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

NucPred

Fetching P46940 from www.uniprot.org...

The NucPred score for your sequence is 0.82 (see score help below)

   1  MSAADEVDGLGVARPHYGSVLDNERLTAEEMDERRRQNVAYEYLCHLEEA    50
  51  KRWMEACLGEDLPPTTELEEGLRNGVYLAKLGNFFSPKVVSLKKIYDREQ   100
 101  TRYKATGLHFRHTDNVIQWLNAMDEIGLPKIFYPETTDIYDRKNMPRCIY   150
 151  CIHALSLYLFKLGLAPQIQDLYGKVDFTEEEINNMKTELEKYGIQMPAFS   200
 201  KIGGILANELSVDEAALHAAVIAINEAIDRRIPADTFAALKNPNAMLVNL   250
 251  EEPLASTYQDILYQAKQDKMTNAKNRTENSERERDVYEELLTQAEIQGNI   300
 301  NKVNTFSALANIDLALEQGDALALFRALQSPALGLRGLQQQNSDWYLKQL   350
 351  LSDKQQKRQSGQTDPLQKEELQSGVDAANSAAQQYQRRLAAVALINAAIQ   400
 401  KGVAEKTVLELMNPEAQLPQVYPFAADLYQKELATLQRQSPEHNLTHPEL   450
 451  SVAVEMLSSVALINRALESGDVNTVWKQLSSSVTGLTNIEEENCQRYLDE   500
 501  LMKLKAQAHAENNEFITWNDIQACVDHVNLVVQEEHERILAIGLINEALD   550
 551  EGDAQKTLQALQIPAAKLEGVLAEVAQHYQDTLIRAKREKAQEIQDESAV   600
 601  LWLDEIQGGIWQSNKDTQEAQKFALGIFAINEAVESGDVGKTLSALRSPD   650
 651  VGLYGVIPECGETYHSDLAEAKKKKLAVGDNNSKWVKHWVKGGYYYYHNL   700
 701  ETQEGGWDEPPNFVQNSMQLSREEIQSSISGVTAAYNREQLWLANEGLIT   750
 751  RLQARCRGYLVRQEFRSRMNFLKKQIPAITCIQSQWRGYKQKKAYQDRLA   800
 801  YLRSHKDEVVKIQSLARMHQARKRYRDRLQYFRDHINDIIKIQAFIRANK   850
 851  ARDDYKTLINAEDPPMVVVRKFVHLLDQSDQDFQEELDLMKMREEVITLI   900
 901  RSNQQLENDLNLMDIKIGLLVKNKITLQDVVSHSKKLTKKNKEQLSDMMM   950
 951  INKQKGGLKALSKEKREKLEAYQHLFYLLQTNPTYLAKLIFQMPQNKSTK  1000
1001  FMDSVIFTLYNYASNQREEYLLLRLFKTALQEEIKSKVDQIQEIVTGNPT  1050
1051  VIKMVVSFNRGARGQNALRQILAPVVKEIMDDKSLNIKTDPVDIYKSWVN  1100
1101  QMESQTGEASKLPYDVTPEQALAHEEVKTRLDSSIRNMRAVTDKFLSAIV  1150
1151  SSVDKIPYGMRFIAKVLKDSLHEKFPDAGEDELLKIIGNLLYYRYMNPAI  1200
1201  VAPDAFDIIDLSAGGQLTTDQRRNLGSIAKMLQHAASNKMFLGDNAHLSI  1250
1251  INEYLSQSYQKFRRFFQTACDVPELQDKFNVDEYSDLVTLTKPVIYISIG  1300
1301  EIINTHTLLLDHQDAIAPEHNDPIHELLDDLGEVPTIESLIGESSGNLND  1350
1351  PNKEALAKTEVSLTLTNKFDVPGDENAEMDARTILLNTKRLIVDVIRFQP  1400
1401  GETLTEILETPATSEQEAEHQRAMQRRAIRDAKTPDKMKKSKSVKEDSNL  1450
1451  TLQEKKEKIQTGLKKLTELGTVDPKNKYQELINDIARDIRNQRRYRQRRK  1500
1501  AELVKLQQTYAALNSKATFYGEQVDYYKSYIKTCLDNLASKGKVSKKPRE  1550
1551  MKGKKSKKISLKYTAARLHEKGVLLEIEDLQVNQFKNVIFEISPTEEVGD  1600
1601  FEVKAKFMGVQMETFMLHYQDLLQLQYEGVAVMKLFDRAKVNVNLLIFLL  1650
1651  NKKFYGK                                             1657

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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