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

NucPred

Fetching Q18823 from www.uniprot.org...

The NucPred score for your sequence is 0.65 (see score help below)

   1  MTSILWLFSLAVLWHMGQPQPAELYPSVDPNHFGADGNPCYDRATRQPQR    50
  51  CVPDFVNAAFNLEVQVTNTCGTKRPTKFCVQSGHTGQRSVCETCDDRHEG   100
 101  FSHPAKYLTDFNVGNNETWWQSDTMQEGQQYPTTTNLTLVLGKSFDITYV   150
 151  RLKFISPRPESFTIYKKTHTDSEWEPWQFYSGSCRATYGLSDRAPILPGN   200
 201  EATAQCTKEFSDISPITGGNIAFSTLEGRPSAHAFEESEVLQKWVTASAI   250
 251  RISLNRMNTFGDEVFKDPQVLRSYYYAISDFAVGGRCKCNGHASECVGSS   300
 301  SVDGENRLVCRCEHNTQGADCNECLPFYNDRPWRSGTSVEANECIACNCS   350
 351  QLSNRCYFDQQLFEETGHGGHCIDCQGNTQGVHCEQCIANHWRRPGENYC   400
 401  VACGCNEIGSLSTQCDNEGKCQCKPGVTGRFCDQCLDGFYDFSTNGCKNC   450
 451  GCETSGSLNNQPRCDSSSGSCSCKLNVEGRQCDKCKPGYFDLSTENQFGC   500
 501  TPCFCFGHSSICNTADGYFAMNVSSVFDQDKQKWAGQNRIGLQDTQWAEL   550
 551  DKAVAVSDTDNSPVYFVAPEQFLGDQRSSYNQDLVFTLKVAKHVTNQDVK   600
 601  DIIIVGADRQELSTSITAQGNPFPTTEAQTYRFRVHADPYFGWYPRINEL   650
 651  DFIGILSNITAIKIRGTYSYKDIGYLSNVNLGTAGVAPSAANPKQATWIE   700
 701  HCECLPGFVGQFCESCESGFRRETKFGGPFNHCIKCDCHNHSNSCEAESG   750
 751  SCICEHNTAGDTCERCARGYYGDALQGTEEDCQKCPCPNDGPCILHADGD   800
 801  VICTECPNGYTGRRCDECSDGYFGNPKDGTECVECACSGNTDPNSIGNCD   850
 851  KITGECKKCIFNTHGFNCENCKPGYWGDALIEPKGNCQSCGCFAAGTRRP   900
 901  NNDYTLLECNQQDGQCDCLPNVIGIQCDQCAHGFYNITSGLGCQECNCDP   950
 951  LGSEGNTCDVNTGQCQCKPGVTGQRCDRCADYHFGFSANGCQPCDCEYIG  1000
1001  SENQQCDVNSGQCLCKENVEGRRCDQCAENRYGITQGCLPCDDCYTLIQS  1050
1051  RVNVFREKVKSLDNTLQEIIENPAPVNDTKFDEKVKETSRAASEVWEAVK  1100
1101  QKTKEGGGTIKTKSKAIKDEIVAALEKLTSIDESVAQAKVGADAAENDMK  1150
1151  RWEIIIENARREIENVLHYLETEGEERAQIAYNASQKYGEQSKRMSELAS  1200
1201  GTREEAEKHLKQASEIEQLSEQAIANATQANKEASDAIYGGEQISKQIAE  1250
1251  LKEKQNQLNESIHRTLDLAEEQKKSADEANNLAAVSLTNVEAVKIPSVDP  1300
1301  KELRNDVAGVLEESENLVDSSVKENSANDELFDEVNRSVADARNELQSSQ  1350
1351  DQQRVSDQLMLELEKSRERIVDSVSTADKTLKDAEAALQVLEEFGAKIEK  1400
1401  SRNDAVAEFAGVEGINQRLDDIIDAQDKRRNSLPIDKQFVIDYRKSADVL  1450
1451  LNETHALADRYKDIIHSDVDTRDSTEAVQYDIEQLMEELTDSNENLQYYK  1500
1501  KQAEDDKQMATEAVRKATLAKNSAIEANATILAEEDEIKKIINSLDTMEE  1550
1551  VNNAELDELEEEIDRLDQLLAQAQLAKEVPTYQQYRADEDVKVAQLKNDI  1600
1601  SELQKEVLNLEEIRDNLPTKCFNVINLEQEGQK                   1633

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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