A network thermodynamic analysis of amyloid aggregation along competing pathways

Highlights：

• This paper deals with the mathematical modeling of aggregation dynamics of amyloid β (Aβ) peptides which underpins Alzheimer disease (AD). Aβ aggregates, especially the low molecular weight oligomers, are the primary toxic agents in AD pathogenesis. Therefore, there is considerable interest in understanding their formation and behavior.

• In this paper, we use our previously established investigations on heterotypic interactions between Aβ and fatty acids (FAs) that adopt off-fibril formation pathway under the control of FA concentrations, to develop a new mathematical framework in defining this complex mechanism. We propose some novel theoretical approaches, including, a game-theoretic competition based framework built upon a mass-action based differential equation model to define and simulate the competing on- and off-pathways kinetics of Aβ.

• The analysis also employs a classical network thermodynamics approach, combining topological and non-equilibrium thermodynamic features of the dynamical system to understand the aggregation dynamics. The work is grounded on well-established and previously published theory and experiments performed by our group.

• Important computational and theoretical findings regarding multiple pathways of aggregation that result from our computations point to possible interventions in future treatments of neurodegenerative diseases such as Alzheimer’s disease.

摘要

This paper deals with the mathematical modeling of aggregation dynamics of amyloid β (Aβ) peptides which underpins Alzheimer disease (AD). Aβ aggregates, especially the low molecular weight oligomers, are the primary toxic agents in AD pathogenesis. Therefore, there is considerable interest in understanding their formation and behavior.•In this paper, we use our previously established investigations on heterotypic interactions between Aβ and fatty acids (FAs) that adopt off-fibril formation pathway under the control of FA concentrations, to develop a new mathematical framework in defining this complex mechanism. We propose some novel theoretical approaches, including, a game-theoretic competition based framework built upon a mass-action based differential equation model to define and simulate the competing on- and off-pathways kinetics of Aβ.•The analysis also employs a classical network thermodynamics approach, combining topological and non-equilibrium thermodynamic features of the dynamical system to understand the aggregation dynamics. The work is grounded on well-established and previously published theory and experiments performed by our group.•Important computational and theoretical findings regarding multiple pathways of aggregation that result from our computations point to possible interventions in future treatments of neurodegenerative diseases such as Alzheimer’s disease.