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Auer2010 - Correlation between lag time and aggregation rate in protein aggregation

ABSTRACT: Auer2010 - Correlation between lag time and aggregation rate in protein aggregation This model is described in the article: Insight into the correlation between lag time and aggregation rate in the kinetics of protein aggregation. Auer S, Kashchiev D. Proteins 2010 Aug; 78(11): 2412-2416 Abstract: Under favorable conditions, many proteins can assemble into macroscopically large aggregates such as the amyloid fibrils that are associated with Alzheimer's, Parkinson's, and other neurological and systemic diseases. The overall process of protein aggregation is characterized by initial lag time during which no detectable aggregation occurs in the solution and by maximal aggregation rate at which the dissolved protein converts into aggregates. In this study, the correlation between the lag time and the maximal rate of protein aggregation is analyzed. It is found that the product of these two quantities depends on a single numerical parameter, the kinetic index of the curve quantifying the time evolution of the fraction of protein aggregated. As this index depends relatively little on the conditions and/or system studied, our finding provides insight into why for many experiments the values of the product of the lag time and the maximal aggregation rate are often equal or quite close to each other. It is shown how the kinetic index is related to a basic kinetic parameter of a recently proposed theory of protein aggregation. This model is hosted on BioModels Database and identified by: BIOMD0000000555. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

DISEASE(S): Alzheimer's Disease,Parkinson's Disease

SUBMITTER: Audald Lloret i Villas

PROVIDER: BIOMD0000000555 | BioModels | 2014-11-10

REPOSITORIES: BioModels

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Publications

Insight into the correlation between lag time and aggregation rate in the kinetics of protein aggregation.

Auer Stefan S Kashchiev Dimo D

Proteins 20100801 11

Under favorable conditions, many proteins can assemble into macroscopically large aggregates such as the amyloid fibrils that are associated with Alzheimer's, Parkinson's, and other neurological and systemic diseases. The overall process of protein aggregation is characterized by initial lag time during which no detectable aggregation occurs in the solution and by maximal aggregation rate at which the dissolved protein converts into aggregates. In this study, the correlation between the lag time ...[more]

PMID: 20602358

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Project description:Morris2009 - α-Synuclein aggregation variable temperature and pH This model is described in the article: 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. Morris AM, Finke RG. Biophys. Chem. 2009 Mar; 140(1-3): 9-15 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. This model is hosted on BioModels Database and identified by: BIOMD0000000566. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Protein aggregation is a hallmark of many neurodegenerative diseases. In order to cope with misfolding and aggregation, cells have evolved an elaborate network of molecular chaperones, composed of different families. But while chaperoning mechanisms for different families are well established, functional and regulatory diversification within chaperone families is still largely a mystery. Here we decided to explore chaperone functional diversity, through the lens of pathological aggregation. We revealed that different naturally-occurring isoforms of DNAJ chaperones showed differential effects on different types of aggregates. We performed a chaperone screen for modulators of two neurodegeneration-related aggregating proteins, the Huntington’s disease-related HTT-polyQ, and the ALS-related mutant FUS (mutFUS). The screen identified known modulators of HTT-polyQ aggregation, confirming the validity of our approach. Surprisingly, modulators of mutFUS aggregation were completely different than those of HTT-polyQ. Interestingly, different naturally-occurring isoforms of DNAJ chaperones had opposing effects on HTT-polyQ vs. mutFUS aggregation. We identified a complex of the full length (FL) DNAJB14 and DNAJB12 isoforms which substantially alleviated mutFUS aggregation, in an HSP70-dependent manner. Their naturally occurring short isoforms were unable to form the complex, nor to interact with HSP70, and lost their ability to reduce mutFUS aggregation. In contrast, the short isoform of DNAJB12 significantly alleviated HTT-polyQ aggregation, while DNAJB12-FL aggravated HTT-polyQ aggregation. Finally, we demonstrated that full-length DNAJB14 ameliorated mutFUS aggregation compared to DNAJB14-short in primary neurons. Together, our data unraveled distinct molecular properties required for aggregation protection in different neurodegenerative diseases, and revealed a new layer of complexity of the chaperone network elicited by naturally occurring J-protein isoforms, highlighting functional diversity among the DNAJ family.

Dataset Information

Auer2010 - Correlation between lag time and aggregation rate in protein aggregation

Publications

Insight into the correlation between lag time and aggregation rate in the kinetics of protein aggregation.

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