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

NucPred

Fetching Q4IB89 from www.uniprot.org...

The NucPred score for your sequence is 0.91 (see score help below)

   1  MASHNVMNLARDVKSAAVRDREKAVDELSHLLNPRNRSTNLSDLGDKSYH    50
  51  EIFEAIFSFVLREKPVLSDRKKSQATLNSTATRLSKCAEAVRMTVGRGNS   100
 101  KIGRKTLLAIVDHITQVLPGPNGDDFVTPLLQDYIKALTEVLSRPAHVEI   150
 151  LARKGGQHWETCVGFFLDVAQYLLPDEADISTLSLARASPALTRSSPAPG   200
 201  SGYSRSGGRSTPSTQSQRRAAPGEGGLLKDVLEGLHYIVIGGNAPILRQY   250
 251  KDITLVVLRVLSLKQLSLGSLQTLAFAIINTVFTTTNADDLAHASSVVQS   300
 301  ILPLMSYWWRCEKVSQDEVIRALRIEISRSIFLMHLHIENLVINSSDEKI   350
 351  RSDLEELTENIWSEYSRRSEAFRLQMSDITFALSSLPTYGLQLNMFGLRA   400
 401  HNVYGEGHWAVIQNLAFLEGIMLLPQSRTPADDAEQSEQRRKRRRIEQDM   450
 451  SRIRLKLKTVEVGVRGTALQLIPFLLADNSLSRDELVDLLPELALLATDK   500
 501  NPVTASWALIASASCISKPEVCHDQIDVWRQLWHFATRSVSLPGTSRAAS   550
 551  VLLHAILEADVLPYHTISQDINNMVTTADVNGPSVLCDTSISLMFHVLQL   600
 601  RNARVPSASQSTCHHIIRWVFLRWNPNESTFASYHSMHAQPIQLVNLIRA   650
 651  CCGTTALELNSHQAAPGGPLTETWSSFKQTEKFTRYVLLAKDEFHDADPI   700
 701  GCCDLSEQSDPASLVDANSRYASRKLTLELFYPKLSELSDLCTSWNKKPN   750
 751  EGGIQISFDRFQSLLSACLAGTLLLPIFGDLNSTQSSSVDSTLKYILDKA   800
 801  LNSALTSVEPTAFVDSVLRVVRAVMPDMITSSLNRIQANNPDLFHLFGRI   850
 851  WKSIGQQKDQTDPDNNIDLMDIDEDFDSQSSRASSVHAPVAAPRFNIQMK   900
 901  LDMQTFYIETKARLRFLSILDSDFGQIGLVPDTYVDHLIKMPDEDLLMCQ   950
 951  SLLLELFGSDLVITPENALSIIERLGDCISLSEYQCAEVALSTCIGVIDG  1000
1001  LHSIWLNDKQHLSERVGDLYYHFIKVCLTSNIFSPGVQMSMVQLLFTLLR  1050
1051  TNTEYGKDQGLDSPRTCLLYILKNGPMSVKYTISQKIADIFDLFVLKLHD  1100
1101  EVFVDVLDSLPTDPLDTTGIAFRLLVLSNLACRWSTLLRRCTYHIFETPG  1150
1151  KIPRSTDYATRCLVNVSRTLNLESPKALFRLFSRQLLYTWLEYDHIEDIP  1200
1201  FSIFGFKTLGDLLKSAQSEAIGLTVMRGQDQTFAEVCHLLGSSESDLVRE  1250
1251  NFTTAVAYSMIFGDSNGGDDKERGEAHVKRLLGRAAYMELIYINFVDIAA  1300
1301  LFFDLIDQENSFERVFARFKLDYAGQILSAVKAISHSPAELPANQQPMFK  1350
1351  AKYLINELHRLCQNTEFQFHDLWTPPVVVSIARKLLNTVHPALGPLHACS  1400
1401  VLRKVRVLISLGGSVALESYPLEMLLNATRTFITDSECADDALGISQYLL  1450
1451  AEGARHLSNVPSFLAGYALSTLASLRVFLESSQSSTTQESQFKATMSKAE  1500
1501  KFHVWISKYLEEYESPMFKNLEQRSAFKSITRSAARIRSSGNAERGTAES  1550
1551  KLLLDILADQAADHQLLNEPSRQLALGLLCGDFSIPETIKDDVIESDEDA  1600
1601  LKYSTAVWKSCDTENLSEEYLSWAGRVVGRAFSASGEIPTGVLRESNLSQ  1650
1651  YQKMAPGSNGSETGILYLLQDLTSNPDSITAGLAEAALRSIVSDANNLDD  1700
1701  ELLAVACQKSLTESLLVTSQWGTHRSPPSDKGLITPTSSPNQLDVWSTDI  1750
1751  TSKDWLLNLSAHLARYVPESIVLSVLAPILARVEHFAERAFPFVVHLALF  1800
1801  FTRNQQHSPKRQLSVAIKSWLECTVTEAKENQKLLINMLLYLRTQQYPKE  1850
1851  SSIADRSHWLEVDSALVAAAASRCGMYKTSLLFVEYVPPETSRSSRTSSA  1900
1901  ATKEVDMSETLLAIFENIDDPDAYYGLPEEPSLSKILARVEYENDGPMSL  1950
1951  AFRGAEYDSNVHLGNPMAQSDGQALVRAFSTLGLSGPSNWFLQTQDNMET  2000
2001  SPPVLEDTFNTARKLGIWNLPAPPSDHHAVTVFKAYQSIHQATDIANVRA  2050
2051  AVHDGFGRTMSSLVVHSLNATALRKRLGALASLTELDDVLGVSDSSEMNL  2100
2101  LIEKFKNRSGWMRSGLYESVGQILSCRSTTMSMVSQQETLRTNIKLSAAT  2150
2151  ARQMEVESMITASQIYRYHQATQESLKISTILTKLIPSCTALDLHVDAAV  2200
2201  TIEAANSAWDYGQMSTSIRMLQDIDKDSVLEKQTLPVSRSDLLSKIGYQV  2250
2251  SVARLEKPHDIQKNYLEPALKELKGKGQGRQAGSVFHQFAMFCDQQLQDP  2300
2301  DGLEDLARLQSLKKAKSDEVSELKTLISGTRDTQLKTRYSHVLNKEKQWL  2350
2351  NLDEQELRRVEQTRSEFVRLSLENYLLSLIASDEHNNDALRFTALWLERS  2400
2401  EEESTNQAVMRHLSEVPTRKFAGLTNQLTSRLQDNNTTFQKLLLELVYKI  2450
2451  CVDHPYHGMYQIWSGTKAKAQQKDDVAVLRVRATDRVAKSLAETQSVANI  2500
2501  WLSIDKTSKYYHALAMDRNPNKYKSGVKIPLRDSTPGHNLVNCLAKYRIP  2550
2551  SPTMHIELSATKDYSKVPIISKLEPTMTIASGVSAPKIITAVGSDGVRYK  2600
2601  QLVKGGHDDLRQDAIMEQVFSAVSSLLKLHRITQQRNLSIRTYKVLPLTA  2650
2651  SSGLIEFVPNTIPLHEFLMPAHERYYPKDLKGSQCRKEIFGVQGRAVATR  2700
2701  ISTYRRMTEKFHPVMRYFFMENFMDPDEWFLKRLAYTRSTAAISMLGHVL  2750
2751  GLGDRHGHNILLDHKTGEVVHIDLGVAFEAGRILPVPEMVPFRLTRDIVD  2800
2801  GMGITKTEGVFRRCCEFTLDALREEQYSIMTILDVLRFDPLYTWSISPLR  2850
2851  LAKLQKARHNDDSPMDDEQSEAETKKGKKAAGHVNEPSEADRALEVVRKK  2900
2901  LSKTLSVTATVNDLINQATDERNLAVLYSGWAAYA                 2935

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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