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Information gain from isotopic contrast variation in neutron reflectometry on protein-membrane complex structures.

Frank HeinrichPaul A KienzleDavid P HoogerheideMathias Lösche
Published in: Journal of applied crystallography (2020)
A framework is applied to quantify information gain from neutron or X-ray reflectometry experiments [Treece, Kienzle, Hoogerheide, Majkrzak, Lösche & Heinrich (2019). J. Appl. Cryst. 52, 47-59], in an in-depth investigation into the design of scattering contrast in biological and soft-matter surface architectures. To focus the experimental design on regions of interest, the marginalization of the information gain with respect to a subset of model parameters describing the structure is implemented. Surface architectures of increasing complexity from a simple model system to a protein-lipid membrane complex are simulated. The information gain from virtual surface scattering experiments is quantified as a function of the scattering length density of molecular components of the architecture and the surrounding aqueous bulk solvent. It is concluded that the information gain is mostly determined by the local scattering contrast of a feature of interest with its immediate molecular environment, and experimental design should primarily focus on this region. The overall signal-to-noise ratio of the measured reflectivity modulates the information gain globally and is a second factor to be taken into consideration.
Keyphrases
  • health information
  • magnetic resonance
  • high resolution
  • machine learning
  • healthcare
  • contrast enhanced
  • ionic liquid
  • air pollution
  • single molecule
  • protein protein
  • computed tomography
  • small molecule
  • fatty acid