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

NucPred

Fetching O15078 from www.uniprot.org...

The NucPred score for your sequence is 0.91 (see score help below)

   1  MPPNINWKEIMKVDPDDLPRQEELADNLLISLSKVEVNELKSEKQENVIH    50
  51  LFRITQSLMKMKAQEVELALEEVEKAGEEQAKFENQLKTKVMKLENELEM   100
 101  AQQSAGGRDTRFLRNEICQLEKQLEQKDRELEDMEKELEKEKKVNEQLAL   150
 151  RNEEAENENSKLRRENKRLKKKNEQLCQDIIDYQKQIDSQKETLLSRRGE   200
 201  DSDYRSQLSKKNYELIQYLDEIQTLTEANEKIEVQNQEMRKNLEESVQEM   250
 251  EKMTDEYNRMKAIVHQTDNVIDQLKKENDHYQLQVQELTDLLKSKNEEDD   300
 301  PIMVAVNAKVEEWKLILSSKDDEIIEYQQMLHNLREKLKNAQLDADKSNV   350
 351  MALQQGIQERDSQIKMLTEQVEQYTKEMEKNTCIIEDLKNELQRNKGAST   400
 401  LSQQTHMKIQSTLDILKEKTKEAERTAELAEADAREKDKELVEALKRLKD   450
 451  YESGVYGLEDAVVEIKNCKNQIKIRDREIEILTKEINKLELKISDFLDEN   500
 501  EALRERVGLEPKTMIDLTEFRNSKHLKQQQYRAENQILLKEIESLEEERL   550
 551  DLKKKIRQMAQERGKRSATSGLTTEDLNLTENISQGDRISERKLDLLSLK   600
 601  NMSEAQSKNEFLSRELIEKERDLERSRTVIAKFQNKLKELVEENKQLEEG   650
 651  MKEILQAIKEMQKDPDVKGGETSLIIPSLERLVNAIESKNAEGIFDASLH   700
 701  LKAQVDQLTGRNEELRQELRESRKEAINYSQQLAKANLKIDHLEKETSLL   750
 751  RQSEGSNVVFKGIDLPDGIAPSSASIINSQNEYLIHLLQELENKEKKLKN   800
 801  LEDSLEDYNRKFAVIRHQQSLLYKEYLSEKETWKTESKTIKEEKRKLEDQ   850
 851  VQQDAIKVKEYNNLLNALQMDSDEMKKILAENSRKITVLQVNEKSLIRQY   900
 901  TTLVELERQLRKENEKQKNELLSMEAEVCEKIGCLQRFKEMAIFKIAALQ   950
 951  KVVDNSVSLSELELANKQYNELTAKYRDILQKDNMLVQRTSNLEHLECEN  1000
1001  ISLKEQVESINKELEITKEKLHTIEQAWEQETKLGNESSMDKAKKSITNS  1050
1051  DIVSISKKITMLEMKELNERQRAEHCQKMYEHLRTSLKQMEERNFELETK  1100
1101  FAELTKINLDAQKVEQMLRDELADSVSKAVSDADRQRILELEKNEMELKV  1150
1151  EVSKLREISDIARRQVEILNAQQQSRDKEVESLRMQLLDYQAQSDEKSLI  1200
1201  AKLHQHNVSLQLSEATALGKLESITSKLQKMEAYNLRLEQKLDEKEQALY  1250
1251  YARLEGRNRAKHLRQTIQSLRRQFSGALPLAQQEKFSKTMIQLQNDKLKI  1300
1301  MQEMKNSQQEHRNMENKTLEMELKLKGLEELISTLKDTKGAQKVINWHMK  1350
1351  IEELRLQELKLNRELVKDKEEIKYLNNIISEYERTISSLEEEIVQQNKFH  1400
1401  EERQMAWDQREVDLERQLDIFDRQQNEILNAAQKFEEATGSIPDPSLPLP  1450
1451  NQLEIALRKIKENIRIILETRATCKSLEEKLKEKESALRLAEQNILSRDK  1500
1501  VINELRLRLPATAEREKLIAELGRKEMEPKSHHTLKIAHQTIANMQARLN  1550
1551  QKEEVLKKYQRLLEKAREEQREIVKKHEEDLHILHHRLELQADSSLNKFK  1600
1601  QTAWDLMKQSPTPVPTNKHFIRLAEMEQTVAEQDDSLSSLLVKLKKVSQD  1650
1651  LERQREITELKVKEFENIKLQLQENHEDEVKKVKAEVEDLKYLLDQSQKE  1700
1701  SQCLKSELQAQKEANSRAPTTTMRNLVERLKSQLALKEKQQKALSRALLE  1750
1751  LRAEMTAAAEERIISATSQKEAHLNVQQIVDRHTRELKTQVEDLNENLLK  1800
1801  LKEALKTSKNRENSLTDNLNDLNNELQKKQKAYNKILREKEEIDQENDEL  1850
1851  KRQIKRLTSGLQGKPLTDNKQSLIEELQRKVKKLENQLEGKVEEVDLKPM  1900
1901  KEKNAKEELIRWEEGKKWQAKIEGIRNKLKEKEGEVFTLTKQLNTLKDLF  1950
1951  AKADKEKLTLQRKLKTTGMTVDQVLGIRALESEKELEELKKRNLDLENDI  2000
2001  LYMRAHQALPRDSVVEDLHLQNRYLQEKLHALEKQFSKDTYSKPSISGIE  2050
2051  SDDHCQREQELQKENLKLSSENIELKFQLEQANKDLPRLKNQVRDLKEMC  2100
2101  EFLKKEKAEVQRKLGHVRGSGRSGKTIPELEKTIGLMKKVVEKVQRENEQ  2150
2151  LKKASGILTSEKMANIEQENEKLKAELEKLKAHLGHQLSMHYESKTKGTE  2200
2201  KIIAENERLRKELKKETDAAEKLRIAKNNLEILNEKMTVQLEETGKRLQF  2250
2251  AESRGPQLEGADSKSWKSIVVTRMYETKLKELETDIAKKNQSITDLKQLV  2300
2301  KEATEREQKVNKYNEDLEQQIKILKHVPEGAETEQGLKRELQVLRLANHQ  2350
2351  LDKEKAELIHQIEANKDQSGAESTIPDADQLKEKIKDLETQLKMSDLEKQ  2400
2401  HLKEEIKKLKKELENFDPSFFEEIEDLKYNYKEEVKKNILLEEKVKKLSE  2450
2451  QLGVELTSPVAASEEFEDEEESPVNFPIY                       2479

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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