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

NucPred

Fetching O08653 from www.uniprot.org...

The NucPred score for your sequence is 0.84 (see score help below)

   1  MEKLCGYVPVHPDILSLKNRCLTMLSDIQPLEKIHGQRSVNPDILSLENR    50
  51  CLTLLPDLQPMEKIHGQRSVHPDILSSENRCLTLLPDLQSLEKLCGHMSS   100
 101  HPDVLSLENRCLATLPTVKRTVSSGPLLQCLHRSHTAQADLRDPNFRNCL   150
 151  FPEPPTIEAPCFLKELDLPTGPRALKSMSATARVQEVALGQRCVSEGKEL   200
 201  QEEKESAEVPMPLYSLSLGGEEEEVVGAPVLKLTSGDSDSHPETTDQILQ   250
 251  EKKMALLTLLCSAMASSVNVKDASDPTRASIHEVCSALAPLEPEFILKAS   300
 301  LYARQQLNLRDIANIVLAVAALLPACRPHVRRYYSAIVHLPSDWIQVAEF   350
 351  YQSLAEGDEKKLVPLPACLRAAMTDKFAQFDEYQLAKYNPRKHRSKTRSR   400
 401  QPPRPQRTKPPFSESGKCFPKSVWPLKNEQISFEAAYNAVSEKKRLPRFT   450
 451  LKKLVEQLHIHEPAQHVQALLGYRYPSTLELFSRSHLPGPWDSSRAGQRM   500
 501  KLQRPETWERELSLRGNRASVWEELIDNGKLPFMAMLRNLCNLLRTGISA   550
 551  HHHELVLQRLQHEKSVIHSRQFPFRFLNAHDSLDRLEAQLRSKASPFPSN   600
 601  TTLMKRIMIRNSKKIKRPANPRYLCTLTQRQLRAAMAIPVMYEHLKREKL   650
 651  RLHKARQWTCDLELLERYRQALETAVNISVKHNLPPLPGRTLLVYLTDAN   700
 701  ANRLCPKSHLQGPPLNYVLLLIGMMMARAEQTTVWLCGTGTVKTPVLTAD   750
 751  EGILKTAIKLQAQVQELEENDEWPLETFEKYLLSLAVRRTPIDRVILFGQ   800
 801  RMDTELLNVAKQIIWQHVNSKCLFVSVLLRKMQYMSPNLNPNDVTLSGCT   850
 851  DGILKFIAEHGASRLLEHVGQLDKIFKIPPPPGKTKVSPLRPLEENNPGP   900
 901  FVPISQHGWRNIRLFISSTFRDMHGERDLLMRSVLPALQARAFPHRISLH   950
 951  AIDLRWGITEEETRRNRQLEVCLGEVENSQLFVGILGSRYGYTPPSYDLP  1000
1001  DHPHFHWTQRYPSGRSVTEMEVMQFLNRGQRSEPSDQALIYFRDPGFLSS  1050
1051  VPDVWKPDFISESEEAAHRVSELKRFLQEQKEVTCRRYSCEWGGVAAGRP  1100
1101  YTGGLEEFGQLVLQDVWSVIQKRYLQPGAQLEQPGSISEEDLIQASFQQL  1150
1151  KSPPSPARPRLLQDTVQQLMLPHGRLSLVIGQAGQGKTAFLASLVSALKV  1200
1201  PDQPNVAPFVFFHFSAARPDQCLAFNLLRRLCTHLHQKLGEPSALPSTYR  1250
1251  GLVWELQQKLLLKSAQWLQPGQTLVLIIDGADKLVDHNGQLISDWIPKSL  1300
1301  PRRVHLVLSVSSDSGLGETLQQSQSAYVVALGSLVPSSRAQLVREELALY  1350
1351  GKRLEESPFNNQMRLLLAKQGSSLPLYLHLVTDYLRLFTLYEQVSERLRT  1400
1401  LPATLPLLLQHILSTLEQEHGHNVLPQALTALEVTHSGLTVDQLHAVLST  1450
1451  WLTLPKETKSWEEAVAASHSGNLYPLAPFAYLVQSLRSLLGEGPVERPGA  1500
1501  RLCLSDGPLRTAVKRRYGKRLGLEKTAHVLIAAHLWKMCDPDASGTFRSC  1550
1551  PPEALKDLPYHLLQSGNHGLLAKFLTNLHVVAAYLEVGLVPDLLEAYELY  1600
1601  ASSKPEVNQKLPEADVAVFHNFLKQQASLLTQYPLLLLQQAASQPEESPV  1650
1651  CCQAPLLTQRWHNQCILKWINKPQTLKGQQSLSLPISSSPTAVAFSPNGQ  1700
1701  RAAVGTAGGTIYLLNLRTWQEEKALVSGCDGISSFAFLSDTALFLTTFDG  1750
1751  LLELWDLQHGCWVFQTKAHQYQITGCCLSPDRRLLATVCLGGYVKLWDTV  1800
1801  QGQLAFQYTHPKSLNCITFHPEGQVVATGNWSGIVTFFQADGLKVTKELG  1850
1851  GPGPSVRTLAFSAPGKVVALGRIDGTVELWAWQEGTRLAAFPAQCGGVST  1900
1901  VLFLHAGGRFLTAGEDGKAQLWSGFLGRPRGCLGSLYLSPALSVALNPDG  1950
1951  DQVAVGYRGDGIKIYRISSGPQEAQCQELNVAVSALVWLSPSVLVSGAED  2000
2001  GSLHGWMLRRNSLQSLWLSSVCQKPVLGLAASQEFLASASEDFTVRLWPR  2050
2051  QLLTQPHAVEELPCAAELRGHEGPVCCCSFSPDGRILATAGRDRNLLCWD  2100
2101  VKVAQAPLLIHTFSSCHRDWITGCTWTKDNILISCSSDGSVGLWNPEAGQ  2150
2151  QLGQFPGHQSAVSAVVAVEEHIVSVSRDGTLKVWDRQGVELTSIPAHSGP  2200
2201  ISQCAAALEPRPAGQPGSELMVVTVGLDGATKLWHPLLVCQIHTLQGHSG  2250
2251  PVTAAAASEASGLLLTSDNSSVRLWQIPKEADDTCKPRSSAVITAVAWAP  2300
2301  DGSLVVSGNEAGELTLWQKAQAVATARAPGRVSDLIWCSANAFFVLSANE  2350
2351  NVSEWQVELRKGSTCTNFRLYLKRVLQEDLGVLTGMALAPDGQSLILMKE  2400
2401  DVELLQMKPGSTPSSICRRYAVHSSILCTSKDYGLFYLQQGNSGSLSILE  2450
2451  QEESGKFEKTLDFNLNLNNPNGSPVSITQAEPESGSSLLCATSDGMLWNL  2500
2501  SECTPEGEWVVDNIWQKKSRNPKSRTPGTDSSPGLFCMDSWVEPTHLKAR  2550
2551  QCKKIHLGSVTALHVLPGLLVTASEDRDVKLWERPSMQLLGLFRCEGPVS  2600
2601  CLEPWMEPSSPLQLAVGDAQGNLYFLSWE                       2629

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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