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

NucPred

Fetching Q9NR09 from www.uniprot.org...

The NucPred score for your sequence is 0.74 (see score help below)

   1  MVTGGGAAPPGTVTEPLPSVIVLSAGRKMAAAAAAASGPGCSSAAGAGAA    50
  51  GVSEWLVLRDGCMHCDADGLHSLSYHPALNAILAVTSRGTIKVIDGTSGA   100
 101  TLQASALSAKPGGQVKCQYISAVDKVIFVDDYAVGCRKDLNGILLLDTAL   150
 151  QTPVSKQDDVVQLELPVTEAQQLLSACLEKVDISSTEGYDLFITQLKDGL   200
 201  KNTSHETAANHKVAKWATVTFHLPHHVLKSIASAIVNELKKINQNVAALP   250
 251  VASSVMDRLSYLLPSARPELGVGPGRSVDRSLMYSEANRRETFTSWPHVG   300
 301  YRWAQPDPMAQAGFYHQPASSGDDRAMCFTCSVCLVCWEPTDEPWSEHER   350
 351  HSPNCPFVKGEHTQNVPLSVTLATSPAQFPCTDGTDRISCFGSGSCPHFL   400
 401  AAATKRGKICIWDVSKLMKVHLKFEINAYDPAIVQQLILSGDPSSGVDSR   450
 451  RPTLAWLEDSSSCSDIPKLEGDSDDLLEDSDSEEHSRSDSVTGHTSQKEA   500
 501  MEVSLDITALSILQQPEKLQWEIVANVLEDTVKDLEELGANPCLTNSKSE   550
 551  KTKEKHQEQHNIPFPCLLAGGLLTYKSPATSPISSNSHRSLDGLSRTQGE   600
 601  SISEQGSTDNESCTNSELNSPLVRRTLPVLLLYSIKESDEKAGKIFSQMN   650
 651  NIMSKSLHDDGFTVPQIIEMELDSQEQLLLQDPPVTYIQQFADAAANLTS   700
 701  PDSEKWNSVFPKPGTLVQCLRLPKFAEEENLCIDSITPCADGIHLLVGLR   750
 751  TCPVESLSAINQVEALNNLNKLNSALCNRRKGELESNLAVVNGANISVIQ   800
 801  HESPADVQTPLIIQPEQRNVSGGYLVLYKMNYATRIVTLEEEPIKIQHIK   850
 851  DPQDTITSLILLPPDILDNREDDCEEPIEDMQLTSKNGFEREKTSDISTL   900
 901  GHLVITTQGGYVKILDLSNFEILAKVEPPKKEGTEEQDTFVSVIYCSGTD   950
 951  RLCACTKGGELHFLQIGGTCDDIDEADILVDGSLSKGIEPSSEGSKPLSN  1000
1001  PSSPGISGVDLLVDQPFTLEILTSLVELTRFETLTPRFSATVPPCWVEVQ  1050
1051  QEQQQRRHPQHLHQQHHGDAAQHTRTWKLQTDSNSWDEHVFELVLPKACM  1100
1101  VGHVDFKFVLNSNITNIPQIQVTLLKNKAPGLGKVNALNIEVEQNGKPSL  1150
1151  VDLNEEMQHMDVEESQCLRLCPFLEDHKEDILCGPVWLASGLDLSGHAGM  1200
1201  LTLTSPKLVKGMAGGKYRSFLIHVKAVNERGTEEICNGGMRPVVRLPSLK  1250
1251  HQSNKGYSLASLLAKVAAGKEKSSNVKNENTSGTRKSENLRGCDLLQEVS  1300
1301  VTIRRFKKTSISKERVQRCAMLQFSEFHEKLLNTLCRKTDDGQITEHAQS  1350
1351  LVLDTLCWLAGVHSNGPGSSKEGNENLLSKTRKFLSDIVRVCFFEAGRSI  1400
1401  AHKCARFLALCISNGKCDPCQPAFGPVLLKALLDNMSFLPAATTGGSVYW  1450
1451  YFVLLNYVKDEDLAGCSTACASLLTAVSRQLQDRLTPMEALLQTRYGLYS  1500
1501  SPFDPVLFDLEMSGSSCKNVYNSSIGVQSDEIDLSDVLSGNGKVSSCTAA  1550
1551  EGSFTSLTGLLEVEPLHFTCVSTSDGTRIERDDAMSSFGVTPAVGGLSSG  1600
1601  TVGEASTALSSAAQVALQSLSHAMASAEQQLQVLQEKQQQLLKLQQQKAK  1650
1651  LEAKLHQTTAAAAAAASAVGPVHNSVPSNPVAAPGFFIHPSDVIPPTPKT  1700
1701  TPLFMTPPLTPPNEAVSVVINAELAQLFPGSVIDPPAVNLAAHNKNSNKS  1750
1751  RMNPLGSGLALAISHASHFLQPPPHQSIIIERMHSGARRFVTLDFGRPIL  1800
1801  LTDVLIPTCGDLASLSIDIWTLGEEVDGRRLVVATDISTHSLILHDLIPP  1850
1851  PVCRFMKITVIGRYGSTNARAKIPLGFYYGHTYILPWESELKLMHDPLKG  1900
1901  EGESANQPEIDQHLAMMVALQEDIQCRYNLACHRLETLLQSIDLPPLNSA  1950
1951  NNAQYFLRKPDKAVEEDSRVFSAYQDCIQLQLQLNLAHNAVQRLKVALGA  2000
2001  SRKMLSETSNPEDLIQTSSTEQLRTIIRYLLDTLLSLLHASNGHSVPAVL  2050
2051  QSTFHAQACEELFKHLCISGTPKIRLHTGLLLVQLCGGERWWGQFLSNVL  2100
2101  QELYNSEQLLIFPQDRVFMLLSCIGQRSLSNSGVLESLLNLLDNLLSPLQ  2150
2151  PQLPMHRRTEGVLDIPMISWVVMLVSRLLDYVATVEDEAAAAKKPLNGNQ  2200
2201  WSFINNNLHTQSLNRSSKGSSSLDRLYSRKIRKQLVHHKQQLNLLKAKQK  2250
2251  ALVEQMEKEKIQSNKGSSYKLLVEQAKLKQATSKHFKDLIRLRRTAEWSR  2300
2301  SNLDTEVTTAKESPEIEPLPFTLAHERCISVVQKLVLFLLSMDFTCHADL  2350
2351  LLFVCKVLARIANATRPTIHLCEIVNEPQLERLLLLLVGTDFNRGDISWG  2400
2401  GAWAQYSLTCMLQDILAGELLAPVAAEAMEEGTVGDDVGATAGDSDDSLQ  2450
2451  QSSVQLLETIDEPLTHDITGAPPLSSLEKDKEIDLELLQDLMEVDIDPLD  2500
2501  IDLEKDPLAAKVFKPISSTWYDYWGADYGTYNYNPYIGGLGIPVAKPPAN  2550
2551  TEKNGSQTVSVSVSQALDARLEVGLEQQAELMLKMMSTLEADSILQALTN  2600
2601  TSPTLSQSPTGTDDSLLGGLQAANQTSQLIIQLSSVPMLNVCFNKLFSML  2650
2651  QVHHVQLESLLQLWLTLSLNSSSTGNKENGADIFLYNANRIPVISLNQAS  2700
2701  ITSFLTVLAWYPNTLLRTWCLVLHSLTLMTNMQLNSGSSSAIGTQESTAH  2750
2751  LLVSDPNLIHVLVKFLSGTSPHGTNQHSPQVGPTATQAMQEFLTRLQVHL  2800
2801  SSTCPQIFSEFLLKLIHILSTERGAFQTGQGPLDAQVKLLEFTLEQNFEV  2850
2851  VSVSTISAVIESVTFLVHHYITCSDKVMSRSGSDSSVGARACFGGLFANL  2900
2901  IRPGDAKAVCGEMTRDQLMFDLLKLVNILVQLPLSGNREYSARVSVTTNT  2950
2951  TDSVSDEEKVSGGKDGNGSSTSVQGSPAYVADLVLANQQIMSQILSALGL  3000
3001  CNSSAMAMIIGASGLHLTKHENFHGGLDAISVGDGLFTILTTLSKKASTV  3050
3051  HMMLQPILTYMACGYMGRQGSLATCQLSEPLLWFILRVLDTSDALKAFHD  3100
3101  MGGVQLICNNMVTSTRAIVNTARSMVSTIMKFLDSGPNKAVDSTLKTRIL  3150
3151  ASEPDNAEGIHNFAPLGTITSSSPTAQPAEVLLQATPPHRRARSAAWSYI  3200
3201  FLPEEAWCDLTIHLPAAVLLKEIHIQPHLASLATCPSSVSVEVSADGVNM  3250
3251  LPLSTPVVTSGLTYIKIQLVKAEVASAVCLRLHRPRDASTLGLSQIKLLG  3300
3301  LTAFGTTSSATVNNPFLPSEDQVSKTSIGWLRLLHHCLTHISDLEGMMAS  3350
3351  AAAPTANLLQTCAALLMSPYCGMHSPNIEVVLVKIGLQSTRIGLKLIDIL  3400
3401  LRNCAASGSDPTDLNSPLLFGRLNGLSSDSTIDILYQLGTTQDPGTKDRI  3450
3451  QALLKWVSDSARVAAMKRSGRMNYMCPNSSTVEYGLLMPSPSHLHCVAAI  3500
3501  LWHSYELLVEYDLPALLDQELFELLFNWSMSLPCNMVLKKAVDSLLCSMC  3550
3551  HVHPNYFSLLMGWMGITPPPVQCHHRLSMTDDSKKQDLSSSLTDDSKNAQ  3600
3601  APLALTESHLATLASSSQSPEAIKQLLDSGLPSLLVRSLASFCFSHISSS  3650
3651  ESIAQSIDISQDKLRRHHVPQQCNKMPITADLVAPILRFLTEVGNSHIMK  3700
3701  DWLGGSEVNPLWTALLFLLCHSGSTSGSHNLGAQQTSARSASLSSAATTG  3750
3751  LTTQQRTAIENATVAFFLQCISCHPNNQKLMAQVLCELFQTSPQRGNLPT  3800
3801  SGNISGFIRRLFLQLMLEDEKVTMFLQSPCPLYKGRINATSHVIQHPMYG  3850
3851  AGHKFRTLHLPVSTTLSDVLDRVSDTPSITAKLISEQKDDKEKKNHEEKE  3900
3901  KVKAENGFQDNYSVVVASGLKSQSKRAVSATPPRPPSRRGRTIPDKIGST  3950
3951  SGAEAANKIITVPVFHLFHKLLAGQPLPAEMTLAQLLTLLYDRKLPQGYR  4000
4001  SIDLTVKLGSRVITDPSLSKTDSYKRLHPEKDHGDLLASCPEDEALTPGD  4050
4051  ECMDGILDESLLETCPIQSPLQVFAGMGGLALIAERLPMLYPEVIQQVSA  4100
4101  PVVTSTTQEKPKDSDQFEWVTIEQSGELVYEAPETVAAEPPPIKSAVQTM  4150
4151  SPIPAHSLAAFGLFLRLPGYAEVLLKERKHAQCLLRLVLGVTDDGEGSHI  4200
4201  LQSPSANVLPTLPFHVLRSLFSTTPLTTDDGVLLRRMALEIGALHLILVC  4250
4251  LSALSHHSPRVPNSSVNQTEPQVSSSHNPTSTEEQQLYWAKGTGFGTGST  4300
4301  ASGWDVEQALTKQRLEEEHVTCLLQVLASYINPVSSAVNGEAQSSHETRG  4350
4351  QNSNALPSVLLELLSQSCLIPAMSSYLRNDSVLDMARHVPLYRALLELLR  4400
4401  AIASCAAMVPLLLPLSTENGEEEEEQSECQTSVGTLLAKMKTCVDTYTNR  4450
4451  LRSKRENVKTGVKPDASDQEPEGLTLLVPDIQKTAEIVYAATTSLRQANQ  4500
4501  EKKLGEYSKKAAMKPKPLSVLKSLEEKYVAVMKKLQFDTFEMVSEDEDGK  4550
4551  LGFKVNYHYMSQVKNANDANSAARARRLAQEAVTLSTSLPLSSSSSVFVR  4600
4601  CDEERLDIMKVLITGPADTPYANGCFEFDVYFPQDYPSSPPLVNLETTGG  4650
4651  HSVRFNPNLYNDGKVCLSILNTWHGRPEEKWNPQTSSFLQVLVSVQSLIL  4700
4701  VAEPYFNEPGYERSRGTPSGTQSSREYDGNIRQATVKWAMLEQIRNPSPC  4750
4751  FKEVIHKHFYLKRVEIMAQCEEWIADIQQYSSDKRVGRTMSHHAAALKRH  4800
4801  TAQLREELLKLPCPEGLDPDTDDAPEVCRATTGAEETLMHDQVKPSSSKE  4850
4851  LPSDFQL                                             4857

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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