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

NucPred

Fetching Q8NFP9 from www.uniprot.org...

The NucPred score for your sequence is 0.60 (see score help below)

   1  MASEKPGPGPGLEPQPVGLIAVGAAGGGGGGSGGGGTGGSGMGELRGASG    50
  51  SGSVMLPAGMINPSVPIRNIRMKFAVLIGLIQVGEVSNRDIVETVLNLLV   100
 101  GGEFDLEMNFIIQDAESITCMTELLEHCDVTCQAEIWSMFTAILRKSVRN   150
 151  LQTSTEVGLIEQVLLKMSAVDDMIADLLVDMLGVLASYSITVKELKLLFS   200
 201  MLRGESGIWPRHAVKLLSVLNQMPQRHGPDTFFNFPGCSAAAIALPPIAK   250
 251  WPYQNGFTLNTWFRMDPLNNINVDKDKPYLYCFRTSKGVGYSAHFVGNCL   300
 301  IVTSLKSKGKGFQHCVKYDFQPRKWYMISIVHIYNRWRNSEIRCYVNGQL   350
 351  VSYGDMAWHVNTNDSYDKCFLGSSETADANRVFCGQLGAVYVFSEALNPA   400
 401  QIFAIHQLGPGYKSTFKFKSESDIHLAEHHKQVLYDGKLASSIAFTYNAK   450
 451  ATDAQLCLESSPKENASIFVHSPHALMLQDVKAIVTHSIHSAIHSIGGIQ   500
 501  VLFPLFAQLDNRQLNDSQVETTVCATLLAFLVELLKSSVAMQEQMLGGKG   550
 551  FLVIGYLLEKSSRVHITRAVLEQFLSFAKYLDGLSHGAPLLKQLCDHILF   600
 601  NPAIWIHTPAKVQLSLYTYLSAEFIGTATIYTTIRRVGTVLQLMHTLKYY   650
 651  YWVINPADSSGITPKGLDGPRPSQKEIISLRAFMLLFLKQLILKDRGVKE   700
 701  DELQSILNYLLTMHEDENIHDVLQLLVALMSEHPASMIPAFDQRNGIRVI   750
 751  YKLLASKSESIWVQALKVLGYFLKHLGHKRKVEIMHTHSLFTLLGERLML   800
 801  HTNTVTVTTYNTLYEILTEQVCTQVVHKPHPEPDSTVKIQNPMILKVVAT   850
 851  LLKNSTPSAELMEVRRLFLSDMIKLFSNSRENRRCLLQCSVWQDWMFSLG   900
 901  YINPKNSEEQKITEMVYNIFRILLYHAIKYEWGGWRVWVDTLSIAHSKVT   950
 951  YEAHKEYLAKMYEEYQRQEEENIKKGKKGNVSTISGLSSQTTGAKGGMEI  1000
1001  REIEDLSQSQSPESETDYPVSTDTRDLLMSTKVSDDILGNSDRPGSGVHV  1050
1051  EVHDLLVDIKAEKVEATEVKLDDMDLSPETLVGGENGALVEVESLLDNVY  1100
1101  SAAVEKLQNNVHGSVGIIKKNEEKDNGPLITLADEKEDLPNSSTSFLFDK  1150
1151  IPKQEEKLLPELSSNHIIPNIQDTQVHLGVSDDLGLLAHMTGSVDLTCTS  1200
1201  SIIEEKEFKIHTTSDGMSSISERDLASSTKGLEYAEMTATTLETESSSSK  1250
1251  IVPNIDAGSIISDTERSDDGKESGKEIRKIQTTTTTQAVQGRSITQQDRD  1300
1301  LRVDLGFRGMPMTEEQRRQFSPGPRTTMFRIPEFKWSPMHQRLLTDLLFA  1350
1351  LETDVHVWRSHSTKSVMDFVNSNENIIFVHNTIHLISQMVDNIIIACGGI  1400
1401  LPLLSAATSPTGSKTELENIEVTQGMSAETAVTFLSRLMAMVDVLVFASS  1450
1451  LNFSEIEAEKNMSSGGLMRQCLRLVCCVAVRNCLECRQRQRDRGNKSSHG  1500
1501  SSKPQEVPQSVTATAASKTPLENVPGNLSPIKDPDRLLQDVDINRLRAVV  1550
1551  FRDVDDSKQAQFLALAVVYFISVLMVSKYRDILEPQRETTRTGSQPGRNI  1600
1601  RQEINSPTSTVVVIPSIPHPSLNHGFLAKLIPEQSFGHSFYKETPAAFPD  1650
1651  TIKEKETPTPGEDIQVESSIPHTDSGIGEEQVASILNGAELETSTGPDAM  1700
1701  SELLSTLSSEVKKSQESLTENPSETLKPATSISSISQTKGINVKEILKSL  1750
1751  VAAPVEIAECGPEPIPYPDPALKRETQAILPMQFHSFDRSVVVPVKKPPP  1800
1801  GSLAVTTVGATTAGSGLPTGSTSNIFAATGATPKSMINTTGAVDSGSSSS  1850
1851  SSSSSFVNGATSKNLPAVQTVAPMPEDSAENMSITAKLERALEKVAPLLR  1900
1901  EIFVDFAPFLSRTLLGSHGQELLIEGLVCMKSSTSVVELVMLLCSQEWQN  1950
1951  SIQKNAGLAFIELINEGRLLCHAMKDHIVRVANEAEFILNRQRAEDVHKH  2000
2001  AEFESQCAQYAADRREEEKMCDHLISAAKHRDHVTANQLKQKILNILTNK  2050
2051  HGAWGAVSHSQLHDFWRLDYWEDDLRRRRRFVRNAFGSTHAEALLKAAIE  2100
2101  YGTEEDVVKSKKTFRSQAIVNQNAETELMLEGDDDAVSLLQEKEIDNLAG  2150
2151  PVVLSTPAQLIAPVVVAKGTLSITTTEIYFEVDEDDSAFKKIDTKVLAYT  2200
2201  EGLHGKWMFSEIRAVFSRRYLLQNTALEVFMANRTSVMFNFPDQATVKKV  2250
2251  VYSLPRVGVGTSYGLPQARRISLATPRQLYKSSNMTQRWQRREISNFEYL  2300
2301  MFLNTIAGRTYNDLNQYPVFPWVLTNYESEELDLTLPGNFRDLSKPIGAL  2350
2351  NPKRAVFYAERYETWEDDQSPPYHYNTHYSTATSTLSWLVRIEPFTTFFL  2400
2401  NANDGKFDHPDRTFSSVARSWRTSQRDTSDVKELIPEFYYLPEMFVNSNG  2450
2451  YNLGVREDEVVVNDVDLPPWAKKPEDFVRINRMALESEFVSCQLHQWIDL  2500
2501  IFGYKQRGPEAVRALNVFHYLTYEGSVNLDSITDPVLREAMEAQIQNFGQ  2550
2551  TPSQLLIEPHPPRSSAMHLCFLPQSPLMFKDQMQQDVIMVLKFPSNSPVT  2600
2601  HVAANTLPHLTIPAVVTVTCSRLFAVNRWHNTVGLRGAPGYSLDQAHHLP  2650
2651  IEMDPLIANNSGVNKRQITDLVDQSIQINAHCFVVTADNRYILICGFWDK  2700
2701  SFRVYSTETGKLTQIVFGHWDVVTCLARSESYIGGDCYIVSGSRDATLLL  2750
2751  WYWSGRHHIIGDNPNSSDYPAPRAVLTGHDHEVVCVSVCAELGLVISGAK  2800
2801  EGPCLVHTITGDLLRALEGPENCLFPRLISVSSEGHCIIYYERGRFSNFS  2850
2851  INGKLLAQMEINDSTRAILLSSDGQNLVTGGDNGVVEVWQACDFKQLYIY  2900
2901  PGCDAGIRAMDLSHDQRTLITGMASGSIVAFNIDFNRWHYEHQNRY      2946

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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