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

NucPred

Fetching Q5ABX0 from www.uniprot.org...

The NucPred score for your sequence is 0.88 (see score help below)

   1  MSTSDINKTIALLQSSKIKERNDALNNLENIAASKFRLNPKQFRQLTQAI    50
  51  LALIKHESQIYFNNKSTTVDSRLSQASYNLRLLTEKSIEDTRIDFKYRTY   100
 101  LDLCMGIKDQFFVHSELLEPCSIDFIKTITSILNLSYVKEHLNRKEWSIL   150
 151  YIFLVSLINNILDDCEGSFSNNGNNEKLLIDLYTALQNLLQCESSVSINY   200
 201  LQLYDNDNYFKLLRILDKTSELLKKENVIIIIIFRIINKLITVIATEKFK   250
 251  FVNKLIKIGIRLMVYFHHSHWEKLQEQFLIFINLPGTHDLINLHNLPKLI   300
 301  GDRYILSEISTQEDGDSINSQADNQDEVFLYNLGVLIHHLMKKLMSGSFE   350
 351  LKTEDIGMCTINNSITWFNLKTIYSDSQNYKPWLLTLGVSRLLKSYYDLK   400
 401  QFINKQSNDPQTSLLLYSNGSPNKNKRQKLGSIADTISDSNSAIELCNKL   450
 451  IHSKESSDNQVLGLKLLTFYLELYTFEKPKEQSTESDSMDTTIGENTTFD   500
 501  FVISTTDNTFIDKNVVMKNILITFDDNSMNFWSSLCARSVLLDEILQSNH   550
 551  GGFKFKKSFSIQLLKLSLLLLKEPEVANIACNIIFKLVFEQKTNLSELID   600
 601  DSVIIQLETLIDLSEINGPYKITEESFQFWYAINKLAIEVNLSKKNFLGR   650
 651  RIQDWMLAKWDITFSPGADFVSVGSSLANFIYWLSGNSISYSPTTTQKST   700
 701  YEGDIYEFYYFAQSYDSLEKFLCLKSVSDSSETIKFDIISIASSDRIDAI   750
 751  LNKVNSTFMVFDRSSVTSGSLFCWIIVLSNIVAKVRSMKFVTHELTGLQF   800
 801  QLSAGLNSFKDITLSCEEIIDVMEMVNKFLPTDPDTIQIFIQNFPSEKLV   850
 851  NIIKFDYPGLADKDNRKSVPEDGFGWEFSRVRDATTPPSTTSTSTISLAK   900
 901  LNYKKIQSLEVSKFIMFTADIEGKLQSDILTAFLNYVETLESDDFLPSLL   950
 951  FVVENIFTDHSAHFIDEIQLAKLLRIINEKLLSTQNYERNEFVSVVISRF  1000
1001  LSATAQVWINSSDNSLASDFYSLVSRLYSSGRDDLILTETSIVEYCRFLA  1050
1051  HFITHNDERVLSNTDIKNELLEKFSKSPNNIKDRLANSFGELVSLSTVQQ  1100
1101  QGQIYSDLFDRFVNPEQSVESAGTYTKFFTNLSQSSLHILRLALFNLLEC  1150
1151  SRFPFFISYLEICLKEFCMIMKLDNANKLFKIFKFEILRNWWKYDSIDAF  1200
1201  PFVLFSYTDLSSFYRDNYRELIAVALSTKSRSPEISNAFVEQLADLKQSH  1250
1251  SETLVAESLSIIVPLSYSKDGVRNDVFQILLDYLKNSFKQEFIDKLPLIV  1300
1301  LEIIKFTEISNEKSFESLGTDGLVTMLLNDTGFSSTIQTAGEMVISFDSS  1350
1351  VQLLKKLVEKYHQPEHETFWSSRQIYFLIRRLSISLKLATTFEQKVIFLR  1400
1401  KFKFVLVLGGKKSIDYAVSRLLVDTLCPLLSNEPKMSADVFLILQSLTDV  1450
1451  YSHRYTYDKSISLIIQIINSLLETEAVDRSRALLDCIDDFVNTGDQDRAI  1500
1501  CQLLKSSVAILKGQAVEIESSLIELCLEESGPDYIKQMILISRIFGNVVF  1550
1551  ATTHSGSKLPVVEKLLALSKNQIQEFSDGYKLWIANYLSDFYIEGGCKEQ  1600
1601  IKALTFDEYEGIPVNDFENEVRSFDFTLKSIEQYIYKDDFEAAACAESII  1650
1651  GVLIRKYETSKREVSKFLNFETTLEKHSDSILPIDFHTCVILNDKADVEY  1700
1701  LGDELIDIINNFESFLSNGTELWCTKLYLALLQELAVETSIAPLLSTFVI  1750
1751  MVPEFAKTSLPVLVCNYLAIKRTHSQDRIISLLNEFLHTSKKSESSIKVF  1800
1801  LQILILIRVGAKIFKKPVFANVFAKIDKLKFYQLACEVKQFKTALMLFED  1850
1851  VASDTNSDVHLQDHYQTLQHVYESLDDDDLVFGLPERTTLEYSISMINRV  1900
1901  GNSDDRLRFSSAGFDTDMILNQEPSYSNIVGSLSAAGLLGVSRALSKNTS  1950
1951  FASNDDSQYEWSWKLSKWDLPISKNATKENEVIYKTLKQIHDFPMNSQDI  2000
2001  CSSSLLNAVDNKVSATNMSVKEFKQEGINWLKTISTVASIAEIANATGDN  2050
2051  IIPMTNQFSEKTQWFGEVEFSMFENLLLARQTTFGLINDRPISSLPSDTA  2100
2101  WMGALCDLVRYNNLARTNGEYQKMVTSTMLVDVVSKKLQSSSLDMVAFNA  2150
2151  NNLASFQTAQTLWCQGNTNVPVMIMKDLYAAGGIDMSENILKVDKCLIRA  2200
2201  MMVDWMSQSRQEVASSIMEKYVMPTEELSNHMIDLQQQSKIFSILARFCE  2250
2251  EQYKFKSLSEKISKLEKRVLNKENEIKDLKKQYEKVTVTHAEQKQVQQYY  2300
2301  NRLKKQFVSESKDLESLRKSKQLFSSKAVQYYMKSIIVDDFEEENLDKFF  2350
2351  SLWLEQSGNNELNQSIQSNLLALPSYKLVSWCTQLISRLSNETNNFQILL  2400
2401  KKLIINMCLDHPHHSLYLLLSLKKHKPNTNEVLNPSLLSRCAAAQAIWDQ  2450
2451  LLLQDHRYISDVLLPIDGFTDQCITLAAYKVSKGKSIDLTKFSAGDYWLN  2500
2501  ELPAIPPPTETIRVDPSKQYKNVPVLHSIDKKISIATSGLSLPKIANFIL  2550
2551  SNGTEHRVLLKHGTDGIRQDSIMEQVFNKVNNIFAKDRECNKRGLTIRTY  2600
2601  NAVPLGPLSGIIEFVPNSMAFIDVISGYHQMHDKISYDKAREMMKSCQSG  2650
2651  DKQKRIHSFEQIEAKIKPVMRYFFQETFLTSDSWFESRVKYTHGIATSSI  2700
2701  VGHILGLGDRHCNNILIDRSTGEPIHIDLGVAFDQGKRLAIPETVPFRLT  2750
2751  RDIVDGFGVTGVEGMFKKSCEHTLRVLRTNKEHIISILDVLRWDPLYSWT  2800
2801  LSRFKKRKLQEDETGPGVQPEEEGSEAGTAIMTVIEKLNANGLSTEAAVR  2850
2851  ELIQEATSTQNLALIYFGWSPFY                             2873

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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