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

NucPred

Fetching P02549 from www.uniprot.org...

The NucPred score for your sequence is 0.94 (see score help below)

   1  MEQFPKETVVESSGPKVLETAEEIQERRQEVLTRYQSFKERVAERGQKLE    50
  51  DSYHLQVFKRDADDLGKWIMEKVNILTDKSYEDPTNIQGKYQKHQSLEAE   100
 101  VQTKSRLMSELEKTREERFTMGHSAHEETKAHIEELRHLWDLLLELTLEK   150
 151  GDQLLRALKFQQYVQECADILEWIGDKEAIATSVELGEDWERTEVLHKKF   200
 201  EDFQVELVAKEGRVVEVNQYANECAEENHPDLPLIQSKQNEVNAAWERLR   250
 251  GLALQRQKALSNAANLQRFKRDVTEAIQWIKEKEPVLTSEDYGKDLVASE   300
 301  GLFHSHKGLERNLAVMSDKVKELCAKAEKLTLSHPSDAPQIQEMKEDLVS   350
 351  SWEHIRALATSRYEKLQATYWYHRFSSDFDELSGWMNEKTAAINADELPT   400
 401  DVAGGEVLLDRHQQHKHEIDSYDDRFQSADETGQDLVNANHEASDEVREK   450
 451  MEILDNNWTALLELWDERHRQYEQCLDFHLFYRDSEQVDSWMSRQEAFLE   500
 501  NEDLGNSLGSAEALLQKHEDFEEAFTAQEEKIITVDKTATKLIGDDHYDS   550
 551  ENIKAIRDGLLARRDALREKAATRRRLLKESLLLQKLYEDSDDLKNWINK   600
 601  KKKLADDEDYKDIQNLKSRVQKQQVFEKELAVNKTQLENIQKTGQEMIEG   650
 651  GHYASDNVTTRLSEVASLWEELLEATKQKGTQLHEANQQLQFENNAEDLQ   700
 701  RWLEDVEWQVTSEDYGKGLAEVQNRLRKHGLLESAVAARQDQVDILTDLA   750
 751  AYFEEIGHPDSKDIRARQESLVCRFEALKEPLATRKKKLLDLLHLQLICR   800
 801  DTEDEEAWIQETEPSATSTYLGKDLIASKKLLNRHRVILENIASHEPRIQ   850
 851  EITERGNKMVEEGHFAAEDVASRVKSLNQNMESLRARAARRQNDLEANVQ   900
 901  FQQYLADLHEAETWIREKEPIVDNTNYGADEEAAGALLKKHEAFLLDLNS   950
 951  FGDSMKALRNQANACQQQQAAPVEGVAGEQRVMALYDFQARSPREVTMKK  1000
1001  GDVLTLLSSINKDWWKVEAADHQGIVPAVYVRRLAHDEFPMLPQRRREEP  1050
1051  GNITQRQEQIENQYRSLLDRAEERRRRLLQRYNEFLLAYEAGDMLEWIQE  1100
1101  KKAENTGVELDDVWELQKKFDEFQKDLNTNEPRLRDINKVADDLLFEGLL  1150
1151  TPEGAQIRQELNSRWGSLQRLADEQRQLLGSAHAVEVFHREADDTKEQIE  1200
1201  KKCQALSAADPGSDLFSVQALQRRHEGFERDLVPLGDKVTILGETAERLS  1250
1251  ESHPDATEDLQRQKMELNEAWEDLQGRTKDRKESLNEAQKFYLFLSKARD  1300
1301  LQNWISSIGGMVSSQELAEDLTGIEILLERHQEHRADMEAEAPTFQALED  1350
1351  FSAELIDSGHHASPEIEKKLQAVKLERDDLEKAWEKRKKILDQCLELQMF  1400
1401  QGNCDQVESWMVARENSLRSDDKSSLDSLEALMKKRDDLDKAITAQEGKI  1450
1451  TDLEHFAESLIADEHYAKEEIATRLQRVLDRWKALKAQLIDERTKLGDYA  1500
1501  NLKQFYRDLEELEEWISEMLPTACDESYKDATNIQRKYLKHQTFAHEVDG  1550
1551  RSEQVHGVINLGNSLIECSACDGNEEAMKEQLEQLKEHWDHLLERTNDKG  1600
1601  KKLNEASRQQRFNTSIRDFEFWLSEAETLLAMKDQARDLASAGNLLKKHQ  1650
1651  LLEREMLAREDALKDLNTLAEDLLSSGTFNVDQIVKKKDNVNKRFLNVQE  1700
1701  LAAAHHEKLKEAYALFQFFQDLDDEESWIEEKLIRVSSQDYGRDLQGVQN  1750
1751  LLKKHKRLEGELVAHEPAIQNVLDMAEKLKDKAAVGQEEIQLRLAQFVEH  1800
1801  WEKLKELAKARGLKLEESLEYLQFMQNAEEEEAWINEKNALAVRGDCGDT  1850
1851  LAATQSLLMKHEALENDFAVHETRVQNVCAQGEDILNKVLQEESQNKEIS  1900
1901  SKIEALNEKTPSLAKAIAAWKLQLEDDYAFQEFNWKADVVEAWIADKETS  1950
1951  LKTNGNGADLGDFLTLLAKQDTLDASLQSFQQERLPEITDLKDKLISAQH  2000
2001  NQSKAIEERYAALLKRWEQLLEASAVHRQKLLEKQLPLQKAEDLFVEFAH  2050
2051  KASALNNWCEKMEENLSEPVHCVSLNEIRQLQKDHEDFLASLARAQADFK  2100
2101  CLLELDQQIKALGVPSSPYTWLTVEVLERTWKHLSDIIEEREQELQKEEA  2150
2151  RQVKNFEMCQEFEQNASTFLQWILETRAYFLDGSLLKETGTLESQLEANK  2200
2201  RKQKEIQAMKRQLTKIVDLGDNLEDALILDIKYSTIGLAQQWDQLYQLGL  2250
2251  RMQHNLEQQIQAKDIKGVSEETLKEFSTIYKHFDENLTGRLTHKEFRSCL  2300
2301  RGLNYYLPMVEEDEHEPKFEKFLDAVDPGRKGYVSLEDYTAFLIDKESEN  2350
2351  IKSSDEIENAFQALAEGKSYITKEDMKQALTPEQVSFCATHMQQYMDPRG  2400
2401  RSHLSGYDYVGFTNSYFGN                                 2419

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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