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       UniCon3D: de novo protein structure prediction using united-residue 
          conformational search via stepwise, probabilistic sampling

Purpose  :  United-residue protein folding via stepwise, probabilistic sampling
Author   :  Debswapna Bhattacharya
Lab      :  Bioinformatics, Data Mining, Machine Learning (BDM) Laboratory 
            University of Missouri, Columbia MO 65211
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Developer:
		Debswapna Bhattacharya
		Department of Computer Science
		University of Missouri, Columbia
		Email: db279@mail.missouri.edu

Contact:
		Jianlin Cheng, PhD
		Department of Computer Science
		University of Missouri, Columbia
		Email: chengji@missouri.edu

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1. INSTALLATION
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Binaries for linux 64 bit system and osx has been included in the package and 
no installation is needed when using binaries. The linux binary was compiled 
using GNU Fortran (GCC) 4.1.2 20080704 (Red Hat 4.1.2-54) and the osx binary was 
compiled using GNU Fortran (GCC) 5.1.0. Users need to have these versions of 
Fortran and GCC compilers when using binaries. Alternatively, users may install 
it from the source.

Please Follow the below steps to install it from source:

1) download and install Mocapy++ software package from sourceforge at:
   http://sourceforge.net/projects/mocapy/

2) copy and paste UniCon3D source code from /src folder in UniCon3D package 
   to the examples folder of Mocapy++.
   
3) edit CMakeLists.txt file under examples folder of Mocapy++ to include FRAGSION:
   SET(PROGS UniCon3D)

4) compile and link it by typing make.

   Installation is done!

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2. USAGE
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The binary UniCon3D has various options which can be seen during execution. 
Run UniCon3D in help mode to explore the options:

e.g. ./UniCon3D -h

Usage: ./UniCon3D -i id -f fasta -s ss -c cmap -m model
   -i id     : job id                                     : mandatory
   -f fasta  : fasta file                                 : mandatory
   -s ss     : secondary structure file                   : mandatory
   -c cmap   : contact map file                           : mandatory
   -m model  : model file                                 : mandatory
   -d decoy  : number of decoys to generate               : optional (default is 100)
   -x factor : increase monte carlo cycles by this factor : optional (default is 1)
   -n native : native structure for comparison            : optional
   -h help   : this message

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3. OUTPUT
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UniCon3D produces two types of output files: (1) decoys and (2) stats.

(1) decoys : The decoy files are named as <Job-ID>_xxxxxx.pdb in united-residue 
             format having coordinates of CA and SC atoms only. By default, 100
             decoys are generated that can be changed by setting -d option. 

(2) stats  : The folding statistics file is named as <Job-ID>_stats.txt and
             contains the individual as well as weighted total energy for each
             decoy. In case, the native structure is provided for comparison,
             CA-rmsd of each decoy compared to the native is also shown. 

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4. TEST
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Please Follow the below steps to test it in linux environment:

1) Go to the examples folder of UniCon3D package to locate example input files.

2) Execute UniCon3D using exmaple input to generate 10 decoys:
	 ../bin/linux/UniCon3D -i test -f test.fa -s test.ss -c test.cm -m ../lib/UniCon.iohmm -d 10

3) 10 decoys are generated in the examples folder starting from test_000001.pdb to
   test_000010.pdb and test_stats.txt contains the folding statistics.

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5. DISCLAIMER
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The executable software and the source code of UniCon3D is distributed free of 
charge as it is to any non-commercial users. The authors hold no liabilities to 
the performance of the program.

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6. RELEASE NOTES
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Version                  Released On                    Comments
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1.0                      March 2016                 First released version