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
Hauptverfasser: WHIRL-CARRILLO, MICHELLE, GABASHVILI, IRENE S., BADA, MICHAEL, BANATAO, D. REY, ALTMAN, RUSS B.
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container_issue 3
container_start_page 279
container_title RNA (Cambridge)
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creator WHIRL-CARRILLO, MICHELLE
GABASHVILI, IRENE S.
BADA, MICHAEL
BANATAO, D. REY
ALTMAN, RUSS B.
description 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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subjects Algorithms
BIOINFORMATICS
Data Interpretation, Statistical
Databases, Factual
DNA Footprinting
Humans
Models, Molecular
Protein Biosynthesis
Proteins - chemistry
Ribosomes - chemistry
Ribosomes - metabolism
RNA - metabolism
title Mining biochemical information: Lessons taught by the ribosome
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