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

NucPred

Fetching P50851 from www.uniprot.org...

The NucPred score for your sequence is 0.77 (see score help below)

   1  MASEDNRVPSPPPTGDDGGGGGREETPTEGGALSLKPGLPIRGIRMKFAV    50
  51  LTGLVEVGEVSNRDIVETVFNLLVGGQFDLEMNFIIQEGESINCMVDLLE   100
 101  KCDITCQAEVWSMFTAILKKSIRNLQVCTEVGLVEKVLGKIEKVDNMIAD   150
 151  LLVDMLGVLASYNLTVRELKLFFSKLQGDKGRWPPHAGKLLSVLKHMPQK   200
 201  YGPDAFFNFPGKSAAAIALPPIAKWPYQNGFTFHTWLRMDPVNNINVDKD   250
 251  KPYLYCFRTSKGLGYSAHFVGGCLIVTSIKSKGKGFQHCVKFDFKPQKWY   300
 301  MVTIVHIYNRWKNSELRCYVNGELASYGEITWFVNTSDTFDKCFLGSSET   350
 351  ADANRVFCGQMTAVYLFSEALNAAQIFAIYQLGLGYKGTFKFKAESDLFL   400
 401  AEHHKLLLYDGKLSSAIAFTYNPRATDAQLCLESSPKDNPSIFVHSPHAL   450
 451  MLQDVKAVLTHSIQSAMHSIGGVQVLFPLFAQLDYRQYLSDEIDLTICST   500
 501  LLAFIMELLKNSIAMQEQMLACKGFLVIGYSLEKSSKSHVSRAVLELCLA   550
 551  FSKYLSNLQNGMPLLKQLCDHVLLNPAIWIHTPAKVQLMLYTYLSTEFIG   600
 601  TVNIYNTIRRVGTVLLIMHTLKYYYWAVNPQDRSGITPKGLDGPRPNQKE   650
 651  MLSLRAFLLMFIKQLVMKDSGVKEDELQAILNYLLTMHEDDNLMDVLQLL   700
 701  VALMSEHPNSMIPAFDQRNGLRVIYKLLASKSEGIRVQALKAMGYFLKHL   750
 751  APKRKAEVMLGHGLFSLLAERLMLQTNLITMTTYNVLFEILIEQIGTQVI   800
 801  HKQHPDPDSSVKIQNPQILKVIATLLRNSPQCPESMEVRRAFLSDMIKLF   850
 851  NNSRENRRSLLQCSVWQEWMLSLCYFNPKNSDEQKITEMVYAIFRILLYH   900
 901  AVKYEWGGWRVWVDTLSITHSKVTFEIHKENLANIFREQQGKVDEEIGLC   950
 951  SSTSVQAASGIRRDINVSVGSQQPDTKDSPVCPHFTTNGNENSSIEKTSS  1000
1001  LESASNIELQTTNTSYEEMKAEQENQELPDEGTLEETLTNETRNADDLEV  1050
1051  SSDIIEAVAISSNSFITTGKDSMTVSEVTASISSPSEEDASEMPEFLDKS  1100
1101  IVEEEEDDDYVELKVEGSPTEEANLPTELQDNSLSPAASEAGEKLDMFGN  1150
1151  DDKLIFQEGKPVTEKQTDTETQDSKDSGIQTMTASGSSAMSPETTVSQIA  1200
1201  VESDLGQMLEEGKKATNLTRETKLINDCHGSVSEASSEQKIAKLDVSNVA  1250
1251  TDTERLELKASPNVEAPQPHRHVLEISRQHEQPGQGIAPDAVNGQRRDSR  1300
1301  STVFRIPEFNWSQMHQRLLTDLLFSIETDIQMWRSHSTKTVMDFVNSSDN  1350
1351  VIFVHNTIHLISQVMDNMVMACGGILPLLSAATSATHELENIEPTQGLSI  1400
1401  EASVTFLQRLISLVDVLIFASSLGFTEIEAEKSMSSGGILRQCLRLVCAV  1450
1451  AVRNCLECQQHSQLKTRGDKALKPMHSLIPLGKSAAKSPVDIVTGGISPV  1500
1501  RDLDRLLQDMDINRLRAVVFRDIEDSKQAQFLALAVVYFISVLMVSKYRD  1550
1551  ILEPQNERHSQSCTETGSENENVSLSEITPAAFSTLTTASVEESESTSSA  1600
1601  RRRDSGIGEETATGLGSHVEVTPHTAPPGVSAGPDAISEVLSTLSLEVNK  1650
1651  SPETKNDRGNDLDTKATPSVSVSKNVNVKDILRSLVNIPADGVTVDPALL  1700
1701  PPACLGALGDLSVEQPVQFRSFDRSVIVAAKKSAVSPSTFNTSIPTNAVS  1750
1751  VVSSVDSAQASDMGGESPGSRSSNAKLPSVPTVDSVSQDPVSNMSITERL  1800
1801  EHALEKAAPLLREIFVDFAPFLSRTLLGSHGQELLIEGTSLVCMKSSSSV  1850
1851  VELVMLLCSQEWQNSIQKNAGLAFIELVNEGRLLSQTMKDHLVRVANEAE  1900
1901  FILSRQRAEDIHRHAEFESLCAQYSADKREDEKMCDHLIRAAKYRDHVTA  1950
1951  TQLIQKIINILTDKHGAWGNSAVSRPLEFWRLDYWEDDLRRRRRFVRNPL  2000
2001  GSTHPEATLKTAVEHVCIFKLRENSKATDEDILAKGKQSIRSQALGNQNS  2050
2051  ENEILLEGDDDTLSSVDEKDLENLAGPVSLSTPAQLVAPSVVVKGTLSVT  2100
2101  SSELYFEVDEEDPNFKKIDPKILAYTEGLHGKWLFTEIRSIFSRRYLLQN  2150
2151  TALEIFMANRVAVMFNFPDPATVKKVVNYLPRVGVGTSFGLPQTRRISLA  2200
2201  SPRQLFKASNMTQRWQHREISNFEYLMFLNTIAGRSYNDLNQYPVFPWVI  2250
2251  TNYESEELDLTLPTNFRDLSKPIGALNPKRAAFFAERYESWEDDQVPKFH  2300
2301  YGTHYSTASFVLAWLLRIEPFTTYFLNLQGGKFDHADRTFSSISRAWRNS  2350
2351  QRDTSDIKELIPEFYYLPEMFVNFNNYNLGVMDDGTVVSDVELPPWAKTS  2400
2401  EEFVHINRLALESEFVSCQLHQWIDLIFGYKQQGPEAVRALNVFYYLTYE  2450
2451  GAVNLNSITDPVLREAVEAQIRSFGQTPSQLLIEPHPPRGSAMQVSPLMF  2500
2501  TDKAQQDVIMVLKFPSNSPVTHVAANTQPGLATPAVITVTANRLFAVNKW  2550
2551  HNLPAHQGAVQDQPYQLPVEIDPLIASNTGMHRRQITDLLDQSIQVHSQC  2600
2601  FVITSDNRYILVCGFWDKSFRVYSTDTGRLIQVVFGHWDVVTCLARSESY  2650
2651  IGGNCYILSGSRDATLLLWYWNGKCSGIGDNPGSETAAPRAILTGHDYEV  2700
2701  TCAAVCAELGLVLSGSQEGPCLIHSMNGDLLRTLEGPENCLKPKLIQASR  2750
2751  EGHCVIFYENGLFCTFSVNGKLQATMETDDNIRAIQLSRDGQYLLTGGDR  2800
2801  GVVVVRQVSDLKQLFAYPGCDAGIRAMALSYDQRCIISGMASGSIVLFYN  2850
2851  DFNRWHHEYQTRY                                       2863

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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