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Computational Evolution Protocol for Peptide Design

Rodrigo Ochoa
•
Miguel A. Soler
•
Ivan Gladich
altro
Alessandro Laio
2022
  • book

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.
DOI
10.1007/978-1-0716-1855-4_16
Archivio
https://hdl.handle.net/11368/3034882
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85127000380
https://link.springer.com/protocol/10.1007/978-1-0716-1855-4_16
Diritti
open access
license:copyright editore
license:digital rights management non definito
license uri:iris.pri02
license uri:iris.pri00
FVG url
https://arts.units.it/request-item?handle=11368/3034882
Soggetti
  • Affinity optimization...

  • Antibody design

  • Consensus scoring fun...

  • Evolutionary algorith...

  • In silico antibody ma...

  • Molecular dynamic

  • Peptide design

  • Sensor technology.

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