Simulating oligomerization at experimental concentrations and long timescales: A Markov state model approach

Area of Science:

• Computational chemistry
• Biophysics
• Molecular dynamics

Background:

• Amyloid-beta (Abeta) oligomers are implicated in Alzheimer's disease pathogenesis.
• Understanding Abeta oligomerization at experimental concentrations and timescales is crucial.

Purpose of the Study:

• To present a novel computational method for simulating oligomeric assembly formation.
• To apply this method to study the oligomerization of an Abeta peptide fragment (Abeta(21-43)).

Main Methods:

• Extension of the Markovian state model approach to include low concentration oligomeric states analytically.
• All-atom molecular dynamics simulations at experimental concentrations (micromolar) and long timescales (seconds).

Main Results:

• Predicted formation of Abeta trimers at micromolar concentrations within 10 ms.
• Predicted tetramer formation to be 1000 times slower than trimer formation.
• Identification of specific intermonomer contacts and structures of small molecular weight Abeta oligomers.

Conclusions:

• The novel computational method enables simulations of oligomerization under biologically relevant conditions.
• Abeta trimer formation is kinetically favored over tetramer formation.
• Proposed a novel mutation to stabilize the Abeta trimer form for experimental validation.