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

NucPred

Fetching Q5U1Z0 from www.uniprot.org...

The NucPred score for your sequence is 0.56 (see score help below)

   1  MACSIVQFCSFQDLQSARDFLFPQLREETPGALRRDPSKTSNWEDDSWGA    50
  51  WEETEPQEPEEEGNTSKTQKHSWLQECVLSLSPTSDLMVIAREQKAAFLV   100
 101  RKWKHSDKGKEEMQFAVGWSGSVSAEEGEYVTSALCIPLASQKRSSTGRP   150
 151  DWTCIVVGFTSGYVRFYTEGVLLLAQLLNEDRVLQLKCRTYEIPRHPGVT   200
 201  EQNEELSILYPAAIVTIDGFSLFQSLRACRNQVAKAAASGNENIQPPPLA   250
 251  YKKWGLQDIDTIIDHASIGIMTLSPFDQMKTASNIGGFNAAIKNSPPAMS   300
 301  QYITVGSSPFTGFFYALEGSTQPLLSHVALAVASKLTSALFSAASGWLGW   350
 351  KSKHEEETVQKQKPKMEPATPLAVRFGLPDSRRHGESICLSPCNTLAAVT   400
 401  DDFGRVILLDVARGIAIRMWKGYRDAQIGWIQIVEDLHERVPEKGDFSPF   450
 451  GNTQGPSRVAQFLVIYAPRRGILEVWSTQQGPRVGAFNVGKHCRLLYPGY   500
 501  KIMGLNNVTSQSWQPQTYQICLVDPVSASVKAVNVPFHLALSDKKSERAK   550
 551  DLHLVKKLAALLRAKSPRPDSFEAEIKELILDIKYPATKKQALESILASD   600
 601  RVSFSCLRNVTQTSMDTLKNQELESVDEGLLQFCASKLKLLHLYESVSQL   650
 651  NTLDFHSDTPFSDNDLAVLLRLDDKELLKLRALLEKYKQENTKATVRFSE   700
 701  DADGVLPVKTFLEYLDYEKDALSIRKTSEEECVALGSFFFWKCLHGESST   750
 751  EDMCHTLESAGLSPQQLLSLLLSVWLSKEKDILDKPQSVCCLHTMLSLLS   800
 801  KMKVAIDETWDSQSVSPWWQQMRMACIQSENNGAALLSAHVGHSVAAQMS   850
 851  SSATDKKFSQMVLDADAEALTDSWEALSLDTEYWKLLLRQLEDCLILQTL   900
 901  LHSRASPPAAKASSPQTEPLPRLSVKKLLEGGKGGIADSVAKWIFKQDLS   950
 951  PELLKCANREKDVENPDEPREGIARSPPEVSEVETDLGAVPDLLRLAYEQ  1000
1001  FPCSLELDVLHAHCCWEYVVQWNKDPEEARFLVRSIEHLRHILNPHVQNG  1050
1051  ISLMMWNTFLVKRFSAATYLMDKVGKSPKDRLCRRDVGMSDTALTSFLGS  1100
1101  CLDLLQTSLEADISRDEVQVPVLDTEDAWLSVEGPTSIVELALEQKPIHY  1150
1151  PLVEHHSILCSILYAAMSFSLKSVKPLALFDSKGKNAFFKDLTSIQLLPS  1200
1201  GEMDPNFISVRQQFLLKVVSAAVQAQHSKDKDPSARAADTHGQDLNWTAL  1250
1251  AVDLAHHLQVSEDVIRRHYVGELYSYGADLLGEEAILQVQDKEVLASQLL  1300
1301  VLTGQRLAHALFHTQTKEGMELLARLPPTLCTWLKAMNPQDLQNTGVPVA  1350
1351  ATAKLVHKVMELLPEKHGQYSLALHLIEAVEAMATL                1386

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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