Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Michael T. Woodside “OBSERVING THE FOLDING AND MISFOLDING OF SINGLE PROTEIN
Document related concepts
Hedgehog signaling pathway wikipedia , lookup
Signal transduction wikipedia , lookup
Phosphorylation wikipedia , lookup
Magnesium transporter wikipedia , lookup
List of types of proteins wikipedia , lookup
G protein–coupled receptor wikipedia , lookup
Protein phosphorylation wikipedia , lookup
Rosetta@home wikipedia , lookup
Protein design wikipedia , lookup
Protein moonlighting wikipedia , lookup
Intrinsically disordered proteins wikipedia , lookup
Protein (nutrient) wikipedia , lookup
Circular dichroism wikipedia , lookup
Protein domain wikipedia , lookup
Homology modeling wikipedia , lookup
Protein–protein interaction wikipedia , lookup
Protein structure prediction wikipedia , lookup
Protein folding wikipedia , lookup
Nuclear magnetic resonance spectroscopy of proteins wikipedia , lookup
Transcript
COLLOQUIUM
Tuesday November 22nd, 2011
12:00 P.M. (SHARP) –1:00 P.M.
Instructional Building 240
Michael T. Woodside
University of Alberta, Physics
“OBSERVING THE FOLDING AND
MISFOLDING OF SINGLE PROTEIN
MOLECULES WITH FORCE
SPECTROSCOPY”
Proteins self-assemble ("fold") reliably into many different structures capable of an
astounding range of functions, but our inability to predict folding from sequence
remains a major challenge of modern science. I will discuss experiments on single
prion protein molecules that allow us to follow the change in structure of the
protein as it folds in real time, by applying tension across the protein with optical
tweezers. The prion protein is responsible for "mad cow" disease, through the
action of an incorrectly folded structure that is infectious. By pulling apart the
protein structure and letting it refold, we are able to observe both the native folding
pathway and several non-native pathways leading from the unfolded state.
Interestingly, the incorrect structures form more frequently than the correct
structure, but they are much less stable. I will also discuss how time correlations in
the length of the molecule can be used to derive the microscopic transition rates,
and how the free-energy landscape through which the protein moves can be
reconstructed from fluctuation theorems.
