Computational Evolution Protocol for Peptide Design

Rodrigo Ochoa, Miguel A. Soler, Ivan Gladich, Anna Battisti, Nikola Minovski, Alex Rodriguez, Sara Fortuna, Pilar Cossio, Alessandro Laio*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

5 Citations (Scopus)

Abstract

Computational peptide design is useful for therapeutics, diagnostics, and vaccine development. To select the most promising peptide candidates, the key is describing accurately the peptide–target interactions at the molecular level. We here review a computational peptide design protocol whose key feature is the use of all-atom explicit solvent molecular dynamics for describing the different peptide–target complexes explored during the optimization. We describe the milestones behind the development of this protocol, which is now implemented in an open-source code called PARCE. We provide a basic tutorial to run the code for an antibody fragment design example. Finally, we describe three additional applications of the method to design peptides for different targets, illustrating the broad scope of the proposed approach.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages335-359
Number of pages25
DOIs
Publication statusPublished - 2022

Publication series

NameMethods in Molecular Biology
Volume2405
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords

  • Affinity optimization
  • Antibody design
  • Consensus scoring functions
  • Evolutionary algorithm
  • In silico antibody maturation
  • Molecular dynamics
  • Peptide design
  • Sensor technology

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