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

NucPred

Fetching Q75N90 from www.uniprot.org...

The NucPred score for your sequence is 0.47 (see score help below)

   1  MTLEGLYLARGPLARLLLAWSALLCMAGGQGRWDGALEAAGPGRVRRRGS    50
  51  PGILQGPNVCGSRFHAYCCPGWRTFPGRSQCVVPICRRACGEGFCSQPNL   100
 101  CTCADGTLAPSCGVSRGSGCSVSCMNGGTCRGASCLCQKGYTGTVCGQPI   150
 151  CDRGCHNGGRCIGPNRCACVYGFMGPQCERDYRTGPCFGQVGPEGCQHQL   200
 201  TGLVCTKALCCATVGRAWGLPCELCPAQPHPCRRGFIPNIHTGACQDVDE   250
 251  CQAVPGLCQGGSCVNMVGSFHCRCPVGHRLSDSSAACEDYRAGACFSVLF   300
 301  GGRCAGDLAGHYTRRQCCCDRGRCWAAGPVPELCPPRGSNEFQQLCAQRL   350
 351  PLLPGHPGLFPGLLGFGSNGMGPPLGPARLNPHGSDARGIPSLGPGNSNI   400
 401  GTATLNQTIDICRHFTNLCLNGRCLPTPSSYRCECNVGYTQDVRGECIDV   450
 451  DECTSSPCHHGDCVNIPGTYHCRCYPGFQATPTRQACVDVDECIVSGGLC   500
 501  HLGRCVNTEGSFQCVCNAGFELSPDGKNCVDHNECATSTMCVNGVCLNED   550
 551  GSFSCLCKPGFLLAPGGHYCMDIDECQTPGICVNGHCTNTEGSFRCQCLG   600
 601  GLAVGTDGRVCVDTHVRSTCYGAIEKGSCARPFPGTVTKSECCCANPDHG   650
 651  FGEPCQLCPAKDSAEFQALCSSGLGITTDGRDINECALDPEVCANGVCEN   700
 701  LRGSYRCVCNLGYEAGASGKDCTDVDECALNSLLCDNGWCQNSPGSYSCS   750
 751  CPPGFHFWQDTEICKDVDECLSSPCVSGVCRNLAGSYTCKCGPGSRLDPS   800
 801  GTFCLDSTKGTCWLKIQESRCEVNLQGASLRSECCATLGAAWGSPCERCE   850
 851  IDPACARGFARMTGVTCDDVNECESFPGVCPNGRCVNTAGSFRCECPEGL   900
 901  MLDASGRLCVDVRLEPCFLRWDEDECGVTLPGKYRMDVCCCSIGAVWGVE   950
 951  CEACPDPESLEFASLCPRGLGFASRDFLSGRPFYKDVNECKVFPGLCTHG  1000
1001  TCRNTVGSFHCACAGGFALDAQERNCTDIDECRISPDLCGQGTCVNTPGS  1050
1051  FECECFPGYESGFMLMKNCMDVDECARDPLLCRGGTCTNTDGSYKCQCPP  1100
1101  GHELTAKGTACEDIDECSLSDGLCPHGQCVNVIGAFQCSCHAGFQSTPDR  1150
1151  QGCVDINECRVQNGGCDVHCINTEGSYRCSCGQGYSLMPDGRACADVDEC  1200
1201  EENPRVCDQGHCTNMPGGHRCLCYDGFMATPDMRTCVDVDECDLNPHICL  1250
1251  HGDCENTKGSFVCHCQLGYMVRKGATGCSDVDECEVGGHNCDSHASCLNI  1300
1301  PGSFSCRCLPGWVGDGFECHDLDECVSQEHRCSPRGDCLNVPGSYRCTCR  1350
1351  QGFAGDGFFCEDRDECAENVDLCDNGQCLNAPGGYRCECEMGFDPTEDHR  1400
1401  ACQDVDECAQGNLCAFGSCENLPGMFRCICNGGYELDRGGGNCTDINECA  1450
1451  DPVNCINGVCINTPGSYLCSCPQDFELNPSGVGCVDTRAGNCFLETHDRG  1500
1501  DSGISCSAEIGVGVTRASCCCSLGRAWGNPCELCPMANTTEYRTLCPGGE  1550
1551  GFQPNRITVILEDIDECQELPGLCQGGDCVNTFGSFQCECPPGYHLSEHT  1600
1601  RICEDIDECSTHSGICGPGTCYNTLGNYTCVCPAEYLQVNGGNNCMDMRK  1650
1651  SVCFRHYNGTCQNELAFNVTRKMCCCSYNIGQAWNRPCEACPTPISPDYQ  1700
1701  ILCGNQAPGFLTDIHTGKPLDIDECGEIPAICANGICINQIGSFRCECPA  1750
1751  GFNYNSILLACEDVDECGSRESPCQQNADCINIPGSYRCKCTRGYKLSPG  1800
1801  GACVGRNECREIPNVCSHGDCMDTEGSYMCLCHRGFQASADQTLCMDIDE  1850
1851  CDRQPCGNGTCKNIIGSYNCLCFPGFVVTHNGDCVDFDECTTLVGQVCRF  1900
1901  GHCLNTAGSFHCLCQDGFELTADGKNCVDTNECLSLAGTCLPGTCQNLEG  1950
1951  SFRCICPPGFQVQSDHCIDIDECSEEPNLCLFGTCTNSPGSFQCLCPPGF  2000
2001  VLSDNGHRCFDTRQSFCFTRFEAGKCSVPKAFNTTKTRCCCSKRPGEGWG  2050
2051  DPCELCPQEGSAAFQELCPFGHGAVPGPDDSREDVNECAENPGVCTNGVC  2100
2101  VNTDGSFRCECPFGYSLDFTGINCVDTDECSVGHPCGQGTCTNVIGGFEC  2150
2151  ACADGFEPGLMMTCEDIDECSLNPLLCAFRCHNTEGSYLCTCPAGYTLRE  2200
2201  DGAMCRDVDECADGQQDCHARGMECKNLIGTFACVCPPGMRPLPGSGEGC  2250
2251  TDDNECHAQPDLCVNGRCVNTAGSFRCDCDEGFQPSPTLTECHDIRQGPC  2300
2301  FAEVLQTMCRSLSSSSEAVTRAECCCGGGRGWGPRCELCPLPGTSAYRKL  2350
2351  CPHGSGYTAEGRDVDECRMLAHLCAHGECINSLGSFRCHCQAGYTPDATA  2400
2401  TTCLDMDECSQVPKPCTFLCKNTKGSFLCSCPRGYLLEEDGRTCKDLDEC  2450
2451  TSRQHNCQFLCVNTVGAFTCRCPPGFTQHHQACFDNDECSAQPGPCGAHG  2500
2501  HCHNTPGSFRCECHQGFTLVSSGHGCEDVNECDGPHRCQHGCQNQLGGYR  2550
2551  CSCPQGFTQHSQWAQCVDENECALSPPTCGSASCRNTLGGFRCVCPSGFD  2600
2601  FDQALGGCQEVDECAGRRGPCSYSCANTPGGFLCGCPQGYFRAGQGHCVS  2650
2651  GLGFSPGPQDTPDKEELLSSEACYECKINGLSPRDRPRRSAHRDHQVNLA  2700
2701  TLDSEALLTLGLNLSHLGRAERILELRPALEGLEGRIRYVIVRGNEQGFF  2750
2751  RMHHLRGVSSLQLGRRRPGPGTYRLEVVSHMAGPWGVQPEGQPGPWGQAL  2800
2801  RLKVQLQLL                                           2809

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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