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

NucPred

Fetching P48681 from www.uniprot.org...

The NucPred score for your sequence is 0.74 (see score help below)

   1  MEGCMGEESFQMWELNRRLEAYLARVKALEEQNELLSAELGGLRAQSADT    50
  51  SWRAHADDELAALRALVDQRWREKHAAEVARDNLAEELEGVAGRCQQLRL   100
 101  ARERTTEEVARNRRAVEAEKCARAWLSSQVAELERELEALRVAHEEERVG   150
 151  LNAQAACAPRCPAPPRGPPAPAPEVEELARRLGEAWRGAVRGYQERVAHM   200
 201  ETSLGQARERLGRAVQGAREGRLELQQLQAERGGLLERRAALEQRLEGRW   250
 251  QERLRATEKFQLAVEALEQEKQGLQSQIAQVLEGRQQLAHLKMSLSLEVA   300
 301  TYRTLLEAENSRLQTPGGGSKTSLSFQDPKLELQFPRTPEGRRLGSLLPV   350
 351  LSPTSLPSPLPATLETPVPAFLKNQEFLQARTPTLASTPIPPTPQAPSPA   400
 401  VDAEIRAQDAPLSLLQTQGGRKQAPEPLRAEARVAIPASVLPGPEEPGGQ   450
 451  RQEASTGQSPEDHASLAPPLSPDHSSLEAKDGESGGSRVFSICRGEGEGQ   500
 501  IWGLVEKETAIEGKVVSSLQQEIWEEEDLNRKEIQDSQVPLEKETLKSLG   550
 551  EEIQESLKTLENQSHETLERENQECPRSLEEDLETLKSLEKENKELLKDV   600
 601  EVVRPLEKEAVGQLKPTGKEDTQTLQSLQKENQELMKSLEGNLETFLFPG   650
 651  TENQELVSSLQENLESLTALEKENQEPLRSPEVGDEEALRPLTKENQEPL   700
 701  RSLEDENKEAFRSLEKENQEPLKTLEEEDQSIVRPLETENHKSLRSLEEQ   750
 751  DQETLRTLEKETQQRRRSLGEQDQMTLRPPEKVDLEPLKSLDQEIARPLE   800
 801  NENQEFLKSLKEESVEAVKSLETEILESLKSAGQENLETLKSPETQAPLW   850
 851  TPEEINQGAMNPLEKEIQEPLESVEVNQETFRLLEEENQESLRSLGAWNL   900
 901  ENLRSPEEVDKESQRNLEEEENLGKGEYQESLRSLEEEGQELPQSADVQR   950
 951  WEDTVEKDQELAQESPPGMAGVENEDEAELNLREQDGFTGKEEVVEQGEL  1000
1001  NATEEVWIPGEGHPESPEPKEQRGLVEGASVKGGAEGLQDPEGQSQQVGA  1050
1051  PGLQAPQGLPEAIEPLVEDDVAPGGDQASPEVMLGSEPAMGESAAGAEPG  1100
1101  PGQGVGGLGDPGHLTREEVMEPPLEEESLEAKRVQGLEGPRKDLEEAGGL  1150
1151  GTEFSELPGKSRDPWEPPREGREESEAEAPRGAEEAFPAETLGHTGSDAP  1200
1201  SPWPLGSEEAEEDVPPVLVSPSPTYTPILEDAPGPQPQAEGSQEASWGVQ  1250
1251  GRAEALGKVESEQEELGSGEIPEGPQEEGEESREESEEDELGETLPDSTP  1300
1301  LGFYLRSPTSPRWDPTGEQRPPPQGETGKEGWDPAVLASEGLEAPPSEKE  1350
1351  EGEEGEEECGRDSDLSEEFEDLGTEAPFLPGVPGEVAEPLGQVPQLLLDP  1400
1401  AAWDRDGESDGFADEEESGEEGEEDQEEGREPGAGRWGPGSSVGSLQALS  1450
1451  SSQRGEFLESDSVSVSVPWDDSLRGAVAGAPKTALETESQDSAEPSGSEE  1500
1501  ESDPVSLEREDKVPGPLEIPSGMEDAGPGADIIGVNGQGPNLEGKSQHVN  1550
1551  GGVMNGLEQSEEVGQGMPLVSEGDRGSPFQEEEGSALKTSWAGAPVHLGQ  1600
1601  GQFLKFTQREGDRESWSSGED                               1621

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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