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

NucPred

Fetching O75037 from www.uniprot.org...

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

   1  MAGQGDCCVKVAVRIRPQLSKEKIEGCHICTSVTPGEPQVLLGKDKAFTY    50
  51  DFVFDLDTWQEQIYSTCVSKLIEGCFEGYNATVLAYGQTGAGKTYTMGTG   100
 101  FDMATSEEEQGIIPRAIAHLFGGIAERKRRAQEQGVAGPEFKVSAQFLEL   150
 151  YNEEILDLFDSTRDPDTRHRRSNIKIHEDANGGIYTTGVTSRLIHSQEEL   200
 201  IQCLKQGALSRTTASTQMNVQSSRSHAIFTIHLCQMRMCTQPDLVNEAVT   250
 251  GLPDGTPPSSEYETLTAKFHFVDLAGSERLKRTGATGERAKEGISINCGL   300
 301  LALGNVISALGDQSKKVVHVPYRDSKLTRLLQDSLGGNSQTIMIACVSPS   350
 351  DRDFMETLNTLKYANRARNIKNKVVVNQDKTSQQISALRAEIARLQMELM   400
 401  EYKAGKRVIGEDGAEGYSDLFRENAMLQKENGALRLRVKAMQEAIDAINN   450
 451  RVTQLMSQEANLLLAKAGDGNEAIGALIQNYIREIEELRTKLLESEAMNE   500
 501  SLRRSLSRASARSPYSLGASPAAPAFGGSPASSMEDASEVIRRAKQDLER   550
 551  LKKKEVRQRRKSPEKEAFKKRAKLQQENSEETDENEAEEEEEERDESGCE   600
 601  EEEGREDEDEDSGSEESLVDSDSDPEEKEVNFQADLADLTCEIEIKQKLI   650
 651  DELENSQRRLQTLKHQYEEKLILLQNKIRDTQLERDRVLQNLSTMECYTE   700
 701  EKANKIKADYEKRLREMNRDLQKLQAAQKEHARLLKNQSRYERELKKLQA   750
 751  EVAEMKKAKVALMKQMREEQQRRRLVETKRNREIAQLKKEQRRQEFQIRA   800
 801  LESQKRQQEMVLRRKTQEVSALRRLAKPMSERVAGRAGLKPPMLDSGAEV   850
 851  SASTTSSEAESGARSVSSIVRQWNRKINHFLGDHPAPTVNGTRPARKKFQ   900
 901  KKGASQSFSKAARLKWQSLERRIIDIVMQRMTIVNLEADMERLIKKREEL   950
 951  FLLQEALRRKRERLQAESPEEEKGLQELAEEIEVLAANIDYINDGITDCQ  1000
1001  ATIVQLEETKEELDSTDTSVVISSCSLAEARLLLDNFLKASIDKGLQVAQ  1050
1051  KEAQIRLLEGRLRQTDMAGSSQNHLLLDALREKAEAHPELQALIYNVQQE  1100
1101  NGYASTDEEISEFSEGSFSQSFTMKGSTSHDDFKFKSEPKLSAQMKAVSA  1150
1151  ECLGPPLDISTKNITKSLASLVEIKEDGVGFSVRDPYYRDRVSRTVSLPT  1200
1201  RGSTFPRQSRATETSPLTRRKSYDRGQPIRSTDVGFTPPSSPPTRPRNDR  1250
1251  NVFSRLTSNQSQGSALDKSDDSDSSLSEVLRGIISPVGGAKGARTAPLQC  1300
1301  VSMAEGHTKPILCLDATDELLFTGSKDRSCKMWNLVTGQEIAALKGHPNN  1350
1351  VVSIKYCSHSGLVFSVSTSYIKVWDIRDSAKCIRTLTSSGQVISGDACAA  1400
1401  TSTRAITSAQGEHQINQIALSPSGTMLYAASGNAVRIWELSRFQPVGKLT  1450
1451  GHIGPVMCLTVTQTASQHDLVVTGSKDHYVKMFELGECVTGTIGPTHNFE  1500
1501  PPHYDGIECLAIQGDILFSGSRDNGIKKWDLDQQELIQQIPNAHKDWVCA  1550
1551  LAFIPGRPMLLSACRAGVIKVWNVDNFTPIGEIKGHDSPINAICTNAKHI  1600
1601  FTASSDCRVKLWNYVPGLTPCLPRRVLAIKGRATTLP               1637

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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