Literature DB >> 19101068

Alpha-synuclein aggregation variable temperature and variable pH kinetic data: a re-analysis using the Finke-Watzky 2-step model of nucleation and autocatalytic growth.

Aimee M Morris1, Richard G Finke.   

Abstract

The aggregation of proteins is believed to be intimately connected to many neurodegenerative disorders. We recently reported an "Ockham's razor"/minimalistic approach to analyze the kinetic data of protein aggregation using the Finke-Watzky (F-W) 2-step model of nucleation (A-->B, rate constant k(1)) and autocatalytic growth (A+B-->2B, rate constant k(2)). With that kinetic model we have analyzed 41 representative protein aggregation data sets in two recent publications, including amyloid beta, alpha-synuclein, polyglutamine, and prion proteins (Morris, A. M., et al. (2008) Biochemistry 47, 2413-2427; Watzky, M. A., et al. (2008) Biochemistry 47, 10790-10800). Herein we use the F-W model to reanalyze protein aggregation kinetic data obtained under the experimental conditions of variable temperature or pH 2.0 to 8.5. We provide the average nucleation (k(1)) and growth (k(2)) rate constants and correlations with variable temperature or varying pH for the protein alpha-synuclein. From the variable temperature data, activation parameters DeltaG(double dagger), DeltaH(double dagger), and DeltaS(double dagger) are provided for nucleation and growth, and those values are compared to the available parameters reported in the previous literature determined using an empirical method. Our activation parameters suggest that nucleation and growth are energetically similar for alpha-synuclein aggregation (DeltaG(double dagger)(nucleation)=23(3) kcal/mol; DeltaG(double dagger)(growth)=22(1) kcal/mol at 37 degrees C). From the variable pH data, the F-W analyses show a maximal k(1) value at pH approximately 3, as well as minimal k(1) near the isoelectric point (pI) of alpha-synuclein. Since solubility and net charge are minimized at the pI, either or both of these factors may be important in determining the kinetics of the nucleation step. On the other hand, the k(2) values increase with decreasing pH (i.e., do not appear to have a minimum or maximum near the pI) which, when combined with the k(1) vs. pH (and pI) data, suggest that solubility and charge are less important factors for growth, and that charge is important in the k(1), nucleation step of alpha-synuclein. The chemically well-defined nucleation (k(1)) rate constants obtained from the F-W analysis are, as expected, different than the 1/lag-time empirical constants previously obtained. However, k(2)x[A](0) (where k(2) is the rate constant for autocatalytic growth and [A](0) is the initial protein concentration) is related to the empirical constant, k(app) obtained previously. Overall, the average nucleation and average growth rate constants for alpha-synuclein aggregation as a function of pH and variable temperature have been quantitated. Those values support the previously suggested formation of a partially folded intermediate that promotes aggregation under high temperature or acidic conditions.

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Year:  2008        PMID: 19101068     DOI: 10.1016/j.bpc.2008.11.003

Source DB:  PubMed          Journal:  Biophys Chem        ISSN: 0301-4622            Impact factor:   2.352


  20 in total

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Journal:  J Biol Chem       Date:  2019-07-24       Impact factor: 5.157

5.  Early aggregation steps in alpha-synuclein as measured by FCS and FRET: evidence for a contagious conformational change.

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6.  Stability analysis of 4-species Aβ aggregation model: A novel approach to obtaining physically meaningful rate constants.

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7.  Charge neutralization and collapse of the C-terminal tail of alpha-synuclein at low pH.

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Journal:  Protein Sci       Date:  2009-07       Impact factor: 6.725

8.  Pulsed Hydrogen-Deuterium Exchange Illuminates the Aggregation Kinetics of α-Synuclein, the Causative Agent for Parkinson's Disease.

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9.  Structural characterization of alpha-synuclein in an aggregation prone state.

Authors:  Min-Kyu Cho; Gabrielle Nodet; Hai-Young Kim; Malene R Jensen; Pau Bernado; Claudio O Fernandez; Stefan Becker; Martin Blackledge; Markus Zweckstetter
Journal:  Protein Sci       Date:  2009-09       Impact factor: 6.725

10.  Nucleated polymerization with secondary pathways. I. Time evolution of the principal moments.

Authors:  Samuel I A Cohen; Michele Vendruscolo; Mark E Welland; Christopher M Dobson; Eugene M Terentjev; Tuomas P J Knowles
Journal:  J Chem Phys       Date:  2011-08-14       Impact factor: 3.488

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