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

NucPred

Fetching Q64511 from www.uniprot.org...

The NucPred score for your sequence is 0.72 (see score help below)

   1  MAKSSLAGSDGALTWVNNATKKEELETANKNDSTKKLSVERVYQKKTQLE    50
  51  HILLRPDTYIGSVEPLTQLMWVYDEDVGMNCREVTFVPGLYKIFDEILVN   100
 101  AADNKQRDKNMTCIKVSIDPESNIISIWNNGKGIPVVEHKVEKVYVPALI   150
 151  FGQLLTSSNYDDDEKKVTGGRNGYGAKLCNIFSTKFTVETACKEYKHSFK   200
 201  QTWMNNMMKTSEAKIKHFDGEDYTCITFQPDLSKFKMEKLDKDIVALMTR   250
 251  RAYDLAGSCKGVKVMFNGKKLPVNGFRSYVDLYVKDKLDETGVALKVIHE   300
 301  LANERWDVCLTLSEKGFQQISFVNSIATTKGGRHVDYVVDQVVSKLIEVV   350
 351  KKKNKAGVSVKPFQVKNHIWVFINCLIENPTFDSQTKENMTLQPKSFGSK   400
 401  CQLSEKFFKAASNCGIVESILNWVKFKAQTQLNKKCSSVKYSKIKGIPKL   450
 451  DDANDAGGKHSLECTLILTEGDSAKSLAVSGLGVIGRDRYGVFPLRGKIL   500
 501  NVREASHKQIMENAEINNIIKIVGLQYKKSYDDAESLKTLRYGKIMIMTD   550
 551  QDQDGSHIKGLLINFIHHNWPSLLKHGFLEEFITPIVKASKNKQELSFYS   600
 601  IPEFDEWKKHIENQKAWKIKYYKGLGTSTAKEAKEYFADMERHRILFRYA   650
 651  GPEDDAAITLAFSKKKIDDRKEWLTNFMEDRRQRRLHGLPEQFLYGTATK   700
 701  HLTYNDFINKELILFSNSDNERSIPSLVDGFKPGQRKVLFTCFKRNDKRE   750
 751  VKVAQLAGSVAEMSAYHHGEQALMMTIVNLAQNFVGSNNINLLQPIGQFG   800
 801  TRLHGGKDAASPRYIFTMLSSLARLLFPAVDDNLLKFLYDDNQRVEPEWY   850
 851  IPIIPMVLINGAEGIGTGWACKLPNYDAREIVNNVRRMLEGLDPHPMLPN   900
 901  YKNFKGTIQELGQNQYAVSGEIFVVDRNTVEITELPVRTWTQVYKEQVLE   950
 951  PMLNGTDKTPALISDYKEYHTDTTVKFVVKMTEEKLAQAEAAGLHKVFKL  1000
1001  QTTLTCNSMVLFDHMGCLKKYETVQDILKEFFDLRLSYYGLRKEWLVGML  1050
1051  GAESTKLNNQARFILEKIQGKITIENRSKKDLIQMLVQRGYESDPVKAWK  1100
1101  EAQEKAAEEEDSQNQHDDSSSDSGTPSGPDFNYILNMSLWSLTKEKVEEL  1150
1151  IKQRDTKGREVNDLKRKSPSDLWKEDLAAFVEELDKVEAQEREDILAGMS  1200
1201  GKAIKGKVGKPKVKKLQLEETMPSPYGRRIVPEITAMKADASRKLLKKKK  1250
1251  GDPDTTVVKVEFDEEFSGTPAEGTGEETLTPSAPVNKGPKPKREKKEPGT  1300
1301  RVRKTPTSTGKTNAKKVKKRNPWSDDESKSESDLEEAEPVVIPRDSLLRR  1350
1351  AAAERPKYTFDFSEEEDDDAAAADDSNDLEELKVKASPITNDGEDEFVPS  1400
1401  DGLDKDEYAFSSGKSKATPEKSSNDKKSQDFGNLFSFPSYSQKSEDDSAK  1450
1451  FDSNEEDTASVFAPSFGLKQTDKLPSKTVAAKKGKPPSDTAPKAKRAPKQ  1500
1501  KKIVETINSDSDSEFGIPKKTTTPKGKGRGAKKRKASGSENEGDYNPGRK  1550
1551  PSKTASKKPKKTSFDQDSDVDIFPSDFTSEPPALPRTGRARKEVKYFAES  1600
1601  DEEEDVDFAMFN                                        1612

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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