Mining biochemical information: Lessons taught by the ribosome
The publication of the crystal structures of the ribosome offers an opportunity to retrospectively evaluate the information content of hundreds of qualitative biochemical and biophysical studies of these structures. We assessed the correspondence between more than 2,500 experimental proximity measur...
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Veröffentlicht in: | RNA (Cambridge) 2002-03, Vol.8 (3), p.279-289, Article S135583820202407X |
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Zusammenfassung: | The publication of the crystal structures of the ribosome offers
an opportunity to retrospectively evaluate the information content
of hundreds of qualitative biochemical and biophysical studies
of these structures. We assessed the correspondence between
more than 2,500 experimental proximity measurements and the
distances observed in the ribosomal crystals. Although detailed
experimental procedures and protocols are unique in almost each
analyzed paper, the data can be grouped into subsets with similar
patterns and analyzed in an integrative fashion. We found that,
for crosslinking, footprinting, and cleavage data, the
corresponding distances observed in crystal structures generally
did not exceed the maximum values expected (from the estimated
length of the agent and maximal anticipated deviations from
the conformations found in crystals). However, the distribution
of distances had heavier tails than those typically assumed
when building three-dimensional models, and the fraction of
incompatible distances was greater than expected. Some of these
incompatibilities can be attributed to the experimental methods
used. In addition, the accuracy of these procedures appears
to be sensitive to the different reactivities, flexibilities,
and interactions among the components. These findings demonstrate
the necessity of a very careful analysis of data used for
structural modeling and consideration of all possible parameters
that could potentially influence the quality of measurements.
We conclude that experimental proximity measurements can provide
useful distance information for structural modeling, but with
a broad distribution of inferred distance ranges. We also conclude
that development of automated modeling approaches would benefit
from better annotations of experimental data for detection and
interpretation of their significance. |
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ISSN: | 1355-8382 1469-9001 |
DOI: | 10.1017/S135583820202407X |