A molecular dynamics approach to the structural characterization of amyloid aggregation

Area of Science:

• Computational biology
• Biophysics
• Structural biology

Background:

• Ordered beta-aggregation is a hallmark of amyloid diseases.
• Understanding the sequence-structure relationship in aggregation is crucial.
• Existing methods may not fully capture aggregation propensities along protein sequences.

Purpose of the Study:

• To develop and validate a novel computational approach for analyzing beta-aggregation.
• To identify specific 'hot-spots' of beta-aggregation in amyloidogenic polypeptides.
• To investigate the role of specific sequence segments in fibril formation and stability.

Main Methods:

• Decomposition of protein sequences into overlapping stretches.
• Equilibrium implicit solvent molecular dynamics (MD) simulations of oligomeric systems for each stretch.
• Validation using explicit water simulations and in vitro thioflavin T binding assays for designed mutants.

Main Results:

• Identified heterogeneous beta-aggregation propensity in Alzheimer's amyloid-beta (Abeta(42)), with a maximum at V(12)HHQKLVFFAE(22) and minima at turn-like segments.
• Found similar aggregation patterns in human amylin, with a maximal propensity at Q(10)RLANFLVHSSNN(22).
• Pinpointed beta-aggregation 'hot-spots' in yeast prion Ure2p(1-94) and designed a mutant (Ure2p-N4748S(1-94)) with reduced aggregation propensity, verified experimentally.

Conclusions:

• The computational MD approach effectively predicts beta-aggregation propensity and identifies critical aggregation sites.
• Specific sequence segments, particularly turn-like regions, play a significant role in modulating aggregation tendency and fibril structure.
• This method offers a valuable tool for understanding amyloid formation and designing therapeutic strategies.