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

NucPred

Fetching Q8BYH8 from www.uniprot.org...

The NucPred score for your sequence is 1.00 (see score help below)

   1  MTDPMMDFFDDANLFGETLEGLSDDTFVQPGPVSLVDELNLGAEFEPLHI    50
  51  DSLNHVQGTPTHQKMADFEQLSQFDSMKFHPVNQSFGSPVEHVLSPHSQF   100
 101  NCSPIHPPNQPNGLFQDVADGSPMWGHQTATGLANQNGSPFHQPGHSHSL   150
 151  HQNKSFVAHPDFALFQASEHQTQCSSLHSQQSRSNLNPGQNSLGQAKNFL   200
 201  DANVSGAHRVNVNHLATAPSSQQTLPVQFSPTANPPAHFLKCSSHQEGNY   250
 251  NRPSPSMTSCSVSNSQQFPSHYSFSSGHVSPSSLLQSSAGLAPGHTNQAL   300
 301  SDFAGSNSFSPHRGMKQEPTQHLLNPTPSLNSNNFQILHSSHPQGNYSNS   350
 351  KLSPVHMNFPDPVDAGPPVGHFNDHAETNGFSSLEENLLHHVDSHAEPFA   400
 401  GLDPEDLLQEGLLPQFDESPFGQDNSNHVLDHDLDRQFTSHLVSRPSDMA   450
 451  QTQLQYQARGWPSPLSTNHQHLHSRNHLCLQRQPPSSKKSDGSGTYTKLQ   500
 501  NTQVRVMSEKKPRKRVESESKQEKANRIISEAIARAKERGERNIPRVMSP   550
 551  ENFPSASVEGKEEKRGRRMKSKPKDRDNKKPKTYSKLKEKTKIGKLIITL   600
 601  GKKHKRRNESSDELSDAEQRSQHTFKEQHSQKRRSNRQIKRKKYAEDAEG   650
 651  KQSEEEVKGSLRVKRNSAPPPGEQPLQLFVENPSEEDAAIVDKILACRTV   700
 701  KKEVSPGVMLDIEEFFVKYKNYSYLHCEWATEQQLLKDKRIQQKIKRFKL   750
 751  RQAQRAHFLADMEEEPFNPDYVEVDRILEVSFCEDKDTGESVIYYLVKWC   800
 801  SLPYEDSTWELKEDVDLAKIEEFEQLQASRPDTRHLDRPPSNIWKKIEQS   850
 851  REYKNGNQLREYQLEGLNWLLFNWYNRRNCILADEMGLGKTIQSITFLYE   900
 901  ILLTGIRGPFLIIAPLSTIANWEREFRTWTDINVVVYHGSLISRQMIQQY   950
 951  EMYFRDSQGRIIRGAYRFQAIITTFEMILGGCGELNAIDWRCVIIDEAHR  1000
1001  LKNKNCKLLEGLKLMNLEHKVLLTGTPLQNTVEELFSLLHFLEPLRFPSE  1050
1051  STFMQEFGDLKTEEQVQKLQAILKPMMLRRLKEDVEKKLAPKEETIIEVE  1100
1101  LTNIQKKYYRAILEKNFSFLSKGAGQTNVPNLVNTMMELRKCCNHPYLIK  1150
1151  GAEEKILGEFRDTYNPSASDFHLQAMIQSAGKLVLIDKLLPKMKAGGHKV  1200
1201  LIFSQMVRCLDILEDYLIHKRYLYERIDGRVRGNLRQAAIDRFSKPDSDR  1250
1251  FVFLLCTRAGGLGINLTAADTCIIFDSDWNPQNDLQAQARCHRIGQNKAV  1300
1301  KVYRLVTRNSYEREMFDRASLKLGLDKAVLQSMSGRDSNVSGIQQLSKKE  1350
1351  IEDLLRRGAYGAIMEEEDEGSKFCEEDIDQILLRRTKTITIESEGRGSTF  1400
1401  AKASFVASGNRTDISLDDPNFWQKWAKKAELDIDTISGRNSLVIDTPRIR  1450
1451  KQTRPFSATKDELAELSEAESEGEEKPKLRRPCDRSGGYGRTECFRVEKN  1500
1501  LLVYGWGRWREILSHGRFKRQLNEHDVEVICRALLAYCLIHYRGDEKIKG  1550
1551  FIWDLITPTEDGQTRELQNHLGLSAPVPRGRKGKKVKTQTSSFDIQKAEW  1600
1601  LRKYNPEQLLQDEGYKKHVKHHCNKVLLRVRMLYYLKQEVIGNESQKVFD  1650
1651  GVDASDIDVWVPEPDHSEVPAAWWDFDADKSLLIGVFKHGYEKYNTIRAD  1700
1701  PALCFLERVGKPDDKAVAAEQRANDYMDGDVEDPEYKPAPAIFKDDIEDD  1750
1751  VSSPGDLVIADGEGQLMEGDKVYWPTPSALTTRLRRLITAYQRTNKNRHI  1800
1801  QQMQPTFSLPANAMQPLYEEATLNPKMAAKIERQQRWTRREEADFYRVVS  1850
1851  TFGVVFDPDRGQFDWTKFRALARLHKKTDNSLEKYLCAFMSMCRRVCRLP  1900
1901  SKEELVDPNIFIQPITEERASRTLYRIELLRKVREQALRHPQLFERLKLC  1950
1951  HPNPDLPIWWECGSHDRDLLIGAAKHGVSRTDYHILRDPELSFMAAQRNY  2000
2001  NQSKAAHSRTSAPLLQQYQVALSASPLTSLPRLLGAKGTLLEDMKVKSES  2050
2051  LTEEPQSSEEESMSSMETRTRVKSEPVSPKNGVLSQATGDQKSGGKSETD  2100
2101  RRMVAARTEPLTPNPASKKPRVHKRGSQSSSDSDSDSARSSCSSRSSSSS  2150
2151  SSSSSCSHSRSGSSSSSSSSCSSASSSSSSSSSSSSSSSSSSSEESDSEE  2200
2201  DVQKREGTPHRKAYDEESVASLSTTQDETQDSFQANNGTPESAYLLQGGY  2250
2251  MLAASYWPKDRVMINRLDSICQTVLKGKWPSARRHYDANTVASFYTTKLL  2300
2301  DSPGAATERGEPSVPTPPAVAVREEHEQSAQMSKVKKHVREKEFTVKIKD  2350
2351  EGGLKLTFQKQGLAQKRPFDGEDGALGQQQYLTRLRELQSTSETSLVNLP  2400
2401  KAVPASGTSIQPTLGANGAILDSQPIVKKRRGRRRNVEGADILFLNRNKP  2450
2451  PNHIPTGMNPALSYPQPQRIPDTESPVPVINLKDGTRLAGDDAPKRKDLD  2500
2501  RWLKEHPGYVEDLGAFIPRVQLHEGRPKQKRHRCRNPNKLDINSLTGEER  2550
2551  VQLINRRNARKVGGAFAPPLKDLCRFLKENSEYGVAPEWGDVVKQSGFLP  2600
2601  ESMFERILTGPVVREEVSRRGRRPKSGIAKATTAAAVPAGSVPGNPLLAN  2650
2651  GLLPGVDLTALQALQQNLQNLQSLQVTAGLMGMPAGLSSGGETKNMAAMF  2700
2701  PMLFSGMAGLPNLLGMGGLLSKTAESGAEEKRGNDSKELEGKKERTESQS  2750
2751  PENGGERCVPGSPSTSSTAALSSAAAAKPIALNPLLLSNILYPGMLLTPG  2800
2801  LNLHLPTLSQSNAFDVQKNKSDDLDSSKSVEIKEENSRVRDQEEKGGTEP  2850
2851  SPLNENSTDEGSERASSGSDSSSSSSEDSDSSNED                 2885

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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