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disulfinder(1)


NAME

   disulfinder - cysteines disulfide bonding state and connectivity
   predictor

SYNOPSIS

   disulfinder [OPTIONS]

DESCRIPTION

   'disulfinder' is for predicting the disulfide bonding state of
   cysteines and their disulfide connectivity starting from sequence
   alone. Disulfide bridges play a major role in the stabilization of the
   folding process for several proteins. Prediction of disulfide bridges
   from sequence alone is therefore useful for the study of structural and
   functional properties of specific proteins. In addition, knowledge
   about the disulfide bonding state of cysteines may help the
   experimental structure determination process and may be useful in other
   genomic annotation tasks.  'disulfinder' predicts disulfide patterns in
   two computational stages: (1) the disulfide bonding state of each
   cysteine is predicted by a BRNN-SVM binary classifier; (2) cysteines
   that are known to participate in the formation of bridges are paired by
   a Recursive Neural Network to obtain a connectivity pattern.

REFERENCES

   A. Ceroni, A. Passerini, A. Vullo and P. Frasconi. DISULFIND: a
   Disulfide Bonding State and Cysteine Connectivity Prediction Server,
   Nucleic Acids Research, 34(Web Server issue):W177-W181, 2006.

   For the disulphide connectivity predictor see:

   A. Vullo and P. Frasconi. Disulfide Connectivity Prediction using
   Recursive Neural Networks and Evolutionary Information, Bioinformatics,
   20, 653-659, 2004.

   For the cystein bonding state predictor see:

   P. Frasconi, A. Passerini, and A. Vullo. A Two-Stage SVM Architecture
   for Predicting the Disulfide Bonding State of Cysteines, Proc. IEEE
   Workshop on Neural Networks for Signal Processing, pp.25-34, 2002.
   A.Ceroni, P.Frasconi, A.Passerini and A.Vullo. Predicting the Disulfide
   Bonding State of Cysteines with Combinations of Kernel Machines,
   Journal of VLSI Signal Processing, 35, 287-295, 2003.

OPTIONS

   -a, --alternatives=NUMBER
       alternative connectivity patterns (default=3)

   -o, --output=DIR
       output dir where predictions will be saved (default=$PWD)

   -p, --psi2=FILE|DIR
       input in psi2 format (PSI-BLAST Matrix in ASCII), either a single
       file or a directory(?). Generate this with "blastpgp -j <N> -Q
       FILE" where N >= 2.

   -r, --rootdir=DIR
       work directory (default=~/disulfinder)

   -k, --pkgdatadir=DIR
       package data directory containing Models
       (default=/usr/share/disulfinder)

   -F, --format={html|ascii}
       output format type (default=ascii)

   -d --blastdb=DIR
       blastpgp -d option (default=/data/sp+trembl)

   -c, --cleanpred
       cleanup intermediate prediction files (default=false)

   -P, --usepssm
       use pssm instead of counts for profiles (default=false)

   -C, --knownbondingstate
       assume bonding state is known (one file for each chain in directory
       <rootdir>/Predictions/Bondstate/Viterbi)     (default=false)

   -v, --version
       disulfinder version

   -?, --help
       help screen

EXAMPLES

   "disulfinder -a 1 -p
   /usr/share/doc/disulfinder/examples/res_id_41483.blastPsiMatTmb -o
   ./disulfinder_results_dir"

FILES

   /usr/share/disulfinder
       default package data directory

   ~/disulfinder
       default work directory

RESTRICTIONS

   The work directory is not cleaned up automatically.

AUTHOR

   Ceroni A, Passerini A, Vullo A, Frasconi P.

   Packaging by Laszlo Kajan <lkajan@rostlab.org>

COPYRIGHT AND LICENSE

   GPL

SEE ALSO

   See official web site for help:
       <http://disulfind.dsi.unifi.it/>

   DISULFIND: a disulfide bonding state and cysteine connectivity
   prediction server:
       <http://www.ncbi.nlm.nih.gov/pubmed/?term=16844986[uid]>



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