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

NucPred

Fetching P35169 from www.uniprot.org...

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

   1  MEPHEEQIWKSKLLKAANNDMDMDRNVPLAPNLNVNMNMKMNASRNGDEF    50
  51  GLTSSRFDGVVIGSNGDVNFKPILEKIFRELTSDYKEERKLASISLFDLL   100
 101  VSLEHELSIEEFQAVSNDINNKILELVHTKKTSTRVGAVLSIDTLISFYA   150
 151  YTERLPNETSRLAGYLRGLIPSNDVEVMRLAAKTLGKLAVPGGTYTSDFV   200
 201  EFEIKSCLEWLTASTEKNSFSSSKPDHAKHAALLIITALAENCPYLLYQY   250
 251  LNSILDNIWRALRDPHLVIRIDASITLAKCLSTLRNRDPQLTSQWVQRLA   300
 301  TSCEYGFQVNTLECIHASLLVYKEILFLKDPFLNQVFDQMCLNCIAYENH   350
 351  KAKMIREKIYQIVPLLASFNPQLFAGKYLHQIMDNYLEILTNAPANKIPH   400
 401  LKDDKPQILISIGDIAYEVGPDIAPYVKQILDYIEHDLQTKFKFRKKFEN   450
 451  EIFYCIGRLAVPLGPVLGKLLNRNILDLMFKCPLSDYMQETFQILTERIP   500
 501  SLGPKINDELLNLVCSTLSGTPFIQPGSPMEIPSFSRERAREWRNKNILQ   550
 551  KTGESNDDNNDIKIIIQAFRMLKNIKSRFSLVEFVRIVALSYIEHTDPRV   600
 601  RKLAALTSCEIYVKDNICKQTSLHSLNTVSEVLSKLLAITIADPLQDIRL   650
 651  EVLKNLNPCFDPQLAQPDNLRLLFTALHDESFNIQSVAMELVGRLSSVNP   700
 701  AYVIPSIRKILLELLTKLKFSTSSREKEETASLLCTLIRSSKDVAKPYIE   750
 751  PLLNVLLPKFQDTSSTVASTALRTIGELSVVGGEDMKIYLKDLFPLIIKT   800
 801  FQDQSNSFKREAALKALGQLAASSGYVIDPLLDYPELLGILVNILKTENS   850
 851  QNIRRQTVTLIGILGAIDPYRQKEREVTSTTDISTEQNAPPIDIALLMQG   900
 901  MSPSNDEYYTTVVIHCLLKILKDPSLSSYHTAVIQAIMHIFQTLGLKCVS   950
 951  FLDQIIPTILDVMRTCSQSLLEFYFQQLCSLIIIVRQHIRPHVDSIFQAI  1000
1001  KDFSSVAKLQITLVSVIEAISKALEGEFKRLVPLTLTLFLVILENDKSSD  1050
1051  KVLSRRVLRLLESFGPNLEGYSHLITPKIVQMAEFTSGNLQRSAIITIGK  1100
1101  LAKDVDLFEMSSRIVHSLLRVLSSTTSDELSKVIMNTLSLLLIQMGTSFA  1150
1151  IFIPVINEVLMKKHIQHTIYDDLTNRILNNDVLPTKILEANTTDYKPAEQ  1200
1201  MEAADAGVAKLPINQSVLKSAWNSSQQRTKEDWQEWSKRLSIQLLKESPS  1250
1251  HALRACSNLASMYYPLAKELFNTAFACVWTELYSQYQEDLIGSLCIALSS  1300
1301  PLNPPEIHQTLLNLVEFMEHDDKALPIPTQSLGEYAERCHAYAKALHYKE  1350
1351  IKFIKEPENSTIESLISINNQLNQTDAAIGILKHAQQHHSLQLKETWFEK  1400
1401  LERWEDALHAYNEREKAGDTSVSVTLGKMRSLHALGEWEQLSQLAARKWK  1450
1451  VSKLQTKKLIAPLAAGAAWGLGEWDMLEQYISVMKPKSPDKEFFDAILYL  1500
1501  HKNDYDNASKHILNARDLLVTEISALINESYNRAYSVIVRTQIITEFEEI  1550
1551  IKYKQLPPNSEKKLHYQNLWTKRLLGCQKNVDLWQRVLRVRSLVIKPKQD  1600
1601  LQIWIKFANLCRKSGRMRLANKALNMLLEGGNDPSLPNTFKAPPPVVYAQ  1650
1651  LKYIWATGAYKEALNHLIGFTSRLAHDLGLDPNNMIAQSVKLSSASTAPY  1700
1701  VEEYTKLLARCFLKQGEWRIATQPNWRNTNPDAILGSYLLATHFDKNWYK  1750
1751  AWHNWALANFEVISMVQEETKLNGGKNDDDDDTAVNNDNVRIDGSILGSG  1800
1801  SLTINGNRYPLELIQRHVVPAIKGFFHSISLLETSCLQDTLRLLTLLFNF  1850
1851  GGIKEVSQAMYEGFNLMKIENWLEVLPQLISRIHQPDPTVSNSLLSLLSD  1900
1901  LGKAHPQALVYPLTVAIKSESVSRQKAALSIIEKIRIHSPVLVNQAELVS  1950
1951  HELIRVAVLWHELWYEGLEDASRQFFVEHNIEKMFSTLEPLHKHLGNEPQ  2000
2001  TLSEVSFQKSFGRDLNDAYEWLNNYKKSKDINNLNQAWDIYYNVFRKITR  2050
2051  QIPQLQTLDLQHVSPQLLATHDLELAVPGTYFPGKPTIRIAKFEPLFSVI  2100
2101  SSKQRPRKFSIKGSDGKDYKYVLKGHEDIRQDSLVMQLFGLVNTLLKNDS  2150
2151  ECFKRHLDIQQYPAIPLSPKSGLLGWVPNSDTFHVLIREHRDAKKIPLNI  2200
2201  EHWVMLQMAPDYENLTLLQKIEVFTYALDNTKGQDLYKILWLKSRSSETW  2250
2251  LERRTTYTRSLAVMSMTGYILGLGDRHPSNLMLDRITGKVIHIDFGDCFE  2300
2301  AAILREKYPEKVPFRLTRMLTYAMEVSGIEGSFRITCENVMRVLRDNKES  2350
2351  LMAILEAFALDPLIHWGFDLPPQKLTEQTGIPLPLINPSELLRKGAITVE  2400
2401  EAANMEAEQQNETKNARAMLVLRRITDKLTGNDIKRFNELDVPEQVDKLI  2450
2451  QQATSIERLCQHYIGWCPFW                                2470

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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