SARA (Structural Alignment of Ribonucleic Acids) v1.0
Emidio Capriotti & Marc A. Marti-Renom
http://structure.biofold.org/sara

SETUP
Requirements: python, numpy, biopython and X3DNA

1) Uncompress the sara.tar.gz file
2) Download and uncompress X3DNA from
   http://x3dna.org/
3) Go in the SARA directory and type "python setup.py"
   or edit Tools/ENVIRON file typing the correct find_pair path
4) Test the program running 
   "python runsara.py Test/pdb1q96.ent A Test/pdb1u6b.ent B -b -s"


The SARA program calculates RNA structural alignment between two RNA chains.
It is a python script that needs the istallation of numpy and biopython and
also X3DNA (Lu and Olson 2003).
The runsara.py program is called as follows

	python runsara.py pdbfile1 chain1 pdbfile2 chain2 -b -s 

Optional parameters include

	-a Atom type. The default is C3* but also P atom can be used.
	   In the new PDB format * has been sustituted with '
	   (for exaple C3* have to be substituted with C3\');
        -o Alignment output file name;
	-p PDB output file name (without .pdb extension);
        -g Gap open penalty. Default value 7.00 
	-e Gap extension penalty. Default value 0.60;
	-l Number of unit-vectors. Default values 3 or 7 for the use or
	   not of seconadary structure, respectively;
        -b Evaluates secondary structure base alignment;
	-c Cut-off distance for alignment evaluation. Default 4.0Ang;
	-s optimize superimposition between two structures

GENERAL INFORMATION:

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.

SARA is an implementation for RNA structure of the methods described in 
the following papers:

1. Capriotti E, Marti-Renom MA. (2008) RNA structure alignment by a unit-vector 
   approach. Bioinformatics, 24; i112-i116. 
2. Capriotti E, Marti-Renom MA. (2009). SARA: a server for function annotation 
   of RNA structures. Nucleic Acids Res. 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, 
   16, 776-785. 
