A number of heuristic descriptors have been developed previously
in conjunction with the mfold package that describe
the propensity of individual bases to participate in base
pairs and whether or not a predicted helix is “well-determined.”
They were developed for the “energy dot plot”
output of mfold. Two descriptors, P-num and H-num,
are used to measure the level of promiscuity in the association
of any given nucleotide or helix with alternative complementary
pairs. The third descriptor, S-num, measures the propensity
of bases to be single-stranded. In the current work, we
describe a series of programs that were developed in order
to annotate individual structures with “well-definedness”
information. We use color annotation to present the information.
The programs can annotate PostScript files that are created
by the mfold package or the PostScript secondary
structure plots produced by the Weiser and Noller program
XRNA (Weiser B, Noller HF, 1995, XRNA: Auto-interactive
program for modeling RNA, The Center for Molecular
Biology of RNA, Santa Cruz, California: University of California;
Internet: ftp://fangio.ucsc.edu/pub/XRNA). In addition,
these programs can annotate ss files that serve
as input to XRNA. The annotation package can also handle
structure comparison with a reference structure. This feature
can be used to compare predicted structure with a phylogenetically
deduced model, to compare two different predicted foldings,
and to identify conformational changes that are predicted
between wild-type and mutant RNAs.
We provide several examples of application. Predicted structures
of two RNase P RNAs were colored with P-num information
and further annotated with comparative information. The
comparative model of a 16S rRNA was annotated with P-num
information from mfold and with base pair probabilities
obtained from the Vienna RNA folding package. Further annotation
adds comparisons with the optimal foldings obtained from
mfold and the Vienna package, respectively. The
results of all of these analyses are discussed in the context
of the reliability of structure prediction.