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

NucPred

Fetching Q5UIP0 from www.uniprot.org...

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

   1  MTARGQSPLAPLLETLEDPSASHGGQTDAYLTLTSRMTGEEGKEVITEIE    50
  51  KKLPRLYKVLKTHISSQNSELSSAALQALGFCLYNPKITSELSEANALEL   100
 101  LSKLNDTIKNSDKNVRTRALWVISKQTFPSEVVGKMVSSIIDSLEILFNK   150
 151  GETHSAVVDFEALNVIVRLIEQAPIQMGEEAVRWAKLVIPLVVHSAQKVH   200
 201  LRGATALEMGMPLLLQKQQEIASITEQLMTTKLISELQKLFMSKNETYVL   250
 251  KLWPLFVKLLGRTLHRSGSFINSLLQLEELGFRSGAPMIKKIAFIAWKSL   300
 301  IDNFALNPDILCSAKRLKLLMQPLSSIHVRTETLALTKLEVWWYLLMRLG   350
 351  PHLPANFEQVCVPLIQSTISIDSNASPQGNSCHVATSPGLNPMTPVHKGA   400
 401  SSPYGAPGTPRMNLSSNLGGMATIPSIQLLGLEMLLHFLLGPEALSFAKQ   450
 451  NKLVLSLEPLEHPLISSPSFFSKHANTLITAVHDSFVAVGKDAPDVVVSA   500
 501  IWKELISLVKSVTESGNKKEKPGSEVLTLLLKSLESIVKSEVFPVSKTLV   550
 551  LMEITIKGLPQKVLGSPAYQVANMDILNGTPALFLIQLIFNNFLECGVSD   600
 601  ERFFLSLESLVGCVLSGPTSPLAFSDSVLNVINQNAKQLENKEHLWKMWS   650
 651  VIVTPLTELINQTNEVNQGDALEHNFSAIYGALTLPVNHIFSEQRFPVAT   700
 701  MKTLLRTWSELYRAFARCAALVATAEENLCCEELSSKIMSSLEDEGFSNL   750
 751  LFVDRIIYIITVMVDCIDFSPYNIKYQPKVKSPQRPSDWSKKKNEPLGKL   800
 801  TSLFKLIVKVIYSFHTLSFKEAHSDTLFTIGNSITGIISSVLGHISLPSM   850
 851  IRKIFATLTRPLALFYENSKLDEVPKVYSCLNNKLEKLLGEIIACLQFSY   900
 901  TGTYDSELLEQLSPLLCIIFLHKNKQIRKQSAQFWNATFAKVMMLVYPEE   950
 951  LKPVLTQAKQKFLLLLPGLETVEMMEESSGPYSDGTENSQLNVKISGMER  1000
1001  KSNGKRDSFLAQTKNKKENMKPAAKLKLESSSLKVKGEILLEEEKSTDFV  1050
1051  FIPPEGKDAKERILTDHQKEVLKTKRCDIPAMYNNLDVSQDTLFTQYSQE  1100
1101  EPMEIPTLTRKPKEDSKMMITEEQMDSDIVIPQDVTEDCGMAEHLEKSSL  1150
1151  SNNECGSLDKTSPEMSNSNNDERKKALISSRKTSTECASSTENSFVVSSS  1200
1201  SVSNTTVAGTPPYPTSRRQTFITLEKFDGSENRPFSPSPLNNISSTVTVK  1250
1251  NNQETMIKTDFLPKAKQREGTFSKSDSEKIVNGTKRSSRRAGKAEQTGNK  1300
1301  RSKPLMRSEPEKNTEESVEGIVVLENNPPGLLNQTECVSDNQVHLSESTM  1350
1351  EHDNTKLKAATVENAVLLETNTVEEKNVEINLESKENTPPVVISADQMVN  1400
1401  EDSQVQITPNQKTLRRSSRRRSEVVESTTESQDKENSHQKKERRKEEEKP  1450
1451  LQKSPLHIKDDVLPKQKLIAEQTLQENLIEKGSNLHEKTLGETSANAETE  1500
1501  QNKKKADPENIKSEGDGTQDIVDKSSEKLVRGRTRYQTRRASQGLLSSIE  1550
1551  NSESDSSEAKEEGSRKKRSGKWKNKSNESVDIQDQEEKVVKQECIKAENQ  1600
1601  SHDYKATSEEDVSIKSPICEKQDESNTVICQDSTVTSDLLQVPDDLPNVC  1650
1651  EEKNETSKYAEYSFTSLPVPESNLRTRNAIKRLHKRDSFDNCSLGESSKI  1700
1701  GISDISSLSEKTFQTLECQHKRSRRVRRSKGCDCCGEKSQPQEKSLIGLK  1750
1751  NTENNDVEISETKKADVQAPVSPSETSQANPYSEGQFLDEHHSVNFHLGL  1800
1801  KEDNDTINDSLIVSETKSKENTMQESLPSGIVNFREEICDMDSSEAMSLE  1850
1851  SQESPNENFKTVGPCLGDSKNVSQESLETKEEKPEETPKMELSLENVTVE  1900
1901  GNACKVTESNLEKAKTMELNVGNEASFHGQERTKTGISEEAAIEENKRND  1950
1951  DSEADTAKLNAKEVATEEFNSDISLSDNTTPVKLNAQTEISEQTAAGELD  2000
2001  GGNDVSDLHSSEETNTKMKNNEEMMIGEAMAETGHDGETENEGITTKTSK  2050
2051  PDEAETNMLTAEMDNFVCDTVEMSTEEGIIDANKTETNTEYSKSEEKLDN  2100
2101  NQMVMESDILQEDHHTSQKVEEPSQCLASGTAISELIIEDNNASPQKLRE  2150
2151  LDPSLVSANDSPSGMQTRCVWSPLASPSTSILKRGLKRSQEDEISSPVNK  2200
2201  VRRVSFADPIYQAGLADDIDRRCSIVRSHSSNSSPIGKSVKTSPTTQSKH  2250
2251  NTTSAKGFLSPGSRSPKFKSSKKCLISEMAKESIPCPTESVYPPLVNCVA  2300
2301  PVDIILPQITSNMWARGLGQLIRAKNIKTIGDLSTLTASEIKTLPIRSPK  2350
2351  VSNVKKALRIYHEQQVKTRGLEEIPVFDISEKTVNGIENKSLSPDEERLV  2400
2401  SDIIDPVALEIPLSKNLLAQISALALQLDSEDLHNYSGSQLFEMHEKLSC  2450
2451  MANSVIKNLQSRWRSPSHENSI                              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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