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

NucPred

Fetching Q9ZUT8 from www.uniprot.org...

The NucPred score for your sequence is 0.47 (see score help below)

   1  MGSSFRSSSSRNEHEDGGDEAEHALQWAEIQRLPTFKRLRSSLVDKYGEG    50
  51  TEKGKKVVDVTKLGAMERHLMIEKLIKHIENDNLKLLKKIRRRMERVGVE   100
 101  FPSIEVRYEHLGVEAACEVVEGKALPTLWNSLKHVFLDLLKLSGVRTNEA   150
 151  NIKILTDVSGIISPGRLTLLLGPPGCGKTTLLKALSGNLENNLKCYGEIS   200
 201  YNGHGLNEVVPQKTSAYISQHDLHIAEMTTRETIDFSARCQGVGSRTDIM   250
 251  MEVSKREKDGGIIPDPEIDAYMKAISVKGLKRSLQTDYILKILGLDICAE   300
 301  TLVGNAMKRGISGGQKKRLTTAEMIVGPTKALFMDEITNGLDSSTAFQII   350
 351  KSLQQVAHITNATVFVSLLQPAPESYDLFDDIVLMAEGKIVYHGPRDDVL   400
 401  KFFEECGFQCPERKGVADFLQEVISKKDQGQYWLHQNLPHSFVSVDTLSK   450
 451  RFKDLEIGRKIEEALSKPYDISKTHKDALSFNVYSLPKWELFRACISREF   500
 501  LLMKRNYFVYLFKTFQLVLAAIITMTVFIRTRMDIDIIHGNSYMSCLFFA   550
 551  TVVLLVDGIPELSMTVQRLSVFYKQKQLCFYPAWAYAIPATVLKIPLSFF   600
 601  ESLVWTCLTYYVIGYTPEPYRFFRQFMILFAVHFTSISMFRCIAAIFQTG   650
 651  VAAMTAGSFVMLITFVFAGFAIPYTDMPGWLKWGFWVNPISYAEIGLSVN   700
 701  EFLAPRWQKMQPTNVTLGRTILESRGLNYDDYMYWVSLSALLGLTIIFNT   750
 751  IFTLALSFLKSPTSSRPMISQDKLSELQGTKDSSVKKNKPLDSSIKTNED   800
 801  PGKMILPFKPLTITFQDLNYYVDVPVEMKGQGYNEKKLQLLSEITGAFRP   850
 851  GVLTALMGISGAGKTTLLDVLAGRKTSGYIEGEIRISGFLKVQETFARVS   900
 901  GYCEQTDIHSPSITVEESLIYSAWLRLVPEINPQTKIRFVKQVLETIELE   950
 951  EIKDALVGVAGVSGLSTEQRKRLTVAVELVANPSIIFMDEPTTGLDARAA  1000
1001  AIVMRAVKNVAETGRTIVCTIHQPSIHIFEAFDELVLLKRGGRMIYSGPL  1050
1051  GQHSSCVIEYFQNIPGVAKIRDKYNPATWMLEVTSESVETELDMDFAKIY  1100
1101  NESDLYKNNSELVKELSKPDHGSSDLHFKRTFAQNWWEQFKSCLWKMSLS  1150
1151  YWRSPSYNLMRIGHTFISSFIFGLLFWNQGKKIDTQQNLFTVLGAIYGLV  1200
1201  LFVGINNCTSALQYFETERNVMYRERFAGMYSAFAYALAQVVTEIPYIFI  1250
1251  QSAEFVIVIYPMIGFYASFSKVFWSLYAMFCNLLCFNYLAMFLISITPNF  1300
1301  MVAAILQSLFFTTFNIFAGFLIPKPQIPKWWVWFYYITPTSWTLNLFFSS  1350
1351  QYGDIHQKINAFGETKTVASFLEDYFGFHHDRLMITAIILIAFPIALATM  1400
1401  YAFFVAKLNFQKR                                       1413

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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