Contact info:
 
Mark Berjanskii
David Wishart
 
RCI-related links:
 
BMRB
PDB
PSSI
Shiftcor
RefDB
 
 
 

 


 

 

Instructions:
 
ABOUT RCI
-------------


RCI is a Python program that predicts protein flexibility by calculating the 
Random Coil Index from backbone chemical shifts (CA, CO, CB, N, HA) and 
estimating values of model-free order parameters as well as per-residue RMSD of 
NMR and MD ensembles from the Random Coil Index.


REFERENCE
---------
Mark V. Berjanskii, David S. Wishart (2005) A Simple Method To Predict Protein 
Flexibility Using Secondary Chemical Shifts. Journal of the American Chemical
 Society (Web Release Date: 05-Oct-2005;)


PROGRAMMING LANGUAGE, SOFTWARE AND OS REQUIREMENT
--------------------------------------------------
RCI is written in Python for Linux OS. It requires both Python (www.python.org) 
and Numeric (http://numeric.scipy.org/) to be installed on your system. RCI was 
tested with Python 2.3.4 and Numeric 24.0 beta 2. However, other working 
combinations of Python (version 2 and above) and Numeric could be used too. The 
authors expect that RCI will work with installations of Python and Numeric on 
Unix operating systems other than Linux. However, the program was not tested in 
a different OS environment. At the moment, RCI cannot work with Windows. 

If you want the RCI program to create figures, you will need to have Gnuplot 
(http://www.gnuplot.info/) installed on your computer. Chances are that you 
already have Gnuplot installed because it is often a part of Linux 
distributions.

Optionally, you can install Grace (http://plasma-gate.weizmann.ac.il/Grace/) to 
quickly plot output text files with results (see below). 


INSTALLATION
--------------
Uncompress the file rci.tar.gz

	>gunzip rci.tar.gz
	>tar -xvf rci.tar


USAGE
------
python program_name -b chemical_shifts [-ps -gif -jpg]

Examples: 

	python  rci_v_1c.py -b PyJCScorr  
(Only text files with results will be created)
	
	python  rci_v_1c.py -b PyJCScorr -ps          
(Text files and PostScript pictures will be created)
	
	python  rci_v_1c.py -b PyJCScorr -ps -jpg     
(Text files, PostScript and JPEG pictures will be created)

INPUT
-----

RCI requires an input file with chemical shifts that has a genuine 
BMRB NMR-STAR format. The program uses standard NMR STAR tags to parse 
the input file. It also obtains protein primary sequence from the Polymer 
Residue Sequence part of an NMR STAR-formatted file. The program will not work 
with files in NMR STAR-like format produced by some programs such as NMRVIEW. 

The input file and the RCI program should be located in the same directory.

If you are not absolutely confident in the chemical shift referencing of your 
NMR spectra, you MUST re-reference chemical shifts using either ShiftCor 
(http://redpoll.pharmacy.ualberta.ca/shiftcor/), if protein structure is 
available, or PSSI (http://pronmr.com/yunjunwang_files/yjw_pssi.html), 
if the structure is not available.

OUTPUT
------

RCI produces output text files with extension ".RCI.txt", ".MD_RMSD.txt", 
".NMR_RMSD.txt", and ".S2.txt" for the Random Coil Index, per-residue MD RMSD 
and NMR RMSD of backbone nitrogens, and model-free order parameters, 
respectively. Each file has the following three columns: (1) Residue Number, (2) 
Calculated parameter (e.g. RCI, MD RMSD, etc), (3) Residue Name.  Files with 
such a format can be easily plotted using the Grace program 
(http://plasma-gate.weizmann.ac.il/Grace/). 

Example: 

	xmgrace  PyJCScorr_RCI.txt
	
If options "-ps", "-gif", and "-jpg" are specified, the program will use Gnuplot 
installed on your computer to create pictures of per-residue distribution of 
each calculated parameter in PostScript, GIF, and JPEG formats, respectively. If 
you use these options on a computer without a Gnuplot installation, the program 
will crash. 
	
TEST FILES
----------
You can test the RCI program using included test input file "PyJCScorr" and 
compare program output file "PyJCScorr_RCI.txt" with the included test file 
"PyJCScorr_RCI.txt_compare". 

You can use the command "diff" to compare the files: 

         diff PyJCScorr_RCI.txt_compare PyJCScorr_RCI.txt

If this command produces an output, use Grace or any other plotting software to 
see whether the differences between these output files are really significant or 
if they are just negligible deviations due to a difference in round-off methods. 


MORE INFORMATION
----------------
 If you have any questions about the program, please contact David Wishart 
(david.wishart@ualberta.ca) or Mark Berjanskii(mberjans@bionmr.com)