Computational Model for Studying Breakage-Dependent Amyloid Growth

ACS Chem Neurosci. 2020 Nov 4;11(21):3615-3622. doi: 10.1021/acschemneuro.0c00481. Epub 2020 Oct 13.

Abstract

Amyloid fibrils are typically associated with neurodegenerative diseases. Recent studies have suggested that, similar to prions, many amyloid proteins are infectious in nature and may cause spreading and dissemination of diseases. Typical amyloid infection propagates by recruiting functional proteins into amyloidogenic form and multiplying by breaking the existing fibril. In this study, we model the kinetics of fibril growth through breakage and the subsequent elongation process, similar to the prion infection process. Using kinetic Monte Carlo simulations as well as mathematical counting methods, we show how the measurable quantities like the 50% aggregation time (T50) and the maximum growth rate (Vmax) scale with various parameters in the problem. This study has a direct application where it can be used to understand experiments that amplify the minute amount of amyloid seeds present in biological fluid for early detection of human disease. Using the knowledge from our simulations, we can predict the initial seed concentration, known as the filament kinetics.

Keywords: Amyloid filament growth; Breaking of amyloid; Computational model; Growth kinetics; Neurodegenerative diseases; PMCA; Prediction of initial seed concentration.

MeSH terms

  • Amyloid
  • Amyloidogenic Proteins
  • Amyloidosis*
  • Humans
  • Kinetics
  • Prions*

Substances

  • Amyloid
  • Amyloidogenic Proteins
  • Prions