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Download fileDefining a Physical Basis for Diversity in Protein Self-Assemblies Using a Minimal Model
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posted on 2016-10-03, 00:00 authored by Srivastav Ranganathan, Samir K. Maji, Ranjith PadinhateeriSelf-assembly of proteins into ordered,
fibrillar structures is
a commonly observed theme in biology. It has been observed that diverse
set of proteins (e.g., alpha-synuclein, insulin, TATA-box binding
protein, Sup35, p53), independent of their sequence, native structure,
or function could self-assemble into highly ordered structures known
as amyloids. What are the crucial features underlying amyloidogenesis
that make it so generic? Using coarse-grained simulations of peptide
self-assembly, we argue that variation in two physical parametersbending
stiffness of the polypeptide and strength of intermolecular interactionscan
give rise to many of the structural features typically associated
with amyloid self-assembly. We show that the interplay between these
two factors gives rise to a rich phase diagram displaying high diversity
in aggregated states. For certain parameters, we find a bimodal distribution
for the order parameter implying the coexistence of ordered and disordered
aggregates. Our findings may explain the experimentally observed variability
including the “off-pathway” aggregated structures. Further,
we demonstrate that sequence-dependence and protein-specific signatures
could be mapped to our coarse-grained framework to study self-assembly
behavior of realistic systems such as the STVIIE peptide and Aβ42.
The work also provides certain guiding principles that could be used
to design novel peptides with desired self-assembly properties, by
tuning a few physical parameters.
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Keywords
coarse-grained frameworkaggregated statesphase diagrambimodal distributionfibrillar structurespeptide self-assemblyprotein-specific signaturesorder parameterself-assembly propertiesTATA-box binding proteincoarse-grained simulationsamyloid self-assemblydesign novel peptidesProtein Self-Assembliesstudy self-assembly behaviorMinimal Model Self-assemblySTVIIE peptidePhysical Basis