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Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids

Non-natural amino acids are increasingly used as building blocks in the development of peptide-based drugs as they expand the available chemical space to tailor function, half-life and other key properties. However, while the chemical space of modified amino acids (mAAs) such as residues containing...

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Autores principales: Oeller, Marc, Kang, Ryan J. D., Bolt, Hannah L., Gomes dos Santos, Ana L., Weinmann, Annika Langborg, Nikitidis, Antonios, Zlatoidsky, Pavol, Su, Wu, Czechtizky, Werngard, De Maria, Leonardo, Sormanni, Pietro, Vendruscolo, Michele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10656490/
https://www.ncbi.nlm.nih.gov/pubmed/37978172
http://dx.doi.org/10.1038/s41467-023-42940-w
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author Oeller, Marc
Kang, Ryan J. D.
Bolt, Hannah L.
Gomes dos Santos, Ana L.
Weinmann, Annika Langborg
Nikitidis, Antonios
Zlatoidsky, Pavol
Su, Wu
Czechtizky, Werngard
De Maria, Leonardo
Sormanni, Pietro
Vendruscolo, Michele
author_facet Oeller, Marc
Kang, Ryan J. D.
Bolt, Hannah L.
Gomes dos Santos, Ana L.
Weinmann, Annika Langborg
Nikitidis, Antonios
Zlatoidsky, Pavol
Su, Wu
Czechtizky, Werngard
De Maria, Leonardo
Sormanni, Pietro
Vendruscolo, Michele
author_sort Oeller, Marc
collection PubMed
description Non-natural amino acids are increasingly used as building blocks in the development of peptide-based drugs as they expand the available chemical space to tailor function, half-life and other key properties. However, while the chemical space of modified amino acids (mAAs) such as residues containing post-translational modifications (PTMs) is potentially vast, experimental methods for measuring the developability properties of mAA-containing peptides are expensive and time consuming. To facilitate developability programs through computational methods, we present CamSol-PTM, a method that enables the fast and reliable sequence-based prediction of the intrinsic solubility of mAA-containing peptides in aqueous solution at room temperature. From a computational screening of 50,000 mAA-containing variants of three peptides, we selected five different small-size mAAs for a total number of 37 peptide variants for experimental validation. We demonstrate the accuracy of the predictions by comparing the calculated and experimental solubility values. Our results indicate that the computational screening of mAA-containing peptides can extend by over four orders of magnitude the ability to explore the solubility chemical space of peptides and confirm that our method can accurately assess the solubility of peptides containing mAAs. This method is available as a web server at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolptm.
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spelling pubmed-106564902023-11-17 Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids Oeller, Marc Kang, Ryan J. D. Bolt, Hannah L. Gomes dos Santos, Ana L. Weinmann, Annika Langborg Nikitidis, Antonios Zlatoidsky, Pavol Su, Wu Czechtizky, Werngard De Maria, Leonardo Sormanni, Pietro Vendruscolo, Michele Nat Commun Article Non-natural amino acids are increasingly used as building blocks in the development of peptide-based drugs as they expand the available chemical space to tailor function, half-life and other key properties. However, while the chemical space of modified amino acids (mAAs) such as residues containing post-translational modifications (PTMs) is potentially vast, experimental methods for measuring the developability properties of mAA-containing peptides are expensive and time consuming. To facilitate developability programs through computational methods, we present CamSol-PTM, a method that enables the fast and reliable sequence-based prediction of the intrinsic solubility of mAA-containing peptides in aqueous solution at room temperature. From a computational screening of 50,000 mAA-containing variants of three peptides, we selected five different small-size mAAs for a total number of 37 peptide variants for experimental validation. We demonstrate the accuracy of the predictions by comparing the calculated and experimental solubility values. Our results indicate that the computational screening of mAA-containing peptides can extend by over four orders of magnitude the ability to explore the solubility chemical space of peptides and confirm that our method can accurately assess the solubility of peptides containing mAAs. This method is available as a web server at https://www-cohsoftware.ch.cam.ac.uk/index.php/camsolptm. Nature Publishing Group UK 2023-11-17 /pmc/articles/PMC10656490/ /pubmed/37978172 http://dx.doi.org/10.1038/s41467-023-42940-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Oeller, Marc
Kang, Ryan J. D.
Bolt, Hannah L.
Gomes dos Santos, Ana L.
Weinmann, Annika Langborg
Nikitidis, Antonios
Zlatoidsky, Pavol
Su, Wu
Czechtizky, Werngard
De Maria, Leonardo
Sormanni, Pietro
Vendruscolo, Michele
Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids
title Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids
title_full Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids
title_fullStr Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids
title_full_unstemmed Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids
title_short Sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids
title_sort sequence-based prediction of the intrinsic solubility of peptides containing non-natural amino acids
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10656490/
https://www.ncbi.nlm.nih.gov/pubmed/37978172
http://dx.doi.org/10.1038/s41467-023-42940-w
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