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

NucPred

Fetching O00750 from www.uniprot.org...

The NucPred score for your sequence is 0.89 (see score help below)

   1  MSSTQGNGEHWKSLESVGISRKELAMAEALQMEYDALSRLRHDKEENRAK    50
  51  QNADPSLISWDEPGVDFYSKPAGRRTDLKLLRGLSGSDPTLNYNSLSPQE   100
 101  GPPNHSTSQGPQPGSDPWPKGSLSGDYLYIFDGSDGGVSSSPGPGDIEGS   150
 151  CKKLSPPPLPPRASIWDTPPLPPRKGSPSSSKISQPSDINTFSLVEQLPG   200
 201  KLLEHRILEEEEVLGGGGQGRLLGSVDYDGINDAITRLNLKSTYDAEMLR   250
 251  DATRGWKEGRGPLDFSKDTSGKPVARSKTMPPQVPPRTYASRYGNRKNAT   300
 301  PGKNRRISAAPVGSRPHTVANGHELFEVSEERDEEVAAFCHMLDILRSGS   350
 351  DIQDYFLTGYVWSAVTPSPEHLGDEVNLKVTVLCDRLQEALTFTCNCSST   400
 401  VDLLIYQTLCYTHDDLRNVDVGDFVLKPCGLEEFLQNKHALGSHEYIQYC   450
 451  RKFDIDIRLQLMEQKVVRSDLARTVNDDQSPSTLNYLVHLQERPVKQTIS   500
 501  RQALSLLFDTYHNEVDAFLLADGDFPLKADRVVQSVKAICNALAAVETPE   550
 551  ITSALNQLPPCPSRMQPKIQKDPSVLAVRENREKVVEALTAAILDLVELY   600
 601  CNTFNADFQTAVPGSRKHDLVQEACHFARSLAFTVYATHRIPIIWATSYE   650
 651  DFYLSCSLSHGGKELCSPLQTRRAHFSKYLFHLIVWDQQICFPVQVNRLP   700
 701  RETLLCATLYALPIPPPGSSSEANKQRRVPEALGWVTTPLFNFRQVLTCG   750
 751  RKLLGLWPATQENPSARWSAPNFHQPDSVILQIDFPTSAFDIKFTSPPGD   800
 801  KFSPRYEFGSLREEDQRKLKDIMQKESLYWLTDADKKRLWEKRYYCHSEV   850
 851  SSLPLVLASAPSWEWACLPDIYVLLKQWTHMNHQDALGLLHATFPDQEVR   900
 901  RMAVQWIGSLSDAELLDYLPQLVQALKYECYLDSPLVRFLLKRAVSDLRV   950
 951  THYFFWLLKDGLKDSQFSIRYQYLLAALLCCCGKGLREEFNRQCWLVNAL  1000
1001  AKLAQQVREAAPSARQGILRTGLEEVKQFFALNGSCRLPLSPSLLVKGIV  1050
1051  PRDCSYFNSNAVPLKLSFQNVDPLGENIRVIFKCGDDLRQDMLTLQMIRI  1100
1101  MSKIWVQEGLDMRMVIFRCFSTGRGRGMVEMIPNAETLRKIQVEHGVTGS  1150
1151  FKDRPLADWLQKHNPGEDEYEKAVENFIYSCAGCCVATYVLGICDRHNDN  1200
1201  IMLKTTGHMFHIDFGRFLGHAQMFGNIKRDRAPFVFTSDMAYVINGGDKP  1250
1251  SSRFHDFVDLCCQAYNLIRKHTHLFLNLLGLMLSCGIPELSDLEDLKYVY  1300
1301  DALRPQDTEANATTYFTRLIESSLGSVATKLNFFIHNLAQMKFTGSDDRL  1350
1351  TLSFASRTHTLKSSGRISDVFLCRHEKIFHPNKGYIYVVKVMRENTHEAT  1400
1401  YIQRTFEEFQELHNKLRLLFPSSHLPSFPSRFVIGRSRGEAVAERRREEL  1450
1451  NGYIWHLIHAPPEVAECDLVYTFFHPLPRDEKAMGTSPAPKSSDGTWARP  1500
1501  VGKVGGEVKLSISYKNNKLFIMVMHIRGLQLLQDGNDPDPYVKIYLLPDP  1550
1551  QKTTKRKTKVARKTCNPTYNEMLVYDGIPKGDLQQRELQLSVLSEQGFWE  1600
1601  NVLLGEVNIRLRELDLAQEKTGWFALGSRSHGTL                  1634

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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