SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching Q5T200 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MSKIRRKVTVENTKTISDSTSRRPSVFERLGPSTGSTAETQCRNWLKTGN    50
  51  CLYGNTCRFVHGPSPRGKGYSSNYRRSPERPTGDLRERMKNKRQDVDTEP   100
 101  QKRNTEESSSPVRKESSRGRHREKEDIKITKERTPESEEENVEWETNRDD   150
 151  SDNGDINYDYVHELSLEMKRQKIQRELMKLEQENMEKREEIIIKKEVSPE   200
 201  VVRSKLSPSPSLRKSSKSPKRKSSPKSSSASKKDRKTSAVSSPLLDQQRN   250
 251  SKTNQSKKKGPRTPSPPPPIPEDIALGKKYKEKYKVKDRIEEKTRDGKDR   300
 301  GRDFERQREKRDKPRSTSPAGQHHSPISSRHHSSSSQSGSSIQRHSPSPR   350
 351  RKRTPSPSYQRTLTPPLRRSASPYPSHSLSSPQRKQSPPRHRSPMREKGR   400
 401  HDHERTSQSHDRRHERREDTRGKRDREKDSREEREYEQDQSSSRDHRDDR   450
 451  EPRDGRDRRDARDTRDRRELRDSRDMRDSREMRDYSRDTKESRDPRDSRS   500
 501  TRDAHDYRDREGRDTHRKEDTYPEESRSYGRNHLREESSRTEIRNESRNE   550
 551  SRSEIRNDRMGRSRGRVPELPEKGSRGSRGSQIDSHSSNSNYHDSWETRS   600
 601  SYPERDRYPERDNRDQARDSSFERRHGERDRRDNRERDQRPSSPIRHQGR   650
 651  NDELERDERREERRVDRVDDRRDERARERDRERERDRERERERERERDRE   700
 701  REKERELERERAREREREREKERDRERDRDRDHDRERERERERDREKERE   750
 751  REREERERERERERERERERERERERARERDKERERQRDWEDKDKGRDDR   800
 801  REKREEIREDRNPRDGHDERKSKKRYRNEGSPSPRQSPKRRREHSPDSDA   850
 851  YNSGDDKNEKHRLLSQVVRPQESRSLSPSHLTEDRQGRWKEEDRKPERKE   900
 901  SSRRYEEQELKEKVSSVDKQREQTEILESSRMRAQDIIGHHQSEDRETSD   950
 951  RAHDENKKKAKIQKKPIKKKKEDDVGIERGNIETTSEDGQVFSPKKGQKK  1000
1001  KSIEKKRKKSKGDSDISDEEAAQQSKKKRGPRTPPITTKEELVEMCNGKN  1050
1051  GILEDSQKKEDTAFSDWSDEDVPDRTEVTEAEHTATATTPGSTPSPLSSL  1100
1101  LPPPPPVATATATTVPATLAATTAAAATSFSTSAITISTSATPTNTTNNT  1150
1151  FANEDSHRKCHRTRVEKVETPHVTIEDAQHRKPMDQKRSSSLGSNRSNRS  1200
1201  HTSGRLRSPSNDSAHRSGDDQSGRKRVLHSGSRDREKTKSLEITGERKSR  1250
1251  IDQLKRGEPSRSTSSDRQDSRSHSSRRSSPESDRQVHSRSGSFDSRDRLQ  1300
1301  ERDRYEHDRERERERRDTRQREWDRDADKDWPRNRDRDRLRERERERERD  1350
1351  KRRDLDRERERLISDSVERDRDRDRDRTFESSQIESVKRCEAKLEGEHER  1400
1401  DLESTSRDSLALDKERMDKDLGSVQGFEETNKSERTESLEGDDESKLDDA  1450
1451  HSLGSGAGEGYEPISDDELDEILAGDAEKREDQQDEEKMPDPLDVIDVDW  1500
1501  SGLMPKHPKEPREPGAALLKFTPGAVMLRVGISKKLAGSELFAKVKETCQ  1550
1551  RLLEKPKDADNLFEHELGALNMAALLRKEERASLLSNLGPCCKALCFRRD  1600
1601  SAIRKQLVKNEKGTIKQAYTSAPMVDNELLRLSLRLFKRKTTCHAPGHEK  1650
1651  TEDNKLSQSSIQQELCVS                                  1668

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

What does the NucPred score mean?

You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper.

NucPred score threshold Specificity Sensitivity
see above fraction of proteins predicted to be nuclear that actually are nuclear fraction of true nuclear proteins that are predicted (coverage)
0.10 0.45 0.88
0.20 0.52 0.83
0.30 0.57 0.77
0.40 0.63 0.69
0.50 0.70 0.62
0.60 0.71 0.53
0.70 0.81 0.44
0.80 0.84 0.32
0.90 0.88 0.21
1.00 1.00 0.02

Sequences which score >= 0.8 with NucPred and which are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.)

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