Designing and identifying β-hairpin peptide macrocycles with antibiotic potential

Area of Science:

• Medicinal Chemistry
• Biotechnology
• Drug Discovery

Background:

• Peptide macrocycles are promising therapeutics, but their design, particularly for β-hairpin structures, is challenging due to folding and aggregation issues.
• Developing structured antimicrobial peptides requires overcoming inherent design complexities.

Purpose of the Study:

• To develop a synthetic strategy for designing and discovering structured macrocyclic peptides.
• To identify key biochemical features contributing to the antimicrobial activity of β-hairpin peptides.

Main Methods:

• Proteomic analysis and common antimicrobial features were used to design a large peptide library.
• An activity-driven high-throughput screen identified potent antimicrobial peptides.
• Machine learning analyzed the biochemical features of active peptides.

Main Results:

• Dozens of peptides were identified that kill bacteria via selective membrane disruption.
• Active peptides exhibit a unique constrained structure and high cationic charge, particularly arginine in the turn region.
• A synthetic strategy for structured macrocyclic peptide design was established.

Conclusions:

• This study provides a novel synthetic strategy for designing and discovering structured macrocyclic peptides.
• Key characteristics for effective β-hairpin antimicrobial peptide activity were elucidated, including structural constraints and cationic charge.
• The findings advance the development of peptide-based therapeutics.