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Louros N, Ramakers M, Michiels E, Konstantoulea K, Morelli C, Garcia T, D’Haeyer S, Goossens V, Audenaert D, Rousseau F, Schymkowitz J. Mapping the sequence specificity of heterotypic amyloid interactions enables the identification of aggregation modifiers. bioRxiv, July 30, 2021 bioRxiv.
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University of Melbourne
Florey Instotute of Neurosciece and Mental Health
Utilizing extensive proteomic data of Aβ plaques from AD patients and multiple sequence alignments, this sound work produced a library of peptides that modify Aβ assembly kinetics, fibril morphology, and deposition pattern, all in vitro. Proteomic analysis showed that enriched proteins harbor homologous sequences to the Aβ aggregation-prone regions (APRs) as defined a priori as 16-21 and the c-terminal 29-end.
It is not surprising that highly hydrophobic “sticky” Aβ aggregates can collect hydrophobic fragments of other proteins through heterotypic interactions. This is another example of how sensitive aggregation of Aβ (or any intrinsically disordered protein) is to variations in conditions: pH, metal binding, and various co-factors. The varying elements are infinite. Modified aggregation produces different forms of Aβ which may have different toxicities and thus may even stabilize nontoxic forms.
Further, in the following publication, the authors have performed a systematic thermodynamic evaluation, coupled with multidimensionality analysis to investigate structural compatibility for the entire sequence space of single variants of the APR dataset. The results “indicated that even for highly conserved sequences, such as single position variants, a thermodynamically favourable fit within the defined aggregation core is rather hardly accommodated. … This apparent incompatibility of APR cores to sequence variation was also supported by the fact that only a limited fraction of sequence variants was predicted to favour self-assembly (6.9%) possibly suggesting that the template backbone arrangements are strongly tailored to their particular sequences.”
Indeed, those sequences are from globular proteins where the “sequence-structures” unique relationship is held. Intrinsically disordered proteins (Aβ, tau, etc.) challenge this postulate. A further support to this observation could be our test run of DeepMind Alphafold2 AI system for predicting Aβ or tau folds. The system iterates between multiple sequence alignment (as above) plus residue pairs to predict pairwise distances between all protein residues. The selected sequences can form potentially an additional library of peptides to be analyzed and tested. However, the system fails to predict any stable sensible structural templates/folds as expected.
With so many variables in play, it is difficult to interpret the biological significance of the findings. The best guideposts still seem to be the hits thrown up by genetic analyses.
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