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                                     by
                          C. Geourjon & G. Deleage
 
                 Institut de Biologie et Chimie des Proteines
                             IBCP-CNRS UPR 412
                      Groupe de modelisation et RMN
                          7, Passage du vercors
                          69 367 Lyon cedex 07
                                  France
                         Tel : (33) 72 72 26 47
                         Fax : (33) 72 72 26 01
                              deleage@ibcp.fr
                              geourjon@ibcp.fr
                      Web page : http://www.ibcp.fr
 

                SOPMA (Self Optimized Prediction Method from Alignment) is a
package to make secondary structure predictions of proteins. This program is
developed for Unix workstations and has been successfully checked onto IBM
rs6000 workstations and SGI.

                1       10        20        30        40        50        60
                |        |         |         |         |         |         |
IBCP-Web server MALDGPEQMELEEGKAGSGLRQYYLSKIEELQLIVNDKSQNLRRLQAQRNELNAKVRLLR
Gibrat method   HCCCCCCHHHHHHHHCCCCCEEEEECHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH
Levin method    ECCCCCCCHHHHHHCCTTTCHHHHCCHHHHHHEEECCTCHCHHHHHHHHHHHHHHHHHHH
DPM method      CCHCTCHHHHHHHCTTTCCCCCCCHCHHHHHHHEECCCTCCHHHHHHHHCHHCHHHHHHH
SOPMA predict   CCCCCHHHHHHHHHHHCCHHHHHHHHHCCHHCCCCCCCTHHHHHHHHHHHHTTHHHHHHH
Consensus       CCCCCCCHHHHHHHHCCCCCHHHHHCHHHHHHHEECCCTHCHHHHHHHHHHHHHHHHHHH
   
IBCP-Web server RELQLLQEQGSYVGEVVRAMDKKKVLVKVHPEGKFVVDVDKNIDINDVTPNCRVALRNDS
Gibrat method   HHHHHHHHCCCCCCHHHHHHHHHHHHHHHCCCCHEEHHHHCCCCCCCCCCCCEEEECCCC
Levin method    HHHHHCHCHHHCHHHHHHHHHHSCEEEEECTTSCCCEECCSCCCCCTCCCCCCEEECTTS
DPM method      HHHHHHHHTTCCECHEEHHHHHHHEEEHECCCCCEEECECCCCCCCCCCCCCHHHHHCCC
SOPMA predict   HHHHHHHHHCCCHHHEEECCCHHHEEEEECCTTCEEEEETCCCCTHHHCCCCEEEHCCCC
Consensus       HHHHHHHHHCCCHCHHHHHHHHHHEEEHECCCCCEEEEECCCCCCCCCCCCCEEEHCCCC
   
IBCP-Web server YTLHKILPNKVDPLVSLMMVEKVPDSTYEMIGGLDKQIKEIKEVIELPVKHPELFEALGI
Gibrat method   HHHHHHCCCCCCCHHHHHHEECCCCCCHHEHHCCHHHHHHHHHHHHHHHCCHHHHHHHHH
Levin method    ECEHTECCTCCCHHHEEEEEHCCCTCCHHEHHSCHHHHHHHHHHHHCCCSCCHHHHHHCC
DPM method      CCCCCCCCCCCCCCEEHHHHHHCCCCCCCHCCCCCCHHHHHHHHEHHCCCCCHHHHHHCH
SOPMA predict   CCCEEECTTTCCHHCTTEEETTCCCCEEEEHHCCCCCHHHHHHHHHHHCCCCCTEEEEEE
Consensus       CCCH-ECCCCCCCHHEHHHEHCCCCCCHHEHHCCCCHHHHHHHHHHHCCCCCHHHHHHCH
   
IBCP-Web server AQPKGVLLYGPPGTGKTLLARAVAHHTDCTFIRVSGSELVQKFIGEGARMVRELFVMARE
Gibrat method   HCCCCEEEECCCCCCHHHHHHHHHCCCCEEEEEECCCCEEEEEHHCCHHHHHHHHHHHHH
Levin method    CSCSEEEEECCCCSCHHHHHHHHHHCCCCEEEEECTHHHHHHHHHCTHHHHHHHHHHHTT
DPM method      HCCCCECCCCCCTCCCCHHHHHHHHCCCCCEEEECTCHHEHHHECCCHHHHHHHHHHHHH
SOPMA predict   EEETTEEEEECCCCCTHHHHHHHHHEEEEEEEECCCTHEEEEEEHCTHHHHHHHHHHHHH
Consensus       HCCCCEEEECCCCCCHHHHHHHHHHCCCCEEEEECCCHHEHHHHHCCHHHHHHHHHHHHH
   
IBCP-Web server HAPSIIFMDEIDSIGSSRLEGGSGGDSEVQRTMLELLNQLDGFEATKNIKVIMATNRIDI
Gibrat method   CCCCHEEEEEECCCCEEEEECCCCCCCEHHHHHHHHHHHHHHHHHHHHHHHHHHHCCHHH
Levin method    CCCCCEEECHCSCCCCSCCCCCCTCCHHHHHHHHHHHHHHHHHHHHHCHHEEECTSCCCE
DPM method      HHCCEEEHHHCCCCCTCCTTTTTTTTCCHHHHHHHHHCHHCCHHHCHCEHEEHHCCHCCC
SOPMA predict   HCCEEEEEECCCCCCCCTECCCCCCCCTHHHHHHHHHHHHTCHHHHHHHHHEECTTTCCE
Consensus       CCCCEEEEEHCCCCCCCCECCCCCCCC-HHHHHHHHHHHHHCHHHHHCHHHEHCTCCCCE
   
IBCP-Web server LDSALLRPGRIDRKIEFPPPNEEARLDILKIHSRKMNLTRGINLRKIAELMPGASGAEVK
Gibrat method   HHHHHHCCCCECCEECCCCCCHHHHHHHHHHHHHHHCHHHHHHHHHHHHHCHCCCCCCEE
Levin method    EHHHHHCTTCCCTCCCCCCCCCCHHEEEHHHCTSCCCCCTCCCHHHHHHHCTTCCCHHHH
DPM method      HCCHHHCCCCCCHHHCCCCCCCHHHHHHHHECCHHHCCCCCCCHHHHHHHHCTTCCCHHC
SOPMA predict   EHTTTCEECCCCEEECCCCCCHHHHHHHHHHHHHEEECCCCCCHHHHHHHETTTTTCEEE
Consensus       HHHHHHCCCCCC-EECCCCCCCHHHHHHHHHCHHHHCCCCCCCHHHHHHHCTTCCCCHHE
   
IBCP-Web server GVCTEAGMYALRERRVHVTQEDFEMAVAKVMQKDSEKNMSIKKLWK              
Gibrat method   EEEHHHCCHHEHHHEEECCHHHHHHHHHHHHHHHHHHHHHHHHHHH              
Levin method    HHCHHHHHHHHHHHCSCCCTHHHHHHHHHHHHSTHCCHHHHHHHHH              
DPM method      CECCHHCHHHHHHHHEHECHHHHHHHHHHHHHHTCCCTHCHHHHCC              
SOPMA predict   EEEEHHHEEHHHHHEEEEEHHHHHHHHHHHHHCCCCCCCCHHHHHH              
Consensus       EECHHHCHHHHHHHEEECCHHHHHHHHHHHHHCTCCCHHCHHHHHH              
   
>Please in your publication cite :
 
"SOPM : a self optimised prediction method for protein secondary structure      
prediction."                                                                    
C. Geourjon & G. Deleage, 1994, Protein Engineering, 7, 157-164                 
 
"SOPMA : Significant improvements in protein secondary  structure prediction by 
prediction from multiple alignments."                                           
C. Geourjon & G. Deleage, 1995, Comput. Applic. Biosci., 11, 681-684            
 
Other methods : 
 Gibrat method    : Gibrat et al., (1987) J.Mol.Biol. 198, 425-443
 Levin method     : Levin et al., (1986) Febs Lett. 205, 303-308
 DPM method       : Deleage & Roux, (1987) Prot. Engng. 1, 289-294
 PhD method       : Rost & Sander, (1994) Proteins, 19, 55-72
 
In the prediction : 
  H, G : Helix 
  E    : Sheet
  C    : coil
  S    : Bend
  B    : bridges

 
=========================  SOPMA accuracy  ================================
 
  As checked on our SOPM.BASE (233 proteins chains)
  +--------------------------+---------+----------+----------+-----------+
  |  States                  |  Coil   |   Helix  |   Sheet  |     All   |
  +--------------------------+---------+----------+----------+-----------+
  |  Accuracy                |  77.50  |   72.20  |   65.40  |    73.20  |
  |                          |         |          |          |           |
  |  Standard deviation      |   9.43  |    8.66  |    8.98  |      -    |
  |                          |         |          |          |           |
  |  Correlation Coeficients |   0.54  |    0.62  |    0.57  |      -    |
  |    (Matthews coeficient) |         |          |          |           |
  |                          |         |          |          |           |
  |  SOV Coeficients         |   0.67  |    0.74  |    0.78  |     0.71  |
  +--------------------------+---------+----------+----------+-----------+
 
  As checked on Rost and Sander database (126 proteins chains)
  +--------------------------+---------+----------+----------+-----------+
  |  States                  |  Coil   |   Helix  |   Sheet  |     All   |
  +--------------------------+---------+----------+----------+-----------+
  |  Accuracy                |  74.80  |   70.40  |   60.30  |    69.50  |
  |                          |         |          |          |           |
  |  Standard deviation      |  12.00  |   12.00  |   10.80  |      -    |
  |                          |         |          |          |           |
  |  Correlation Coeficients |   0.48  |    0.56  |    0.51  |      -    |
  |    (Matthews coeficient) |         |          |          |           |
  |                          |         |          |          |           |
  |  SOV Coeficients         |   0.63  |    0.74  |    0.72  |     0.68  |
  +--------------------------+---------+----------+----------+-----------+
 
=========================  SOPMA references ================================
 
  1/ A brief description is given in:
            "SOPM : a self optimised prediction method for protein
             secondary structure prediction."
             C. Geourjon & G. Deleage, 1994, Protein Engineering, 7, 157-164
 
  2/ Latest improvement steps and SOPMA mail server are explained in:
            "SOPMA : Significant improvements in protein secondary
             structure prediction by prediction from multiple alignments."
             C. Geourjon & G. Deleage, 1995, Comput. Appli. Biosc., In press
 

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BCM HGSC