Cryogenic electron microscopy has revealed unprecedented molecular insight into the conformation of β-sheet-rich protein amyloids linked to neurodegenerative diseases. It remains unknown how a protein can adopt a diversity of folds and form multiple distinct fibrillar structures. Here we develop an in silico alanine scan method to estimate the relative energetic contribution of each amino acid in an amyloid assembly. We apply our method to twenty-seven ex vivo and in vitro fibril structural polymorphs of the microtubule-associated protein tau. We uncover networks of energetically important interactions involving amyloid-forming motifs that stabilize the different fibril folds. We test our predictions in cellular and in vitro aggregation assays. Using a machine learning approach, we classify the structures based on residue energetics to identify distinguishing and unifying features. Our energetic profiling suggests that minimal sequence elements that control the stability of tau fibrils, allowing future design of protein sequences that fold into unique structures.
Amyloid deposition of the microtubule-associated protein tau is a unifying theme in a multitude of neurodegenerative diseases. Disease-associated missense mutations in tau are associated with frontotemporal dementia (FTD) and enhance tau aggregation propensity. However, the molecular mechanism of how mutations in tau promote tau assembly into amyloids remains obscure. There is a need to understand how tau folds into pathogenic conformations to cause disease. Here we describe the structural mechanism for how an FTD-tau S320F mutation drives spontaneous aggregation. We use recombinant protein and synthetic peptide systems, computational modeling, cross-linking mass spectrometry, and cell models to investigate the mechanism of spontaneous aggregation of the S320F FTD-tau mutant. We discover that the S320F mutation drives the stabilization of a local hydrophobic cluster which allosterically exposes the 306VQIVYK311 amyloid motif. We identify a suppressor mutation that reverses the S320F aggregation phenotype through the reduction of S320F-based hydrophobic clustering in vitro and in cells. Finally, we use structure-based computational design to engineer rapidly aggregating tau sequences by optimizing nonpolar clusters in proximity to the S320 site revealing a new principle that governs the regulation of tau aggregation. We uncover a mechanism for regulating aggregation that balances transient nonpolar contacts within local protective structures or in longer-range interactions that sequester amyloid motifs. The introduction of a pathogenic mutation redistributes these transient interactions to drive spontaneous aggregation. We anticipate deeper knowledge of this process will permit control of tau aggregation into discrete structural polymorphs to aid design of reagents that can detect disease-specific tau conformations.
Amyloid deposition of the microtubule-associated protein tau is a unifying theme in a multitude of neurodegenerative diseases. Disease-associated missense mutations in tau are associated with frontotemporal dementia (FTD) and enhance tau aggregation propensity. However, the molecular mechanism of how mutations in tau promote tau assembly into amyloids remains obscure. There is a need to understand how tau folds into pathogenic conformations to cause disease. Here we describe the structural mechanism for how an FTD-tau S320F mutation drives spontaneous aggregation. We use recombinant protein and synthetic peptide systems, computational modeling, cross-linking mass spectrometry, and cell models to investigate the mechanism of spontaneous aggregation of the S320F FTD-tau mutant. We discover that the S320F mutation drives the stabilization of a local hydrophobic cluster which allosterically exposes the 306VQIVYK311 amyloid motif. We identify a suppressor mutation that reverses the S320F aggregation phenotype through the reduction of S320F-based hydrophobic clustering in vitro and in cells. Finally, we use structure-based computational design to engineer rapidly aggregating tau sequences by optimizing nonpolar clusters in proximity to the S320 site revealing a new principle that governs the regulation of tau aggregation. We uncover a mechanism for regulating aggregation that balances transient nonpolar contacts within local protective structures or in longer-range interactions that sequester amyloid motifs. The introduction of a pathogenic mutation redistributes these transient interactions to drive spontaneous aggregation. We anticipate deeper knowledge of this process will permit control of tau aggregation into discrete structural polymorphs to aid design of reagents that can detect disease-specific tau conformations.
Cryogenic electron microscopy has revealed unprecedented molecular insight into the conformation of β-sheet-rich protein amyloids linked to neurodegenerative diseases. It remains unknown how a protein can adopt a diversity of folds and form multiple distinct fibrillar structures. Here we develop an in silico alanine scan method to estimate the relative energetic contribution of each amino acid in an amyloid assembly. We apply our method to twenty-seven ex vivo and in vitro fibril structural polymorphs of the microtubule-associated protein tau. We uncover networks of energetically important interactions involving amyloid-forming motifs that stabilize the different fibril folds. We test our predictions in cellular and in vitro aggregation assays. Using a machine learning approach, we classify the structures based on residue energetics to identify distinguishing and unifying features. Our energetic profiling suggests that minimal sequence elements that control the stability of tau fibrils, allowing future design of protein sequences that fold into unique structures.
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