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

NucPred

Fetching Q15652 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MAVETRAELVGKRFLCVAVGDEARSERWESGRGWRSWRAGVIRAVSHRDS    50
  51  RNPDLAVYVEFDDLEWDKREWVKVYEDFSTFLVEYHLIWAKRNDPSQTQG   100
 101  SKSKQIQWPALTFKPLVERNIPSSVTAVEFLVDKQLDFLTEDSAFQPYQD   150
 151  DIDSLNPVLRDNPQLHEEVKVWVKEQKVQEIFMQGPYSLNGYRVRVYRQD   200
 201  SATQWFTGIITHHDLFTRTMIVMNDQVLEPQNVDPSMVQMTFLDDVVHSL   250
 251  LKGENIGITSRRRSRANQNVNAVHSHYTRAQANSPRPAMNSQAAVPKQNT   300
 301  HQQQQQRSIRPNKRKGSDSSIPDEEKMKEEKYDYISRGENPKGKNKHLMN   350
 351  KRRKPEEDEKKLNMKRLRTDNVSDFSESSDSENSNKRIIDNSSEQKPENE   400
 401  LKNKNTSKINGEEGKPHNNEKAGEETLKNSQPPWDQIQEDKKHEEAEKRK   450
 451  SVDTQLQEDMIIHSSEQSTVSDHNSNDLLPQECNMDKTHTMELLPKEKFV   500
 501  SRPPTPKCVIDITNDTNLEKVAQENSSTFGLQTLQKMDPNVSDSKHSIAN   550
 551  AKFLETAKKDSDQSWVSDVVKVDLTQSSVTNASSGNDHLNMEKEKYVSYI   600
 601  SPLSAVSVMEDKLHKRSPPPETIKSKLNTSVDTHKIKSSPSPEVVKPKIT   650
 651  HSPDSVKSKATYVNSQATGERRLANKIEHELSRCSFHPIPTRSSTLETTK   700
 701  SPLIIDKNEHFTVYRDPALIGSETGANHISPFLSQHPFPLHSSSHRTCLN   750
 751  PGTHHPALTPAPHLLAGSSSQTPLPTINTHPLTSGPHHAVHHPHLLPTVL   800
 801  PGVPTASLLGGHPRLESAHASSLSHLALAHQQQQQLLQHQSPHLLGQAHP   850
 851  SASYNQLGLYPIIWQYPNGTHAYSGLGLPSSKWVHPENAVNAEASLRRNS   900
 901  PSPWLHQPTPVTSADGIGLLSHIPVRPSSAEPHRPLKITAHSSPPLTKTL   950
 951  VDHHKEELERKAFMEPLRSVASTSAKNDLDLNRSQTGKDCHLHRHFVDPV  1000
1001  LNQLQRPPQETGERLNKYKEEHRRILQESIDVAPFTTKIKGLEGERENYS  1050
1051  RVASSSSSPKSHIIKQDMDVERSVSDLYKMKHSVPQSLPQSNYFTTLSNS  1100
1101  VVNEPPRSYPSKEVSNIYGDKQSNALAAAAANPQTLTSFITSLSKPPPLI  1150
1151  KHQPESEGLVGKIPEHLPHQIASHSVTTFRNDCRSPTHLTVSSTNTLRSM  1200
1201  PALHRAPVFHPPIHHSLERKEGSYSSLSPPTLTPVMPVNAGGKVQESQKP  1250
1251  PTLIPEPKDSQANFKSSSEQSLTEMWRPNNNLSKEKTEWHVEKSSGKLQA  1300
1301  AMASVIVRPSSSTKTDSMPAMQLASKDRVSERSSAGAHKTDCLKLAEAGE  1350
1351  TGRIILPNVNSDSVHTKSEKNFQAVSQGSVPSSVMSAVNTMCNTKTDVIT  1400
1401  SAADTTSVSSWGGSEVISSLSNTILASTSSECVSSKSVSQPVAQKQECKV  1450
1451  STTAPVTLASSKTGSVVQPSSGFSGTTDFIHLKKHKAALAAAQYKSSNAS  1500
1501  ETEPNAIKNQTLSASLPLDSTVICSTINKANSVGNGQASQTSQPNYHTKL  1550
1551  KKAWLTRHSEEDKNTNKMENSGNSVSEIIKPCSVNLIASTSSDIQNSVDS  1600
1601  KIIVDKYVKDDKVNRRKAKRTYESGSESGDSDESESKSEQRTKRQPKPTY  1650
1651  KKKQNDLQKRKGEIEEDLKPNGVLSRSAKERSKLKLQSNSNTGIPRSVLK  1700
1701  DWRKVKKLKQTGESFLQDDSCCEIGPNLQKCRECRLIRSKKGEEPAHSPV  1750
1751  FCRFYYFRRLSFSKNGVVRIDGFSSPDQYDDEAMSLWTHENFEDDELDIE  1800
1801  TSKYILDIIGDKFCQLVTSEKTALSWVKKDAKIAWKRAVRGVREMCDACE  1850
1851  ATLFNIHWVCQKCGFVVCLDCYKAKERKSSRDKELYAWMKCVKGQPHDHK  1900
1901  HLMPTQIIPGSVLTDLLDAMHTLREKYGIKSHCHCTNKQNLQVGNFPTMN  1950
1951  GVSQVLQNVLNHSNKISLCMPESQQQNTPPKSEKNGGSSPESDVGTDNKL  2000
2001  TPPESQSPLHWLADLAEQKAREEKKENKELTLENQIKEEREQDNSESPNG  2050
2051  RTSPLVSQNNEQGSTLRDLLTTTAGKLRVGSTDAGIAFAPVYSMGAPSSK  2100
2101  SGRTMPNILDDIIASVVENKIPPSKTSKINVKPELKEEPEESIISAVDEN  2150
2151  NKLYSDIPHSWICEKHILWLKDYKNSSNWKLFKECWKQGQPAVVSGVHKK  2200
2201  MNISLWKAESISLDFGDHQADLLNCKDSIISNANVKEFWDGFEEVSKRQK  2250
2251  NKSGETVVLKLKDWPSGEDFKTMMPARYEDLLKSLPLPEYCNPEGKFNLA  2300
2301  SHLPGFFVRPDLGPRLCSAYGVVAAKDHDIGTTNLHIEVSDVVNILVYVG  2350
2351  IAKGNGILSKAGILKKFEEEDLDDILRKRLKDSSEIPGALWHIYAGKDVD  2400
2401  KIREFLQKISKEQGLEVLPEHDPIRDQSWYVNKKLRQRLLEEYGVRTCTL  2450
2451  IQFLGDAIVLPAGALHQVQNFHSCIQVTEDFVSPEHLVESFHLTQELRLL  2500
2501  KEEINYDDKLQVKNILYHAVKEMVRALKIHEDEVEDMEEN            2540

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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