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

NucPred

Fetching Q61687 from www.uniprot.org...

The NucPred score for your sequence is 1.00 (see score help below)

   1  MTAEPMSGNKLSTLVQKLHDFLAHSSEESEETCSSPRLVMNQSTDKICGS    50
  51  GLNSDMMENNKEEGASTSEKSRSSGSSRSKRKPSIVTKYVESDDEKPTDE   100
 101  NVNEKAATENSENDITMQSLPKGTVIVQPEPVLNEDKDDFKGPEFRSRSK   150
 151  MKADNLKKRGEDGLHGIVSCTACGQQVNHFQKDSIYRHPSLKVLICKNCF   200
 201  KYYMSDDISRDSDGMDEQCRWCAEGGNLICCDFCHNAFCKKCILRNLGRK   250
 251  ELSTIMDENNQWYCYICQPEPLLDLVTACNSVFENLEQLLQQNKKKIKVD   300
 301  SEKTSKVCDQTSKFSPKKSSSSCNGEEKKLEESCSGSVSSTYSHSALSVP   350
 351  KEMIKKTTKLIETTSNMNSSYIKFLKQAADNSEMTSAMKLCQLKSFKSVL   400
 401  DDIKKAHLALEEDLNSEIQALDDVHKEKNTKDLKSTDAKSETKLGKGEKS   450
 451  YSTEKREFLKLDARSSVKAIDGEEQRAHKSTSGEHKGSGRKDGSQYEPTN   500
 501  TPEDLDMDIVSVPSSVPEDIFDSLESAMEVQSSADYQGDGNSGTEPELES   550
 551  SSVKLNVSSKDSRGNIKSKVTAKVRKELFVKLTPVSLSNSPIKGVDCQEV   600
 601  SQEKNGRKSSGVARSSEKCRPREEISDHENNVTILLEDSDLRRSPRVKTT   650
 651  PLRRQTESNPAMSNSDEESNGTMKEKQKMSGPIRKKDKRNSADCATDNPK   700
 701  PHKVPKAKQPVIGDQNSDSDEMLAVLKEASQMGHSSSSDTDINEPQMNHK   750
 751  GKTGKDDNGKRKRKNSTSGSDFDTKKGKSTETSIISKKKRQNYSESSNYD   800
 801  SELEREIKTMSRIGAARKSVPEKKEEDSSEDEKQGKKVVDNGGHERAKTT   850
 851  QEGSSADDTGDTEGRQGGSCSIAGGSIEKVRSGVEFREMLCKPGVSSDGA   900
 901  EKPSVKEENVNSPEDKRVSKTKEKTKHLRSRQSRKGKGGSSDGTDRFPKK   950
 951  EQSDESSEGEKKQSRQRPGTKGKKAPDLKGETLKREQEWDSSSDGTERLP  1000
1001  EEEEIGPFSKGIKQSKTDTAGGEKKGKKWKDKSCEKKEELSDSVDKLPGK  1050
1051  GDSCDSSEDKKTRNRVSLREKKRFSLPAKSPGKRPECSSSDTEKSLKGQC  1100
1101  CDSTEKRPKRIDLRERRNSSSKRNTKEVKSASSSSDAEGSSEDNKKQKKQ  1150
1151  RTSAKKKTGNTKEKKRNSLRATPKRKQVDITSSSSDIGDDDQNSAGEESS  1200
1201  DEQKIKPVTENLVLPSHTGFCQSSGDEALSKSVPATVDDDDDDNDPENRI  1250
1251  AKKMLLEEIKANLSSDEDGSSDDEPDGGGKKRIGKQSEESPADDGELRRE  1300
1301  QLAVNQVNSESDSDSEESKKPRYRHRLLRHKLTLSDGESGEEKPTKPKEH  1350
1351  KEAKGRNRRKVSSEDSEDTDFQESGVSEEVSESEDEQRPRTRSAKKAELE  1400
1401  ENQRSYKQKKKRRRIKVQEDSSSENKSHSEEDKKEGDEEDEEDEDEDEED  1450
1451  ENDDSKSPGKGRKKIRKILKDDKLRTETQNALKEEEERRKRIAERERERE  1500
1501  KLREVIEIEDASPTKCPITTKLVLDENEETKEPLVQVHRNMVIKLKPHQV  1550
1551  DGVQFMWDCCCESVEKTKKSPGSGCILAHCMGLGKTLQVVSFLHTVLLCD  1600
1601  KLDFSTALVVCPLNTALNWMNEFEKWQEGLNDNEKLEVSELATVKRPQER  1650
1651  SYMLQRWQEDGGVMIIGYEMYRNLAQGRNVKSRKLKDIFNKALVDPGPDF  1700
1701  VVCDEGHILKNEASAVSKAMNSIKSRRRIILTGTPLQNNLIEYHCMVNFI  1750
1751  KENLLGSIKEFRNRFINPIQNGQCADSTMVDVRVMKKRAHILYEMLAGCV  1800
1801  QRKDYTALTKFLPPKHEYVLAVRMTAIQCKLYQYYLDHLTGVGNSTEGGR  1850
1851  GKAGAKLFQDFQMLSRIWTHPWCLQLDYISKENKGYFDEDSMDEFIASDS  1900
1901  DETSKSLSSDEKKKPKGKKGKKDSSSSGSGSDNDVEVIKVWNSRSRGGGD  1950
1951  GNVDDTGNNPSVSLKLDESKTTSTSNPSSPAPDWYKDFVTDTDAEVLEHS  2000
2001  GKMVLLFEILRMAEEIGDKVLVFSQSLISLDLIEDFLELASREKTEDKEK  2050
2051  PLIYKGEGKWIRNIDYYRLDGSTNAQSRKKWAEEFNDETNVRGRLFIIST  2100
2101  KAGSLGINLVAANRVIIFDASWNPSYDIQSIFRVYRFGQTKPVYVYRFLA  2150
2151  QGTMEDKIYDRQVTKQSLSFRVVDQQQVERHFTMNELTELYTFEPDLLDD  2200
2201  PNSEKKKKRDTPMLPKDTILAELLQIHKEHIVGYHEHDSLLDHKEEEELT  2250
2251  EEERKAAWAEYEAEKKGLTMRFNIPTGTNLPPVTFTSQTPYIPFNLGALS  2300
2301  AMSNQQLEDLINQGREKVVEATNSMTAVRIQPLEDIISTVWKENMNLSEA  2350
2351  QVQALALSRQASQELDVKRREAIYNDVLTKQQMLINCVQRILMNRRLQQQ  2400
2401  YTQQQQQQLTYQQATLSHLMMPKPPNLIMTPSNYQQIDMRGMYQSVAGGM  2450
2451  QPPPLQRAPPPTVRSKNPGPSPGKSM                          2476

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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