Peptide Libraries with Antimicrobial Activity: Comparison
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Please note this is a comparison between Version 2 by Rita Xu and Version 1 by Juan Cruz.

In this review, we describe how by coupling emerging

Authors describe how by coupling emerging

in silico

and experimental tools it is possible to create novel peptide libraries with potential antimicrobial activity. This is in response to the growing public health concern pose by multiresistant microbial strains that take millions of lives annually on a global scale. The 

in silico

tools include emerging artificial intelligence algorithms that allow searching for novel sequences in extremely large databases. Once identified, the required membrane activity can be estimated by looking at the interactions with model lipid bilayers via molecular dynamics (MD) simulations. Experimentally, the sequences can be expressed on the surface of yeasts by the surface display technology and subsequently screened in a high-throughput manner aided by microfluidic systems capable of separating out the most active peptides by precisely monitoring changes in optical properties in-line and real-time. 

  • Antimicrobial peptides
  • recurrent neural networks
  • MD simulations
  • microfluidic separation systems
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