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

NucPred

Fetching Q9ZNZ7 from www.uniprot.org...

The NucPred score for your sequence is 0.29 (see score help below)

   1  MAMQSLSPVPKLLSTTPSSVLSSDKNFFFVDFVGLYCKSKRTRRRLRGDS    50
  51  SSSSRSSSSLSRLSSVRAVIDLERVHGVSEKDLSSPSALRPQVANLEDIL   100
 101  SERGACGVGFIANLDNIPSHGVVKDALIALGCMEHRGGCGADNDSGDGSG   150
 151  LMSSIPWDFFNVWAKEQSLAPFDKLHTGVGMIFLPQDDTFMQEAKQVIEN   200
 201  IFEKEGLQVLGWREVPVNVPIVGKNARETMPNIQQVFVKIAKEDSTDDIE   250
 251  RELYICRKLIERAVATESWGTELYFCSLSNQTIVYKGMLRSEALGLFYLD   300
 301  LQNELYESPFAIYHRRYSTNTSPRWPLAQPMRFLGHNGEINTIQGNLNWM   350
 351  QSREASLKAAVWNGRENEIRPFGNPRGSDSANLDSAAEIMIRSGRTPEEA   400
 401  LMILVPEAYKNHPTLSVKYPEVVDFYDYYKGQMEAWDGPALLLFSDGKTV   450
 451  GACLDRNGLRPARYWRTSDNFVYVASEVGVVPVDEAKVTMKGRLGPGMMI   500
 501  AVDLVNGQVYENTEVKKRISSFNPYGKWIKENSRFLKPVNFKSSTVMENE   550
 551  EILRSQQAFGYSSEDVQMVIESMASQGKEPTFCMGDDIPLAGLSQRPHML   600
 601  YDYFKQRFAQVTNPAIDPLREGLVMSLEVNIGKRGNILELGPENASQVIL   650
 651  SNPVLNEGALEELMKDQYLKPKVLSTYFDIRKGVEGSLQKALYYLCEAAD   700
 701  DAVRSGSQLLVLSDRSDRLEPTRPSIPIMLAVGAVHQHLIQNGLRMSASI   750
 751  VADTAQCFSTHHFACLVGYGASAVCPYLALETCRQWRLSNKTVAFMRNGK   800
 801  IPTVTIEQAQKNYTKAVNAGLLKILSKMGISLLSSYCGAQIFEIYGLGQD   850
 851  VVDLAFTGSVSKISGLTFDELARETLSFWVKAFSEDTTKRLENFGFIQFR   900
 901  PGGEYHSNNPEMSKLLHKAVREKSETAYAVYQQHLSNRPVNVLRDLLEFK   950
 951  SDRAPIPVGKVEPAVAIVQRFCTGGMSLGAISRETHEAIAIAMNRIGGKS  1000
1001  NSGEGGEDPIRWKPLTDVVDGYSPTLPHLKGLQNGDIATSAIKQVASGRF  1050
1051  GVTPTFLVNADQLEIKVAQGAKPGEGGQLPGKKVSAYIARLRSSKPGVPL  1100
1101  ISPPPHHDIYSIEDLAQLIFDLHQINPNAKVSVKLVAEAGIGTVASGVAK  1150
1151  GNADIIQISGHDGGTGASPISSIKHAGGPWELGLTETHQTLIANGLRERV  1200
1201  ILRVDGGLKSGVDVLMAAAMGADEYGFGSLAMIATGCVMARICHTNNCPV  1250
1251  GVASQREELRARFPGVPGDLVNYFLYVAEEVRGILAQLGYNSLDDIIGRT  1300
1301  ELLRPRDISLVKTQHLDLSYLLSSVGTPSLSSTEIRKQEVHTNGPVLDDD  1350
1351  ILADPLVIDAIENEKVVEKTVKICNVDRAACGRVAGVIAKKYGDTGFAGQ  1400
1401  VNLTFLGSAGQSFGCFLIPGMNIRLIGESNDYVGKGMAGGEIVVTPVEKI  1450
1451  GFVPEEATIVGNTCLYGATGGQIFARGKAGERFAVRNSLAEAVVEGTGDH  1500
1501  CCEYMTGGCVVVLGKVGRNVAAGMTGGLAYLLDEDDTLLPKINREIVKIQ  1550
1551  RVTAPAGELQLKSLIEAHVEKTGSSKGATILNEWEKYLPLFWQLVPPSEE  1600
1601  DTPEASAAYVRTSTGEVTFQSA                              1622

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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