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

NucPred

Fetching Q7Z7M0 from www.uniprot.org...

The NucPred score for your sequence is 0.65 (see score help below)

   1  MALGKVLAMALVLALAVLGSLSPGARAGDCKGQRQVLREAPGFVTDGAGN    50
  51  YSVNGNCEWLIEAPSPQHRILLDFLFLDTECTYDYLFVYDGDSPRGPLLA   100
 101  SLSGSTRPPPIEASSGKMLLHLFSDANYNLLGFNASFRFSLCPGGCQSHG   150
 151  QCQPPGVCACEPGWGGPDCGLQECSAYCGSHGTCASPLGPCRCEPGFLGR   200
 201  ACDLHLWENQGAGWWHNVSARDPAFSARIGAAGAFLSPPGLLAVFGGQDL   250
 251  NNALGDLVLYNFSANTWESWDLSPAPAARHSHVAVAWAGSLVLMGGELAD   300
 301  GSLTNDVWAFSPLGRGHWELLAPPASSSSGPPGLAGHAAALVDDVWLYVS   350
 351  GGRTPHDLFSSGLFRFRLDSTSGGYWEQVIPAGGRPPAATGHSMVFHAPS   400
 401  RALLVHGGHRPSTARFSVRVNSTELFHVDRHVWTTLKGRDGLQGPRERAF   450
 451  HTASVLGNYMVVYGGNVHTHYQEEKCYEDGIFFYHLGCHQWVSGAELAPP   500
 501  GTPEGRAAPPSGRYSHVAAVLGGSVLLVAGGYSGRPRGDLMAYKVPPFVF   550
 551  QAPAPDYHLDYCSMYTDHSVCSRDPECSWCQGACQAAPPPGTPLGACPAA   600
 601  SCLGLGRLLGDCQACLAFSSPTAPPRGPGTLGWCVHNESCLPRPEQARCR   650
 651  GEQISGTVGWWGPAPVFVTSLEACVTQSFLPGLHLLTFQQPPNTSQPDKV   700
 701  SIVRSTTITLTPSAETDVSLVYRGFIYPMLPGGPGGPGAEDVAVWTRAQR   750
 751  LHVLARMARGPDTENMEEVGRWVAHQEKETRRLQRPGSARLFPLPGRDHK   800
 801  YAVEIQGQLNGSAGPGHSELTLLWDRTGVPGGSEISFFFLEPYRSSSCTS   850
 851  YSSCLGCLADQGCGWCLTSATCHLRQGGAHCGDDGAGGSLLVLVPTLCPL   900
 901  CEEHRDCHACTQDPFCEWHQSTSRKGDAACSRRGRGRGALKSPEECPPLC   950
 951  SQRLTCEDCLANSSQCAWCQSTHTCFLFAAYLARYPHGGCRGWDDSVHSE  1000
1001  PRCRSCDGFLTCHECLQSHECGWCGNEDNPTLGRCLQGDFSGPLGGGNCS  1050
1051  LWVGEGLGLPVALPARWAYARCPDVDECRLGLARCHPRATCLNTPLSYEC  1100
1101  HCQRGYQGDGISHCNRTCLEDCGHGVCSGPPDFTCVCDLGWTSDLPPPTP  1150
1151  APGPPAPRCSRDCGCSFHSHCRKRGPGFCDECQDWTWGEHCERCRPGSFG  1200
1201  NATGSRGCRPCQCNGHGDPRRGHCDNLSGLCFCQDHTEGAHCQLCSPGYY  1250
1251  GDPRAGGSCFRECGGRALLTNVSSVALGSRRVGGLLPPGGGAARAGPGLS  1300
1301  YCVWVVSATEELQPCAPGTLCPPLTLTFSPDSSTPCTLSYVLAFDGFPRF  1350
1351  LDTGVVQSDRSLIAAFCGQRRDRPLTVQALSGLLVLHWEANGSSSWGFNA  1400
1401  SVGSARCGSGGPGSCPVPQECVPQDGAAGAGLCRCPQGWAGPHCRMALCP  1450
1451  ENCNAHTGAGTCNQSLGVCICAEGFGGPDCATKLDGGQLVWETLMDSRLS  1500
1501  ADTASRFLHRLGHTMVDGPDATLWMFGGLGLPQGLLGNLYRYSVSERRWT  1550
1551  QMLAGAEDGGPGPSPRSFHAAAYVPAGRGAMYLLGGLTAGGVTRDFWVLN  1600
1601  LTTLQWRQEKAPQTVELPAVAGHTLTARRGLSLLLVGGYSPENGFNQQLL  1650
1651  EYQLATGTWVSGAQSGTPPTGLYGHSAVYHEATDSLYVFGGFRFHVELAA  1700
1701  PSPELYSLHCPDRTWSLLAPSQGAKRDRMRNVRGSSRGLGQVPGEQPGSW  1750
1751  GFREVRKKMALWAALAGTGGFLEEISPHLKEPRPRLFHASALLGDTMVVL  1800
1801  GGRSDPDEFSSDVLLYQVNCNAWLLPDLTRSASVGPPMEESVAHAVAAVG  1850
1851  SRLYISGGFGGVALGRLLALTLPPDPCRLLSSPEACNQSGACTWCHGACL  1900
1901  SGDQAHRLGCGGSPCSPMPRSPEECRRLRTCSECLARHPRTLQPGDGEAS  1950
1951  TPRCKWCTNCPEGACIGRNGSCTSENDCRINQREVFWAGNCSEAACGAAD  2000
2001  CEQCTREGKCMWTRQFKRTGETRRILSVQPTYDWTCFSHSLLNVSPMPVE  2050
2051  SSPPLPCPTPCHLLPNCTSCLDSKGADGGWQHCVWSSSLQQCLSPSYLPL  2100
2101  RCMAGGCGRLLRGPESCSLGCAQATQCALCLRRPHCGWCAWGGQDGGGRC  2150
2151  MEGGLSGPRDGLTCGRPGASWAFLSCPPEDECANGHHDCNETQNCHDQPH  2200
2201  GYECSCKTGYTMDNMTGLCRPVCAQGCVNGSCVEPDHCRCHFGFVGRNCS  2250
2251  TECRCNRHSECAGVGARDHCLLCRNHTKGSHCEQCLPLFVGSAVGGGTCR  2300
2301  PCHAFCRGNSHICISRKELQMSKGEPKKYSLDPEEIENWVTEGPSEDEAV  2350
2351  CVNCQNNSYGEKCESCLQGYFLLDGKCTKCQCNGHADTCNEQDGTGCPCQ  2400
2401  NNTETGTCQGSSPSDRRDCYKYQCAKCRESFHGSPLGGQQCYRLISVEQE  2450
2451  CCLDPTSQTNCFHEPKRRALGPGRTVLFGVQPKFTNVDIRLTLDVTFGAV  2500
2501  DLYVSTSYDTFVVRVAPDTGVHTVHIQPPPAPPPPPPPADGGPRGAGDPG  2550
2551  GAGASSGPGAPAEPRVREVWPRGLITYVTVTEPSAVLVVRGVRDRLVITY  2600
2601  PHEHHALKSSRFYLLLLGVGDPSGPGANGSADSQGLLFFRQDQAHIDLFV  2650
2651  FFSVFFSCFFLFLSLCVLLWKAKQALDQRQEQRRHLQEMTKMASRPFAKV  2700
2701  TVCFPPDPTAPASAWKPAGLPPPAFRRSEPFLAPLLLTGAGGPWGPMGGG  2750
2751  CCPPAIPATTAGLRAGPITLEPTEDGMAGVATLLLQLPGGPHAPNGACLG  2800
2801  SALVTLRHRLHEYCGGGGGAGGSGHGTGAGRKGLLSQDNLTSMSL       2845

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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