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SUMMARY:Using sequence data to predict the self-assembly of supramolecular
  collagen structures - Dr Anna Puszkarska\, AstraZeneca
DTSTART:20221114T140000Z
DTEND:20221114T143000Z
UID:TALK192413@talks.cam.ac.uk
CONTACT:Jerelle Joseph
DESCRIPTION:The pathway for protein self-assembly is determined by the fre
 e energy landscape coded in the noncovalent interactions between the build
 ing blocks. We use this basic principle to develop a model that describes 
 the mechanisms involved in the staggering of collagen molecules in fibrill
 ar assemblies. In this work we present a simple\, parameter-free model for
  collagen fibril design that allows us to predict the structure of self-as
 sembling collagen fibers on the basis of the amino acid sequence of the co
 nstituent alpha-chain subunits. We develop a classification algorithm and 
 use it to scan through large data sets of collagen molecules to predict th
 e periodicity of the resulting assemblies. We argue that\, with our model\
 , it becomes possible to design tailor-made\, periodic collagen structures
 \, thereby enabling the design of novel biomimetic materials based on coll
 agen-mimetic trimers.
LOCATION:Zoom
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