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Tytuł:
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Energy Landscapes of Protein Aggregation and Conformation Switching in Intrinsically Disordered Proteins.
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Autorzy:
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Strodel B; Institute of Biological Information Processing (IBI-7: Structural Biochemistry), Forschungszentrum Jülich, 52425 Jülich, Germany; Institute of Theoretical and Computational Chemistry, Heinrich Heine University Düsseldorf, Universitätstrasse 1, 40225 Düsseldorf, Germany.
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Źródło:
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Journal of molecular biology [J Mol Biol] 2021 Oct 01; Vol. 433 (20), pp. 167182. Date of Electronic Publication: 2021 Aug 03.
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Typ publikacji:
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Journal Article; Review
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Język:
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English
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Imprint Name(s):
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Publication: Amsterdam : Elsevier
Original Publication: 1959- : London : Academic Press
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MeSH Terms:
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Protein Aggregates*
Intrinsically Disordered Proteins/*chemistry
Amyloid/chemistry ; Animals ; Humans ; Models, Molecular ; Protein Conformation ; Protein Folding ; Thermodynamics
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Contributed Indexing:
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Keywords: IDPs; amyloid aggregation; disconnectivity graphs; energy landscapes; molecular dynamics simulations
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Substance Nomenclature:
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0 (Amyloid)
0 (Intrinsically Disordered Proteins)
0 (Protein Aggregates)
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Entry Date(s):
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Date Created: 20210806 Date Completed: 20211109 Latest Revision: 20211109
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Update Code:
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20240105
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DOI:
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10.1016/j.jmb.2021.167182
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PMID:
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34358545
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The protein folding problem was apparently solved recently by the advent of a deep learning method for protein structure prediction called AlphaFold. However, this program is not able to make predictions about the protein folding pathways. Moreover, it only treats about half of the human proteome, as the remaining proteins are intrinsically disordered or contain disordered regions. By definition these proteins differ from natively folded proteins and do not adopt a properly folded structure in solution. However these intrinsically disordered proteins (IDPs) also systematically differ in amino acid composition and uniquely often become folded upon binding to an interaction partner. These factors preclude solving IDP structures by current machine-learning methods like AlphaFold, which also cannot solve the protein aggregation problem, since this meta-folding process can give rise to different aggregate sizes and structures. An alternative computational method is provided by molecular dynamics simulations that already successfully explored the energy landscapes of IDP conformational switching and protein aggregation in multiple cases. These energy landscapes are very different from those of 'simple' protein folding, where one energy funnel leads to a unique protein structure. Instead, the energy landscapes of IDP conformational switching and protein aggregation feature a number of minima for different competing low-energy structures. In this review, I discuss the characteristics of these multifunneled energy landscapes in detail, illustrated by molecular dynamics simulations that elucidated the underlying conformational transitions and aggregation processes.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2021 Elsevier Ltd. All rights reserved.)
