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

NucPred

Fetching O43432 from www.uniprot.org...

The NucPred score for your sequence is 0.92 (see score help below)

   1  MNSQPQTRSPFFQRPQIQPPRATIPNSSPSIRPGAQTPTAVYQANQHIMM    50
  51  VNHLPMPYPVPQGPQYCIPQYRHSGPPYVGPPQQYPVQPPGPGPFYPGPG   100
 101  PGDFPNAYGTPFYPSQPVYQSAPIIVPTQQQPPPAKREKKTIRIRDPNQG   150
 151  GKDITEEIMSGGGSRNPTPPIGRPTSTPTPPQQLPSQVPEHSPVVYGTVE   200
 201  SAHLAASTPVTAASDQKQEEKPKPDPVLKSPSPVLRLVLSGEKKEQEGQT   250
 251  SETTAIVSIAELPLPPSPTTVSSVARSTIAAPTSSALSSQPIFTTAIDDR   300
 301  CELSSPREDTIPIPSLTSCTETSDPLPTNENDDDICKKPCSVAPNDIPLV   350
 351  SSTNLINEINGVSEKLSATESIVEIVKQEVLPLTLELEILENPPEEMKLE   400
 401  CIPAPITPSTVPSFPPTPPTPPASPPHTPVIVPAAATTVSSPSAAITVQR   450
 451  VLEEDESIRTCLSEDAKEIQNKIEVEADGQTEEILDSQNLNSRRSPVPAQ   500
 501  IAITVPKTWKKPKDRTRTTEEMLEAELELKAEEELSIDKVLESEQDKMSQ   550
 551  GFHPERDPSDLKKVKAVEENGEEAEPVRNGAESVSEGEGIDANSGSTDSS   600
 601  GDGVTFPFKPESWKPTDTEGKKQYDREFLLDFQFMPACIQKPEGLPPISD   650
 651  VVLDKINQPKLPMRTLDPRILPRGPDFTPAFADFGRQTPGGRGVPLLNVG   700
 701  SRRSQPGQRREPRKIITVSVKEDVHLKKAENAWKPSQKRDSQADDPENIK   750
 751  TQELFRKVRSILNKLTPQMFNQLMKQVSGLTVDTEERLKGVIDLVFEKAI   800
 801  DEPSFSVAYANMCRCLVTLKVPMADKPGNTVNFRKLLLNRCQKEFEKDKA   850
 851  DDDVFEKKQKELEAASAPEERTRLHDELEEAKDKARRRSIGNIKFIGELF   900
 901  KLKMLTEAIMHDCVVKLLKNHDEESLECLCRLLTTIGKDLDFEKAKPRMD   950
 951  QYFNQMEKIVKERKTSSRIRFMLQDVIDLRLCNWVSRRADQGPKTIEQIH  1000
1001  KEAKIEEQEEQRKVQQLMTKEKRRPGVQRVDEGGWNTVQGAKNSRVLDPS  1050
1051  KFLKITKPTIDEKIQLVPKAQLGSWGKGSSGGAKASETDALRSSASSLNR  1100
1101  FSALQPPAPSGSTPSTPVEFDSRRTLTSRGSMGREKNDKPLPSATARPNT  1150
1151  FMRGGSSKDLLDNQSQEEQRREMLETVKQLTGGVDVERNSTEAERNKTRE  1200
1201  SAKPEISAMSAHDKAALSEEELERKSKSIIDEFLHINDFKEAMQCVEELN  1250
1251  AQGLLHVFVRVGVESTLERSQITRDHMGQLLYQLVQSEKLSKQDFFKGFS  1300
1301  ETLELADDMAIDIPHIWLYLAELVTPMLKEGGISMRELTIEFSKPLLPVG  1350
1351  RAGVLLSEILHLLCKQMSHKKVGALWREADLSWKDFLPEGEDVHNFLLEQ  1400
1401  KLDFIESDSPCSSEALSKKELSAEELYKRLEKLIIEDKANDEQIFDWVEA  1450
1451  NLDEIQMSSPTFLRALMTAVCKAAIIADSSTFRVDTAVIKQRVPILLKYL  1500
1501  DSDTEKELQALYALQASIVKLDQPANLLRMFFDCLYDEEVISEDAFYKWE  1550
1551  SSKDPAEQNGKGVALKSVTAFFTWLREAEEESEDN                 1585

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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