Engineering antimicrobial peptides with improved antimicrobial and hemolytic activities

Area of Science:

• Biochemistry
• Computational Biology
• Drug Discovery

Background:

• Antibiotic resistance is a major global health threat.
• Antimicrobial peptides (AMPs) are a natural defense against infections.
• Developing new AMPs is crucial for combating resistant pathogens.

Purpose of the Study:

• To computationally design and experimentally validate antimicrobial peptides (AMPs).
• To investigate the membrane interaction and biological activity of designed AMPs.
• To correlate computational predictions with experimental antimicrobial and hemolytic activities.

Main Methods:

• Coarse-grained molecular dynamics simulations (MARTINI) with adaptive biasing force and umbrella sampling.
• Calculation of potential of mean force (PMF) to determine free energy profiles of peptide translocation.
• Experimental assays for antimicrobial activity (bacterial growth inhibition) and hemolytic activity (red blood cell lysis).

Main Results:

• PMF profiles successfully mapped peptide-lipid energy landscapes and insertion scenarios.
• Computational predictions showed good correlation with experimental antimicrobial and hemolytic activities.
• Optimized peptide substitutions (Arg and Trp) enhanced antimicrobial efficacy and reduced red blood cell lysis.

Conclusions:

• The study provides a computational framework for understanding AMP membrane insertion energetics.
• Rational design of AMPs based on computational predictions can lead to improved therapeutic agents.
• This approach facilitates the development of novel antibiotics with selective toxicity.