Thermodynamic phase diagram of amyloid-β (16–22) peptide

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 116; no. 6; pp. 2091 - 2096
• Main Authors: Wang, Yiming, Bunce, Samuel J., Radford, Sheena E., Wilson, Andrew J., Auer, Stefan, Hall, Carol K.
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 05.02.2019
• Subjects: Agglomeration; Amyloid - chemistry; Amyloid - metabolism; Amyloid - ultrastructure; Amyloid beta-Peptides - chemistry; Amyloid beta-Peptides - metabolism; Amyloidogenesis; Biological Sciences; Biopharmaceuticals; Brain; Computational neuroscience; Computer simulation; Fibrillation; Fibrils; Metastable phases; Molecular dynamics; Morphology; Nanofibers; Oligomers; Peptide Fragments; Peptides; Phase diagrams; Protein Aggregates; Protein Binding; Protein Conformation; Protein Multimerization; Proteins; Solubility; Temperature dependence; Temperature effects; Thermodynamic properties; Thermodynamics; Tissue engineering; Transmission electron microscopy; β-Amyloid; coarse-grained simulation; solubility; phase diagram; amyloid; protein aggregation
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.1819592116

The aggregation of monomeric amyloid β protein (Aβ) peptide into oligomers and amyloid fibrils in the mammalian brain is associated with Alzheimer’s disease. Insight into the thermodynamic stability of the Aβ peptide in different polymeric states is fundamental to defining and predicting the aggregation process. Experimental determination of Aβ thermodynamic behavior is challenging due to the transient nature of Aβ oligomers and the low peptide solubility. Furthermore, quantitative calculation of a thermodynamic phase diagram for a specific peptide requires extremely long computational times. Here, using a coarse-grained protein model, molecular dynamics (MD) simulations are performed to determine an equilibrium concentration and temperature phase diagram for the amyloidogenic peptide fragment Aβ16–22. Our results reveal that the only thermodynamically stable phases are the solution phase and the macroscopic fibrillar phase, and that there also exists a hierarchy of metastable phases. The boundary line between the solution phase and fibril phase is found by calculating the temperature-dependent solubility of a macroscopic Aβ16–22 fibril consisting of an infinite number of β-sheet layers. This in silico determination of an equilibrium (solubility) phase diagram for a real amyloid-forming peptide, Aβ16–22, over the temperature range of 277–330 K agrees well with fibrillation experiments and transmission electron microscopy (TEM) measurements of the fibril morphologies formed. This in silico approach of predicting peptide solubility is also potentially useful for optimizing biopharmaceutical production and manufacturing nanofiber scaffolds for tissue engineering.