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

NucPred

Fetching P00522 from www.uniprot.org...

The NucPred score for your sequence is 0.84 (see score help below)

   1  MGAQQGKDRGAHSGGGGSGAPVSCIGLSSSPVASVSPHCISSSSGVSSAP    50
  51  LGGGSTLRGSRIKSSSSGVASGSGSGGGGGGSGSGLSQRSGGHKDARCNP   100
 101  TVGLNIFTEHNEALLQSRPLPHIPAGSTAASLLADAAELQQHQQDSGGLG   150
 151  LQGSSLGGGHSSTTSVFESAHRWTSKENLLAPGPEEDDPQLFVALYDFQA   200
 201  GGENQLSLKKGEQVRILSYNKSGEWCEAHSDSGNVGWVPSNYVTPLNSLE   250
 251  KHSWYHGPISRNAAEYLLSSGINGSFLVRESESSPGQRSISLRYEGRVYH   300
 301  YRISEDPDGKVFVTQEAKFNTLAELVHHHSVPHEGHGLITPLLYPAPKQN   350
 351  KPTVFPLSPEPDEWEICRTDIMMKHKLGGGQYGEVYEAVWKRYGNTVAVK   400
 401  TLKEDTMALKDFLEEAAIMKEMKHPNLVQLIGVCTREPPFYIITEFMSHG   450
 451  NLLDFLRSAGRETLDAVALLYMATQIASGMSYLESRNYIHRDLAARNCLV   500
 501  GDNKLVKVADFGLARLMRDDTYTAHAGAKFPIKWTAPEGLAYNKFSTKSD   550
 551  VWAFGVLLWEIATYGMSPYPAIDLTDVYHKLDKGYRMERPPGCPPEVYDL   600
 601  MRQCWQWDATDRPTFKSIHHALEHMFQESSITEAVEKQLNANATSASSSA   650
 651  PSTSGVATGGGATTTTAASGCASSSSATASLSLTPQMVKKGLPGGQALTP   700
 701  NAHHNDPHQQQASTPMSETGSTSTKLSTFSSQGKGNVQMRRTTNKQGKQA   750
 751  PAPPKRTSLLSSSRDSTYREEDPANARCNFIDDLSTNGLARDINSLTQRY   800
 801  DSETDPAADPDTDATGDSLEQSLSQVIAAPVTNKMQHSLHSGGGGGGIGP   850
 851  RSSQQHSSFKRPTGTPVMGNRGLETRQSKRSQLHSQAPGPGPPSTQPHHG   900
 901  NNGVVTSAHPITVGALDVMNVKQVVNRYGTLPKGARIGAYLDSLEDSSEA   950
 951  APALPATAPSLPPANGHATPPAARLNPKASPIPPQQMIRSNSSGGVTMQN  1000
1001  NAAASLNKLQRHRTTTEGTMMTFSSFRAGGSSSSPKRSASGVASGVQPAL  1050
1051  ANLEFPPPPLDLPPPPEEFEGGPPPPPPAPESAVQAIQQHLHAQLPNNGN  1100
1101  ISNGNGTNNNDSSHNDVSNIAPSVEEASSRFGVSLRKREPSTDSCSSLGS  1150
1151  PPEDLKEKLITEIKAAGKDTAPASHLANGSGIAVVDPVSLLVTELAESMN  1200
1201  LPKPPPQQQQKLTNGNSTGSGFKAQLKKVEPKKMSAPMPKAEPANTIIDF  1250
1251  KAHLRRVDKEKEPATPAPAPATVAVANNANCNTTGTLNRKEDGSKKFSQA  1300
1301  MQKTEIKIDVTNSNVEADAGAAGEGDLGKRRSTGSINSLKKLWEQQPPAP  1350
1351  DYATSTILQQQPSVVNGGGTPNAQLSPKYGMKSGAINTVGTLPAKLGNKQ  1400
1401  PPAAPPPPPPNCTTSNSSTTSISTSSRDCTSRQQASSTIKTSHSTQLFTD  1450
1451  DEEQSHTEGLGSGGQGSADMTQSLYEQKPQIQQKPAVPHKPTKLTIYATP  1500
1501  IAKLTEPASSASSTQISRESILELVGLLEGSLKHPVNAIAGSQWLQLSDK  1550
1551  LNILHNSCVIFAENGAMPPHSKFQFRELVTRVEAQSQHLRSAGSKNVQDN  1600
1601  ERLVAEVGQSLRQISNALNR                                1620

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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