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Kinetic models reveal the interplay of protein production and aggregation.

Published version
Peer-reviewed

Repository DOI


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Authors

Dear, Alexander 
Oosterhuis, Matthijs 
Melki, Ronald 

Abstract

Protein aggregation is a key process in the development of many neurodegenerative disorders, including dementias such as Alzheimer's disease. Significant progress has been made in understanding the molecular mechanisms of aggregate formation in pure buffer systems, much of which was enabled by the development of integrated rate laws that allowed for mechanistic analysis of aggregation kinetics. However, in order to translate these findings into disease-relevant conclusions and to make predictions about the effect of potential alterations to the aggregation reactions by the addition of putative inhibitors, the current models need to be extended to account for the altered situation encountered in living systems. In particular, in vivo, the total protein concentrations typically do not remain constant and aggregation-prone monomers are constantly being produced but also degraded by cells. Here, we build a theoretical model that explicitly takes into account monomer production, derive integrated rate laws and discuss the resulting scaling laws and limiting behaviours. We demonstrate that our models are suited for the aggregation-prone Huntington's disease-associated peptide HttQ45 utilizing a system for continuous in situ monomer production and the aggregation of the tumour suppressor protein P53. The aggregation-prone HttQ45 monomer was produced through enzymatic cleavage of a larger construct in which a fused protein domain served as an internal inhibitor. For P53, only the unfolded monomers form aggregates, making the unfolding a rate-limiting step which constitutes a source of aggregation-prone monomers. The new model opens up possibilities for a quantitative description of aggregation in living systems, allowing for example the modelling of inhibitors of aggregation in a dynamic environment of continuous protein synthesis.

Description

Acknowledgements: We wish to acknowledge the support from the ERC grant DiProPhys (agreement ID 10100161, T. P. J. K), the Nidus studentship scheme (J. W.), Fondation pour la Recherche Médicale (RM ALZ201912009776) and the Swedish Research Council (VR 2015-00143 to S. L.).

Keywords

34 Chemical Sciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurodegenerative, Brain Disorders, Acquired Cognitive Impairment, Dementia, Neurosciences, Rare Diseases, Aging, 2.1 Biological and endogenous factors, 2 Aetiology

Journal Title

Chem Sci

Conference Name

Journal ISSN

2041-6520
2041-6539

Volume Title

Publisher

Royal Society of Chemistry (RSC)
Sponsorship
Fondation pour la Recherche Médicale (RM ALZ201912009776)
Vetenskapsrådet (VR 2015-00143)
H2020 European Research Council (10100161)