Computational Evolution Protocol for Peptide Design
- PMID: 35298821
- DOI: 10.1007/978-1-0716-1855-4_16
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.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
References
-
- Kim BY, Rutka JT, Chan WC (2010) Nanomedicine. N Engl J Med 363(25):2434–2443 - PubMed
-
- Zhang X-X, Eden HS, Chen X (2012) Peptides in cancer nanomedicine: drug carriers, targeting ligands and protease substrates. J Controll Release 159(1):2–13
-
- Chung EJ (2016) Targeting and therapeutic peptides in nanomedicine for atherosclerosis. Exp Biol Med 241(9):891–898
-
- Brayden DJ, Hill T, Fairlie D, Maher S, Mrsny R (2020). Systemic delivery of peptides by the oral route: formulation and medicinal chemistry approaches. Adv Drug Deliv Rev
-
- Kurrikoff K, Aphkhazava D, Langel Ü (2019) The future of peptides in cancer treatment. Curr Opin Pharmacol 47:27–32 - PubMed