Determination of critical nucleation number for a single nucleation amyloid-β aggregation model

Preetam Ghosh, Ashwin Vaidya, Amit Kumar, Vijayaraghavan Rangachari

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


Aggregates of amyloid-β (Aβ) peptide are known to be the key pathological agents in Alzheimer disease (AD). Aβ aggregates to form large, insoluble fibrils that deposit as senile plaques in AD brains. The process of aggregation is nucleation-dependent in which the formation of a nucleus is the rate-limiting step, and controls the physiochemical fate of the aggregates formed. Therefore, understanding the properties of nucleus and pre-nucleation events will be significant in reducing the existing knowledge-gap in AD pathogenesis. In this report, we have determined the plausible range of critical nucleation number (n*, the number of monomers associated within the nucleus for a homogenous aggregation model with single unique nucleation event, by two independent methods: A reduced-order stability analysis and ordinary differential equation based numerical analysis, supported by experimental biophysics. The results establish that the most likely range of n* is between 7 and 14 and within, this range, n* = 12 closely supports the experimental data. These numbers are in agreement with those previously reported, and importantly, the report establishes a new modeling framework using two independent approaches towards a convergent solution in modeling complex aggregation reactions. Our model also suggests that the formation of large protofibrils is dependent on the nature of n*, further supporting the idea that pre-nucleation events are significant in controlling the fate of larger aggregates formed. This report has re-opened an old problem with a new perspective and holds promise towards revealing the molecular events in amyloid pathologies in the future.

Original languageEnglish
Pages (from-to)70-79
Number of pages10
JournalMathematical Biosciences
StatePublished - 1 Mar 2016


  • Aggregation
  • Amyloid-β
  • Nucleation
  • Oligomers
  • Simulation
  • Stability analysis


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