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

NucPred

Fetching Q9WU42 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MSGSTQPVAQTWRAAEPRYPPHGISYPVQIARSHTDVGLLEYQHHPRDYT    50
  51  SHLSPGSIIQPQRRRPSLLSEFQPGSERSQELHLRPESRTFLPELGKPDI   100
 101  EFTESKRPRLELLPDTLLRPSPLLATGQPSGSEDLTKDRSLAGKLEPVSP   150
 151  PSPPHADPELELAPSRLSKEELIQNMDRVDREITMVEQQISKLKKKQQQL   200
 201  EEEAAKPPEPEKPVSPPPIESKHRSLVQIIYDENRKKAEAAHRILEGLGP   250
 251  QVELPLYNQPSDTRQYHENIKINQAMRKKLILYFKRRNHARKQWEQRFCQ   300
 301  RYDQLMEAWEKKVERIENNPRRRAKESKVREYYEKQFPEIRKQRELQERM   350
 351  QSRVGQRGSGLSMSAARSEHEVSEIIDGLSEQENLEKQMRQLAVIPPMLY   400
 401  DADQQRIKFINMNGLMDDPMKVYKDRQVTNMWSEQERDTFREKFMQHPKN   450
 451  FGLIASFLERKTVAECVLYYYLTKKNENYKSLVRRSYRRRGKSQQQQQQQ   500
 501  QQQQQQQMARSSQEEKEEKEKEKEADKEEEKQDAENEKEELSKEKTDDTS   550
 551  GEDNDEKEAVASKGRKTANSQGRRKGRITRSMANEANHEETATPQQSSEL   600
 601  ASMEMNESSRWTEEEMETAKKGLLEHGRNWSAIARMVGSKTVSQCKNFYF   650
 651  NYKKRQNLDEILQQHKLKMEKERNARRKKKKTPAAASEETAFPPAAEDEE   700
 701  MEASGASANEEELAEEAEASQASGNEVPRVGECSGPAAVNNSSDTESVPS   750
 751  PRSEATKDTGPKPTGTEALPAATQPPVPPPEEPAVAPAEPSPVPDASGPP   800
 801  SPEPSPSPAAPPATVDKDEQEAPAAPAPQTEDAKEQKSEAEEIDVGKPEE   850
 851  PEASEEPPESVKSDHKEETEEEPEDKAKGTEAIETVSEAPLKVEEAGSKA   900
 901  AVTKGSSSGATQDSDSSATCSADEVDEPEGGDKGRLLSPRPSLLTPAGDP   950
 951  RASTSPQKPLDLKQLKQRAAAIPPIVTKVHEPPREDTVPPKPVPPVPPPT  1000
1001  QHLQPEGDVSQQSGGSPRGKSRSPVPPAEKEAEKPAFFPAFPTEGPKLPT  1050
1051  EPPRWSSGLPFPIPPREVIKTSPHAADPSAFSYTPPGHPLPLGLHDSARP  1100
1101  VLPRPPISNPPPLISSAKHPGVLERQLGAISQQGMSVQLRVPHSEHAKAP  1150
1151  MGPLTMGLPLAVDPKKLGTALGSATSGSITKGLPSTRAADGPSYRGSITH  1200
1201  GTPADVLYKGTISRIVGEDSPSRLDRAREDTLPKGHVIYEGKKGHVLSYE  1250
1251  GGMSVSQCSKEDGRSSSGPPHETAAPKRTYDMMEGRVGRTVTSASIEGLM  1300
1301  GRAIPEQHSPHLKEQHHIRGSITQGIPRSYVEAQEDYLRREAKLLKREGT  1350
1351  PPPPPPPRDLTETYKPRPLDPLGPLKLKPTHEGVVATVKEAGRSIHEIPR  1400
1401  EELRRTPELPLAPRPLKEGSITQGTPLKYDSGAPSTGTKKHDVRSIIGSP  1450
1451  GRPFPALHPLDIMADARALERACYEESLKSRSGTSSGAGGSITRGAPVVV  1500
1501  PELGKPRQSPLTYEDHGAPFTSHLPRGSPVTTREPTPRLQEGSLLSSKAS  1550
1551  QDRKLTSTPREIAKSPHSTVPEHHPHPISPYEHLLRGVTGVDLYRGHIPL  1600
1601  AFDPTSIPRGIPLEAAAAAYYLPRHLAPSPTYPHLYPPYLIRGYPDTAAL  1650
1651  ENRQTIINDYITSQQMHHNAASAMAQRADMLRGLSPRESSLALNYAAGPR  1700
1701  GIIDLSQVPHLPVLVPPTPGTPATAIDRLAYLPTAPPPFSSRHSSSPLSP  1750
1751  GGPTHLAKPTATSSSERERERERERDKSILTSTTTVEHAPIWRPGTEQSS  1800
1801  GAGGSSRPASHTHQHSPISPRTQDALQQRPSVLHNTSMKGVVTSVEPGTP  1850
1851  TVLRWARSTSTSSPVRPAATFPPATHCPLGGTLEGVYPTLMEPVLLPKET  1900
1901  SRVARPERPRVDAGHAFLTKPPAREPASSPSKSSEPRSLAPPSSSHTAIA  1950
1951  RTPAKNLAPHHASPDPPAPTSASDLHREKTQSKPFSIQELELRSLGYHSG  2000
2001  AGYSPDGVEPISPVSSPSLTHDKGLSKPLEELEKSHLEGELRHKQPGPMK  2050
2051  LSAEAAHLPHLRPLPESQPSSSPLLQTAPGIKGHQRVVTLAQHISEVITQ  2100
2101  DYTRHHPQQLSGPLPAPLYSFPGASCPVLDLRRPPSDLYLPPPDHGTPAR  2150
2151  GSPHSEGGKRSPEPSKTSVLGSSEDAIEPVSPPEGMTEPGHARSTAYPLL  2200
2201  YRDGEQGEPRMGSKSPGNTSQPPAFFSKLTESNSAMVKSKKQEINKKLNT  2250
2251  HNRNEPEYNIGQPGTEIFNMPAITGAGLMTCRSQAVQEHASTNMGLEAII  2300
2301  RKALMGKYDQWEEPPPLGANAFNPLNASASLPAAAMPITTADGRSDHALT  2350
2351  SPGGGGKAKVSGRPSSRKAKSPAPGLASGDRPPSVSSVHSEGDCNRRTPL  2400
2401  TNRVWEDRPSSAGSTPFPYNPLIMRLQAGVMASPPPPGLAAGSGPLAGPH  2450
2451  HAWDEEPKPLLCSQYETLSDSE                              2472

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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