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

NucPred

Fetching P35194 from www.uniprot.org...

The NucPred score for your sequence is 0.93 (see score help below)

   1  MAKQRQTTKSSKRYRYSSFKARIDDLKIEPARNLEKRVHDYVESSHFLAS    50
  51  FDQWKEINLSAKFTEFAAEIEHDVQTLPQILYHDKKIFNSLVSFINFHDE   100
 101  FSLQPLLDLLAQFCHDLGPDFLKFYEEAIKTLINLLDAAIEFESSNVFEW   150
 151  GFNCLAYIFKYLSKFLVKKLVLTCDLLIPLLSHSKEYLSRFSAEALSFLV   200
 201  RKCPVSNLREFVRSVFEKLEGDDEQTNLYEGLLILFTESMTSTQETLHSK   250
 251  AKAIMSVLLHEALTKSSPERSVSLLSDIWMNISKYASIESLLPVYEVMYQ   300
 301  DFNDSLDATNIDRILKVLTTIVFSESGRKIPDWNKITILIERIMSQSENC   350
 351  ASLSQDKVAFLFALFIRNSDVKTLTLFHQKLFNYALTNISDCFLEFFQFA   400
 401  LRLSYERVFSFNGLKFLQLFLKKNWQSQGKKIALFFLEVDDKPELQKVRE   450
 451  VNFPEEFILSIRDFFVTAEINDSNDLFEIYWRAIIFKYSKLQNTEIIIPL   500
 501  LERIFSTFASPDNFTKDMVGTLLKIYRKEDDASGNNLLKTILDNYENYKE   550
 551  SLNFLRGWNKLVSNLHPSESLKGLMSHYPSLLLSLTDNFMLPDGKIRYET   600
 601  LELMKTLMILQGMQVPDLLSSCMVIEEIPLTLQNARDLTIRIKNVGAEFG   650
 651  KTKTDKLVSSFFLKYLFGLLTVRFSPVWTGVFDTLPNVYTKDEALVWKLV   700
 701  LSFIKLPDENQNLDYYQPLLEDGANKVLWDSSVVRLRDTIDTFSHIWSKY   750
 751  STQNTSIISTTIERRGNTTYPILIRNQALKVMLSIPQVAENHFVDIAPFV   800
 801  YNDFKTYKDEEDMENERVITGSWTEVDRNVFLKTLSKFKNIKNVYSATEL   850
 851  HDHLMVLLGSRNTDVQKLALDALLAYKNPTLNKYRDNLKNLLDDTLFKDE   900
 901  ITTFLTENGSQSIKAEDEKVVMPYVLRIFFGRAQVPPTSGQKRSRKIAVI   950
 951  SVLPNFKKPYINDFLSLASERLDYNYFFGNSHQINSSKATLKTIRRMTGF  1000
1001  VNIVNSTLSVLRTNFPLHTNSVLQPLIYSIAMAYYVLDTESTEEVHLRKM  1050
1051  ASNLRQQGLKCLSSVFEFVGNTFDWSTSMEDIYAVVVKPRISHFSDENLQ  1100
1101  QPSSLLRLFLYWAHNPSLYQFLYYDEFATATALMDTISNQHVKEAVIGPI  1150
1151  IEAADSIIRNPVNDDHYVDLVTLICTSCLKILPSLYVKLSDSNSISTFLN  1200
1201  LLVSITEMGFIQDDHVRSRLISSLISILKGKLKKLQENDTQKILKILKLI  1250
1251  VFNYNCSWSDIEELYTTISSLFKTFDERNLRVSLTELFIELGRKVPELES  1300
1301  ISKLVADLNSYSSSRMHEYDFPRILSTFKGLIEDGYKSYSELEWLPLLFT  1350
1351  FLHFINNKEELALRTNASHAIMKFIDFINEKPNLNEASKSISMLKDILLP  1400
1401  NIRIGLRDSLEEVQSEYVSVLSYMVKNTKYFTDFEDMAILLYNGDEEADF  1450
1451  FTNVNHIQLHRRQRAIKRLGEHAHQLKDNSISHYLIPMIEHYVFSDDERY  1500
1501  RNIGNETQIAIGGLAQHMSWNQYKALLRRYISMLKTKPNQMKQAVQLIVQ  1550
1551  LSVPLRETLRIVRDGAESKLTLSKFPSNLDEPSNFIKQELYPTLSKILGT  1600
1601  RDDETIIERMPIAEALVNIVLGLTNDDITNFLPSILTNICQVLRSKSEEL  1650
1651  RDAVRVTLGKISIILGAEYLVFVIKELMATLKRGSQIHVLSYTVHYILKS  1700
1701  MHGVLKHSDLDTSSSMIVKIIMENIFGFAGEEKDSENYHTKVKEIKSNKS  1750
1751  YDAGEILASNISLTEFGTLLSPVKALLMVRINLRNQNKLSELLRRYLLGL  1800
1801  NHNSDSESESILKFCHQLFQESEMSNSPQIPKKKVKDQVDEKEDFFLVNL  1850
1851  ESKSYTINSNSLLLNSTLQKFALDLLRNVITRHRSFLTVSHLEGFIPFLR  1900
1901  DSLLSENEGVVISTLRILITLIRLDFSDESSEIFKNCARKVLNIIKVSPS  1950
1951  TSSELCQMGLKFLSAFIRHTDSTLKDTALSYVLGRVLPDLNEPSRQGLAF  2000
2001  NFLKALVSKHIMLPELYDIADTTREIMVTNHSKEIRDVSRSVYYQFLMEY  2050
2051  DQSKGRLEKQFKFMVDNLQYPTESGRQSVMELINLIITKANPALLSKLSS  2100
2101  SFFLALVNVSFNDDAPRCREMASVLISTMLPKLENKDLEIVEKYIAAWLK  2150
2151  QVDNASFLNLGLRTYKVYLKSIGFEHTIELDELAIKRIRYILSDTSVGSE  2200
2201  HQWDLVYSALNTFSSYMEATESVYKHGFKDIWDGIITCLLYPHSWVRQSA  2250
2251  ANLVHQLIANKDKLEISLTNLEIQTIATRILHQLGAPSIPENLANVSIKT  2300
2301  LVNISILWKEQRTPFIMDVSKQTGEDLKYTTAIDYMVTRIGGIIRSDEHR  2350
2351  MDSFMSKKACIQLLALLVQVLDEDEVIAEGEKILLPLYGYLETYYSRAVD  2400
2401  EEQEELRTLSNECLKILEDKLQVSDFTKIYTAVKQTVLERRKERRSKRAI  2450
2451  LAVNAPQISADKKLRKHARSREKRKHEKDENGYYQRRNKRKRA         2493

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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