Structure detection through automated covariance search
Mathematics and Computer Science Division, Argonne National Laboratory Argonne, IL 60439
1Microbiology Department, University of Illinois at Urbana Urbana, IL 61801
2Department of Computer Science, Texas A&M University College Station, TX 77840, USA
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This paper summarizes our investigations into the computational detection of secondary and tertiary structure of ribosomal RNA. We have developed a new automated procedure that not only identifies potential secondary and tertiary structural interactions, but also provides the covariation evidence that supports the proposed bondings, and any counterevidence that can be detected in the known sequences. A small number of previously unknown higher-order structural features have been detected in individual RNA molecules (16S rRNA and 7S RNA) through the use of our automated procedure. We are systematically studying mitochondrial rRNA, seeking tertiary structure within 16S rRNA and quaternary structure between J6Sand 23S rRNA. To test hypotheses suggested by an examination of our program's output, our colleagues in biology are sequencing key portions of the 23S ribosomal RNA for species in which the known 16S ribosomal RNA exhibits variation (from the dominant pattern) at the site of a proposed bonding. Our ultimate hope is that automated covariation analysis will contribute significantly to a refined picture of ribosomal structure.
Received on January 17, 1990; accepted on June 1, 1990
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