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Towards rational computational peptide design

Peptides are prevalent in biology, mediating as many as 40% of protein-protein interactions, and involved in other cellular functions such as transport and signaling. Their ability to bind with high specificity make them promising therapeutical agents with intermediate properties between small molec...

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Detalles Bibliográficos
Autores principales: Chang, Liwei, Mondal, Arup, Perez, Alberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9634169/
https://www.ncbi.nlm.nih.gov/pubmed/36338806
http://dx.doi.org/10.3389/fbinf.2022.1046493
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author Chang, Liwei
Mondal, Arup
Perez, Alberto
author_facet Chang, Liwei
Mondal, Arup
Perez, Alberto
author_sort Chang, Liwei
collection PubMed
description Peptides are prevalent in biology, mediating as many as 40% of protein-protein interactions, and involved in other cellular functions such as transport and signaling. Their ability to bind with high specificity make them promising therapeutical agents with intermediate properties between small molecules and large biologics. Beyond their biological role, peptides can be programmed to self-assembly, and they are already being used for functions as diverse as oligonuclotide delivery, tissue regeneration or as drugs. However, the transient nature of their interactions has limited the number of structures and knowledge of binding affinities available–and their flexible nature has limited the success of computational pipelines that predict the structures and affinities of these molecules. Fortunately, recent advances in experimental and computational pipelines are creating new opportunities for this field. We are starting to see promising predictions of complex structures, thermodynamic and kinetic properties. We believe in the following years this will lead to robust rational peptide design pipelines with success similar to those applied for small molecule drug discovery.
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spelling pubmed-96341692022-11-05 Towards rational computational peptide design Chang, Liwei Mondal, Arup Perez, Alberto Front Bioinform Bioinformatics Peptides are prevalent in biology, mediating as many as 40% of protein-protein interactions, and involved in other cellular functions such as transport and signaling. Their ability to bind with high specificity make them promising therapeutical agents with intermediate properties between small molecules and large biologics. Beyond their biological role, peptides can be programmed to self-assembly, and they are already being used for functions as diverse as oligonuclotide delivery, tissue regeneration or as drugs. However, the transient nature of their interactions has limited the number of structures and knowledge of binding affinities available–and their flexible nature has limited the success of computational pipelines that predict the structures and affinities of these molecules. Fortunately, recent advances in experimental and computational pipelines are creating new opportunities for this field. We are starting to see promising predictions of complex structures, thermodynamic and kinetic properties. We believe in the following years this will lead to robust rational peptide design pipelines with success similar to those applied for small molecule drug discovery. Frontiers Media S.A. 2022-10-21 /pmc/articles/PMC9634169/ /pubmed/36338806 http://dx.doi.org/10.3389/fbinf.2022.1046493 Text en Copyright © 2022 Chang, Mondal and Perez. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioinformatics
Chang, Liwei
Mondal, Arup
Perez, Alberto
Towards rational computational peptide design
title Towards rational computational peptide design
title_full Towards rational computational peptide design
title_fullStr Towards rational computational peptide design
title_full_unstemmed Towards rational computational peptide design
title_short Towards rational computational peptide design
title_sort towards rational computational peptide design
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9634169/
https://www.ncbi.nlm.nih.gov/pubmed/36338806
http://dx.doi.org/10.3389/fbinf.2022.1046493
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