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

NucPred

Fetching Q74ZX0 from www.uniprot.org...

The NucPred score for your sequence is 0.79 (see score help below)

   1  MVIFAIFYVGRVLGYIVSKAANLVLWKQYRVTVSIQSLVFSPLAGKVHFK    50
  51  NVSVTSQDQLISVLKGTITWRYWLIGRYRRSGTADGARRCRFALKFEGFE   100
 101  YFVYNRNGVYDRIARELDGEDTSAEPTVSVPSVEEVIAELQDDPLIRRFL   150
 151  PVEFLHNKGAIVLGNKQTHSVAIMNYEKLAGTVSIEVPDDTRAPSSFRTE   200
 201  AKISNCTVAIKPNISYEVDNPVKIYVEPKRTARLWKKYKTLLGTVLEATL   250
 251  HAKRKKEQHQTPKWYDNWRGLSMYDVNLDEELDEEVKFDIEHHEYAKCTT   300
 301  VLKADQMDVTYSYGMPGTARVTDSDNAENPLLERPELDHSVDILVYDANC   350
 351  TYGPWANRQVQQCLRVFSPTVCRNFKLRTPEEIAQQTEPAAFKLSVTIME   400
 401  DSVLRVPMKESSKDAAFLEKYKQTRDETRPFGWIDIRIAKESNITVRMAA   450
 451  YPTENGFENILHANLVDTTISTSVNHDTLLKAKSHDITVDFSYPYGWQDK   500
 501  AEWNFNVCSTQAELFVLRDHVYLISDLVTDFSGGEEVLYEQFRPFDYRFR   550
 551  WDIRGYSAYLNVNDANIINNPIDFGENCYLSVHGDDAEITFSLPITSIIQ   600
 601  KYVTVDFNIFTPHFSLFLNAPPWHTFSELLHYKEIGRSKNFNIKGSYTSY   650
 651  SEVDVDNVDALNIACETDYIVVLCYGVILKCMLNVKVNYFGEMVHFRTTE   700
 701  EYVEELQRRNKQNPSTCRPFNSDGNVHDSDVVATESNEIIDASFDAFGGP   750
 751  PTIKKSALKRSINELDVWFTFISKGGCFFFPENIYKFDACLGFYFDNLEA   800
 801  SLRFLNYYVDAAVSLDSIYFKRHTDIDARTLFKVIEDIGIPIDASDAYLS   850
 851  QFSFRLHKMLGIMPSEESYACEFDVRVDTLDVHCDLAVLKAFVNTLRNLA   900
 901  FGFKDVENSLQYEREQVFDLNKISCVIENVTVKLQNVDKDEDIWLSLNLP   950
 951  VTTLTSFDLANERYSRRSDLSIPELLFGIYRGDSESTCLGAFSTGVTVTL  1000
1001  FERFEQFARCRVLQRKHILVNDAPFHRCSFMLPPEYKKMPIYRSLYGCIP  1050
1051  PSSSLPLFPEPISADNFEVIFEKLLGEIYQEYASDSSYQITDDSISSTEH  1100
1101  DYHNQTVNAAIGTSSSLFIRSQNHQQTLSSFIVEFDPIDGYLDLSATEFM  1150
1151  LEIYKYLTEVSLDEAIDSLEIGIINQFIQTFGEDNGISEVRVLCPNISLS  1200
1201  ATNKQSKFSMFKLSSKIKNLDITSRIKSSDPNLKPDPEKTTLCYKIDYIR  1250
1251  ANIVQDGIVVPPKQPSQLFSCSIELLEGYLSYDKLSLLDNNVQSCSVTLS  1300
1301  PGTDKLLFEFLNPFISTFDLLQRELSSFEDTLLASKREFLLNILRGGRDY  1350
1351  EIQHDPPVITKPANITRFSNRHIRSAESWRIIMRLRHILNYLPQEWHQSF  1400
1401  TRHLGTQDFTSPEEAGKEFLSIFSDWRSWEPTDVQGSFVHEKVFTKKRSR  1450
1451  PFAALQGFTFSSDDIRLNMKDDARVPITVKGVTLGIRNNGLAPEQVDGRT  1500
1501  EGSMPDPDYISFCTTDEVVMRVDRSFVKTLKEFRDLIHRFKIGGPVGTAK  1550
1551  HDNVSLFSNITFQFGKLYVVAKLAGVYLRICLDNLSALMLTSQSSVESKV  1600
1601  ISSSTLSFDHMQAILGYRSFRFMTIDIDMFSVLLHYLPGQGCYSIDWKAR  1650
1651  KFHIDSSSATTKDLTESLPYVRDEIKYLVEALVPELFAEPPIERESSGNK  1700
1701  IHAVLFQGQVANITLKLQILSPFIILYCAENFELQAESTDSVIFDLNSGE  1750
1751  SYMEISSAKQKLDYFKYTHTCLKLSGTSSSARLFEHISCDIGILKLSVFD  1800
1801  LKTRITDLLQDIKAALFSMKSLSDILNISQSSPTASAFGSWFSILPDNLS  1850
1851  LQATYAGLLLGFGHTLYILEFNNFEAKHTRDGLPDAITPRPCFKVDHSIE  1900
1901  SASFLIKDRRIDDRLAKVVDFAVNFNMVHDTDLCIQSVQIESTHLKITLA  1950
1951  PMTVVRLLSLINEFGIIRKQFTEESIYTPSSAHNNSTATECLEPSVWRLI  2000
2001  IKSGHILSHDFSIVWLFDIPNSSADGLICGYDRLFSVYEKPYGKLTLLNA  2050
2051  YFSAAKILASEADFYSSVVRKQRINTSYLSDMQLRYWFTEDSENTDLFIR  2100
2101  IHGAKLAVDISAEIVTLLEETIQSIQTFNNLKKALVDPFRTKKQDSDISK  2150
2151  EPYNWNNQLATGVRSLNCIINYAGVTLKLHSHDGRGDASPLELTSPSYKV  2200
2201  AIDYKYFPNLEKTHRFRTLITATPTHNTFYSTSAFLIHDLCYRFSKLLKT  2250
2251  SSTENKSSSASTSSSIKVEGSDNSTLLGSIDLVIILNVGKQEVTFSCEPK  2300
2301  AKVQATVGFEKFDIKIFNNNINDEESLCLAIEIENLMTNSRHIYSREVCA  2350
2351  SLKLRHISMVFDIMGSQVRRIYGSTLISSPLFYFNMKQLQDLKLFIDQWF  2400
2401  PQKTPMNTGSYPEGVLVDDISRSIGSKFYKGSSSSSFTWGYSVIVAGSCA  2450
2451  EIELGPSLGVLNVTSEDVWAISKQQVDWSQQLDLNMGKLDVTSSGRLGGN  2500
2501  FLVRNAHLSLELKWPNPKDFFQVPLVCVKLGSDTVDTKLSFDYHTFFISS  2550
2551  LKQGYASLFNERDEDGSLADLLSVTVSFESVNIFLTALAAANISDIKNSI  2600
2601  TRLKKDNELSYLSSFLASDQPSDEPEEDGGIFDTLSLLRTQLSLNLGVFR  2650
2651  LQISPTSLFDSDVLILTATKMMANTGIQADIKIKTDLHWQLDDVSLALLP  2700
2701  FNNSLDESYLATMEVGKYIELSSTIQGGAIFSAPSIVVNMTTWQEPQSNV  2750
2751  IELLYSTSFGGTVKIRWNLGPISFIKDMWQAHMNAMQLREGYYHGLAESG  2800
2801  VAVTPLNSKAVPLEMHLGSDYQYLPLQEPDIEMPRIKDLGDATPPIEWFG  2850
2851  VNRTKFPGFTHQFVIVPLQKLARTAEKEYEKILGRAL               2887

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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