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Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules

Stefano Zamuner, Flavio Seno, View ORCID ProfileAntonio Trovato
doi: https://doi.org/10.1101/2021.08.04.455097
Stefano Zamuner
1Institute of Physics, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
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Flavio Seno
2Department of Physics and Astronomy “G. Galilei”, University of Padova, Via Marzolo 8, I-35131 Padova, Italy
3INFN, Sezione di Padova, Via Marzolo 8, I-35131 Padova, Italy
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Antonio Trovato
2Department of Physics and Astronomy “G. Galilei”, University of Padova, Via Marzolo 8, I-35131 Padova, Italy
3INFN, Sezione di Padova, Via Marzolo 8, I-35131 Padova, Italy
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  • ORCID record for Antonio Trovato
  • For correspondence: antonio.trovato@unipd.it
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Abstract

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, 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.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted August 04, 2021.
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Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules
Stefano Zamuner, Flavio Seno, Antonio Trovato
bioRxiv 2021.08.04.455097; doi: https://doi.org/10.1101/2021.08.04.455097
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Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules
Stefano Zamuner, Flavio Seno, Antonio Trovato
bioRxiv 2021.08.04.455097; doi: https://doi.org/10.1101/2021.08.04.455097

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