4,027 research outputs found
Electrostatics in the Stability and Misfolding of the Prion Protein: Salt Bridges, Self-Energy, and Solvation
Using a recently developed mesoscopic theory of protein dielectrics, we have
calculated the salt bridge energies, total residue electrostatic potential
energies, and transfer energies into a low dielectric amyloid-like phase for 12
species and mutants of the prion protein. Salt bridges and self energies play
key roles in stabilizing secondary and tertiary structural elements of the
prion protein. The total electrostatic potential energy of each residue was
found to be invariably stabilizing. Residues frequently found to be mutated in
familial prion disease were among those with the largest electrostatic
energies. The large barrier to charged group desolvation imposes regional
constraints on involvement of the prion protein in an amyloid aggregate,
resulting in an electrostatic amyloid recruitment profile that favours regions
of sequence between alpha helix 1 and beta strand 2, the middles of helices 2
and 3, and the region N-terminal to alpha helix 1. We found that the
stabilization due to salt bridges is minimal among the proteins studied for
disease-susceptible human mutants of prion protein
Practical rare event sampling for extreme mesoscale weather
Extreme mesoscale weather, including tropical cyclones, squall lines, and
floods, can be enormously damaging and yet challenging to simulate; hence,
there is a pressing need for more efficient simulation strategies. Here we
present a new rare event sampling algorithm called Quantile Diffusion Monte
Carlo (Quantile DMC). Quantile DMC is a simple-to-use algorithm that can sample
extreme tail behavior for a wide class of processes. We demonstrate the
advantages of Quantile DMC compared to other sampling methods and discuss
practical aspects of implementing Quantile DMC. To test the feasibility of
Quantile DMC for extreme mesoscale weather, we sample extremely intense
realizations of two historical tropical cyclones, 2010 Hurricane Earl and 2015
Hurricane Joaquin. Our results demonstrate Quantile DMC's potential to provide
low-variance extreme weather statistics while highlighting the work that is
necessary for Quantile DMC to attain greater efficiency in future applications.Comment: 18 pages, 9 figure
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