Back

Distinct Aβ40 and Aβ42 co-assembly pathways with free lipids: Experiment-driven MD study

Pandey, R.; Olabi, T.; Lee, M.; Urbanc, B.

2026-10-02 biophysics
10.64898/2026.09.28.755027 bioRxiv
Show abstract

Amyloid {beta}-protein (A{beta}), which is known for its role in Alzheimer's disease (AD), is also involved in several physiological functions. Of the two predominant isoforms, A{beta}40 and A{beta}42, the latter is more aggregation-prone and more active in health and disease. In the brain, A{beta} interacts with free lipids, which may affect its assembly pathways. Here, thioflavin T (ThT) fluorescence spectroscopy is combined with molecular dynamics (MD) to investigate A{beta}40 and A{beta}42 co-assembly with free dimyristoylphosphatidylcholine (DMPC) and DMPC/cholesterol (CHOL) lipids. ThT measurements at several protein-to-lipid (PL) ratios show isoform- and lipid composition-dependent kinetics of A{beta} fibril formation with clear isoform-dependent lipid effects at a PL ratio of 1:5. Early co-assembly stages of six A{beta}40/A{beta}42 with DMPC and DMPC/CHOL lipids at this PL ratio are then examined by MD. MD results indicate that lipids alter the secondary structure more and interact more avidly with A{beta}40 than with A{beta}42. In turn, A{beta}40 increases the planar order of lipid bicelles more than A{beta}42. Unlike A{beta}40, A{beta}42 decreases the nematic order of CHOL. In DMPC/CHOL lipids, A{beta}42 but not A{beta}40 exhibits two A{beta}-lipid interaction modes associated with mutually exclusive A{beta}42-lipid and A{beta}42-A{beta}42 interactions. Our MD findings provide a plausible explanation for an experimentally observed increase in the lag time for A{beta}40 fibril formation in DMPC lipids and even more so in DMPC/CHOL lipids that contrasts with much smaller effects of lipids on A{beta}42 fibril formation and offer additional atomistic-level insights into A{beta} co-assembly with lipids amenable to experimental testing.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.