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

NucPred

Fetching O95180 from www.uniprot.org...

The NucPred score for your sequence is 0.69 (see score help below)

   1  MTEGARAADEVRVPLGAPPPGPAALVGASPESPGAPGREAERGSELGVSP    50
  51  SESPAAERGAELGADEEQRVPYPALAATVFFCLGQTTRPRSWCLRLVCNP   100
 101  WFEHVSMLVIMLNCVTLGMFRPCEDVECGSERCNILEAFDAFIFAFFAVE   150
 151  MVIKMVALGLFGQKCYLGDTWNRLDFFIVVAGMMEYSLDGHNVSLSAIRT   200
 201  VRVLRPLRAINRVPSMRILVTLLLDTLPMLGNVLLLCFFVFFIFGIVGVQ   250
 251  LWAGLLRNRCFLDSAFVRNNNLTFLRPYYQTEEGEENPFICSSRRDNGMQ   300
 301  KCSHIPGRRELRMPCTLGWEAYTQPQAEGVGAARNACINWNQYYNVCRSG   350
 351  DSNPHNGAINFDNIGYAWIAIFQVITLEGWVDIMYYVMDAHSFYNFIYFI   400
 401  LLIIVGSFFMINLCLVVIATQFSETKQRESQLMREQRARHLSNDSTLASF   450
 451  SEPGSCYEELLKYVGHIFRKVKRRSLRLYARWQSRWRKKVDPSAVQGQGP   500
 501  GHRQRRAGRHTASVHHLVYHHHHHHHHHYHFSHGSPRRPGPEPGACDTRL   550
 551  VRAGAPPSPPSPGRGPPDAESVHSIYHADCHIEGPQERARVAHAAATAAA   600
 601  SLRLATGLGTMNYPTILPSGVGSGKGSTSPGPKGKWAGGPPGTGGHGPLS   650
 651  LNSPDPYEKIPHVVGEHGLGQAPGHLSGLSVPCPLPSPPAGTLTCELKSC   700
 701  PYCTRALEDPEGELSGSESGDSDGRGVYEFTQDVRHGDRWDPTRPPRATD   750
 751  TPGPGPGSPQRRAQQRAAPGEPGWMGRLWVTFSGKLRRIVDSKYFSRGIM   800
 801  MAILVNTLSMGVEYHEQPEELTNALEISNIVFTSMFALEMLLKLLACGPL   850
 851  GYIRNPYNIFDGIIVVISVWEIVGQADGGLSVLRTFRLLRVLKLVRFLPA   900
 901  LRRQLVVLVKTMDNVATFCTLLMLFIFIFSILGMHLFGCKFSLKTDTGDT   950
 951  VPDRKNFDSLLWAIVTVFQILTQEDWNVVLYNGMASTSSWAALYFVALMT  1000
1001  FGNYVLFNLLVAILVEGFQAEGDANRSDTDEDKTSVHFEEDFHKLRELQT  1050
1051  TELKMCSLAVTPNGHLEGRGSLSPPLIMCTAATPMPTPKSSPFLDAAPSL  1100
1101  PDSRRGSSSSGDPPLGDQKPPASLRSSPCAPWGPSGAWSSRRSSWSSLGR  1150
1151  APSLKRRGQCGERESLLSGEGKGSTDDEAEDGRAAPGPRATPLRRAESLD  1200
1201  PRPLRPAALPPTKCRDRDGQVVALPSDFFLRIDSHREDAAELDDDSEDSC  1250
1251  CLRLHKVLEPYKPQWCRSREAWALYLFSPQNRFRVSCQKVITHKMFDHVV  1300
1301  LVFIFLNCVTIALERPDIDPGSTERVFLSVSNYIFTAIFVAEMMVKVVAL  1350
1351  GLLSGEHAYLQSSWNLLDGLLVLVSLVDIVVAMASAGGAKILGVLRVLRL  1400
1401  LRTLRPLRVISRAPGLKLVVETLISSLRPIGNIVLICCAFFIIFGILGVQ  1450
1451  LFKGKFYYCEGPDTRNISTKAQCRAAHYRWVRRKYNFDNLGQALMSLFVL  1500
1501  SSKDGWVNIMYDGLDAVGVDQQPVQNHNPWMLLYFISFLLIVSFFVLNMF  1550
1551  VGVVVENFHKCRQHQEAEEARRREEKRLRRLERRRRSTFPSPEAQRRPYY  1600
1601  ADYSPTRRSIHSLCTSHYLDLFITFIICVNVITMSMEHYNQPKSLDEALK  1650
1651  YCNYVFTIVFVFEAALKLVAFGFRRFFKDRWNQLDLAIVLLSLMGITLEE  1700
1701  IEMSAALPINPTIIRIMRVLRIARVLKLLKMATGMRALLDTVVQALPQVG  1750
1751  NLGLLFMLLFFIYAALGVELFGRLECSEDNPCEGLSRHATFSNFGMAFLT  1800
1801  LFRVSTGDNWNGIMKDTLRECSREDKHCLSYLPALSPVYFVTFVLVAQFV  1850
1851  LVNVVVAVLMKHLEESNKEAREDAELDAEIELEMAQGPGSARRVDADRPP  1900
1901  LPQESPGARDAPNLVARKVSVSRMLSLPNDSYMFRPVVPASAPHPRPLQE  1950
1951  VEMETYGAGTPLGSVASVHSPPAESCASLQIPLAVSSPARSGEPLHALSP  2000
2001  RGTARSPSLSRLLCRQEAVHTDSLEGKIDSPRDTLDPAEPGEKTPVRPVT  2050
2051  QGGSLQSPPRSPRPASVRTRKHTFGQRCVSSRPAAPGGEEAEASDPADEE  2100
2101  VSHITSSACPWQPTAEPHGPEASPVAGGERDLRRLYSVDAQGFLDKPGRA  2150
2151  DEQWRPSAELGSGEPGEAKAWGPEAEPALGARRKKKMSPPCISVEPPAED  2200
2201  EGSARPSAAEGGSTTLRRRTPSCEATPHRDSLEPTEGSGAGGDPAAKGER  2250
2251  WGQASCRAEHLTVPSFAFEPLDLGVPSGDPFLDGSHSVTPESRASSSGAI  2300
2301  VPLEPPESEPPMPVGDPPEKRRGLYLTVPQCPLEKPGSPSATPAPGGGAD  2350
2351  DPV                                                 2353

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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