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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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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. |
format | Online Article Text |
id | pubmed-9634169 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT changliwei towardsrationalcomputationalpeptidedesign AT mondalarup towardsrationalcomputationalpeptidedesign AT perezalberto towardsrationalcomputationalpeptidedesign |