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

NucPred

Fetching P42346 from www.uniprot.org...

The NucPred score for your sequence is 0.66 (see score help below)

   1  MLGTGPATATAGAATSSNVSVLQQFASGLKSRNEETRAKAAKELQHYVTM    50
  51  ELREMSQEESTRFYDQLNHHIFELVSSSDANERKGGILAIASLIGVEGGN   100
 101  STRIGRFANYLRNLLPSSDPVVMEMASKAIGRLAMAGDTFTAEYVEFEVK   150
 151  RALEWLGADRNEGRRHAAVLVLRELAISVPTFFFQQVQPFFDNIFVAVWD   200
 201  PKQAIREGAVAALRACLILTTQREPKEMQKPQWYRHTFEEAEKGFDETLA   250
 251  KEKGMNRDDRIHGALLILNELVRISSMEGERLREEMEEITQQQLVHDKYC   300
 301  KDLMGFGTKPRHITPFTSFQAVQPQQSNALVGLLGYSSHQGLMGFGASPS   350
 351  PTKSTLVESRCCRDLMEEKFDQVCQWVLKCRSSKNSLIQMTILNLLPRLA   400
 401  AFRPSAFTDTQYLQDTMNHVLSCVKKEKERTAAFQALGLLSVAVRSEFKV   450
 451  YLPRVLDIIRAALPPKDFAHKRQKTVQVDATVFTCISMLARAMGPGIQQD   500
 501  IKELLEPMLAVGLSPALTAVLYDLSRQIPQLKKDIQDGLLKMLSLVLMHK   550
 551  PLRHPGMPKGLAHQLASPGLTTLPEASDVASITLALRTLGSFEFEGHSLT   600
 601  QFVRHCADHFLNSEHKEIRMEAARTCSRLLTPSIHLISGHAHVVSQTAVQ   650
 651  VVADVLSKLLVVGITDPDPDIRYCVLASLDERFDAHLAQAENLQALFVAL   700
 701  NDQVFEIRELAICTVGRLSSMNPAFVMPFLRKMLIQILTELEHSGIGRIK   750
 751  EQSARMLGHLVSNAPRLIRPYMEPILKALILKLKDPDPDPNPGVINNVLA   800
 801  TIGELAQVSGLEMRKWVDELFVIIMDMLQDSSLLAKRQVALWTLGQLVAS   850
 851  TGYVVEPYRKYPTLLEVLLNFLKTEQNQGTRREAIRVLGLLGALDPYKHK   900
 901  VNIGMIDQSRDASAVSLSESKSSQDSSDYSTSEMLVNMGNLPLDEFYPAV   950
 951  SMVALMRIFRDQSLSHHHTMVVQAITFIFKSLGLKCVQFLPQVMPTFLNV  1000
1001  IRVCDGAIREFLFQQLGMLVSFVKSHIRPYMDEIVTLMREFWVMNTSIQS  1050
1051  TIILLIEQIVVALGGEFKLYLPQLIPHMLRVFMHDNSQGRIVSIKLLAAI  1100
1101  QLFGANLDDYLHLLLPPIVKLFDAPEVPLPSRKAALETVDRLTESLDFTD  1150
1151  YASRIIHPIVRTLDQSPELRSTAMDTLSSLVFQLGKKYQIFIPMVNKVLV  1200
1201  RHRINHQRYDVLICRIVKGYTLADEEEDPLIYQHRMLRSSQGDALASGPV  1250
1251  ETGPMKKLHVSTINLQKAWGAARRVSKDDWLEWLRRLSLELLKDSSSPSL  1300
1301  RSCWALAQAYNPMARDLFNAAFVSCWSELNEDQQDELIRSIELALTSQDI  1350
1351  AEVTQTLLNLAEFMEHSDKGPLPLRDDNGIVLLGERAAKCRAYAKALHYK  1400
1401  ELEFQKGPTPAILESLISINNKLQQPEAASGVLEYAMKHFGELEIQATWY  1450
1451  EKLHEWEDALVAYDKKMDTNKDDPELMLGRMRCLEALGEWGQLHQQCCEK  1500
1501  WTLVNDETQAKMARMAAAAAWGLGQWDSMEEYTCMIPRDTHDGAFYRAVL  1550
1551  ALHQDLFSLAQQCIDKARDLLDAELTAMAGESYSRAYGAMVSCHMLSELE  1600
1601  EVIQYKLVPERREIIRQIWWERLQGCQRIVEDWQKILMVRSLVVSPHEDM  1650
1651  RTWLKYASLCGKSGRLALAHKTLVLLLGVDPSRQLDHPLPTVHPQVTYAY  1700
1701  MKNMWKSARKIDAFQHMQHFVQTMQQQAQHAIATEDQQHKQELHKLMARC  1750
1751  FLKLGEWQLNLQGINESTIPKVLQYYSAATEHDRSWYKAWHAWAVMNFEA  1800
1801  VLHYKHQNQARDEKKKLRHASGANITNATTTATTAASAAAATSTEGSNSE  1850
1851  SEAESNESSPTPSPLQKKVTEDLSKTLLLYTVPAVQGFFRSISLSRGNNL  1900
1901  QDTLRVLTLWFDYGHWPDVNEALVEGVKAIQIDTWLQVIPQLIARIDTPR  1950
1951  PLVGRLIHQLLTDIGRYHPQALIYPLTVASKSTTTARHNAANKILKNMCE  2000
2001  HSNTLVQQAMMVSEELIRVAILWHEMWHEGLEEASRLYFGERNVKGMFEV  2050
2051  LEPLHAMMERGPQTLKETSFNQAYGRDLMEAQEWCRKYMKSGNVKDLTQA  2100
2101  WDLYYHVFRRISKQLPQLTSLELQYVSPKLLMCRDLELAVPGTYDPNQPI  2150
2151  IRIQSIAPSLQVITSKQRPRKLTLMGSNGHEFVFLLKGHEDLRQDERVMQ  2200
2201  LFGLVNTLLANDPTSLRKNLSIQRYAVIPLSTNSGLIGWVPHCDTLHALI  2250
2251  RDYREKKKILLNIEHRIMLRMAPDYDHLTLMQKVEVFEHAVNNTAGDDLA  2300
2301  KLLWLKSPSSEVWFDRRTNYTRSLAVMSMVGYILGLGDRHPSNLMLDRLS  2350
2351  GKILHIDFGDCFEVAMTREKFPEKIPFRLTRMLTNAMEVTGLDGNYRTTC  2400
2401  HTVMEVLREHKDSVMAVLEAFVYDPLLNWRLMDTNAKGNKRSRTRTDSYS  2450
2451  AGQSVEILDGVELGEPAHKKTGTTVPESIHSFIGDGLVKPEALNKKAIQI  2500
2501  INRVRDKLTGRDFSHDDTLDVPTQVELLIKQATSHENLCQCYIGWCPFW   2549

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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