Beschreibung:
<jats:title>Significance</jats:title>
<jats:p>
Statistical modeling of experimental data is gaining increasing importance in biological science due to the availability of large datasets. Here we present a statistical analysis of electron–nuclear double resonance, a technique that delivers information on the angstrom to nanometer scale around paramagnetic centers in proteins. The described method allows for recognizing experimental artifacts and provides the most probable signal as well as its uncertainty. Application to representative high-field electron–nuclear double resonance spectra of a prototype tyrosyl radical in a protein, the
<jats:inline-formula>
<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll">
<mml:msub>
<mml:mrow>
<mml:mi mathvariant="normal">β</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mn>2</mml:mn>
</mml:mrow>
</mml:msub>
</mml:math>
</jats:inline-formula>
subunit of
<jats:italic>Escherichia coli</jats:italic>
ribonucleotide reductase, demonstrates that subtle information can be uncovered, such as a distribution of molecular orientations relevant for the biological function of this essential radical.
</jats:p>