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

NucPred

Fetching P97526 from www.uniprot.org...

The NucPred score for your sequence is 0.89 (see score help below)

   1  MAAHRPVEWVQAVVSRFDEQLPIKTGQQNTHTKVSTEHNKECLINISKYK    50
  51  FSLVISGLTTILKNVNNMRIFGEAAEKNLYLSQLIILDTLEKCLAGQPKD   100
 101  TMRLDETMLVKQLLPEICHFLHTCREGNQHAAELRNSASGVLFSLSCNNF   150
 151  NAVFSRISTRLQELTVCSEDNVDVHDIELLQYINVDCAKLKRLLKETAFK   200
 201  FKALKKVAQLAVINSLEKAFWNWVENYPDEFTKLYQIPQTDMAECAGKLF   250
 251  DLVDGFAESTKRKAAVWPLQIILLILCPEIIQDISRDVVDENNTNKKLFL   300
 301  DSLRKALAGHGGSRQLTESAAIACVKLCKASTYINWEDNSVIFLLVQSMV   350
 351  VDLKNLLFNPSKPFSRGSQPADVDLMIDCLVSCFRISPHNNQHFKICLAQ   400
 401  NSPSTFHYVLVNSLHRIITNSAWDWWPKIDAVYCHSVELRNMFGETLHKA   450
 451  VQGCGAHPALRMAPSLTFKEKVTSLKFKEKPTDLEARSYKYLLLSMVKLI   500
 501  HADPKLLLCNPRKQGPETQGSTAELITGLVQLVPQSHMPEVAQEAMEALL   550
 551  VLHQLDSIDLWNPDAPVETFWEISSQMLFYICKKLTSHQMLSSTEILKWL   600
 601  REILICRNKFLLKNKQADRSSCHSLYLYGVGCDLPASGNVTQMSVDHEES   650
 651  LRTCAPGASLRKGRGNSSMDSTAGCSGTPPICRQAQTKLEVALYMFLWSP   700
 701  DTEVVLVAMSCFRHLCEEADIRCGVDEVSVHNFLPNYNTFMEFASVSNML   750
 751  STGRAALQKRVMALLRRIEHPTAGNTEAWEDTHAKWEQATKLILNYPKAK   800
 801  MEDGQAAESLHKTIVKRRMSHVSGGGSIDLSDTDSLQEWINMTGFLCALG   850
 851  GVCLQQRSSSGLATYSPPMGPVSERKGSMISVMSSEGNVDSPVSRFMDRL   900
 901  LSLMVCNHEKVGLQIRTNVKDLVGLELSPALYPMLFNKLKSAISKFFDSQ   950
 951  GQVLLTDSNTQFVEQTIAIMKNLLDNHTEGSSEHLGQASIETMMLNLVRY  1000
1001  VRVLGNMVHAIQIKTKLCQLVEVMMARRDDLSFCQEMKFRNKMVEYLTDW  1050
1051  VMGTSNQAADDDVKCLTRDLDQASMEAVVSLLAGLPLQPEEGDGVELMEA  1100
1101  KSQLFLKYFTLFMNLLNDCSEVEDENAQTGGRKRGMSRRLASLRHCTVLA  1150
1151  MSNLLNANVDSGLMHSIGLGYHKDLQTRATFMEVLTKILQQGTEFDTLAE  1200
1201  TVLADRFERLVELVTMMGDQGELPIAMALANVVPCSQWDELARVLVTLFD  1250
1251  SRHLLYQLLWNMFSKEVELADSMQTLFRGNSLASKIMTFCFKVYGATYLQ  1300
1301  KLLDPLLRIIITSSDWQHVSFEVDPTRLEPSESLEENQRNLLQMTEKFFH  1350
1351  AIISSSSEFPSQLRSVCHCLYQVVSQRFPQNSIGAVGSAMFLRFINPAIV  1400
1401  SPYEAGILDKKPPPRIERGLKLMSKVLQSIANHVLFTKEEHMRPFNDFVK  1450
1451  SNFDLARRFFLDIASDCPTSDAVNHSLSFISDGNVLALHRLLWNNQEKIG  1500
1501  QYLSSNRDHKAVGRRPFDKMATLLAYLGPPEHKPVADTHWSSLNLTSSKF  1550
1551  EEFMTRHQVHEKEEFKALKTLSIFYQAGTSKAGNPIFYYVARRFKTGQIN  1600
1601  GDLLIYHVLLTLKPYYAKPYEIVVDLTHTGPSNRFKTDFLSKWFVVFPGF  1650
1651  AYDNVSAVYIYNCNSWVREYTKYHERLLTGLKGSKRLIFIDCPGKLAEHI  1700
1701  EHEQQKLPAATLALEEDLKVFHNALKLAHKDTKVSIKVGSTAVQVTSAER  1750
1751  TKVLGQSVFLNDIYYASEIEEICLVDENQFTLTIANQGTPLTFMHQECEA  1800
1801  IVQSIIHIRTRWELSQPDSIPQHTKIRPKDVPGTLLNIALLNLGSSDPSL  1850
1851  RSAAYNLLCALTCTFNLKIEGQLLETSGLCIPANNTLFIVSISKTLAANE  1900
1901  PHLTLEFLEECISGFSKSSIELKHLCLEYMTPWLSNLVRFCKHNDDAKRQ  1950
1951  RVTAILDKLITMTINEKQMYPSIQAKIWGSLGQITDLLDVVLDSFIKTSA  2000
2001  TGGLGSIKAEVMADTAVALASGNVKLVSSKVIGRMCKIIDKTCLSPTPTL  2050
2051  EQHLMWDDIAILARYMLMLSFNNSLDVAAHLPYLFHVVTFLVATGPLSLR  2100
2101  ASTHGLVINIIHSLCTCSQLHFSEETKQVLRLSLTEFSLPKFYLLFGISK  2150
2151  VKSAAVIAFRSSYRDRSFSPGSYERETFALTSLETVTEALLEIMEACMRD  2200
2201  IPTCKWLDQWTELAQRFAFQYNPSLQPRALVVFGCISKRVSHGQIKQIIR  2250
2251  ILSKALESCLKGPDTYNSQVLIEATVIALTKLQPLLNKDSPLHKALFWVA  2300
2301  VAVLQLDEVNLYSAGTALLEQNLHTLDSLRIFNDKSPEEVFMAIRNPLEW  2350
2351  HCKQMDHFVGLNFNSNFNFALVGHLLKGYRHPSPAIVARTVRILHTLLTL  2400
2401  VNKHRNCDKFEVNTQSVAYLAALLTVSEEVRSRCSLKHRKSLLLTDISME  2450
2451  NVPMDTYPIHHGDPSSRTLKETQPWSSPRGSEGYLAATYPAVGQTSPRAR  2500
2501  KSMSLDMGQPSQANTKKLLGTRKSFDHLISDTKAPKRQEMESGITTPPKM  2550
2551  RRVAETDYEMETQRISSSQQHPHLRKVSVSESNVLLDEEVLTDPKIQALL  2600
2601  LTVLATLVKYTTDEFDQRILYEYLAEASVVFPKVFPLVHNLLDSKINTLL  2650
2651  SLCQDPNLLNPIHGIVQSVVYHEESPPQYQTSYLQSFGFNGLWRFAGPFS  2700
2701  KQTQIPDYAELIVKFLDALIDTYLPGIDEETSEESLLTPTSPYPPALQSQ  2750
2751  LSITANLNLSNSMTSLATSQHSPGIDKENVELSPTTGHCNSGRTRHGSAS  2800
2801  QVQKQRSAGSFKRNSIKKIV                                2820

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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