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Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules
Knowledge-based approaches use the statistics collected from protein data-bank structures to estimate effective interaction potentials between amino acid pairs. Empirical relations are typically employed that are based on the crucial choice of a reference state associated to the null interaction cas...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8794220/ https://www.ncbi.nlm.nih.gov/pubmed/35085247 http://dx.doi.org/10.1371/journal.pone.0254969 |
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author | Zamuner, Stefano Seno, Flavio Trovato, Antonio |
author_facet | Zamuner, Stefano Seno, Flavio Trovato, Antonio |
author_sort | Zamuner, Stefano |
collection | PubMed |
description | Knowledge-based approaches use the statistics collected from protein data-bank structures to estimate effective interaction potentials between amino acid pairs. Empirical relations are typically employed that are based on the crucial choice of a reference state associated to the null interaction case. Despite their significant effectiveness, the physical interpretation of knowledge-based potentials has been repeatedly questioned, with no consensus on the choice of the reference state. Here we use the fact that the Flory theorem, originally derived for chains in a dense polymer melt, holds also for chain fragments within the core of globular proteins, if the average over buried fragments collected from different non-redundant native structures is considered. After verifying that the ensuing Gaussian statistics, a hallmark of effectively non-interacting polymer chains, holds for a wide range of fragment lengths, although with significant deviations at short spatial scales, we use it to define a ‘bona fide’ reference state. Notably, despite the latter does depend on fragment length, deviations from it do not. This allows to estimate an effective interaction potential which is not biased by the presence of correlations due to the connectivity of the protein chain. We show how different sequence-independent effective statistical potentials can be derived using this approach by coarse-graining the protein representation at varying levels. The possibility of defining sequence-dependent potentials is explored. |
format | Online Article Text |
id | pubmed-8794220 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-87942202022-01-28 Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules Zamuner, Stefano Seno, Flavio Trovato, Antonio PLoS One Research Article Knowledge-based approaches use the statistics collected from protein data-bank structures to estimate effective interaction potentials between amino acid pairs. Empirical relations are typically employed that are based on the crucial choice of a reference state associated to the null interaction case. Despite their significant effectiveness, the physical interpretation of knowledge-based potentials has been repeatedly questioned, with no consensus on the choice of the reference state. Here we use the fact that the Flory theorem, originally derived for chains in a dense polymer melt, holds also for chain fragments within the core of globular proteins, if the average over buried fragments collected from different non-redundant native structures is considered. After verifying that the ensuing Gaussian statistics, a hallmark of effectively non-interacting polymer chains, holds for a wide range of fragment lengths, although with significant deviations at short spatial scales, we use it to define a ‘bona fide’ reference state. Notably, despite the latter does depend on fragment length, deviations from it do not. This allows to estimate an effective interaction potential which is not biased by the presence of correlations due to the connectivity of the protein chain. We show how different sequence-independent effective statistical potentials can be derived using this approach by coarse-graining the protein representation at varying levels. The possibility of defining sequence-dependent potentials is explored. Public Library of Science 2022-01-27 /pmc/articles/PMC8794220/ /pubmed/35085247 http://dx.doi.org/10.1371/journal.pone.0254969 Text en © 2022 Zamuner et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Zamuner, Stefano Seno, Flavio Trovato, Antonio Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules |
title | Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules |
title_full | Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules |
title_fullStr | Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules |
title_full_unstemmed | Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules |
title_short | Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules |
title_sort | statistical potentials from the gaussian scaling behaviour of chain fragments buried within protein globules |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8794220/ https://www.ncbi.nlm.nih.gov/pubmed/35085247 http://dx.doi.org/10.1371/journal.pone.0254969 |
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