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

NucPred

Fetching Q00900 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MDTGDTALGQKATSRSGETDSVSGRWRQEQSAGLKMSTFSSQEGQRQPQI    50
  51  DPDQIGNVASAQLFGSGKLASPGEGVHQVTEKQYPPHRPSPYPCQHSLSF   100
 101  PQHSLPQGMMHSNKPHQSLEGPPWLFSGPLPSVASEDLFPFPMHGHSSGY   150
 151  PRKKISSLNPAYSQYSQKSIEQAEDAHKKEHKPKKPGKYICPYCSRACAK   200
 201  PSVLKKHIRSHTGERPYPCIPCGFSFKTKSNLYKHRKSHAHAIKAGLVPF   250
 251  TESSVSKLDLEAGFIDVEAEIHSDGEQSTDTDEESSLFAEASDKVSPGPP   300
 301  IPLDIASRGGYPGSLEESLGGPMKVPILIIPKSGIPLPNEGSQYLGPDML   350
 351  PNPSLNAKADDSHTVKQKLALRLSEKKGQDSEPSLNLLSPHSKGSTDSGY   400
 401  FSRSESAEQQISPPNTNAKSYEEIIFGKYCRLSPRNTLSVTPTGQERTAM   450
 451  GRRGLVEPLPHVNTRLEVKMFEDPITQLIPSKGEMDPSQVNMLKTTKFNS   500
 501  ECRQPQAMAASVRNEGKPYPGSFPGSNPILLEAPVDSSPLIRSNSMPTSS   550
 551  ATNLSIPPSLRGSHSFDERMTGSDDVFYPGTVGIPPQRMLRRQAAFELPS   600
 601  VQEGHMEFEHPARVPKILAGSSLKEKKLVPGDRSGYDYDACRKPYKKWED   650
 651  PETPKQSYRDISCLSTFKHGGEYFMDPSVPLPGVPTMFGTTCENRKRRKE   700
 701  KSVGDEEDTPMICGGMGSAPGSMMSSEYDSKLQDGGRSGFTMTGHESLPH   750
 751  GYSDRLDLARPQLPSRSPSLGSEDLPSAGDPDKMTDLGKKPPGNVISVIQ   800
 801  HTNSLSRPNSFERSESTEMAVSTQDKTPSPSEMGDSEVLEGPVSPEWAPP   850
 851  GDGAESGSRPTPSQQVPQHSYHGQPRLVRQHNIQVPEIRVTEEPDKPEKE   900
 901  KEAPTKEPEKPVEEFQWPQRSETLSQLPAEKLPPKKKRLRLADMEHSSGE   950
 951  SSFESTGTGLSRSPSQESNLSHSSSFSMSFDRDETVKLTAPPKQDESGKH  1000
1001  SEFLTVPAGSYSLSVPGHHHQKEMRRCSSEQMPCPHPTEVPEIRSKSFDY  1050
1051  GNLSHAPVAGASPSTLSPSRERKKCFLVRQASFSGSPEIAQGEAGMDPSV  1100
1101  KQEQLEQLHAGLRAAWTTVLPPLPGDDPGKQVVGPCGQLSSGPPLHLAQQ  1150
1151  QIMHMDSQESLRNPLIQPTSYMTGKHLPEQPHLFPHQDAVPFSPIQNALF  1200
1201  QFQYPTVCMVHLPAQQPPWWQAHFPHPFTPHPQNSYSKPPFQADIHSSYS  1250
1251  LEHVAEHTGKKSADYPHAKEQTYPCYSGASGLHSKNLPPKFPSDPGSKST  1300
1301  EAPPTEQLLREDFASENAGPLQSLPGTVVPVRIQTHVPSYGSVMYTSISQ  1350
1351  ILGQNSPAIVICKVDENMTQRTLVTNAAMQGIGFNIAQVLGQRTGLEKYP  1400
1401  LWKVPQTLPLGLESSIPLCLPSTSDSAASLGGSKRMLSPASSLELFMETK  1450
1451  QQKRVKEEKMYGQIVEELSAVELTNSDIKKGLSRPQKPQLVRQGCASEPK  1500
1501  DGSSQSRSSSFSSLSPSSSQDHPAASGPFPPNREILSGSRAPPRRKFSGP  1550
1551  SESRESSDELDIDETSSDMSMSPQSSSLPTGGSQQEDEGKARKLPVSMLV  1600
1601  HMASGPGGNVANSTLLFTDVADFQQILQFPSLRTTTTVSWCFLNYTKPNF  1650
1651  VQQATFKSSVYASWCISSCNPNPSGLNTKTTLALLRSKQKITAEIYTLAA  1700
1701  MHRPGTGKLTSSSAWKQFAQMKPDAPFLFGNKLERKLGGNVLKERGKGEI  1750
1751  HGDKDLGSKQTEPIRIKIFEGGYKSNEDYVYVRGRGRGKYICEECGIRCK  1800
1801  KPSMLKKHIRTHTDVRPYVCKLCNFAFKTKGNLTKHMKSKAHMKKCLELG  1850
1851  VSMTSVDETETEEAENMEDLHKTSEKHSMSGISTDHQFSDAEESDGEDGD  1900
1901  DNDEDDEDDDDFDDQGDLTPKTRSRSTSPQPPRFSSLPVNVGAVAHGVPS  1950
1951  DSSLGHSSLISYLVTLPSIQVTQLMTPSDSCEDTQMTEYQRLFQSKSTDS  2000
2001  EPDKDRLDIPSSMDEEAMLSSEPSSSPRDFSPSSYRSSPGYDSSPCRDNS  2050
2051  PKRYLIPKGDLSPRRHLSPRRDLSPMRHLSPRKEAALRREMSQGDASPRR  2100
2101  HLSPRRPLSPGKDITTRRDLSPRRERRYMTTIRAPSPRRALYHNPPLPMG  2150
2151  QYLQTEPIVLGPPNLRRGLPQVPYFSLYGDQEGAYEHHGSSLFPEGPTDY  2200
2201  VFSHLPLHSQQQVRAPIPMVPVGGIQMVHSLPPAISGLHPPPTLPLPTEG  2250
2251  SEEKKGAPGEALTQDPYTLSRRHEKQAPHVLQSSGLPSSPSSPRLLMKQS  2300
2301  TSEDSLNSTEREQEENIQTCTKAIASLRIATEEAALLGADQPTWVQESPQ  2350
2351  KPLESAHISIRHFSGPEPGQLCTSAAHPDLHDGEKDTFGTSQTAVAHPTF  2400
2401  YSKGSVDEKQVDFQSSKELSLSTEEGNEPSSEKNRLH               2437

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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