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

NucPred

Fetching Q60974 from www.uniprot.org...

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

   1  MSSSGYPPNQGAFSTEQSRYPSHSVQYTFPSARHQQEFAVPDYRSSHLEV    50
  51  SQASQLLQQQQQQQLRRRPSLLSEFHPGSDRPQERRSGYEQFHPGPSPVD   100
 101  HDSLESKRPRLEQVSDSHFQRISAAVLPLVHTLPEGLRSSANAKKDPAFG   150
 151  VKHEAPSSPLSGQPCGDDQNASPSKLSKEELIQSMDRVDREIAKVEQQIL   200
 201  KLKKKQQQLEEEAAKPPEPEKPVSPPPVEQKHRSIVQIIYDENRKKAEEA   250
 251  HKIFEGLGPKVELPLYNQPSDTKVYHENIKTNQVMRKKLILFFKRRNHAR   300
 301  KQREQKICQRYDQLMEAWEKKVDRIENNPRRKAKESKTREYYEKQFPEIR   350
 351  KQREQQERFQRVGQRGAGLSATIARSEHEISEIIDGLSEQENNEKQMRQL   400
 401  SVIPPMMFDAEQRRVKFINMNGLMEDPMKVYKDRQFMNVWTDHEKEIFKD   450
 451  KFIQHPKNFGLIASYLERKSVPDCVLYYYLTKKNENYKALVRRNYGKRRG   500
 501  RNQQIARPSQEEKVEEKEEDKAEKTEKKEEEKKDDEEKDDKEDSKETTKE   550
 551  KDRTEATAEEPEEREQVTPRGRKTANSQGRGKGRVTRSMTSEAAAANAAA   600
 601  AATEEPPPPLPPPPEPISTEPVETSRWTEEEMEVAKKGLVEHGRNWAAIA   650
 651  KMVGTKSEAQCKNFYFNYKRRHNLDNLLQQHKQKASRKPREERDVSQCES   700
 701  VASTVSAQEDEDIEASNEEENPEDSEGAENSSDTESAPSPSPVEAAKSSE   750
 751  DSSENAASRGNTEPVAELEATTDPAPCASPSSAVPTTKPAERESVEAQVT   800
 801  DSASAETAEPMDVDHEECGAEGSSVLDPPAPTKADSVDPEMQVPENTASK   850
 851  GEGDAKERDLESTSEKTEARDEDVVVAEQIERPEPQSDDDSSATCSADEG   900
 901  VDGEPERQRVFPMDAKPSLLTPPGSILISSPIKPNLLDLPQLQHRAAVIP   950
 951  PMVSCTPCNIPIGTPVSGYALYQRHIKAMHESALLEEQRQRQEQVDLECR  1000
1001  SSTSPCSTSKSPNREWEVLQPAPHQVITNLPEGVRLPTTRPTRPPPPLIP  1050
1051  SSKTTVASEKPSFIMGGSISQGTPGTYLSSHNQAYPQEAPKPSVGSISLG  1100
1101  LPRQQESTKAAPLTYIKQEEFSPRSQNSQPEGLLVRAQHEGVVRGTAGAV  1150
1151  QEGSITRGTPASKISVETISSLRGSITQGTPALPQAGIPTEALVKGPVSR  1200
1201  MPIEESSPEKVREEAASKGHVIYEGKSGHILSYDNIKNAREGTRSPRTAH  1250
1251  EMSLKRSYEAVEGSIKQGMSMRESPVSAPLEGLICRALPRGSPHSDLKER  1300
1301  TVLSGSIMQGTPRATAESFEDGLKYPKQIKRESPPIRAFEGAITKGKPYD  1350
1351  GITTIKEMGRSIHEIPRQDILTQESRKTPEVVQSTRPIIEGSISQGTPIK  1400
1401  FDNNSGQSAIKHNVKSLITGPSKLPRGMLEIVPENIKVVERGKYEDVKAG  1450
1451  EPVRARHTSVVSSGPSVLRSTLHEAPKAQLSPGLYDDSSARRTPVSYQNT  1500
1501  ISRGSPMMNRTSDVSSSKSASHERKSTLTPTQRESIPAKSPVPGVDPIVS  1550
1551  HSPFDPHHRSSAAGEVYRSHLPTHLDPAMPFHRALDPAAAYLLQRQLSPT  1600
1601  PGYPSQYQLYAMENTRQTILNDYITSQQMQVNLRPDVTRGLSPREQPLGL  1650
1651  PYPATRGIIDLTNMPPTILVPHAGGTSTPPMDRITYIPGTQVTFPPRPYN  1700
1701  AASLSPGHPTHLAAAASAEREREREREKERERERERERERERERIAAAPA  1750
1751  DLYLRPGSEQPGRPGSHGYVRSPSPSVRTQETILQQRPSVFQGTNGTSVI  1800
1801  TPLDPTAQLRIMPLPSGGPSISQGLPASRYNTAADALAALVDAAASAPQM  1850
1851  DVSKTKESKHEAARLEENLRSRSAAVSEQQQLEQKNLEVEKRSVQCVCTS  1900
1901  SALPSGKAQPHASVVYSEAGKDKGPPPKSRYEEELRTRGKTTITAANFID  1950
1951  VIITRQIASDKDARERGSQSSDSSSSLSSHRYETASDAIEVISPASSPAP  2000
2001  PQEKPQAYQPDMVKANQAENESTRQYEGPLHHYRSQQESPSPQQQPPLPP  2050
2051  SSQSEGMGQVPRTHRLITLADHICQIITQDFARNQVPSQASTSTFQTSPS  2100
2101  ALSSTPVRTKTSSRYSPESQSQTVLHPRPGPRVSPENLVDKSRGSRPGKS  2150
2151  PERSHIPSEPYEPISPPQGPAVHEKQDSMLLLSQRGVDPAEQRSDSRSPG  2200
2201  SISYLPSFFTKLESTSPMVKSKKQEIFRKLNSSGGGDSDMAAAQPGTEIF  2250
2251  NLPAVTTSGAVSSRSHSFADPASNLGLEDIIRKALMGSFDDKVEDHGVVM  2300
2301  SHPVGIMPGSASTSVVTSSEARRDEGEPSPHAGVCKPKLINKSNSRKSKS  2350
2351  PIPGQSYLGTERPSSVSSVHSEGDYHRQTPGWAWEDRPSSTGSTQFPYNP  2400
2401  LTIRMLSSTPPTQIACAPSAITQAAPHQQNRIWEREPAPLLSAQYETLSD  2450
2451  SDD                                                 2453

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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