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

NucPred

Fetching Q3BAQ2 from www.uniprot.org...

The NucPred score for your sequence is 0.89 (see score help below)

   1  MEVLMAERTNLVFHNKVIDGTAIKRLISRLIDHFGMAYTSHILDQVKALG    50
  51  LRRATATSISLGIDDLLTIPSKRWLVQDAEQQSFLLEKNHHYGNVHVVEK   100
 101  LRQSIEVWYATSEYLRQEMNPNFQMTDPSNPVHLMSFSGARGNASQVHQL   150
 151  VGMRGLMSDPQGQMIDLPIQSNLREGLSVTEYIISCYGARKGVVDTAVRT   200
 201  SDAGYLTRRLVEVVQHILVRRTDCGTIRGISVSPQNGMTEKIFVQTLIGR   250
 251  VLADDIYIGLRCIGTRNKDIGIGLVNRFITFQAHPIYIRTPFTCRSTSWI   300
 301  CQLCYGRSPTHGDLVELGEAVGIIAGQSIGEPGTQLTLRTFHTGGVFTGG   350
 351  TAEHVRAPSNGKIKFDEGLVHPTRTRHGHPAFLCFIDFYVTIESRDIRHN   400
 401  VNIPTKSLILVQNDQYVESEQVIAEIRAETSTFHFKERVQKHIYSESEGE   450
 451  MHWSTDGYHTPKYPYSNVHLLPKTSHLWILAGGLCRSNSNIVSFSLHKDQ   500
 501  DQMNANSFSLKDLFDLSLTNDQVRHKLLDTFGKKDRESLDYSKPYRIISK   550
 551  GHWNLIEPSTYIRQENSLAKKRRNRFVIPLQYDQEQENKLIPCFGISIKI   600
 601  PINGILRRNSIIAYFDDPRYRRSSSGITKYGIVEVDSIVKKEDLIEYRGA   650
 651  KDFSPKYQTQMKVDQFFFIPEEIHILPGSSPIMVRNNSIIGVDTRLVLNI   700
 701  NTRSRVGGLVRVERKKKSLELKIFSGDIHFYGEVDKISRHSGILIPPGIG   750
 751  KKDSKGSKKLKNWIYVQRITPTKKKYFVLVRPVVTYEIADGINLATLFSQ   800
 801  DLLQEKNNVQLRIVNYILYENGKSIRGISHTSIQLVRACLVLTWDQEKKS   850
 851  SIEEKVHASFVEIRTNDLLCYFIRIELVKSTLSYTEKRYDTAGSGLISNN   900
 901  ELDRIHRKNPFDSKAKIQIFPQHQGTLGTLLNRNKECQSFLILSSSNCSR   950
 951  IGPFNTSRYNNATKELDPMTPIRYLLGPLGTIVPRIVNSRSSYYLRTYNQ  1000
1001  VFLKKSFLLENFQQTFQVLQVPPFQYCFLDENSRIYNPDPCSNIIWNSFH  1050
1051  LNWCFLHHDSCEEAWPIISLGQFLCENVYLLKYGSRIKKSGQIFIVHVDS  1100
1101  LVIRSAKPYLVTPGATVHGHYGETFYEGDTLITFIYEKSRSGDITQGLPK  1150
1151  VEQILEVRSIDSISMNLERRVEGWDERIRRILGIPWGFLIGAELTIAQSR  1200
1201  ISLVNKIQKVYRSQGVQIHNRHLEIIVRQVTSRVLVSEDGMSNVFLPGEF  1250
1251  IGLLRAERAGRVLAESICYRAILLGITKSSLNTQSFISEASFQETARVLA  1300
1301  KAALRGRIDWLKGLKENVVLGGIIPVGTGFNKLVHRSKQDKNIHLKIKRK  1350
1351  NLFELEMSDILLHHRELFCSCAQELSMRHQTNLLRNVS              1388

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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