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

NucPred

Fetching Q92355 from www.uniprot.org...

The NucPred score for your sequence is 0.81 (see score help below)

   1  MAENLSDQDCFEKLSSSKEGQHWFCSGLLTQYIQPTFFWFAHDETPSFKW    50
  51  VLNAYHERLRSCTSCIQAYYELRNESLAKGSYSFTGFSITDLQEKWNKWD   100
 101  IIRVLEDFKALEDETIDFTSLPCLIFETLLNPKLFTCKNIYKNAIDAFNG   150
 151  LLSDWCSNIFLPGYLLFFYEASHPDVLEWVHSFFKENTEIRISSATVDAV   200
 201  FNTVVFESQNSSDSDCNFVSISSPEFWERTYMFLELLPLQSITAACESIL   250
 251  KDYLLNLVKTSESLSSQQMSCLRICCNSSSFWSAADSFKEVSSFLKNLLK   300
 301  NVTATPFEVSDMNWAYIIASFFRTCLNDFVSVFPEWLKGFVEEKRTIGFI   350
 351  IYSVLDALFDLLSLDYSSPSFLNNTLSLMNANSITILQDYPEYMLKLRLH   400
 401  SLLYDIAFISWSHKAITKNPSFVFDPSYELSPFWKLDNLQEEKISDVLFS   450
 451  KISSCCFAHDIEISENSTPSGTMVQFAELWQVMSEYISGFLKGFSEKSST   500
 501  EISNMLGDSSKFDTVVSFLLSPTQPLYVSAFHIVQIITNCTKNRNEALKK   550
 551  LVAMDFRGIVHGLADAVLNWQSILSFFPALRIMRFLSITNKSLSSDNSAF   600
 601  TENDIPTLGAYWQCIWNILDLVFSNVARWSLNNPADTVKALMKLTLKFVD   650
 651  DLFQNDGIFIKLLAKFDSLILLGETSESLFSFIMWLKINDLELRGIVINS   700
 701  LCKLFTKFSNFDYLFEDRTVTFLTDFIIRKQKAHLSADQCKQLANVLTQA   750
 751  SPEAKTVLEQHRLSEMRKTKKQTELTNSAHVIKPSPTPQITVKQNTTKSS   800
 801  SAPRMGMLEQLKQEYLTKRNFESKLKSSAVSSRKPTFNEVKPANLLAEDL   850
 851  SDNEDDIDRKQGLFSLAKANKIPEIRQQERRQVQLLSNSTIKMHPSQIRM   900
 901  MTNRNVANVKARLFPSMTDFYKEILSWEPANQSPNPVLKFHKLDGKIIDS   950
 951  FKTVEHYMEVLQPMIFMECWSQIQSTKLDLKFSPVEGIMVERTAVNNFVD  1000
1001  IGVSVAPKDLYGYPLYDTEVVSLAFNKEDASSMKGLCCFAKVERIVRQTN  1050
1051  GVLVVLRTLPSMEILNKLQGNCALWFLKLTNLATFTRQYAGIRGLPYFHL  1100
1101  ADDIIRARPCSQPVKHSSSEIKAAMKRYQVNEPQAKAIMCALDNNGFTLI  1150
1151  QGPPGTGKTKTIIGIISALLVDLSRYHITRPNQQSKSTESKQQILLCAPS  1200
1201  NAAVDEVLLRLKRGFLLENGEKYIPRVVRIGNPETINVSVRDLSLEYQTE  1250
1251  KQLLEVNQGAIDLGSLQELTRWRDTFYDCIQKIEELEKQIDVARDVAEDT  1300
1301  KSLGKELQNKINEKNLAEQKVEELQSQSFTKNKEVDLLRKKAQKAILKQA  1350
1351  DVVCATLSGSGHDLVAHSSLNFSTVIIDEAAQAVELDTIIPLRYGAKKCI  1400
1401  LVGDPNQLPPTVLSKKAASLNYSQSLFVRIQKNFSNQMCLLSIQYRMHPD  1450
1451  ISHFPSKKFYDSRLEDGDNMAEKTQQVWHVNPKFTQYRLFDVRGKERTSN  1500
1501  TMSTYNLEEVEYLVNMVDELLNKFPDVNFTGRIGVITPYRSQLHELRRAF  1550
1551  KVKYGKSFMSTIDIQTVDGFQGQEKDIIFFSCVKSYSKHGIGFLRDFRRL  1600
1601  NVALTRARSSLLIIGNMETLKTDDLWGSLVDDALSRKLVESPHIDSEGRL  1650
1651  ITISRTSEKRMKNEEFVEPPSKKLANSEPSKEIRQRS               1687

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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