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

NucPred

Fetching P31629 from www.uniprot.org...

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

   1  MDTGDTALGQKATSRSGETDKASGRWRQEQSAVIKMSTFGSHEGQRQPQI    50
  51  EPEQIGNTASAQLFGSGKLASPSEVVQQVAEKQYPPHRPSPYSCQHSLSF   100
 101  PQHSLPQGVMHSTKPHQSLEGPPWLFPGPLPSVASEDLFPFPIHGHSGGY   150
 151  PRKKISSLNPAYSQYSQKSIEQAEEAHKKEHKPKKPGKYICPYCSRACAK   200
 201  PSVLKKHIRSHTGERPYPCIPCGFSFKTKSNLYKHRKSHAHAIKAGLVPF   250
 251  TESAVSKLDLEAGFIDVEAEIHSDGEQSTDTDEESSLFAEASDKMSPGPP   300
 301  IPLDIASRGGYHGSLEESLGGPMKVPILIIPKSGIPLPNESSQYIGPDML   350
 351  PNPSLNTKADDSHTVKQKLALRLSEKKGQDSEPSLNLLSPHSKGSTDSGY   400
 401  FSRSESAEQQISPPNTNAKSYEEIIFGKYCRLSPRNALSVTTTSQERAAM   450
 451  GRKGIMEPLPHVNTRLDVKMFEDPVSQLIPSKGDVDPSQTSMLKSTKFNS   500
 501  ESRQPQIIPSSIRNEGKLYPANFQGSNPVLLEAPVDSSPLIRSNSVPTSS   550
 551  ATNLTIPPSLRGSHSFDERMTGSDDVFYPGTVGIPPQRMLRRQAAFELPS   600
 601  VQEGHVEVEHHGRMLKGISSSSLKEKKLSPGDRVGYDYDVCRKPYKKWED   650
 651  SETPKQNYRDISCLSSLKHGGEYFMDPVVPLQGVPSMFGTTCENRKRRKE   700
 701  KSVGDEEDTPMICSSIVSTPVGIMASDYDPKLQMQEGVRSGFAMAGHENL   750
 751  SHGHTERFDPCRPQLQPGSPSLVSEESPSAIDSDKMSDLGGRKPPGNVIS   800
 801  VIQHTNSLSRPNSFERSESAELVACTQDKAPSPSETCDSEISEAPVSPEW   850
 851  APPGDGAESGGKPSPSQQVQQQSYHTQPRLVRQHNIQVPEIRVTEEPDKP   900
 901  EKEKEAQSKEPEKPVEEFQWPQRSETLSQLPAEKLPPKKKRLRLADMEHS   950
 951  SGESSFESTGTGLSRSPSQESNLSHSSSFSMSFEREETSKLSALPKQDEF  1000
1001  GKHSEFLTVPAGSYSLSVPGHHHQKEMRRCSSEQMPCPHPAEVPEVRSKS  1050
1051  FDYGNLSHAPVSGAAASTVSPSRERKKCFLVRQASFSGSPEISQGEVGMD  1100
1101  QSVKQEQLEHLHAGLRSGWHHGPPAVLPPLQQEDPGKQVAGPCPPLSSGP  1150
1151  LHLAQPQIMHMDSQESLRNPLIQPTSYMTSKHLPEQPHLFPHQETIPFSP  1200
1201  IQNALFQFQYPTVCMVHLPAQQPPWWQAHFPHPFAQHPQKSYGKPSFQTE  1250
1251  IHSSYPLEHVAEHTGKKPAEYAHTKEQTYPCYSGASGLHPKNLLPKFPSD  1300
1301  QSSKSTETPSEQVLQEDFASANAGSLQSLPGTVVPVRIQTHVPSYGSVMY  1350
1351  TSISQILGQNSPAIVICKVDENMTQRTLVTNAAMQGIGFNIAQVLGQHAG  1400
1401  LEKYPIWKAPQTLPLGLESSIPLCLPSTSDSVATLGGSKRMLSPASSLEL  1450
1451  FMETKQQKRVKEEKMYGQIVEELSAVELTNSDIKKDLSRPQKPQLVRQGC  1500
1501  ASEPKDGLQSGSSSFSSLSPSSSQDYPSVSPSSREPFLPSKEMLSGSRAP  1550
1551  LPGQKSSGPSESKESSDELDIDETASDMSMSPQSSSLPAGDGQLEEEGKG  1600
1601  HKRPVGMLVRMASAPSGNVADSTLLLTDMADFQQILQFPSLRTTTTVSWC  1650
1651  FLNYTKPNYVQQATFKSSVYASWCISSCNPNPSGLNTKTTLALLRSKQKI  1700
1701  TAEIYTLAAMHRPGTGKLTSSSAWKQFTQMKPDASFLFGSKLERKLVGNI  1750
1751  LKERGKGDIHGDKDIGSKQTEPIRIKIFEGGYKSNEDYVYVRGRGRGKYI  1800
1801  CEECGIRCKKPSMLKKHIRTHTDVRPYVCKLCNFAFKTKGNLTKHMKSKA  1850
1851  HMKKCLELGVSMTSVDDTETEEAENLEDLHKAAEKHSMSSISTDHQFSDA  1900
1901  EESDGEDGDDNDDDDEDEDDFDDQGDLTPKTRSRSTSPQPPRFSSLPVNV  1950
1951  GAVPHGVPSDSSLGHSSLISYLVTLPSIRVTQLMTPSDSCEDTQMTEYQR  2000
2001  LFQSKSTDSEPDKDRLDIPSCMDEECMLPSEPSSSPRDFSPSSHHSSPGY  2050
2051  DSSPCRDNSPKRYLIPKGDLSPRRHLSPRRDLSPMRHLSPRKEAALRREM  2100
2101  SQRDVSPRRHLSPRRPVSPGKDITARRDLSPRRERRYMTTIRAPSPRRAL  2150
2151  YHNPPLSMGQYLQAEPIVLGPPNLRRGLPQVPYFSLYGDQEGAYEHPGSS  2200
2201  LFPEGPNDYVFSHLPLHSQQQVRAPIPMVPVGGIQMVHSMPPALSSLHPS  2250
2251  PTLPLPMEGFEEKKGASGESFSKDPYVLSKQHEKRGPHALQSSGPPSTPS  2300
2301  SPRLLMKQSTSEDSLNATEREQEENIQTCTKAIASLRIATEEAALLGPDQ  2350
2351  PARVQEPHQNPLGSAHVSIRHFSRPEPGQPCTSATHPDLHDGEKDNFGTS  2400
2401  QTPLAHSTFYSKSCVDDKQLDFHSSKELSSSTEESKDPSSEKSQLH      2446

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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