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

NucPred

Fetching Q28983 from www.uniprot.org...

The NucPred score for your sequence is 0.75 (see score help below)

   1  MLGLPALAGPMAMPHPPLIPSTPTLLAFSFPGGFYMLLDPKNAKPRQRSA    50
  51  LLSPLIQSSGCLSLSFQYTQRGQASGATLMVYASVLGSIRKHTLFSGQPG   100
 101  PSWQPVSVNYTSQGQIQFTLVGVFGKIPEPAVAVDAISIAPCEESFPQCD   150
 151  FEDNAHPFCDWVQASQDGGYWRQGNKNTFIQPAGPFGISLNGEGHYIFLE   200
 201  TDKFSQAGQSFRLVSRPFCAPAVICVTFTYHMYGLGQGTKLRLLLGSPAG   250
 251  SPPSSLWERVGPQSPEWLNTSVTIPSGHQQPMQLIFEAVRGTNTAFVVAL   300
 301  GFVLINHGTCRGPSETSVSTEKPVAPTEKPTVPSEIYTIPTEKPMVHMEK   350
 351  PIVHTEKPTVPTEKPTIPTEKSTVPTKKPTVFKEPTLPPEGPTVPAERPT   400
 401  TPPEGPAVPPKGPTVLTEWPTSHTEKSTVHTEKPILPTGKSTIPTEKPMV   450
 451  PTKRTTTPTERTTIPAEKPTVPIEKPMVPTERTTIPTERTTIPTEKPTVP   500
 501  TEKLTVPTEKPIVPTEKPIVPTEKHTIPTEKLTVLTERTTTPTERTTIPT   550
 551  EKPTVPTEKPSVPTEKPTVPTEEPTIPTEKLTVPTERTTTPTKRTTTPTI   600
 601  RTTTPTIRTTTPTERTTTPTIRTTTPTERTTIPTKKTTVPTEKTIIPTER   650
 651  TIAPTTPQPSPTLVPTQPAAVVMPSTSATTVTPRTTIASCPPNAHFERCA   700
 701  CPVSCQSPTPNCELFCKPGCVCDPGFLFSGSHCVNASSCDCFYNDNYYKL   750
 751  GTDWFSPNCTEHCHCRPSSRMECQTFKCGTHTVCQLKNGQYGCHPYGSAT   800
 801  CSVYGDPHYLTFDGRRFNFMGKCTYILAQPCGNLTEHFFRVLVKKEERGQ   850
 851  EGVSCLSKVYVTLPESTVTLLKGRHTLVGGQRVTLPAIPSRGVFLAPSGR   900
 901  FVELQTAFGLRVRWDGDQQLFVSVPSTFSGKLCGLCGDYDGDSSNDNQKP   950
 951  DGSPAKDEKELGSSWQTSEDADQQCEENQVSPPSCNTALQNTMSGPEFCG  1000
1001  QLVAPHGVFEACLPHLRASSFFKSCTFDMCNFQGLQHMLCAHMSALTENC  1050
1051  QDAGYTVKPWRGPQFCPLACPRNSRYTLCARLCPDTCHSEFSGRACKDRC  1100
1101  VEGCECDPGFVLSGLQCVSRSECGCLDSTAGYVKVGERWFKPGCRQLCIC  1150
1151  EGNNRTRCVLWRCQAQEFCGQQDGIYGCHAQGSATCTVSGDPHYLTFDGA  1200
1201  LHHFTGTCTYTLTKPCWLRSLENSFLVSATNEFRGGNLEASYVRAVQVQV  1250
1251  FNLRISLIKGRKVTLDGRRVALPLWPAQGRVSITSSGSFILLYTDFGLQV  1300
1301  RYDGDHLVEVTVPSSYAGRLCGLCGNYNNNSLDDILQPDKRPASSSVRLG  1350
1351  ASWKINELSEPGCFAEGGKPPRCLGKEVADAWRKNCDVLMNPQGPFSQCH  1400
1401  RVVAPQSSFSSCLYGQCATKGDTLTLCRSLQAYASLCARAGQALTWRNGT  1450
1451  FCPLKCPSGSSYSTCANPCPATCLSLNNPSYCPSTLPCAEGCECQKGHIL  1500
1501  SGTSCVPLSQCGCTTQRGSYHPVGESWYTDNSCSRLCTCSAHNNISCRQA  1550
1551  SCKPSQMCWPQDGLIRCRVAGMGVCRIPDTSHYVSFDGSYHAVRGNCTYV  1600
1601  LVKICHSTMDLPFFKISGENGKREGQPPAFYLRQVYVDIFNTLVTLKQDQ  1650
1651  VLINGTRVSLPATTQIRGVRVISRDGYTVLTINIGVQVKFDGRGFLEVEI  1700
1701  PKAYYGRTCGVCGNFNDEEEDELMMPSDALALDDVMYVDSWRDKEIDPNC  1750
1751  QEDDRKTEAESQEQPSANCRPADLERAQEQCQAAFQAPAWANCATRVVLS  1800
1801  PYVRSCTHKLCEFGGLNRAFCESLQAFGAACQAQGIKPPVWRNSSFCPLD  1850
1851  CSAHSVYTSCVPSCLPSCQDPEGQCTGAGAPSTCEEGCICEPGYVLSEQQ  1900
1901  CVARSQCGCRDARGTFLPVGRFRLSSGCSQMCVCTAGAIECRPFTCPSGS  1950
1951  QCEPNEDGKDFCQPNSSNLCSVFGDPHYRTFDGLSYRFQGRMTYTLVKTL  2000
2001  DVLPDGVEPLVVEGRNKVYPSLTPVFLQEIIVMVYGYTVQLQAELELVVN  2050
2051  GQKVSIPYKPNEYLQVTLRGRRLYLVTDFELVVSFNGRNNAVIAMPSTYL  2100
2101  GLVRGLCGNYDKNKRNDFMLPNGSFTQNLLVFGNSWEVKAKEGHPRFSRA  2150
2151  IREEEEKNEESGFQNVSECSPEQLELVNHTQACGVLVDPQGPFAACHQIV  2200
2201  APGPFQEHCVFDLCAAPGPKEQEELRCQVLSGYAIICQESGPTLAGWRDH  2250
2251  THCALPCPANTVYQSCMTPCPASCATLAVPRACDGPCVEGCASLPGYIYS  2300
2301  GAQSLPMAHCGCTNNGVYYQQGDSFVTENCSQRCTCASSGVLLCEPLSCR  2350
2351  PGEICTLGNLTRGCFRDSPCLQNPCQNDGRCREQGTHFTCECELGYGGDL  2400
2401  CTEPRGVPSPKKPEASNRVAILLGMLMPTVLLVPAVTRVSRKRRRRRRPS  2450
2451  RERTQSQNRGKRAGTDCAPEQAYKVA                          2476

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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