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

NucPred

Fetching Q9VAW5 from www.uniprot.org...

The NucPred score for your sequence is 0.98 (see score help below)

   1  MSSKEETPSTGGAAPVATVAASGSATTSYANVVQNLETKKSGTSNTTTTT    50
  51  ARATVDNKENQPNLKSFKSWSEEAAAAEAAGESPIVGSVSLAQTGEKRAA   100
 101  ASGGDNTAENSSELDDNNDFVPVLSHHRRDRKKARKEKPRDQQPAGGRGD   150
 151  GQKPQQAGGRRVPGSSDTERKSVRPRAPRGGSPRKSAAGAAGAAGSNAGA   200
 201  VSSAVPGGPKVHKDRKDTSPSASIEGAGSSGNEAKSADGDQQAGEKGAAG   250
 251  AAPPPKRFIAAPPPKVNAWKISAKQSGSPKAGTSPLDKRVLQPKAQQQQQ   300
 301  QTKQTASQNNNAQNTASNKKTQQQQQPQQGATTTTQTTTAAAAAATAAAA   350
 351  ATAATTSAAAATSSAAAVPAATTETATTTTVDASQADALAKVVVKDKKKV   400
 401  NQKASDFSNVGDWPTLIGGTSGSGKATSNEPKRNPTKKQQSAKTAAAVAA   450
 451  SSNTTSSEVATESNVAGTTSSSNSNPSSSTTTTNTTTNSQATTAPVASTS   500
 501  HDAKAQRDAEPAANSAAGTTGTAAGPALTKKIPKHKWRPLPIDLAKSSRP   550
 551  KPIGGRPNRRFSDDIADQRRPPRVYHDRQPGAGGAGVESRHPHAGRHPYG   600
 601  SRPATATSERVDSWRSSSSTTTAAFDEQRSGAAGGAGAAGTGVGSATRGP   650
 651  RRYRTPYRGGRQGRGGFSRQGPGRPTYRIPRHLLASGEYANYLPADAAGA   700
 701  DSQSSYVLMGTHYFGNVPAAYIELDANSIKEAIKKQVEYYFSVDNLTGDF   750
 751  FLRRKMDPEGYIPVTLIASFHRVLALTTDVAVIVNAIKESDKLELFEGYK   800
 801  VRTKTTPTTWPITEVPEVNEGEPKAIGTLEQEQLEQNDGQEKLEEQTEAD   850
 851  SPPPILTSAMATKPLNSIPPPPMPRNPQNLVPKMLQDKQQSRSSTIAALN   900
 901  SVNAISALTQQVEGGAAELAGHLSGLAESVKPKSTSTPDKRNAASAGNGA   950
 951  GSAAALVAEPEGIWKEVKRRSKTNAIKENATTPPQQQQPPLSQTLNNNND  1000
1001  NVKTNNTSSKSKSSSNNAPSNASSSATVCVTTNNASSATKATTKTTTTST  1050
1051  ATTTTNNNIKSGNAAYSKTHSKSSSKTAAPPSAQCHAEKEELDFQFDEEL  1100
1101  MDPLPPGTGRINNFTENFSDDDESDYEFADRDINKLLIVAQVGRAPKHEG  1150
1151  YDRTADFTSRTKITQDLENIINDGLVNYEEDLWTTTNVVADYKTVNVISQ  1200
1201  ADFEKLAGGRNKSVLPPQVVPPPPPFEEDLDETLVGDTTLNSTLNNTLKS  1250
1251  RRARFYAAPNSHSIDPRTPRKRKLRHTANPPVEAHVGWLLDTVEHRPRTT  1300
1301  SMGSSAGTSPTASSYGSFGSSVPQSLPVFQHPSHALLKENNFTQQAYHKY  1350
1351  HSRCLKERRRLGYGQSQEMNTLYRFWSFFLRENFNKSMYNEFRSLALEDA  1400
1401  GNGFRYGLECLFRFFSYGLEKKFRPNIYQDFQDETIADYETGQLYGLEKF  1450
1451  WAFLKYYKNGEKLEVQPKLAEYLKSFKNIEDFRVVEPEINEMLQGVGSLN  1500
1501  PGRQLNRHRSVSESDGTAVIAAGGRRLNTTITNRSDYVGRLLQQQHQQQQ  1550
1551  QQQHHQYQQGYGGYNQQQNRRRTGSFGSTTVRIRSGSLGNKPQVANRNQG  1600
1601  SQHELRRGGSNSGLAPHKRQQQQKPKPGAGSQTGSTRATTSAAATATTAA  1650
1651  SAATSTAATPAVTVSSGSSSSKK                             1673

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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