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To use SARA you need to either:
- Enter a PDB chain id (e.g., 1a9n) and the corresponding chain
identifier for the RNA molecules (e.g., Q).
- Upload a PDB formated file containing the RNA structure to annotate.
- Alternatively, SARA accepts NDB codes and their chain ids (e.g., AD0020).
NDB ids are converted to their corresponding PDB ids before SARA's run.
The default usage of SARA would calculate an alignment of the given RNA
structure against a selected set of 162 SCOR entries (192 if large structures
are included). SARA alignments are carried with optimal parameters using
secondary structure: open gap penalty of 7.00, extension gap penalty of 0.60
and Unit-vector length of 3. In the case of not being able to obtain secondary
structure informtion, the optimal parameter for are: open gap penalty of 8.00,
extension gap penalty of 0.20 and Unit-vector length of 7.
Optional parameters include:
- Opening and extension gap penalties to be used during dynamic programming.
Optimal values are -7.00 for opening gap and -0.60 for extension gap.
- Length of the Unit-Vector used to generate the comparison matrix.
Optimal value is 3 consecutive vectors (4 atoms).
- The use of phosphate or C3' atoms to represent the three-dimensional coordinates.
If C3' atoms are not found the phospate atoms are automatically considered.
- The use of secondary structure information calculated from the structure using
the X3DNA program.
If secondary structure are not calculated the basic unit-vector method is used.
SARA (Structure Alignment of Ribonucleic Acids) is a fully automated
method for aligning two RNA structures. SARA computes a unit-vector
root mean square (URMS) distance between all pairs of four successive
base pairs. Once an all-against-all matrix is computed, a Dynamic Programming
algorithm identifies the common similar regions between the two
structures. Finally, a statistical significance of the alignment is
calculated based on a background distibution of random alignments.
Currently, the SARA server is limited to align RNA structures of 9 to 1,000
nucleotides of length. The lower limit constrain is due to its algorithmic
implementation, while the upper limit constrain is due to CPU availability.
SARA and the methods used in SARA are described in the following papers:
1. Capriotti, E. and Marti-Renom, M.A. (2008) RNA structure alignment by a
unit-vector approach. Bioinformatics, 24, i112-i118.
2. Capriotti E, Marti-Renom MA. (2009). SARA: a server for function annotation
of RNA structures. Nucleic Acids Research. 37 (Web Server issue): W260-W265.
3. Ortiz, A.R., Strauss, C.E. and Olmea, O. (2002) MAMMOTH (matching molecular
models obtained from theory): an automated method for model comparison, Pro-
tein Sci, 11, 2606-2621.
4. Kedem, K., Chew, L.P. and Elber, R. (1999) Unit-vector RMS (URMS) as a tool to
analyze molecular dynamics trajectories, Proteins, 37, 554-564.
5. Chew, L., Huttlenlocher, D., Kedem, K. and Kleinberg, J. (1999) Fast detection of
common geometric substructure in proteins. J. Comput. Biol. 6, 313-325.
6. Siew, N., Elofsson, A., Rychlewski, L. and Fischer, D. (2000) MaxSub: an automated
measure for the assessment of protein structure prediction quality, Bioinformatics,
STRUCTURE SETS AND DOWNLOADS:
The sets of structures used to optimze and benchmark SARA are avilable
precompiled versions of SARA are available at this