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

NucPred

Fetching Q9Z0R6 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MMAQFPTAMNGGPNMWAITSEERTKHDKQFDNLKPSGGYITGDQARTFFL    50
  51  QSGLPAPVLAEIWALSDLNKDGKMDQQEFSIAMKLIKLKLQGQQLPVVLP   100
 101  PIMKQPPMFSPLISARFGMGSMPNLSIHQPLPPVAPIATPLSSATSGTSI   150
 151  PPLMMPAPLVPSVSTSSLPNGTASLIQPLSIPYSSSTLPHASSYSLMMGG   200
 201  FGGASIQKAQSLIDLGSSSSTSSTASLSGNSPKTGTSEWAVPQPSRLKYR   250
 251  QKFNSLDKGMSGYLSGFQARNALLQSNLSQTQLATIWTLADIDGDGQLKA   300
 301  EEFILAMHLTDMAKAGQPLPLTLPPELVPPSFRGGKQVDSVNGTLPSYQK   350
 351  TQEEEPQKKLPVTFEDKRKANYERGNMELEKRRQVLMEQQQREAERKAQK   400
 401  EKEEWERKQRELQEQEWKKQLELEKRLEKQRELERQREEERRKEIERREA   450
 451  AKQELERQRRLEWERLRRQELLSQKTREQEDIVRLSSRKKSLHLELEAVN   500
 501  GKHQQISGRLQDVQIRKQTQKTELEVLDKQCDLEIMEIKQLQQELKEYQN   550
 551  KLIYLVPEKQLLNERIKNMQLSNTPDSGISLLHKKSSEKEELCQRLKEQL   600
 601  DALEKETASKLSEMDSFNNQLKELRESYNTQQLALEQLHKIKRDKLKEIE   650
 651  RKRLEQIQKKKLEDEAARKAKQGKENLWRESIRKEEEEKQKRLQEEKSQD   700
 701  KTQEEERKAEAKQSETASALVNYRALYPFEARNHDEMSFSSGDIIQVDEK   750
 751  TVGEPGWLYGSFQGKFGWFPCNYVEKVLSSEKALSPKKALLPPTVSLSAT   800
 801  STSSQPPASVTDYHNVSFSNLTVNTTWQQKSAFTRTVSPGSVSPIHGQGQ   850
 851  AVENLKAQALCSWTAKKENHLNFSKHDVITVLEQQENWWFGEVHGGRGWF   900
 901  PKSYVKLIPGNEVQRGEPEALYAAVTKKPTSTAYPVTSTAYPVGEDYIAL   950
 951  YSYSSVEPGDLTFTEGEEILVTQKDGEWWTGSIGERTGIFPSNYVRPKDQ  1000
1001  ENFGNASKSGASNKKPEIAQVTSAYAASGTEQLSLAPGQLILILKKNTSG  1050
1051  WWQGELQARGKKRQKGWFPASHVKLLGPSSERTMPTFHAVCQVIAMYDYM  1100
1101  ANNEDELNFSKGQLINVMNKDDPDWWQGETNGLTGLFPSNYVKMTTDSDP  1150
1151  SQQWCADLQALDTMQPTERKRQGYIHELIQTEERYMDDDLQLVIEVFQKR  1200
1201  MAEEGFLTEADMALIFVNWKELIMSNTKLLRALRVRKKTGGEKMPVQMIG  1250
1251  DILAAELSHMQAYIRFCSCQLNGATLLQQKTDEDTDFKEFLKKLASDPRC  1300
1301  KGMPLSSFLLKPMQRITRYPLLIRSILENTPQSHVDHSSLKLALERAEEL  1350
1351  CSQVNEGVREKENSDRLEWIQAHVQCEGLAEQLIFNSLTNCLGPRKLLHS  1400
1401  GKLYKTKSNKELHAFLFNDFLLLTYLVRQFAAASGHEKLFNSKSSAQFRM  1450
1451  YKTPIFLNEVLVKLPTDPSGDEPVFHISHIDRVYTLRTDNINERTAWVQK  1500
1501  IKGASEQYIDTEKKKREKAYQARSQKTSGIGRLMVHVIEATELKACKPNG  1550
1551  KSNPYCEVSMGSQSYTTRTLQDTLNPKWNFNCQFFIKDLYQDVLCLTMFD  1600
1601  RDQFSPDDFLGRTEVPVAKIRTEQESKGPTTRRLLLHEVPTGEVWVRFDL  1650
1651  QLFEQKTLL                                           1659

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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