@inbook{d87f1e22554f49c68977a8cf1956b020,
title = "Computational Evolution Protocol for Peptide Design",
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.",
keywords = "Affinity optimization, Antibody design, Consensus scoring functions, Evolutionary algorithm, In silico antibody maturation, Molecular dynamics, Peptide design, Sensor technology",
author = "Rodrigo Ochoa and Soler, {Miguel A.} and Ivan Gladich and Anna Battisti and Nikola Minovski and Alex Rodriguez and Sara Fortuna and Pilar Cossio and Alessandro Laio",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.",
year = "2022",
doi = "10.1007/978-1-0716-1855-4_16",
language = "English",
series = "Methods in Molecular Biology",
publisher = "Humana Press Inc.",
pages = "335--359",
booktitle = "Methods in Molecular Biology",
}