilm eradication, and negligible
resistance development. In murine models of thigh and pneumonia infection,
C16-KA6-Glc achieved therapeutic efficacy comparable to
that of conventional antibiotics while also attenuating inflammatory
responses. These findings demonstrate a generalizable approach to
translating latent proteome fragments into de novo self-assembling peptide therapeutics with clinical potential.