Dataset Information

Steckmann2012 - Amyloid beta-protein fibrillogenesis (kinetics of secondary structure conversion)

ABSTRACT: Steckmann2012 - Amyloid beta-protein fibrillogenesis (kinetics of secondary structure conversion) This model is described in the article: Kinetics of peptide secondary structure conversion during amyloid ?-protein fibrillogenesis. Steckmann T, Awan Z, Gerstman BS, Chapagain PP. J. Theor. Biol. 2012 May; 301: 95-102 Abstract: Amyloid fibrils are a common component in many debilitating human neurological diseases such as Alzheimer's (AD), Parkinson's, and Creutzfeldt-Jakob, and in animal diseases such as BSE. The role of fibrillar ?? proteins in AD has stimulated interest in the kinetics of ?? fibril formation. Kinetic models that include reaction pathways and rate parameters for the various stages of the process can be helpful towards understanding the dynamics on a molecular level. Based upon experimental data, we have developed a mathematical model for the reaction pathways and determined rate parameters for peptide secondary structural conversion and aggregation during the entire fibrillogenesis process from random coil to mature fibrils, including the molecular species that accelerate the conversions. The model and the rate parameters include different molecular structural stages in the nucleation and polymerization processes and the numerical solutions yield graphs of concentrations of different molecular species versus time that are in close agreement with experimental results. The model also allows for the calculation of the time-dependent increase in aggregate size. The calculated results agree well with experimental results, and allow differences in experimental conditions to be included in the calculations. The specific steps of the model and the rate constants that are determined by fitting to experimental data provide insight on the molecular species involved in the fibril formation process. This model is hosted on BioModels Database and identified by: BIOMD0000000533. 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

SUBMITTER: Audald Lloret i Villas

PROVIDER: BIOMD0000000533 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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			Action	DRS
	BIOMD0000000533?filename=BIOMD0000000533-biopax2.owl	Owl
	BIOMD0000000533?filename=BIOMD0000000533-biopax3.owl	Owl
	BIOMD0000000533?filename=BIOMD0000000533.m	Other
	BIOMD0000000533?filename=BIOMD0000000533.pdf	Pdf
	BIOMD0000000533?filename=BIOMD0000000533.png	Other

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Project description:Crespo2012 - Kinetics of Amyloid Fibril Formation This model is described in the article: A generic crystallization-like model that describes the kinetics of amyloid fibril formation. Crespo R, Rocha FA, Damas AM, Martins PM. J. Biol. Chem. 2012 Aug; 287(36): 30585-30594 Abstract: Associated with neurodegenerative disorders such as Alzheimer, Parkinson, or prion diseases, the conversion of soluble proteins into amyloid fibrils remains poorly understood. Extensive "in vitro" measurements of protein aggregation kinetics have been reported, but no consensus mechanism has emerged until now. This contribution aims at overcoming this gap by proposing a theoretically consistent crystallization-like model (CLM) that is able to describe the classic types of amyloid fibrillization kinetics identified in our literature survey. Amyloid conversion represented as a function of time is shown to follow different curve shapes, ranging from sigmoidal to hyperbolic, according to the relative importance of the nucleation and growth steps. Using the CLM, apparently unrelated data are deconvoluted into generic mechanistic information integrating the combined influence of seeding, nucleation, growth, and fibril breakage events. It is notable that this complex assembly of interdependent events is ultimately reduced to a mathematically simple model, whose two parameters can be determined by little more than visual inspection. The good fitting results obtained for all cases confirm the CLM as a good approximation to the generalized underlying principle governing amyloid fibrillization. A perspective is presented on possible applications of the CLM during the development of new targets for amyloid disease therapeutics. This model is hosted on BioModels Database and identified by: BIOMD0000000531. 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:Martins2013 - True and apparent inhibition of amyloid fribril formation This model is described in the article: True and apparent inhibition of amyloid fibril formation. Martins PM. Prion 2013 Mar-Apr; 7(2): 136-139 Abstract: A possible therapeutic strategy for amyloid diseases involves the use of small molecule compounds to inhibit protein assembly into insoluble aggregates. According to the recently proposed Crystallization-Like Model, the kinetics of amyloid fibrillization can be retarded by decreasing the frequency of new fibril formation or by decreasing the elongation rate of existing fibrils. To the compounds that affect the nucleation and/or the growth steps we call true inhibitors. An apparent inhibition mechanism may however result from the alteration of thermodynamic properties such as the solubility of the amyloidogenic protein. Apparent inhibitors markedly influence protein aggregation kinetics measured in vitro, yet they are likely to lead to disappointing results when tested in vivo. This is because cells and tissues media are in general much more buffered against small variations in composition than the solutions prepared in lab. Here we show how to discriminate between true and apparent inhibition mechanisms from experimental data on protein aggregation kinetics. The goal is to be able to identify false positives much earlier during the drug development process. This model is hosted on BioModels Database and identified by: BIOMD0000000561. 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.

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Steckmann2012 - Amyloid beta-protein fibrillogenesis (kinetics of secondary structure conversion)

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