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

NucPred

Fetching P48725 from www.uniprot.org...

The NucPred score for your sequence is 0.96 (see score help below)

   1  MEDEQEQRRRKVEAGRAKLANFRQRKTKGDCPNSKKKTAKRKGSAVHASV    50
  51  QEEGSVATPNSELPQGGAVFESPSCSNTLEGTRGASAAQEQEDCELDVTD   100
 101  LQGQQQTQPPPPQTAHSLELEALRLSLNNMHTAQLELTQANLQKEKETAL   150
 151  TELREMLNGRRAQELALLQSRQQCELELLREQHAREKEEMALRSGQEAAE   200
 201  LKEKLRSEMEKNAQTIETLKQDWESERELCLENLRQELSLKHQSEMEGLQ   250
 251  SQFQKELSEQKVELEKIFQAKHEAEVSLKNLEAQHQAAIKKLQEDLQSEH   300
 301  CQYLQDLEQKFREKEKAKELELETLQASYEDLKAQSQEEIRLLWSQLESM   350
 351  KTNREELNGSWDPVLAQASHLEELEHLRSGFAQQQQQERAQHESELEHLR   400
 401  VYFEKKLKDAEKTYQEDLTVFQQRLQEAREDSLESTEISSSCVLPEETSG   450
 451  REGKEPPDPLDLQLGQPKVQESLVEDCQVKLSKAEEKIQQMKEEFQKKEA   500
 501  EWELSREELKREAEERLASMFLELREKAESEKLSIISRFEHRESSMRHLQ   550
 551  DQQAAQILDLERSLMEQQGHLRQLEQELTRDDLLPCSQCGQEPAMAQEEK   600
 601  NGALLREKEDCALQLLMAQNRFLEERKEIMEKFAKEQDAFLRDAQEKHNH   650
 651  ELQLLQQGHQQQLLALRMELETKHRSELTEQLASSESRRQALLETHVAEL   700
 701  QVKHNAEISALEKRHLSNLDELESCYVADVQTIRDEHQQALELLRAELEE   750
 751  QLQKKESCHREMLTQELENLKRQHAEELQSVRDSLRMEMSAQHIENGKGP   800
 801  AADLQGAHQQDPAMALHNEGHLLVEDGDAVLRSVDAEGLLHQAGPQELGD   850
 851  AHTVEMQKSQAELAKPQELQASQDQVAQVRDKVFLLNRELEECRAELEQL   900
 901  QQRRERENQEGTTLICMLRADLELAQGEGKALRDALRRLLDLFGDTLKAA   950
 951  VTLKSRISERAGLLLDHEDAADTSDARLAAAALGDMWSDEGLLEIDRTLP  1000
1001  EGAETSSVCEISSHVCESFFISPENTLDCEQPIRRVYQSLSTAVEGLLEM  1050
1051  ALDSSKQLEEARQLHRCVEREFRHRNEEMAQAMQKQQELLERLREESAAK  1100
1101  DRLALELHTAKGLLEGFKVEKVDLQEALGKKEESEQQLILELEDLRKQLQ  1150
1151  QAARELLTLKEEKSVLWNQKETLTNEAKEREAALQEEVESLTRVQWESRK  1200
1201  QSEKDRATLLSQMRVLESELEDQLVQHRGCAQLAEEVATLKQQLAALDKH  1250
1251  LRSQRQFMDDQAAEREHEREEFQQEIQRLEGQLRQAARPRPPGPRDSQCV  1300
1301  QLDEEVELLQEKLREKLDGFNELVIKKDFADQQLLIQEEEIKRLEETNAS  1350
1351  IQRQMVQLQEELEKQKKSMEELKEKEILKQENMGDLLLTTVSRSGLDEAG  1400
1401  CPMLPQGSSSRGPEAQPDVTERALLQHENEVVHRRNSEIDELKSLIENLQ  1450
1451  ENQRQLQKDKAEEIEQLHEVIEKLQSELSLMGPKVHEVSDPQAGSLHSEL  1500
1501  ACLRGEGLGGQALRSELQAAQAAKEVFGQLLANQAHGHSQALEALQQRLQ  1550
1551  DAEEVAARHLAELEHCVALREAEVEAMASQIQEFAATLKAKEAIIEQRDL  1600
1601  EIDAVNKWKVSHSLELEAILLALAHFRHALEQQTCATPDEPPELRQLRVQ  1650
1651  CARLSHQLQVLYRPFLKCRMQLDQHQPHVASIGCANPCADDELEQEGVSN  1700
1701  RLALAPHSLAAQAKEELEDCPLGKANLMAQVRQLQEELDHRVHSVASRDT  1750
1751  NSETCKLQQPNLSENGPRNHCCNGEESKPSPPDDVLNIAKTTWDVIDIIK  1800
1801  NQDLLVQVEMPDFPTQEKLTSQGGPFSSQASGHSGSLLPEEAAEPQQDPV  1850
1851  RALDLSSWSSPEVVRKDPSLEPQHSLPLTPGVGTVSLHSVDISPDWTDPL  1900
1901  LQADVSGLLCYPGKSASGQAPLWAVAPSAGKHHAERTATEKDVEDFIVTS  1950
1951  FDSQELLTSPSHELARRSDGSRKSDGPDIAMMLTLGSEGSETPTTDLVAA  2000
2001  AAAAVPFSRRFVQSPGAMKEKEIHAKQMKALLQMVFDESHQILALSESQD  2050
2051  PSSALNKGEPRDPLDGFPRDSQALSEVTTDKGEKESLETHLTWSEELLRA  2100
2101  IQEVFAREQEKAELQPRPYGSNLGDYNSLVQRLEKVIQEQGDPQKVQDHL  2150
2151  CLSDRSSLLAEIQALRAQLRMTHLQNQEKLQQLCAALTSTEARGSQREHQ  2200
2201  LRRQVELLAYKVEQEKCIANELQKTLSKEQETASDVRKRLVVEQNAVQDL  2250
2251  KSELHACKQENTSLLESLDKVQQEVLRLRAVLDGKEKELKVVLEELESER  2300
2301  GKGQALQAQQEEQQLRYLQREGQSSRALEELKLSLEKQLAQNNQLCVALK  2350
2351  HERAAKDNLQKELQIEASRCEALLAQEKGQLSELQKSLEAERSRSLELSE  2400
2401  ALQHERLLTEQLSRNSQEACARQETQVQHALLRKLKAEKTRALELEAMLE  2450
2451  KVQKQAAHTQQQLEAQAQERCVELRREKERELEIQRQRDEHKIEQLQRLV  2500
2501  RELRWKEEVSGGNGPCRGSPGRGSLERDQFQEQQQELEKIRQQLLCAAGL  2550
2551  LTSFTNHTVDRTIKDWTSSNEKAVSSLMRTLEELKSELSMPTSFQKKMTA  2600
2601  ELQVQLMNELLSDNDALTKAVGMATREKAELCRTVSRLEKTLKHHTQKGC  2650
2651  VLNRQSKSSLKQDGTDLQSSLRHSDPEWHSQTTSGDTNTCNIKMEKLYLH  2700
2701  YLRAESFRKALIYQKKYLLLLIGGFQDSEQETLSMIAHLGVFPSKADKKI  2750
2751  TMSRPFTKFRTAVRVVIAVLRLRFLVKKWQEVDRKGALVHPKSTRHGHRT  2800
2801  SQRQRSPSGPRASLPTRDTSSGPTKASRHSPRSAAAGSPGKERSTSTPSS  2850
2851  RLERSLTASQDPEHSLTEYIHHLEMIQQRLGGLPPDSTQKSCHQKIKQ    2898

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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