Literature DB >> 16797587

Interpreting the aggregation kinetics of amyloid peptides.

Riccardo Pellarin1, Amedeo Caflisch.   

Abstract

Amyloid fibrils are insoluble mainly beta-sheet aggregates of proteins or peptides. The multi-step process of amyloid aggregation is one of the major research topics in structural biology and biophysics because of its relevance in protein misfolding diseases like Alzheimer's, Parkinson's, Creutzfeld-Jacob's, and type II diabetes. Yet, the detailed mechanism of oligomer formation and the influence of protein stability on the aggregation kinetics are still matters of debate. Here a coarse-grained model of an amphipathic polypeptide, characterized by a free energy profile with distinct amyloid-competent (i.e. beta-prone) and amyloid-protected states, is used to investigate the kinetics of aggregation and the pathways of fibril formation. The simulation results suggest that by simply increasing the relative stability of the beta-prone state of the polypeptide, disordered aggregation changes into fibrillogenesis with the presence of oligomeric on-pathway intermediates, and finally without intermediates in the case of a very stable beta-prone state. The minimal-size aggregate able to form a fibril is generated by collisions of oligomers or monomers for polypeptides with unstable or stable beta-prone state, respectively. The simulation results provide a basis for understanding the wide range of amyloid-aggregation mechanisms observed in peptides and proteins. Moreover, they allow us to interpret at a molecular level the much faster kinetics of assembly of a recently discovered functional amyloid with respect to the very slow pathological aggregation.

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Year:  2006        PMID: 16797587     DOI: 10.1016/j.jmb.2006.05.033

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  57 in total

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Authors:  Alexey V Krasnoslobodtsev; Alexander M Portillo; Tanja Deckert-Gaudig; Volker Deckert; Yuri L Lyubchenko
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3.  Amyloid-β (Aβ42) Peptide Aggregation Rate and Mechanism on Surfaces with Widely Varied Properties: Insights from Brownian Dynamics Simulations.

Authors:  Timothy Cholko; Joseph Barnum; Chia-En A Chang
Journal:  J Phys Chem B       Date:  2020-06-26       Impact factor: 2.991

4.  Cooperative hydrogen bonding in amyloid formation.

Authors:  Kiril Tsemekhman; Lukasz Goldschmidt; David Eisenberg; David Baker
Journal:  Protein Sci       Date:  2007-02-27       Impact factor: 6.725

5.  Hydrophobic cooperativity as a mechanism for amyloid nucleation.

Authors:  Ronald D Hills; Charles L Brooks
Journal:  J Mol Biol       Date:  2007-02-24       Impact factor: 5.469

6.  Similarities in the thermodynamics and kinetics of aggregation of disease-related Abeta(1-40) peptides.

Authors:  Jessica Meinhardt; Gian Gaetano Tartaglia; Amol Pawar; Tony Christopeit; Peter Hortschansky; Volker Schroeckh; Christopher M Dobson; Michele Vendruscolo; Marcus Fändrich
Journal:  Protein Sci       Date:  2007-06       Impact factor: 6.725

Review 7.  CHARMM: the biomolecular simulation program.

Authors:  B R Brooks; C L Brooks; A D Mackerell; L Nilsson; R J Petrella; B Roux; Y Won; G Archontis; C Bartels; S Boresch; A Caflisch; L Caves; Q Cui; A R Dinner; M Feig; S Fischer; J Gao; M Hodoscek; W Im; K Kuczera; T Lazaridis; J Ma; V Ovchinnikov; E Paci; R W Pastor; C B Post; J Z Pu; M Schaefer; B Tidor; R M Venable; H L Woodcock; X Wu; W Yang; D M York; M Karplus
Journal:  J Comput Chem       Date:  2009-07-30       Impact factor: 3.376

8.  Characterization of the nucleation barriers for protein aggregation and amyloid formation.

Authors:  Stefan Auer; Christopher M Dobson; Michele Vendruscolo
Journal:  HFSP J       Date:  2007-07-27

9.  Coarse-grained model for colloidal protein interactions, B(22), and protein cluster formation.

Authors:  Marco A Blanco; Erinc Sahin; Anne S Robinson; Christopher J Roberts
Journal:  J Phys Chem B       Date:  2013-12-10       Impact factor: 2.991

10.  Analysis of a compartmental model of amyloid beta production, irreversible loss and exchange in humans.

Authors:  Donald L Elbert; Bruce W Patterson; Randall J Bateman
Journal:  Math Biosci       Date:  2014-12-09       Impact factor: 2.144

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