Models for the Prediction of Antimicrobial Peptides Activity

  • Rosaura Parisi
  • Ida Moccia
  • Lucia Sessa
  • Luigi Di Biasi
  • Simona Concilio
  • Stefano PiottoEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 587)


Antimicrobial peptides AMP are small proteins produced by the innate immune system in multicellular microorganisms. The mechanism of action of AMP on target membranes can be divided in two main categories: pore forming and non-pore forming mechanisms. We applied a computational approach to design novel linear peptides having high specificity and low toxicity against common pathogens. We built up QSAR models using the data present in a database of antimicrobial peptides. Here, we present new models of activities obtained by the use of evolutionary methods and the relative statistical validation.


Genetic Algorithm Artificial Neural Network Antimicrobial Peptide Artificial Neural Network Model Methicillin Resistant Staphylococcus Aureus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Rosaura Parisi
    • 1
  • Ida Moccia
    • 1
  • Lucia Sessa
    • 1
  • Luigi Di Biasi
    • 1
    • 2
  • Simona Concilio
    • 3
  • Stefano Piotto
    • 1
    Email author
  1. 1.Department of PharmacyUniversity of SalernoFiscianoItaly
  2. 2.Department of InformaticsUniversity of SalernoFiscianoItaly
  3. 3.Department of Industrial EngineeringUniversity of SalernoFiscianoItaly

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