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

NucPred

Fetching P08032 from www.uniprot.org...

The NucPred score for your sequence is 0.95 (see score help below)

   1  METPKETAVESSGPKVLETAEEIQHRRAEVLNQYQRFKDRVAERGQKLEE    50
  51  SYHYQVFRRDADDLEKWIMEKLEIAKDKTYEPTNIQGKYQKHESFVSEVQ   100
 101  AKSRVLPELEEIREARFAEDHFAHEATKTHLKQLRLLWDLLLELTQEKSD   150
 151  VLLRALKFYQYSQECEDILEWVKEKEAIVTLVELGDDWERTEVLHKKFEE   200
 201  FQEELTARKGKVDRVNQYANECAQEKHPKLPEIKAKQDEVNAAWDRLWSL   250
 251  ALKRRESLSNAADLQRFKRDVNEAIQWMEEKEPQLTSEDYGKDLVSSEAL   300
 301  FHNHKRLERNLAVMDDKVKELCAKADKLMISHSADAPQIQQMKLDLVSNW   350
 351  ERIRALATNRYAKLKASYGYHRFLSDYDELSGWMKEKTALINADELPTDV   400
 401  ASGEALLARHQQHKHEIDSYDDRFQSADATGQELLDGNHEASEEIREKMT   450
 451  ILANDWAALLELWDKCQHQYRQCLDFHLFYRDSEQVDSWMSRQEAFLENE   500
 501  DLGNSVGSVEALLQKHDDFEEAFTAQEEKIITLDETATKLIDNDHYDSEN   550
 551  IAAIRDGLLARRDALRERAATRRKLLVDSQLLQQLYQDSDDLKTWINKKK   600
 601  KLADDDDYKDVQNLKSRVQKQQDFEEELAVNEIMLNNLEKTGQEMIEDGH   650
 651  YASEAVAARLSEVANLWKELLEATAQKGTQLYEANQLLQFENNAEDLKRW   700
 701  LEEVEWQVTSEDYGKGLADVQNLLRKHGLLESDVTARQNQVDTLTDMAAH   750
 751  FEEIGHPDSGDIRARQESLLSRFEALKEPLAIRKKKLIDLLKLQQICRDS   800
 801  EDEEAWIQETEPSAASTHLGKDLVAAKNLLNRHEVILADIASHEPRIQVI   850
 851  TERGNKMVEEGHFAAEDIASRVESLNKNMESLHARAIRRENDLKANVQLQ   900
 901  QYLADLHEAEAWIKEKEPIVDNKNYGADEEAAGALLKKHEAFLVDLNAFE   950
 951  NSIKALRDQAEVCQQQQAAPVDEAGREARVIALYDFEARSRREVSMKKND  1000
1001  VLTLLSSINKDWWKVEADDHQGFVPAVYVRKLAPDELPGFPQHRQEEPVN  1050
1051  IPQLQQQVETLYHSLLDRAEERRRRLLQRYNEFLLAYEAGDMLEWIQEKK  1100
1101  TENTGVELDDVWELQKKFDEFQRDLKSNEPRLKDINKVADELLFEELLTP  1150
1151  EGAHIRQELNTRWNSLKRLADEQYQLLSSAHAVEMFHREADDVKEQIDKK  1200
1201  CRALNAADPGSDLLSVQALQRQHEVFERDIIPLGEKVTTLGETAERLCES  1250
1251  HPDATEDLQKQRTELNEAWDTLQGLTSDRKESLNEAHKFFLFLSKASDLE  1300
1301  NWIKTIGGVISSPELAEDLTGTEILLERHQEHHDDIKREDPTFQALEDFG  1350
1351  TELIDSGHRNRREIDNTLQNINSKRDNLEKSWENRKKMLDQCLELQLFRG  1400
1401  KCDQVESWMVARENSLRSDDRDHLNSLQALMKKRDDLDKAITAQEGKISD  1450
1451  LENVATRLIDNDHYAKEEIAARLQRVLDRWKALKEQLLTELGKLGDYADL  1500
1501  KQFYRDLEDLEEWINEMLPIACDESYKDPTNIQRKYLKHQAFENEVNGRA  1550
1551  EQVDGVINLGNSLIERRVCDGDEENMQEQLDKLKENWDYLLERTTDKGQK  1600
1601  LNEASRQQRFNTSIRDFEFWLSEAEGLLAMKDQARDLTSAGNLLKKHQLL  1650
1651  EAEMLAREDPLKDLNDLAQELISSGTFNIDQIEEKMNGVNERFENVQSLA  1700
1701  AAHHEKLKETYALFQFFQDLDDEEAWIEEKLLRVSSQDYGRDLQSVQNLL  1750
1751  KKHKRLEGELVAHEPAVQNVLDTAESLRDKAAVGKEEIQERLAQFVQHWE  1800
1801  KLKELAKTRGVNLEESLEYLQFMENAEEEEAWLGEKCALVSRGDSGDTLA  1850
1851  ATQSLLKKHEALENDFAVHKNRVQDVCAQGEDILNKEETQNKDKISTKIQ  1900
1901  VLNEKTASLAKALAAWKSQLDDVHAFQQFNWKADVVESWIGEKEASLKTK  1950
1951  SNGADLTAFLTLLAKHDTLDASLQSFQQERLSEIAELKDQLVAGEHSQAK  2000
2001  AIEEQHAALLRHWEQLLEASRVHRQKLLEKQLPLQKAEELFMEFAHKASA  2050
2051  FNNWCENAEEDLSEPVHCVSLNEIRQLQKEHEAFLASLAGAQEDFNYLLE  2100
2101  LDKQIKALNVPSSPYTWLTVDVLGRIWNHLPDIIKEREQELQKEEARQIK  2150
2151  NFEMCQEFEQNASAFLQWIQETRAYFLDGSLLKETGTLESQLEANKRKQK  2200
2201  EIQAMKRHLTKIEDLGDSMEEALILDIKYSTIGLAQQWDQLHQLGMRMQH  2250
2251  NLEQQIQAKDTIGVSEETLKEFSTTYKHFDENLTGRLTHKEFRSCLRGLN  2300
2301  YYLPMVEEGEPEPKFEKFLNAVDPGRKGYVSLEDYTSFLIDKESENIKTS  2350
2351  DDIESAFQALAEGKAYITKEDMKQALTPEQVSFCTIHMQQYMDPRGRSQP  2400
2401  AGYDYVGFTNSFFGN                                     2415

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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