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

NucPred

Fetching Q8WXD9 from www.uniprot.org...

The NucPred score for your sequence is 0.82 (see score help below)

   1  MGKEQELVQAVKAEDVGTAQRLLQRPRPGKAKLLGSTKKINVNFQDPDGF    50
  51  SALHHAALNGNTELISLLLEAQAAVDIKDNKGMRPLHYAAWQGRKEPMKL   100
 101  VLKAGSAVNIPSDEGHIPLHLAAQHGHYDVSEMLLQHQSNPCMVDNSGKT   150
 151  PLDLACEFGRVGVVQLLLSSNMCAALLEPRPGDATDPNGTSPLHLAAKNG   200
 201  HIDIIRLLLQAGIDINRQTKSGTALHEAALCGKTEVVRLLLDSGINAHVR   250
 251  NTYSQTALDIVHQFTTSQASREIKQLLREASAALQVRATKDYCNNYDLTS   300
 301  LNVKAGDIITVLEQHPDGRWKGCIHDNRTGNDRVGYFPSSLGEAIVKRAG   350
 351  SRAGTEPSLPQGSSSSGPSAPPEEIWVLRKPFAGGDRSGSISGMAGGRGS   400
 401  GGHALHAGSEGVKLLATVLSQKSVSESGPGDSPAKPPEGSAGVARSQPPV   450
 451  AHAGQVYGEQPPKKLEPASEGKSSEAVSQWLTAFQLQLYAPNFISAGYDL   500
 501  PTISRMTPEDLTAIGVTKPGHRKKIAAEISGLSIPDWLPEHKPANLAVWL   550
 551  SMIGLAQYYKVLVDNGYENIDFITDITWEDLQEIGITKLGHQKKLMLAVR   600
 601  KLAELQKAEYAKYEGGPLRRKAPQSLEVMAIESPPPPEPTPADCQSPKMT   650
 651  TFQDSELSDELQAAMTGPAEVGPTTEKPSSHLPPTPRATTRQDSSLGGRA   700
 701  RHMSSSQELLGDGPPGPSSPMSRSQEYLLDEGPAPGTPPREARPGRHGHS   750
 751  IKRASVPPVPGKPRQVLPPGTSHFTPPQTPTKTRPGSPQALGGPHGPAPA   800
 801  TAKVKPTPQLLPPTERPMSPRSLPQSPTHRGFAYVLPQPVEGEVGPAAPG   850
 851  PAPPPVPTAVPTLCLPPEADAEPGRPKKRAHSLNRYAASDSEPERDELLV   900
 901  PAAAGPYATVQRRVGRSHSVRAPAGADKNVNRSQSFAVRPRKKGPPPPPP   950
 951  KRSSSALASANLADEPVPDAEPEDGLLGVRAQCRRASDLAGSVDTGSAGS  1000
1001  VKSIAAMLELSSIGGGGRAARRPPEGHPTPRPASPEPGRVATVLASVKHK  1050
1051  EAIGPGGEVVNRRRTLSGPVTGLLATARRGPGESADPGPFVEDGTGRQRP  1100
1101  RGPSKGEAGVEGPPLAKVEASATLKRRIRAKQNQQENVKFILTESDTVKR  1150
1151  RPKAKEREAGPEPPPPLSVYHNGTGTVRRRPASEQAGPPELPPPPPPAEP  1200
1201  PPTDLAHLPPLPPPEGEARKPAKPPVSPKPVLTQPVPKLQGSPTPTSKKV  1250
1251  PLPGPGSPEVKRAHGTPPPVSPKPPPPPTAPKPVKAVAGLPSGSAGPSPA  1300
1301  PSPARQPPAALAKPPGTPPSLGASPAKPPSPGAPALHVPAKPPRAAAAAA  1350
1351  AAAAAPPAPPEGASPGDSARQKLEETSACLAAALQAVEEKIRQEDAQGPR  1400
1401  DSAAEKSTGSILDDIGSMFDDLADQLDAMLE                     1431

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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