The program performs prediction of SS-bonding states of cysteines and locating of disulphide bridges in proteins.

**Methodology**

**Procedure:** The sequence is processed in steps.

- Secondary structure is predicted for a query sequence.
- Amino acid fragment as well as fragment of secondary structure in ±10 positions interval of each cysteine is compared with such fragments of training sets using prepared log-odds matrix, and the maximal score is defined for each set.
- Scores of comparisons with profiles (weight matrices) constructed on positive (bounded) and negative examples are calculated for a given fragment.
- Value of linear discriminant function is calculated based on 4 the most significant amino acid properties.
- The resulting score computed as a linear combination of five scores listed above is used for the recognition of SS-bonding states of cysteines.
- A neural network calculates some scores for each possible pair of cisteines forming a 'Matrix of pair scores'.
- A pattern of possible pairs of bounded cysteines is defined for maximum of sum of the scores of the matrix.

**Input Format**

Fasta formatted sequence divided by lines ≤ 80 positions in lengths is accepted.

Specially prepared alignment without gaps in the first sequence is accepted too.

**Example of alignment:**

T0129 5 182 MLISHSDLNQQLKSAGIGFNATELHGFLSGLLCGGLKDQSWLPLLYQFSN ---SYSDFSQQLKTAGIALSAAELHGFLTGLICGGIHDQSWQPLLFQFTN -LPTYPSLALALSQQAVALTPAEMHGLISGMLCGGSKDNGWQTLVHDLTN ----YDEMNRFLNQQGAGLTPAEMHGLISGMICGGNNDSSWQPLLHDLTN ----YNEMNQYLNQQGTGLTPAEMHGLISGMICGGNDDSSWLPLLHDLTN DNHAYPTGLVQPVTELYEQISQTLSDVEGFTFELGLTEDENVFTQADSLS ENHAYPTALLQEVTQIQQHISKKLADIDGFDFELWLPENEDVFTRADALS EGVAFPQALSLPLQQLHEATQEALEN-EGFMFQLLIPEGEDVFDRADALS EGLAFGHELAQALRKMHAATSDALED-DGFLFQLYLPEDVSVFDRADALA EGMAFGHELAQALRKMHSATSDALQD-DGFLFQLYLPDDVSVFDRADALA DWANQFLLGIGLAQPELAKEKGEIGEAVDDLQDICQLGYDEDDNEEELAE EWTNHFLLGLGLAQPKLDKEKGDIGEAIDDLHDICQLGYDESDDKEELSE GWVNHFLLGLGMLQPKLAQVKDEVGEAIDDLRNIAQLGYDEDEDQEELAQ GWVNHFLLGLGVTQPKLDKVTGETGEAIDDLRNIAQLGYDESEDQEELEM GWVNHFLLGLGVTQPKLDKVTGETGEAIDDLRNIAQLGYDEDEDQEELEM ALEEIIEYVRTIAMLFYSHFNEGEIESKPVLH ALEEIIEYVRTLACLLFTHFQPQLPEQKPVLH SLEEVVEYVRVAAILCHIEFTQQKPTAKPTLH SLEEIIEYVRVAALLCHDTFTRQQPTAKPTLH SLEEIIEYVRVAALLCHDTFTHPQPTAKPTLH |

**Output Format **

Query sequence

Positions of cysteines which are predicted to form disulfide bonds, matrix of pair scores results of SS-bonding states predictions, the most probable pattern of pairs.

**Example of output:**

CYS_REC Version 2. Recognition of SS-bounded cysteines >1AC5_ length=483 LPSSEEYKVAYELLPGLSEVPDPSNIPQMHAGHIPLRSEDADEQDSSDLEYFFWKFTNNDSNGNVDRPLIIWLNGGPGCSS MDGALVESGPFRVNSDGKLYLNEGSWISKGDLLFIDQPTGTGFSVEQNKDEGKIDKNKFDEDLEDVTKHFMDFLENYFKIF PEDLTRKIILSGESYAGQYIPFFANAILNHNKFSKIDGDTYDLKALLIGNGWIDPNTQSLSYLPFAMEKKLIDESNPNFKH LTNAHENCQNLINSASTDEAAHFSYQECENILNLLLSYTRESSQKGTADCLNMYNFNLKDSYPSCGMNWPKDISFVSKFFS TPGVIDSLHLDSDKIDHWKECTNSVGTKLSNPISKPSIHLLPGLLESGIEIVLFNGDKDLICNNKGVLDTIDNLKWGGIKG FSDDAVSFDWIHKSKSTDDSEEFSGYVKYDRNLTFVSVYNASHMVPFDKSLVSRGIVDIYSNDVMIIDNNGKNVMITT 7 cysteines are found in positions: 79 251 271 293 308 345 386 Matrix of pair scores POS: 79 251 271 293 308 345 79: -999 -21 -4 8 18 143 251: -21 -999 155 7 -3 -12 271: -4 155 -999 13 -20 -15 293: 8 7 13 -999 133 -8 308: 18 -3 -20 133 -999 -7 345: 143 -12 -15 -8 -7 -999 CYS 79 is SS-bounded Score= 56.7 CYS 251 is SS-bounded Score= 53.2 CYS 271 is SS-bounded Score= 47.0 CYS 293 is SS-bounded Score= 68.1 CYS 308 is SS-bounded Score= 63.9 CYS 345 is SS-bounded Score= 60.7 CYS 386 is not SS-bounded Score= -70.7 The most probable pattern of pairs: 79-345, 251-271, 293-308, |

**Performance: **
3000 positive and 3000 negative examples (i.e ± 10 fragments surrounding bounded and not bounded cysteines) were prepared from PDB sequences that were not participated in the training. An accuracy of SS-bonding states recognition by combined function on this control set was ~90%.