Literature DB >> 26774039

Determination of critical nucleation number for a single nucleation amyloid-β aggregation model.

Preetam Ghosh1, Ashwin Vaidya2, Amit Kumar3, Vijayaraghavan Rangachari4.   

Abstract

Aggregates of amyloid-β (Aβ) peptide are known to be the key pathological agents in Alzheimer disease (AD). Aβ aggregates to form large, insoluble fibrils that deposit as senile plaques in AD brains. The process of aggregation is nucleation-dependent in which the formation of a nucleus is the rate-limiting step, and controls the physiochemical fate of the aggregates formed. Therefore, understanding the properties of nucleus and pre-nucleation events will be significant in reducing the existing knowledge-gap in AD pathogenesis. In this report, we have determined the plausible range of critical nucleation number (n(*)), the number of monomers associated within the nucleus for a homogenous aggregation model with single unique nucleation event, by two independent methods: A reduced-order stability analysis and ordinary differential equation based numerical analysis, supported by experimental biophysics. The results establish that the most likely range of n(*) is between 7 and 14 and within, this range, n(*) = 12 closely supports the experimental data. These numbers are in agreement with those previously reported, and importantly, the report establishes a new modeling framework using two independent approaches towards a convergent solution in modeling complex aggregation reactions. Our model also suggests that the formation of large protofibrils is dependent on the nature of n(*), further supporting the idea that pre-nucleation events are significant in controlling the fate of larger aggregates formed. This report has re-opened an old problem with a new perspective and holds promise towards revealing the molecular events in amyloid pathologies in the future.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Aggregation; Amyloid-β; Nucleation; Oligomers; Simulation; Stability analysis

Mesh:

Substances:

Year:  2016        PMID: 26774039      PMCID: PMC4822416          DOI: 10.1016/j.mbs.2015.12.004

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  37 in total

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Authors:  Michael R Nichols; Melissa A Moss; Dana Kim Reed; Wen-Lang Lin; Rajendrani Mukhopadhyay; Jan H Hoh; Terrone L Rosenberry
Journal:  Biochemistry       Date:  2002-05-14       Impact factor: 3.162

2.  Mechanisms of protein fibril formation: nucleated polymerization with competing off-pathway aggregation.

Authors:  Evan T Powers; David L Powers
Journal:  Biophys J       Date:  2007-09-21       Impact factor: 4.033

3.  Quantitative analysis of the time course of Aβ oligomerization and subsequent growth steps using tetramethylrhodamine-labeled Aβ.

Authors:  Kanchan Garai; Carl Frieden
Journal:  Proc Natl Acad Sci U S A       Date:  2013-02-11       Impact factor: 11.205

4.  Fibril breaking accelerates α-synuclein fibrillization.

Authors:  Volodymyr V Shvadchak; Mireille M A E Claessens; Vinod Subramaniam
Journal:  J Phys Chem B       Date:  2015-01-27       Impact factor: 2.991

5.  Globular amyloid beta-peptide oligomer - a homogenous and stable neuropathological protein in Alzheimer's disease.

Authors:  Stefan Barghorn; Volker Nimmrich; Andreas Striebinger; Carsten Krantz; Patrick Keller; Bodo Janson; Michael Bahr; Martin Schmidt; Robert S Bitner; John Harlan; Eve Barlow; Ulrich Ebert; Heinz Hillen
Journal:  J Neurochem       Date:  2005-08-31       Impact factor: 5.372

6.  Specific soluble oligomers of amyloid-β peptide undergo replication and form non-fibrillar aggregates in interfacial environments.

Authors:  Amit Kumar; Lea C Paslay; Daniel Lyons; Sarah E Morgan; John J Correia; Vijayaraghavan Rangachari
Journal:  J Biol Chem       Date:  2012-04-27       Impact factor: 5.157

7.  Amyloid beta-protein fibrillogenesis. Detection of a protofibrillar intermediate.

Authors:  D M Walsh; A Lomakin; G B Benedek; M M Condron; D B Teplow
Journal:  J Biol Chem       Date:  1997-08-29       Impact factor: 5.157

8.  Non-esterified fatty acids generate distinct low-molecular weight amyloid-β (Aβ42) oligomers along pathway different from fibril formation.

Authors:  Amit Kumar; Rebekah L Bullard; Pritesh Patel; Lea C Paslay; Dipti Singh; Ewa A Bienkiewicz; Sarah E Morgan; Vijayaraghavan Rangachari
Journal:  PLoS One       Date:  2011-04-19       Impact factor: 3.240

9.  Dynamics of protofibril elongation and association involved in Aβ42 peptide aggregation in Alzheimer's disease.

Authors:  Preetam Ghosh; Amit Kumar; Bhaswati Datta; Vijayaraghavan Rangachari
Journal:  BMC Bioinformatics       Date:  2010-10-07       Impact factor: 3.169

10.  Proliferation of amyloid-β42 aggregates occurs through a secondary nucleation mechanism.

Authors:  Samuel I A Cohen; Sara Linse; Leila M Luheshi; Erik Hellstrand; Duncan A White; Luke Rajah; Daniel E Otzen; Michele Vendruscolo; Christopher M Dobson; Tuomas P J Knowles
Journal:  Proc Natl Acad Sci U S A       Date:  2013-05-23       Impact factor: 11.205

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  10 in total

Review 1.  Amyloidogenesis of Tau protein.

Authors:  Bartosz Nizynski; Wojciech Dzwolak; Krzysztof Nieznanski
Journal:  Protein Sci       Date:  2017-09-13       Impact factor: 6.725

2.  Propagation of an Aβ Dodecamer Strain Involves a Three-Step Mechanism and a Key Intermediate.

Authors:  Dexter N Dean; Pratip Rana; Ryan P Campbell; Preetam Ghosh; Vijayaraghavan Rangachari
Journal:  Biophys J       Date:  2018-02-06       Impact factor: 4.033

3.  Molecular Mechanism and Kinetics of Amyloid-β42 Aggregate Formation: A Simulation Study.

Authors:  Viet Hoang Man; Xibing He; Beihong Ji; Shuhan Liu; Xiang-Qun Xie; Junmei Wang
Journal:  ACS Chem Neurosci       Date:  2019-11-11       Impact factor: 4.418

4.  A Network Thermodynamic Analysis of Amyloid Aggregation along Competing Pathways.

Authors:  P Ghosh; J Pateras; V Rangachari; A Vaidya
Journal:  Appl Math Comput       Date:  2020-11-18       Impact factor: 4.091

5.  Strain-specific Fibril Propagation by an Aβ Dodecamer.

Authors:  Dexter N Dean; Pradipta K Das; Pratip Rana; Franklin Burg; Yona Levites; Sarah E Morgan; Preetam Ghosh; Vijayaraghavan Rangachari
Journal:  Sci Rep       Date:  2017-01-18       Impact factor: 4.379

6.  Fatty Acid Concentration and Phase Transitions Modulate Aβ Aggregation Pathways.

Authors:  Pratip Rana; Dexter N Dean; Edward D Steen; Ashwin Vaidya; Vijayaraghavan Rangachari; Preetam Ghosh
Journal:  Sci Rep       Date:  2017-09-04       Impact factor: 4.379

7.  Development of a Simple Kinetic Mathematical Model of Aggregation of Particles or Clustering of Receptors.

Authors:  Andrei K Garzon Dasgupta; Alexey A Martyanov; Aleksandra A Filkova; Mikhail A Panteleev; Anastasia N Sveshnikova
Journal:  Life (Basel)       Date:  2020-06-26

8.  A game-theoretic approach to deciphering the dynamics of amyloid-β aggregation along competing pathways.

Authors:  Preetam Ghosh; Pratip Rana; Vijayaraghavan Rangachari; Jhinuk Saha; Edward Steen; Ashwin Vaidya
Journal:  R Soc Open Sci       Date:  2020-04-29       Impact factor: 2.963

9.  Macromolecular crowding and supersaturation protect hemodialysis patients from the onset of dialysis-related amyloidosis.

Authors:  Kichitaro Nakajima; Keiichi Yamaguchi; Masahiro Noji; César Aguirre; Kensuke Ikenaka; Hideki Mochizuki; Lianjie Zhou; Hirotsugu Ogi; Toru Ito; Ichiei Narita; Fumitake Gejyo; Hironobu Naiki; Suguru Yamamoto; Yuji Goto
Journal:  Nat Commun       Date:  2022-10-03       Impact factor: 17.694

10.  Near-Wall Aggregation of Amyloidogenic Aβ 1-40 Peptide: Direct Observation by the FRET.

Authors:  Natalia Katina; Alisa Mikhaylina; Nelly Ilina; Irina Eliseeva; Vitalii Balobanov
Journal:  Molecules       Date:  2021-12-15       Impact factor: 4.411

  10 in total

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