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

NucPred

Fetching Q9Y4A5 from www.uniprot.org...

The NucPred score for your sequence is 0.66 (see score help below)

   1  MAFVATQGATVVDQTTLMKKYLQFVAALTDVNTPDETKLKMMQEVSENFE    50
  51  NVTSSPQYSTFLEHIIPRFLTFLQDGEVQFLQEKPAQQLRKLVLEIIHRI   100
 101  PTNEHLRPHTKNVLSVMFRFLETENEENVLICLRIIIELHKQFRPPITQE   150
 151  IHHFLDFVKQIYKELPKVVNRYFENPQVIPENTVPPPEMVGMITTIAVKV   200
 201  NPEREDSETRTHSIIPRGSLSLKVLAELPIIVVLMYQLYKLNIHNVVAEF   250
 251  VPLIMNTIAIQVSAQARQHKLYNKELYADFIAAQIKTLSFLAYIIRIYQE   300
 301  LVTKYSQQMVKGMLQLLSNCPAETAHLRKELLIAAKHILTTELRNQFIPC   350
 351  MDKLFDESILIGSGYTARETLRPLAYSTLADLVHHVRQHLPLSDLSLAVQ   400
 401  LFAKNIDDESLPSSIQTMSCKLLLNLVDCIRSKSEQESGNGRDVLMRMLE   450
 451  VFVLKFHTIARYQLSAIFKKCKPQSELGAVEAALPGVPTAPAAPGPAPSP   500
 501  APVPAPPPPPPPPPPATPVTPAPVPPFEKQGEKDKEDKQTFQVTDCRSLV   550
 551  KTLVCGVKTITWGITSCKAPGEAQFIPNKQLQPKETQIYIKLVKYAMQAL   600
 601  DIYQVQIAGNGQTYIRVANCQTVRMKEEKEVLEHFAGVFTMMNPLTFKEI   650
 651  FQTTVPYMVERISKNYALQIVANSFLANPTTSALFATILVEYLLDRLPEM   700
 701  GSNVELSNLYLKLFKLVFGSVSLFAAENEQMLKPHLHKIVNSSMELAQTA   750
 751  KEPYNYFLLLRALFRSIGGGSHDLLYQEFLPLLPNLLQGLNMLQSGLHKQ   800
 801  HMKDLFVELCLTVPVRLSSLLPYLPMLMDPLVSALNGSQTLVSQGLRTLE   850
 851  LCVDNLQPDFLYDHIQPVRAELMQALWRTLRNPADSISHVAYRVLGKFGG   900
 901  SNRKMLKESQKLHYVVTEVQGPSITVEFSDCKASLQLPMEKAIETALDCL   950
 951  KSANTEPYYRRQAWEVIKCFLVAMMSLEDNKHALYQLLAHPNFTEKTIPN  1000
1001  VIISHRYKAQDTPARKTFEQALTGAFMSAVIKDLRPSALPFVASLIRHYT  1050
1051  MVAVAQQCGPFLLPCYQVGSQPSTAMFHSEENGSKGMDPLVLIDAIAICM  1100
1101  AYEEKELCKIGEVALAVIFDVASIILGSKERACQLPLFSYIVERLCACCY  1150
1151  EQAWYAKLGGVVSIKFLMERLPLTWVLQNQQTFLKALLFVMMDLTGEVSN  1200
1201  GAVAMAKTTLEQLLMRCATPLKDEERAEEIVAAQEKSFHHVTHDLVREVT  1250
1251  SPNSTVRKQAMHSLQVLAQVTGKSVTVIMEPHKEVLQDMVPPKKHLLRHQ  1300
1301  PANAQIGLMEGNTFCTTLQPRLFTMDLNVVEHKVFYTELLNLCEAEDSAL  1350
1351  TKLPCYKSLPSLVPLRIAALNALAACNYLPQSREKIIAALFKALNSTNSE  1400
1401  LQEAGEACMRKFLEGATIEVDQIHTHMRPLLMMLGDYRSLTLNVVNRLTS  1450
1451  VTRLFPNSFNDKFCDQMMQHLRKWMEVVVITHKGGQRSDGNESISECGRC  1500
1501  PLSPFCQFEEMKICSAIINLFHLIPAAPQTLVKPLLEVVMKTERAMLIEA  1550
1551  GSPFREPLIKFLTRHPSQTVELFMMEATLNDPQWSRMFMSFLKHKDARPL  1600
1601  RDVLAANPNRFITLLLPGGAQTAVRPGSPSTSTMRLDLQFQAIKIISIIV  1650
1651  KNDDSWLASQHSLVSQLRRVWVSENFQERHRKENMAATNWKEPKLLAYCL  1700
1701  LNYCKRNYGDIELLFQLLRAFTGRFLCNMTFLKEYMEEEIPKNYSIAQKR  1750
1751  ALFFRFVDFNDPNFGDELKAKVLQHILNPAFLYSFEKGEGEQLLGPPNPE  1800
1801  GDNPESITSVFITKVLDPEKQADMLDSLRIYLLQYATLLVEHAPHHIHDN  1850
1851  NKNRNSKLRRLMTFAWPCLLSKACVDPACKYSGHLLLAHIIAKFAIHKKI  1900
1901  VLQVFHSLLKAHAMEARAIVRQAMAILTPAVPARMEDGHQMLTHWTRKII  1950
1951  VEEGHTVPQLVHILHLIVQHFKVYYPVRHHLVQHMVSAMQRLGFTPSVTI  2000
2001  EQRRLAVDLSEVVIKWELQRIKDQQPDSDMDPNSSGEGVNSVSSSIKRGL  2050
2051  SVDSAQEVKRFRTATGAISAVFGRSQSLPGADSLLAKPIDKQHTDTVVNF  2100
2101  LIRVACQVNDNTNTAGSPGEVLSRRCVNLLKTALRPDMWPKSELKLQWFD  2150
2151  KLLMTVEQPNQVNYGNICTGLEVLSFLLTVLQSPAILSSFKPLQRGIAAC  2200
2201  MTCGNTKVLRAVHSLLSRLMSIFPTEPSTSSVASKYEELECLYAAVGKVI  2250
2251  YEGLTNYEKATNANPSQLFGTLMILKSACSNNPSYIDRLISVFMRSLQKM  2300
2301  VREHLNPQAASGSTEATSGTSELVMLSLELVKTRLAVMSMEMRKNFIQAI  2350
2351  LTSLIEKSPDAKILRAVVKIVEEWVKNNSPMAANQTPTLREKSILLVKMM  2400
2401  TYIEKRFPEDLELNAQFLDLVNYVYRDETLSGSELTAKLEPAFLSGLRCA  2450
2451  QPLIRAKFFEVFDNSMKRRVYERLLYVTCSQNWEAMGNHFWIKQCIELLL  2500
2501  AVCEKSTPIGTSCQGAMLPSITNVINLADSHDRAAFAMVTHVKQEPRERE  2550
2551  NSESKEEDVEIDIELAPGDQTSTPKTKELSEKDIGNQLHMLTNRHDKFLD  2600
2601  TLREVKTGALLSAFVQLCHISTTLAEKTWVQLFPRLWKILSDRQQHALAG  2650
2651  EISPFLCSGSHQVQRDCQPSALNCFVEAMSQCVPPIPIRPCVLKYLGKTH  2700
2701  NLWFRSTLMLEHQAFEKGLSLQIKPKQTTEFYEQESITPPQQEILDSLAE  2750
2751  LYSLLQEEDMWAGLWQKRCKYSETATAIAYEQHGFFEQAQESYEKAMDKA  2800
2801  KKEHERSNASPAIFPEYQLWEDHWIRCSKELNQWEALTEYGQSKGHINPY  2850
2851  LVLECAWRVSNWTAMKEALVQVEVSCPKEMAWKVNMYRGYLAICHPEEQQ  2900
2901  LSFIERLVEMASSLAIREWRRLPHVVSHVHTPLLQAAQQIIELQEAAQIN  2950
2951  AGLQPTNLGRNNSLHDMKTVVKTWRNRLPIVSDDLSHWSSIFMWRQHHYQ  3000
3001  GKPTWSGMHSSSIVTAYENSSQHDPSSNNAMLGVHASASAIIQYGKIARK  3050
3051  QGLVNVALDILSRIHTIPTVPIVDCFQKIRQQVKCYLQLAGVMGKNECMQ  3100
3101  GLEVIESTNLKYFTKEMTAEFYALKGMFLAQINKSEEANKAFSAAVQMHD  3150
3151  VLVKAWAMWGDYLENIFVKERQLHLGVSAITCYLHACRHQNESKSRKYLA  3200
3201  KVLWLLSFDDDKNTLADAVDKYCIGVPPIQWLAWIPQLLTCLVGSEGKLL  3250
3251  LNLISQVGRVYPQAVYFPIRTLYLTLKIEQRERYKSDPGPIRATAPMWRC  3300
3301  SRIMHMQRELHPTLLSSLEGIVDQMVWFRENWHEEVLRQLQQGLAKCYSV  3350
3351  AFEKSGAVSDAKITPHTLNFVKKLVSTFGVGLENVSNVSTMFSSAASESL  3400
3401  ARRAQATAQDPVFQKLKGQFTTDFDFSVPGSMKLHNLISKLKKWIKILEA  3450
3451  KTKQLPKFFLIEEKCRFLSNFSAQTAEVEIPGEFLMPKPTHYYIKIARFM  3500
3501  PRVEIVQKHNTAARRLYIRGHNGKIYPYLVMNDACLTESRREERVLQLLR  3550
3551  LLNPCLEKRKETTKRHLFFTVPRVVAVSPQMRLVEDNPSSLSLVEIYKQR  3600
3601  CAKKGIEHDNPISRYYDRLATVQARGTQASHQVLRDILKEVQSNMVPRSM  3650
3651  LKEWALHTFPNATDYWTFRKMFTIQLALIGFAEFVLHLNRLNPEMLQIAQ  3700
3701  DTGKLNVAYFRFDINDATGDLDANRPVPFRLTPNISEFLTTIGVSGPLTA  3750
3751  SMIAVARCFAQPNFKVDGILKTVLRDEIIAWHKKTQEDTSSPLSAAGQPE  3800
3801  NMDSQQLVSLVQKAVTAIMTRLHNLAQFEGGESKVNTLVAAANSLDNLCR  3850
3851  MDPAWHPWL                                           3859

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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