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Proteins Structure Function and Bioinformatics
Article . 2023 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
Proteins Structure Function and Bioinformatics
Article
License: Wiley Online Library User Agreement
Data sources: Sygma
https://doi.org/10.1101/2023.0...
Article . 2023 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2023
License: CC BY NC ND
Data sources: Datacite
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A geometrical framework for thinking about proteins

Authors: Jayanth R. Banavar; Achille Giacometti; Trinh X. Hoang; Amos Maritan; Tatjana Škrbić;

A geometrical framework for thinking about proteins

Abstract

Abstract We present a model, based on symmetry and geometry, for proteins. Using elementary ideas from mathematics and physics, we derive the geometries of discrete helices and sheets. We postulate a compatible solvent‐mediated emergent pairwise attraction that assembles these building blocks, while respecting their individual symmetries. Instead of seeking to mimic the complexity of proteins, we look for a simple abstraction of reality that yet captures the essence of proteins. We employ analytic calculations and detailed Monte Carlo simulations to explore some consequences of our theory. The predictions of our approach are in accord with experimental data. Our framework provides a rationalization for understanding the common characteristics of proteins. Our results show that the free energy landscape of a globular protein is pre‐sculpted at the backbone level, sequences and functionalities evolve in the fixed backdrop of the folds determined by geometry and symmetry, and that protein structures are unique in being simultaneously characterized by stability, diversity, and sensitivity.

Country
Italy
Keywords

Models, Molecular, Protein Folding, Protein Conformation, Proteins, FOS: Physical sciences, Biomolecules (q-bio.BM), Condensed Matter - Soft Condensed Matter, backbone, globular, poking, side chains, structure, symmetry, Quantitative Biology - Biomolecules, Biological Physics (physics.bio-ph), FOS: Biological sciences, Thermodynamics, Soft Condensed Matter (cond-mat.soft), Physics - Biological Physics, Monte Carlo Method

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
Green