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

NucPred

Fetching Q15413 from www.uniprot.org...

The NucPred score for your sequence is 0.80 (see score help below)

   1  MAEGGEGGEDEIQFLRTEDEVVLQCIATIHKEQRKFCLAAEGLGNRLCFL    50
  51  EPTSEAKYIPPDLCVCNFVLEQSLSVRALQEMLANTGENGGEGAAQGGGH   100
 101  RTLLYGHAVLLRHSFSGMYLTCLTTSRSQTDKLAFDVGLREHATGEACWW   150
 151  TIHPASKQRSEGEKVRIGDDLILVSVSSERYLHLSVSNGNIQVDASFMQT   200
 201  LWNVHPTCSGSSIEEGYLLGGHVVRLFHGHDECLTIPSTDQNDSQHRRIF   250
 251  YEAGGAGTRARSLWRVEPLRISWSGSNIRWGQAFRLRHLTTGHYLALTED   300
 301  QGLILQDRAKSDTKSTAFSFRASKELKEKLDSSHKRDIEGMGVPEIKYGD   350
 351  SVCFVQHIASGLWVTYKAQDAKTSRLGPLKRKVILHQEGHMDDGLTLQRC   400
 401  QREESQAARIIRNTTALFSQFVSGNNRTAAPITLPIEEVLQTLQDLIAYF   450
 451  QPPEEEMRHEDKQNKLRSLKNRQNLFKEEGMLALVLNCIDRLNVYNSVAH   500
 501  FAGIAREESGMAWKEILNLLYKLLAALIRGNRNNCAQFSNNLDWLISKLD   550
 551  RLESSSGILEVLHCILTESPEALNLIAEGHIKSIISLLDKHGRNHKVLDI   600
 601  LCSLCLCNGVAVRANQNLICDNLLPRRNLLLQTRLINDVTSIRPNIFLGV   650
 651  AEGSAQYKKWYFELIIDQVDPFLTAEPTHLRVGWASSSGYAPYPGGGEGW   700
 701  GGNGVGDDLYSYGFDGLHLWSGRIPRAVASINQHLLRSDDVVSCCLDLGV   750
 751  PSISFRINGQPVQGMFENFNTDGLFFPVMSFSAGVKVRFLMGGRHGEFKF   800
 801  LPPSGYAPCYEALLPKEKMRLEPVKEYKRDADGIRDLLGTTQFLSQASFI   850
 851  PCPVDTSQVILPPHLEKIRDRLAENIHELWGMNKIELGWTFGKIRDDNKR   900
 901  QHPCLVEFSKLPETEKNYNLQMSTETLKTLLALGCHIAHVNPAAEEDLKK   950
 951  VKLPKNYMMSNGYKPAPLDLSDVKLLPPQEILVDKLAENAHNVWAKDRIK  1000
1001  QGWTYGIQQDLKNKRNPRLVPYALLDERTKKSNRDSLREAVRTFVGYGYN  1050
1051  IEPSDQELADSAVEKVSIDKIRFFRVERSYAVRSGKWYFEFEVVTGGDMR  1100
1101  VGWARPGCRPDVELGADDQAFVFEGNRGQRWHQGSGYFGRTWQPGDVVGC  1150
1151  MINLDDASMIFTLNGELLITNKGSELAFADYEIENGFVPICCLGLSQIGR  1200
1201  MNLGTDASTFKFYTMCGLQEGFEPFAVNMNRDVAMWFSKRLPTFVNVPKD  1250
1251  HPHIEVMRIDGTMDSPPCLKVTHKTFGTQNSNADMIYCRLSMPVECHSSF  1300
1301  SHSPCLDSEAFQKRKQMQEILSHTTTQCYYAIRIFAGQDPSCVWVGWVTP  1350
1351  DYHLYSEKFDLNKNCTVTVTLGDERGRVHESVKRSNCYMVWGGDIVASSQ  1400
1401  RSNRSNVDLEIGCLVDLAMGMLSFSANGKELGTCYQVEPNTKVFPAVFLQ  1450
1451  PTSTSLFQFELGKLKNAMPLSAAIFRSEEKNPVPQCPPRLDVQTIQPVLW  1500
1501  SRMPNSFLKVETERVSERHGWVVQCLEPLQMMALHIPEENRCVDILELCE  1550
1551  QEDLMRFHYHTLRLYSAVCALGNSRVAYALCSHVDLSQLFYAIDNKYLPG  1600
1601  LLRSGFYDLLISIHLASAKERKLMMKNEYIIPITSTTRNIRLFPDESKRH  1650
1651  GLPGVGLRTCLKPGFRFSTPCFVVTGEDHQKQSPEIPLESLRTKALSMLT  1700
1701  EAVQCSGAHIRDPVGGSVEFQFVPVLKLIGTLLVMGVFDDDDVRQILLLI  1750
1751  DPSVFGEHSAGTEEGAEKEEVTQVEEKAVEAGEKAGKEAPVKGLLQTRLP  1800
1801  ESVKLQMCELLSYLCDCELQHRVEAIVAFGDIYVSKLQANQKFRYNELMQ  1850
1851  ALNMSAALTARKTKEFRSPPQEQINMLLNFQLGENCPCPEEIREELYDFH  1900
1901  EDLLLHCGVPLEEEEEEEEDTSWTGKLCALVYKIKGPPKPEKEQPTEEEE  1950
1951  RCPTTLKELISQTMICWAQEDQIQDSELVRMMFNLLRRQYDSIGELLQAL  2000
2001  RKTYTISHTSVSDTINLLAALGQIRSLLSVRMGKEEELLMINGLGDIMNN  2050
2051  KVFYQHPNLMRVLGMHETVMEVMVNVLGTEKSQIAFPKMVASCCRFLCYF  2100
2101  CRISRQNQKAMFEHLSYLLENSSVGLASPSMRGSTPLDVAASSVMDNNEL  2150
2151  ALSLEEPDLEKVVTYLAGCGLQSCPMLLAKGYPDVGWNPIEGERYLSFLR  2200
2201  FAVFVNSESVEENASVVVKLLIRRPECFGPALRGEGGNGLLAAMQGAIKI  2250
2251  SENPALDLPSQGYKREVSTGDDEEEEEIVHMGNAIMSFYSALIDLLGRCA  2300
2301  PEMHLIQTGKGEAIRIRSILRSLVPTEDLVGIISIPLKLPSLNKDGSVSE  2350
2351  PDMAANFCPDHKAPMVLFLDRVYGIKDQTFLLHLLEVGFLPDLRASASLD  2400
2401  TVSLSTTEAALALNRYICSAVLPLLTRCAPLFAGTEHCTSLIDSTLQTIY  2450
2451  RLSKGRSLTKAQRDTIEECLLAICNHLRPSMLQQLLRRLVFDVPQLNEYC  2500
2501  KMPLKLLTNHYEQCWKYYCLPSGWGSYGLAVEEELHLTEKLFWGIFDSLS  2550
2551  HKKYDPDLFRMALPCLSAIAGALPPDYLDTRITATLEKQISVDADGNFDP  2600
2601  KPINTMNFSLPEKLEYIVTKYAEHSHDKWACDKSQSGWKYGISLDENVKT  2650
2651  HPLIRPFKTLTEKEKEIYRWPARESLKTMLAVGWTVERTKEGEALVQQRE  2700
2701  NEKLRSVSQANQGNSYSPAPLDLSNVVLSRELQGMVEVVAENYHNIWAKK  2750
2751  KKLELESKGGGSHPLLVPYDTLTAKEKFKDREKAQDLFKFLQVNGIIVSR  2800
2801  GMKDMELDASSMEKRFAYKFLKKILKYVDSAQEFIAHLEAIVSSGKTEKS  2850
2851  PRDQEIKFFAKVLLPLVDQYFTSHCLYFLSSPLKPLSSSGYASHKEKEMV  2900
2901  AGLFCKLAALVRHRISLFGSDSTTMVSCLHILAQTLDTRTVMKSGSELVK  2950
2951  AGLRAFFENAAEDLEKTSENLKLGKFTHSRTQIKGVSQNINYTTVALLPI  3000
3001  LTSIFEHVTQHQFGMDLLLGDVQISCYHILCSLYSLGTGKNIYVERQRPA  3050
3051  LGECLASLAAAIPVAFLEPTLNRYNPLSVFNTKTPRERSILGMPDTVEDM  3100
3101  CPDIPQLEGLMKEINDLAESGARYTEMPHVIEVILPMLCNYLSYWWERGP  3150
3151  ENLPPSTGPCCTKVTSEHLSLILGNILKIINNNLGIDEASWMKRIAVYAQ  3200
3201  PIISKARPDLLRSHFIPTLEKLKKKAVKTVQEEEQLKADGKGDTQEAELL  3250
3251  ILDEFAVLCRDLYAFYPMLIRYVDNNRSNWLKSPDADSDQLFRMVAEVFI  3300
3301  LWCKSHNFKREEQNFVIQNEINNLAFLTGDSKSKMSKAMQVKSGGQDQER  3350
3351  KKTKRRGDLYSIQTSLIVAALKKMLPIGLNMCTPGDQELISLAKSRYSHR  3400
3401  DTDEEVREHLRNNLHLQEKSDDPAVKWQLNLYKDVLKSEEPFNPEKTVER  3450
3451  VQRISAAVFHLEQVEQPLRSKKAVWHKLLSKQRKRAVVACFRMAPLYNLP  3500
3501  RHRSINLFLHGYQRFWIETEEYSFEEKLVQDLAKSPKVEEEEEEETEKQP  3550
3551  DPLHQIILYFSRNALTERSKLEDDPLYTSYSSMMAKSCQSGEDEEEDEDK  3600
3601  EKTFEEKEMEKQKTLYQQARLHERGAAEMVLQMISASKGEMSPMVVETLK  3650
3651  LGIAILNGGNAGVQQKMLDYLKEKKDAGFFQSLSGLMQSCSVLDLNAFER  3700
3701  QNKAEGLGMVTEEGTLIVRERGEKVLQNDEFTRDLFRFLQLLCEGHNSDF  3750
3751  QNFLRTQMGNTTTVNVIISTVDYLLRLQESISDFYWYYSGKDIIDESGQH  3800
3801  NFSKALAVTKQIFNSLTEYIQGPCIGNQQSLAHSRLWDAVVGFLHVFANM  3850
3851  QMKLSQDSSQIELLKELLDLLQDMVVMLLSLLEGNVVNGTIGKQMVDTLV  3900
3901  ESSTNVEMILKFFDMFLKLKDLTSSDTFKEYDPDGKGIISKKEFQKAMEG  3950
3951  QKQYTQSEIDFLLSCAEADENDMFNYVDFVDRFHEPAKDIGFNVAVLLTN  4000
4001  LSEHMPNDSRLKCLLDPAESVLNYFEPYLGRIEIMGGAKKIERVYFEISE  4050
4051  SSRTQWEKPQVKESKRQFIFDVVNEGGEQEKMELFVNFCEDTIFEMQLAS  4100
4101  QISESDSADRPEEEEEDEDSSYVLEIAGEEEEDGSLEPASAFAMACASVK  4150
4151  RNVTDFLKRATLKNLRKQYRNVKKMTAKELVKVLFSFFWMLFVGLFQLLF  4200
4201  TILGGIFQILWSTVFGGGLVEGAKNIRVTKILGDMPDPTQFGIHDDTMEA  4250
4251  ERAEVMEPGITTELVHFIKGEKGDTDIMSDLFGLHPKKEGSLKHGPEVGL  4300
4301  GDLSEIIGKDEPPTLESTVQKKRKAQAAEMKAANEAEGKVESEKADMEDG  4350
4351  EKEDKDKEEEQAEYLWTEVTKKKKRRCGQKVEKPEAFTANFFKGLEIYQT  4400
4401  KLLHYLARNFYNLRFLALFVAFAINFILLFYKVTEEPLEEETEDVANLWN  4450
4451  SFNDEEEEEAMVFFVLQESTGYMAPTLRALAIIHTIISLVCVVGYYCLKV  4500
4501  PLVVFKREKEIARKLEFDGLYITEQPSEDDIKGQWDRLVINTPSFPNNYW  4550
4551  DKFVKRKVINKYGDLYGAERIAELLGLDKNALDFSPVEETKAEAASLVSW  4600
4601  LSSIDMKYHIWKLGVVFTDNSFLYLAWYTTMSVLGHYNNFFFAAHLLDIA  4650
4651  MGFKTLRTILSSVTHNGKQLVLTVGLLAVVVYLYTVVAFNFFRKFYNKSE  4700
4701  DDDEPDMKCDDMMTCYLFHMYVGVRAGGGIGDEIEDPAGDPYEMYRIVFD  4750
4751  ITFFFFVIVILLAIIQGLIIDAFGELRDQQEQVREDMETKCFICGIGNDY  4800
4801  FDTTPHGFETHTLQEHNLANYLFFLMYLINKDETEHTGQESYVWKMYQER  4850
4851  CWDFFPAGDCFRKQYEDQLG                                4870

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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