title: A modified Stokes-Einstein equation for Aβ aggregation.
abstract: BACKGROUND
  In all amyloid diseases, protein aggregates have been implicated fully or partly, in the etiology of the disease. Due to their significance in human pathologies, there have been unprecedented efforts towards physiochemical understanding of aggregation and amyloid formation over the last two decades. An important relation from which hydrodynamic radii of the aggregate is routinely measured is the classic Stokes-Einstein equation. Here, we report a modification in the classical Stokes-Einstein equation using a mixture theory approach, in order to accommodate the changes in viscosity of the solvent due to the changes in solute size and shape, to implement a more realistic model for Aβ aggregation involved in Alzheimer's disease. Specifically, we have focused on validating this model in protofibrill lateral association reactions along the aggregation pathway, which has been experimentally well characterized.
  
  
  RESULTS
  The modified Stokes-Einstein equation incorporates an effective viscosity for the mixture consisting of the macromolecules and solvent where the lateral association reaction occurs. This effective viscosity is modeled as a function of the volume fractions of the different species of molecules. The novelty of our model is that in addition to the volume fractions, it incorporates previously published reports on the dimensions of the protofibrils and their aggregates to formulate a more appropriate shape rather than mere spheres. The net result is that the diffusion coefficient which is inversely proportional to the viscosity of the system is now dependent on the concentration of the different molecules as well as their proper shapes. Comparison with experiments for variations in diffusion coefficients over time reveals very similar trends.
  
  
  CONCLUSIONS
  We argue that the standard Stokes-Einstein's equation is insufficient to understand the temporal variations in diffusion when trying to understand the aggregation behavior of Aβ42 proteins. Our modifications also involve inclusion of improved shape factors of molecules and more appropriate viscosities. The modification we are reporting is not only useful in Aβ aggregation but also will be important for accurate measurements in all protein aggregation systems.
authors.affiliation: Department of Mathematical Sciences, Montclair State University, Montclair, NJ 07043, USA.
authors.forename: Srisairam
authors.initials: S
authors.lastname: Achuthan
authors.forename: Bong Jae
authors.initials: BJ
authors.lastname: Chung
authors.forename: Preetam
authors.initials: P
authors.lastname: Ghosh
authors.forename: Vijayaraghavan
authors.initials: V
authors.lastname: Rangachari
authors.forename: Ashwin
authors.initials: A
authors.lastname: Vaidya
mesh_terms: D016229:Amyloid beta-Peptides / Q000737:chemistry* / Q000378:metabolism*; D004058:Diffusion; D006801:Humans; D008954:Models, Biological; D019636:Neurodegenerative Diseases / Q000473:pathology*; D010446:Peptide Fragments / Q000737:chemistry / Q000378:metabolism; D058225:Plaque, Amyloid / Q000737:chemistry*; D012997:Solvents / Q000737:chemistry; D014783:Viscosity
chemical_list: D016229:Amyloid beta-Peptides; D010446:Peptide Fragments; D012997:Solvents; C075222:amyloid beta-protein (1-42)