In silico prediction and mass spectrometric characterization of botanical antimicrobial peptides

Antimicrobial peptides (AMPs) are promising compounds for the treatment of antibiotic-resistant bacteria and are found across all organisms, including plants. Unlike most antibiotics, AMPs tend to act on more generalized and multiple targets, making development of resistance more difficult. Conventional approaches toward AMP identification include bioactivity-guided fractionation and genome mining. Complementary methods leveraging bioactivity-guided fractionation, cysteine motif-guided in silico AMP prediction, and mass spectrometric approaches can be combined to expand botanical AMP discovery. Herein, we present an integrated workflow which serves to streamline implementation toward a robust botanical AMP discovery pipeline.