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

NucPred

Fetching Q8VHK2 from www.uniprot.org...

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

   1  MGKEQELVQAVKAEDVGTAQRLLQRPRPGKAKLLGSTKKINVNFQDPDGF    50
  51  SALHHAALNGNTELISLLLEAQAAVDIKDNKGMRPLHYAAWQGRKEPMKL   100
 101  VLKAGSAVNVPSDEGHIPLHLAAQHGHYDVSEMLLQHQSNPCIVDNSGKT   150
 151  PLDLACEFGRVGVVQLLLSSNMCAALLEPRPGDTTDPNGTSPLHLAAKNG   200
 201  HIDIIRLLLQAGIDINRQTKSGTALHEAALCGKTEVVRLLLDSGINAQVR   250
 251  NTYSQTALDIVHQFTTSQASKEIKQLLREASAALQVRATKDYCNNYDLTS   300
 301  LNVKAGDIITVLEQHPDGRWKGCIHDNRTGNDRVGYFPSSLGEAIVKRAG   350
 351  SRTGSEPSPPQGGGSLGPSAPPEEIWVLRKPFAGGDRSGSLSNVAGGRST   400
 401  GGHALHAGAEGVKLLATVLSQKSVSESSPGDSPVKPPEGSSGAARSQPPA   450
 451  AHAGQVYGEQPPKKLESSSASEGKSAEAVSQWLATFQLQLYAPNFTSAGY   500
 501  DLPTISRMTPEDLTAIGVTKPGHRKKITAEISGLNIPDCLPEHKPANLAV   550
 551  WLSMIGLAQYYKVLVDNGYENIDFITDITWEDLQEIGITKLGHQKKLMLA   600
 601  VRKLAELQKAEYSKYEGGPLRRKAPQSLEMMAIESPPPSEPAAAECQSPK   650
 651  MTTFQDSELSGELQAALSGPAEAGAAAAEKSSNHLPATPRTTSRQESSLS   700
 701  GRARHMSSSQELLGDGPQGPGSPMSRSQEYLLDEGPAPGTPPKEVRSSRH   750
 751  GHSVKRASVPPVPGKPRQVLPSGVSHFTPPQTPTKAQPGSPQALGGPHGP   800
 801  ATAKVKPTPQLLPPTDRPMSPRSLPQSPTHRGFAYVLPQPVEGEAGPPAP   850
 851  GPVPPPVPAAVPTLCLPPEADVEPRRPKKRAHSLNRYAASDSEPERDELL   900
 901  VPAAAGPYATVQRRVGRSHSVRAPAGTDKNVNRSQSFAVRPRKKGPPPPP   950
 951  PKRSSSAMASANLADEPSPDVETEDGRLGVRAQRRRASDLAGSVDTGSAG  1000
1001  SVKSIAAMLELSSIGGGGRAIRRPPEGHPTPRPASPDPGRVATVLASVKH  1050
1051  KEAIGPDGEVVNRRRTLSGPVTGLLATARRGPGEPAEQSHFMEDGTARQR  1100
1101  LRGPAKGEAGVEGPPLARVEASATLKRRIRAKQSQQENVKFILTESDTVK  1150
1151  RRPKAKEPDIGPEPPPPLSVYQNGTATIRRRPASEQAGPPELPPPPPPAE  1200
1201  PPPTDLMPLPPLPLPDGSARKPVKPPVSPKPILAQPVSKIQGSPTPASKK  1250
1251  VPLPGPGSPEVKRAHGTPPPVSPKPPPPPTAPKPAKALAGLQSSSATPSP  1300
1301  VPSPARQPPAALIKPASSPPSQSASPAKPPSPGAPALQVPTKPPRAAASV  1350
1351  VSGPPVASDCASPGDSARQKLEETSACLAAALQAVEEKIRQEDGQGPRPS  1400
1401  SIEEKSTGSILEDIGSMFDDLADQLDAMLE                      1430

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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