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

NucPred

Fetching Q96L73 from www.uniprot.org...

The NucPred score for your sequence is 0.98 (see score help below)

   1  MDQTCELPRRNCLLPFSNPVNLDAPEDKDSPFGNGQSNFSEPLNGCTMQL    50
  51  STVSGTSQNAYGQDSPSCYIPLRRLQDLASMINVEYLNGSADGSESFQDP   100
 101  EKSDSRAQTPIVCTSLSPGGPTALAMKQEPSCNNSPELQVKVTKTIKNGF   150
 151  LHFENFTCVDDADVDSEMDPEQPVTEDESIEEIFEETQTNATCNYETKSE   200
 201  NGVKVAMGSEQDSTPESRHGAVKSPFLPLAPQTETQKNKQRNEVDGSNEK   250
 251  AALLPAPFSLGDTNITIEEQLNSINLSFQDDPDSSTSTLGNMLELPGTSS   300
 301  SSTSQELPFCQPKKKSTPLKYEVGDLIWAKFKRRPWWPCRICSDPLINTH   350
 351  SKMKVSNRRPYRQYYVEAFGDPSERAWVAGKAIVMFEGRHQFEELPVLRR   400
 401  RGKQKEKGYRHKVPQKILSKWEASVGLAEQYDVPKGSKNRKCIPGSIKLD   450
 451  SEEDMPFEDCTNDPESEHDLLLNGCLKSLAFDSEHSADEKEKPCAKSRAR   500
 501  KSSDNPKRTSVKKGHIQFEAHKDERRGKIPENLGLNFISGDISDTQASNE   550
 551  LSRIANSLTGSNTAPGSFLFSSCGKNTAKKEFETSNGDSLLGLPEGALIS   600
 601  KCSREKNKPQRSLVCGSKVKLCYIGAGDEEKRSDSISICTTSDDGSSDLD   650
 651  PIEHSSESDNSVLEIPDAFDRTENMLSMQKNEKIKYSRFAATNTRVKAKQ   700
 701  KPLISNSHTDHLMGCTKSAEPGTETSQVNLSDLKASTLVHKPQSDFTNDA   750
 751  LSPKFNLSSSISSENSLIKGGAANQALLHSKSKQPKFRSIKCKHKENPVM   800
 801  AEPPVINEECSLKCCSSDTKGSPLASISKSGKVDGLKLLNNMHEKTRDSS   850
 851  DIETAVVKHVLSELKELSYRSLGEDVSDSGTSKPSKPLLFSSASSQNHIP   900
 901  IEPDYKFSTLLMMLKDMHDSKTKEQRLMTAQNLVSYRSPGRGDCSTNSPV   950
 951  GVSKVLVSGGSTHNSEKKGDGTQNSANPSPSGGDSALSGELSASLPGLLS  1000
1001  DKRDLPASGKSRSDCVTRRNCGRSKPSSKLRDAFSAQMVKNTVNRKALKT  1050
1051  ERKRKLNQLPSVTLDAVLQGDRERGGSLRGGAEDPSKEDPLQIMGHLTSE  1100
1101  DGDHFSDVHFDSKVKQSDPGKISEKGLSFENGKGPELDSVMNSENDELNG  1150
1151  VNQVVPKKRWQRLNQRRTKPRKRMNRFKEKENSECAFRVLLPSDPVQEGR  1200
1201  DEFPEHRTPSASILEEPLTEQNHADCLDSAGPRLNVCDKSSASIGDMEKE  1250
1251  PGIPSLTPQAELPEPAVRSEKKRLRKPSKWLLEYTEEYDQIFAPKKKQKK  1300
1301  VQEQVHKVSSRCEEESLLARGRSSAQNKQVDENSLISTKEEPPVLEREAP  1350
1351  FLEGPLAQSELGGGHAELPQLTLSVPVAPEVSPRPALESEELLVKTPGNY  1400
1401  ESKRQRKPTKKLLESNDLDPGFMPKKGDLGLSKKCYEAGHLENGITESCA  1450
1451  TSYSKDFGGGTTKIFDKPRKRKRQRHAAAKMQCKKVKNDDSSKEIPGSEG  1500
1501  ELMPHRTATSPKETVEEGVEHDPGMPASKKMQGERGGGAALKENVCQNCE  1550
1551  KLGELLLCEAQCCGAFHLECLGLTEMPRGKFICNECRTGIHTCFVCKQSG  1600
1601  EDVKRCLLPLCGKFYHEECVQKYPPTVMQNKGFRCSLHICITCHAANPAN  1650
1651  VSASKGRLMRCVRCPVAYHANDFCLAAGSKILASNSIICPNHFTPRRGCR  1700
1701  NHEHVNVSWCFVCSEGGSLLCCDSCPAAFHRECLNIDIPEGNWYCNDCKA  1750
1751  GKKPHYREIVWVKVGRYRWWPAEICHPRAVPSNIDKMRHDVGEFPVLFFG  1800
1801  SNDYLWTHQARVFPYMEGDVSSKDKMGKGVDGTYKKALQEAAARFEELKA  1850
1851  QKELRQLQEDRKNDKKPPPYKHIKVNRPIGRVQIFTADLSEIPRCNCKAT  1900
1901  DENPCGIDSECINRMLLYECHPTVCPAGGRCQNQCFSKRQYPEVEIFRTL  1950
1951  QRGWGLRTKTDIKKGEFVNEYVGELIDEEECRARIRYAQEHDITNFYMLT  2000
2001  LDKDRIIDAGPKGNYARFMNHCCQPNCETQKWSVNGDTRVGLFALSDIKA  2050
2051  GTELTFNYNLECLGNGKTVCKCGAPNCSGFLGVRPKNQPIATEEKSKKFK  2100
2101  KKQQGKRRTQGEITKEREDECFSCGDAGQLVSCKKPGCPKVYHADCLNLT  2150
2151  KRPAGKWECPWHQCDICGKEAASFCEMCPSSFCKQHREGMLFISKLDGRL  2200
2201  SCTEHDPCGPNPLEPGEIREYVPPPVPLPPGPSTHLAEQSTGMAAQAPKM  2250
2251  SDKPPADTNQMLSLSKKALAGTCQRPLLPERPLERTDSRPQPLDKVRDLA  2300
2301  GSGTKSQSLVSSQRPLDRPPAVAGPRPQLSDKPSPVTSPSSSPSVRSQPL  2350
2351  ERPLGTADPRLDKSIGAASPRPQSLEKTSVPTGLRLPPPDRLLITSSPKP  2400
2401  QTSDRPTDKPHASLSQRLPPPEKVLSAVVQTLVAKEKALRPVDQNTQSKN  2450
2451  RAALVMDLIDLTPRQKERAASPHQVTPQADEKMPVLESSSWPASKGLGHM  2500
2501  PRAVEKGCVSDPLQTSGKAAAPSEDPWQAVKSLTQARLLSQPPAKAFLYE  2550
2551  PTTQASGRASAGAEQTPGPLSQSPGLVKQAKQMVGGQQLPALAAKSGQSF  2600
2601  RSLGKAPASLPTEEKKLVTTEQSPWALGKASSRAGLWPIVAGQTLAQSCW  2650
2651  SAGSTQTLAQTCWSLGRGQDPKPEQNTLPALNQAPSSHKCAESEQK      2696

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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