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

NucPred

Fetching P27884 from www.uniprot.org...

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

   1  MARFGDEMPARYGGGGAGAAAGVVVGAAGGRGAGGSRQGGQPGAQRMYKQ    50
  51  SMAQRARTMALYNPIPVRQNCLTVNRSLFLFSEDNVVRKYAKKITEWPPF   100
 101  EYMILATIIANCIVLALEQHLPDDDKTPMSERLDDTEPYFIGIFCFEAGI   150
 151  KIIALGFAFHKGSYLRNGWNVMDFVVVLTGILATVGTEFDLRTLRAVRVL   200
 201  RPLKLVSGIPSLQVVLKSIMKAMIPLLQIGLLLFFAILIFAIIGLEFYMG   250
 251  KFHTTCFEEGTDDIQGESPAPCGTEEPARTCPNGTRCQPYWEGPNNGITQ   300
 301  FDNILFAVLTVFQCITMEGWTDLLYNSNDASGNTWNWLYFIPLIIIGSFF   350
 351  MLNLVLGVLSGEFAKERERVENRRAFLKLRRQQQIERELNGYMEWISKAE   400
 401  EVILAEDETDVEQRHPFDGALRRATIKKSKTDLLHPEEAEDQLADIASVG   450
 451  SPFARASIKSAKLENSSFFHKKERRMRFYIRRMVKTQAFYWTVLSLVALN   500
 501  TLCVAIVHYNQPEWLSDFLYYAEFIFLGLFMSEMFIKMYGLGTRPYFHSS   550
 551  FNCFDCGVIIGSIFEVIWAVIKPGTSFGISVLRALRLLRIFKVTKYWASL   600
 601  RNLVVSLLNSMKSIISLLFLLFLFIVVFALLGMQLFGGQFNFDEGTPPTN   650
 651  FDTFPAAIMTVFQILTGEDWNEVMYDGIKSQGGVQGGMVFSIYFIVLTLF   700
 701  GNYTLLNVFLAIAVDNLANAQELTKDEQEEEEAVNQKLALQKAKEVAEVS   750
 751  PLSAANMSIAMKEQQKNQKPAKSVWEQRTSEMRKQNLLASREALYSEMDP   800
 801  EERWKASYARHLRPDMKTHLDRPLVVDPQENRNNNTNKSRVAEPTVDQRL   850
 851  GQQRAEDFLRKQARHHDRARDPSAHAAAGLDARRPWAGSQEAELSREGPY   900
 901  GRESDHQAREGGLEPPGFWEGEAERGKAGDPHRRHAHRQGVGGSGGSRSG   950
 951  SPRTGTADGEPRRHRVHRRPGEDGPDDKAERRGRHREGSRPARSGEGEAE  1000
1001  GPDGGGGGGGERRRRHRHGPPPAYDPDARRDDRERRHRRRKDTQGSGVPV  1050
1051  SGPNLSTTRPIQQDLSRQEPPLAEDMDNLKNSRLATAEPVSPHENLSHAG  1100
1101  LPQSPAKMGSSTDPAGPTPATAANPQNSTASRRTPNNPGNPSNPGPPKTP  1150
1151  ENSLIVTNPSTAQTNSAKTARKPDHTTVEIPPACPPPLNHTVVQVNKNAN  1200
1201  PDPLPKKEDEKKEEVDEGPGEDGPKPMPPYSSMFILSTTNPLRRLCHYIL  1250
1251  NLRYFEMCILMVIAMSSIALAAEDPVQPNAPRNNVLRYFDYVFTGVFTFE  1300
1301  MVIKMIDLGLVLHQGAYFRDLWNILDFIVVSGALVAFAFTGNSKGKDINT  1350
1351  IKSLRVLRVLRPLKTIKRLPKLKAVFDCVVNSLKNVFNILIVYMLFMFIF  1400
1401  AVVAVQLFKGKFFHCTDESKEFEKDCRGKYLLYEKNEVKARDREWKKYEF  1450
1451  HYDNVLWALLTLFTVSTGEGWPQVLKHSVDATFENQGPSPGYRMEMSIFY  1500
1501  VVYFVVFPFFFVNIFVALIIITFQEQGDKMMEEYSLEKNERACIDFAISA  1550
1551  KPLTRHMPQNKQSFQYRMWQFVVSPPFEYTIMAMIALNTIVLMMKFYGAS  1600
1601  VAYDNALKVFNIVFTSLFSLECLLKVLAFGILNYFRDAWNIFDFVTVLGS  1650
1651  ITDILVTEFGNNFINLSFLRLFRAARLIKLLRQGYTIRILLWTFVQSFKA  1700
1701  LPYVCLLIAMLFFIYAIIGMQVFGNIGIDMEDEDSDEDEFQITEHNNFRT  1750
1751  FFQALMLLFRSATGEAWHNIMLSCLSGKPCDKNSGILTPECGNEFAYFYF  1800
1801  VSFIFLCSFLMLNLFVAVIMDNFEYLTRDSSILGPHHLDEYVRVWAEYDP  1850
1851  AAWGRMLYRDMYAMLRHMPPPLGLGKNCPARVAYKRLLRMDLPVADDNTV  1900
1901  HFNSTLMALIRTALDIKIAKGGADKQQMDAELRKEMMAIWPNLSQKTLDL  1950
1951  LVTPHKSTDLTVGKIYAAMMIMEYYRQSKAKKLQAMREEQNRTPLMFQRM  2000
2001  EPPPDEGGAGQNALPSTQLDPAGGLMAHEDGLKDSPSWVTQRAQEMFQKT  2050
2051  GTWSPERAPPADMADSQPKPQSVEMREMSQDGYSDSEHCLPMEGQARAAS  2100
2101  MPRLPAENQRRRGRPRGSDLSTICDTSPMKRSASVLGPKASRRLDDYSLE  2150
2151  RVPPEENQRHHPRRRERAHRTSERSLGRYTDVDTGLGTDLSMTTQSGDLP  2200
2201  SREREQERGRPKDRKHRPHHHHHHHHHPGRGPGRVSPGVSARRRRRGPVA  2250
2251  RVRPARAPALAHARARARAPARLLPELRLRRARRPRPRQRRRPRRRRGGG  2300
2301  GRALRRAPGPREPLAQDSPGRGPSVCLARAARPAGPQRLLPGPRTGQAPR  2350
2351  ARLPQKPARSVQRERRGLVLSPPPPPPGELAPRAHPARTPRPGPGDSRSR  2400
2401  RGGRRWTASAGKGGGGPRASAPSP                            2424

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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