Proteome-Scale Mining and Multi-Objective Prioritization of Encrypted Antimicrobial Peptides with Experimental Validation

Encrypted antimicrobial peptides (eAMPs) represent a hidden reservoir of bioactive compounds within larger proteins. A new study unveiled a robust multi-layer proteome-mining framework to uncover and rank these elusive eAMPs from a vast pool of 95%-identical bacterial protein sequences. The strategy involved three distinct extraction routes, each targeting specific peptide formation sites, ultimately generating a staggering 29.25 million unique peptide candidates.

Further refinement was achieved by combining dual AMP prediction tools with Macrel to narrow the candidate pool to 3.25 million consensus sequences. The final prioritisation process split into two complementary streams: one emphasizing low-haemolysis to isolate selective candidates, and another retaining haemolytic sequences for mechanistic comparison. Of the 185 selected candidates, 18 passed rigorous structural review and membrane-activity screening.

To validate their antimicrobial potential, three sequence-matched eAMP representatives were subjected to experimental testing. Computational simulations revealed that GEAMP_71c139393ac596b5 exhibits robust water-phase stability and the ability to deeply insert into membranes, while GEAMP_12ffb5d589c8cb1b demonstrated remarkable activity against both E. coli and S. aureus.

At concentrations ranging from 8 to 128 µM, GEAMP_12ffb5d589c8cb1b achieved log10 reductions of 1.52 and 2.27, respectively, outperforming the control condition. These findings provide a traceable sequence-to-structure-to-function pathway, linking large-scale eAMP discovery with high-throughput evaluation and experimental validation.