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

NucPred

Fetching Q8IWJ2 from www.uniprot.org...

The NucPred score for your sequence is 0.63 (see score help below)

   1  MEDLVQDGVASPATPGTGKSKLETLPKEDLIKFAKKQMMLIQKAKSRCTE    50
  51  LEKEIEELRSKPVTEGTGDIIKALTERLDALLLEKAETEQQCLSLKKENI   100
 101  KMKQEVEDSVTKMGDAHKELEQSHINYVKEIENLKNELMAVRSKYSEDKA   150
 151  NLQKQLEEAMNTQLELSEQLKFQNNSEDNVKKLQEEIEKIRPGFEEQILY   200
 201  LQKQLDATTDEKKETVTQLQNIIEANSQHYQKNINSLQEELLQLKAIHQE   250
 251  EVKELMCQIEASAKEHEAEINKLNELKENLVKQCEASEKNIQKKYECELE   300
 301  NLRKATSNANQDNQICSILLQENTFVEQVVNEKVKHLEDTLKELESQHSI   350
 351  LKDEVTYMNNLKLKLEMDAQHIKDEFFHEREDLEFKINELLLAKEEQGCV   400
 401  IEKLKSELAGLNKQFCYTVEQHNREVQSLKEQHQKEISELNETFLSDSEK   450
 451  EKLTLMFEIQGLKEQCENLQQEKQEAILNYESLREIMEILQTELGESAGK   500
 501  ISQEFESMKQQQASDVHELQQKLRTAFTEKDALLETVNRLQGENEKLLSQ   550
 551  QELVPELENTIKNLQEKNGVYLLSLSQRDTMLKELEGKINSLTEEKDDFI   600
 601  NKLKNSHEEMDNFHKKCEREERLILELGKKVEQTIQYNSELEQKVNELTG   650
 651  GLEETLKEKDQNDQKLEKLMVQMKVLSEDKEVLSAEVKSLYEENNKLSSE   700
 701  KKQLSRDLEVFLSQKEDVILKEHITQLEKKLQLMVEEQDNLNKLLENEQV   750
 751  QKLFVKTQLYGFLKEMGSEVSEDSEEKDVVNVLQAVGESLAKINEEKCNL   800
 801  AFQRDEKVLELEKEIKCLQEESVVQCEELKSLLRDYEQEKVLLRKELEEI   850
 851  QSEKEALQSDLLEMKNANEKTRLENQNLLIQVEEVSQTCSKSEIHNEKEK   900
 901  CFIKEHENLKPLLEQKELRDRRAELILLKDSLAKSPSVKNDPLSSVKELE   950
 951  EKIENLEKECKEKEEKINKIKLVAVKAKKELDSSRKETQTVKEELESLRS  1000
1001  EKDQLSASMRDLIQGAESYKNLLLEYEKQSEQLDVEKERANNFEHRIEDL  1050
1051  TRQLRNSTLQCETINSDNEDLLARIETLQSNAKLLEVQILEVQRAKAMVD  1100
1101  KELEAEKLQKEQKIKEHATTVNELEELQVQLQKQKKQLQKTMQELELVKK  1150
1151  DAQQTTLMNMEIADYERLMKELNQKLTNKNNKIEDLEQEIKIQKQKQETL  1200
1201  QEEITSLQSSVQQYEEKNTKIKQLLVKTKKELADSKQAETDHLILQASLK  1250
1251  GELEASQQQVEVYKIQLAEITSEKHKIHEHLKTSAEQHQRTLSAYQQRVT  1300
1301  ALQEECRAAKAEQATVTSEFESYKVRVHNVLKQQKNKSMSQAETEGAKQE  1350
1351  REHLEMLIDQLKIKLQDSQNNLQINVSELQTLQSEHDTLLERHNKMLQET  1400
1401  VSKEAELREKLCSIQSENMMMKSEHTQTVSQLTSQNEVLRNSFRDQVRHL  1450
1451  QEEHRKTVETLQQQLSKMEAQLFQLKNEPTTRSPVSSQQSLKNLRERRNT  1500
1501  DLPLLDMHTVTREEGEGMETTDTESVSSASTYTQSLEQLLNSPETKLEPP  1550
1551  LWHAEFTKEELVQKLSSTTKSADHLNGLLRETEATNAILMEQIKLLKSEI  1600
1601  RRLERNQEREKSAANLEYLKNVLLQFIFLKPGSERERLLPVINTMLQLSP  1650
1651  EEKGKLAAVAQGEEENASRSSGWASYLHSWSGLR                  1684

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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