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

NucPred

Fetching Q6PRD1 from www.uniprot.org...

The NucPred score for your sequence is 0.85 (see score help below)

   1  MGTRGAVMPPPMWGLLGCCFVCAWALGGPRPIRSLPPLSSQVKPGSVPMQ    50
  51  VPLEGAEAALAYLYSGDAQQLSQVNCSERYEARGAGAMPGLPPSLQGAAG   100
 101  TLAQAANFLNMLLQANDIRESSVEEDVEWYQALVRSVAEGDPRVYRALLT   150
 151  FNPPPGASHLQLALQATRTGEETILQDLSGNWVQEENPPGDLDTPALKKR   200
 201  VLTNDLGSLGSPKWPQADGYVGDTQQVRLSPPFLECQEGRLRPGWLITLS   250
 251  ATFYGLKPDLSPEVRGQVQMDVDLQSVDINQCASGPGWYSNTHLCDLNST   300
 301  QCVPLESQGFVLGRYLCRCRPGFYGASPSGGLEESDFQTTGQFGFPEGRS   350
 351  GRLLQCLPCPEGCTSCMDATPCLVEEAAVLRAAVLACQACCMLAIFLSML   400
 401  VSYRCRRNKRIWASGVVLLETVLFGFLLLYFPVFILYFKPSVFRCIALRW   450
 451  VRLLGFAIVYGTIILKLYRVLQLFLSRTAQRSALLSSGRLLRRLGLLLLP   500
 501  VLGFLAVWTVGALERGIQHAPLVIRGHTPSGRHFYLCHHDRWDYIMVVAE   550
 551  LLLLCWGSFLCYATRAVLSAFHEPRYMGIALHNELLLSAAFHTARFVLVP   600
 601  SLHPDWTLLLFFFHTHSTVTTTLALIFIPKFWKLGAPPREEMVDEVCEDE   650
 651  LDLQHSGSYLGSSIASAWSEHSLDPGDIRDELKKLYAQLEVHKTKEMAAN   700
 701  NPHLPKKRGSSCQGLGRSFMRYLAEFPEALARQHSRDSGSPGHGSLPGSS   750
 751  RRRLLSSSLQEPEGTPALHKSRSTYDQRREQDPPLLDSLLRRKLAKKASR   800
 801  TESRESVEGPPALGFRSASAHNLTVGERLPRARPASLQKSLSVASSREKA   850
 851  LLMASQAYLEETYRQAKEREERKKAKAAMASLVRRPSARRLERPRGAPLS   900
 901  APPSPAKSSSVDSSHTSGRLHEEARRRLPHPPIRHQVSTPILALSGGLGE   950
 951  PRMLSPTSTLAPALLPALAPTPAPALAPVPVSPQSPNLLTYICPWENAEL  1000
1001  PAKQENVPQEGPSGPERGHHSPAPARARLWRALSVAVEKSRAGENEMDAE  1050
1051  DAHHQREANDVDEDRPKIFPKSHSLKAPVQQGSMRSLGLAIKALTRSRST  1100
1101  YREKESVEESPEGQNSGTAGESMGAPSRSPRLGRPKAVSKQAALIPSDDK  1150
1151  ESLQNQQNAHTSRMLQVCQREGSREQEDRGRRMTQGLGERKAERAGKTGL  1200
1201  AMLRQVSRDKNIKQSKETPVGWQELPKAGLQSLGSADHRVAEVCPWEVTE  1250
1251  SETRQPDSGNKAEICPWETSEGAPESRALRQDPGDSQKKRGEARGKSEPI  1300
1301  DVVPMMRKKPERLVREQEAVCPWESADRGGLSPGSAPQDPGRIRDKSEAG  1350
1351  DSVEARKVEKPGWEAAGPEAHTPDITKAEPCPWEASEGGEDGKPAQEAVK  1400
1401  DLPQEKQKTRKATFWKEQKPGGDLESLCPWESTDFRGPSAVSIQAPGSSE  1450
1451  CSGSLGSGIAEVCLWEAGDAPAIQKAEICPWELDDNVMGQEMLSLGTGRE  1500
1501  SLQEKEKASRKGSFGEMGEQTVKAVQKLSQQQESVCPRESTVPGHSSPCL  1550
1551  DNSSSKAGSQFLCNGGSRATQVCPQEDLRPEAQEATPAKTEICPWEVNER  1600
1601  TREEWTSAQVPRGGESQKDKEKMPGKSEIEDVTAWEKPEGQIQKQEAVGP  1650
1651  WESVDPGSFSPQPRPQDTERPQTLLQMSGSVGSKAADICPLDVEENLTAG  1700
1701  KAEICPWEVGAGAGEERALGAEAIRKSPNDTGKVSADLGPRERAVTAPEK  1750
1751  PQKPTPEWEVACPWGSVGPGACSQHPGTLDADGPKAGFQELDHMGCRPGE  1800
1801  VCPWEAQEAATSEKAKICPWEVSEGTTGKGLDQKAGSESAEQREKALEKG  1850
1851  RLTSLGEDVSKGMAKLCQQQETICIWENKDLRESPAQAPKISDLPSSMSS  1900
1901  EVAEGHSLEATEKGDLRQDPKTGSFPEHITQEKAPAADTEEFTTEDGEKT  1950
1951  SHELQSVCPWETTAPADSVSHLDRQRPDQPKASSQRLVSTGGRAADVCPW  2000
2001  DVPDAGVYKSDSSAKAETCPWEVTERIPVKGVSRQDGKGDSQEEKGRAPE  2050
2051  KSEPKGVPVQKKPEMADFRQQEAVCPWESQDGKGLSPQPAPDASDRSRGS  2100
2101  SEAAGSVETRVAEVCLWEVVEAPSAKKAEICPWEAGGGAAEEGEQERESQ  2150
2151  GQGEMFLQKAGPGGTEEHFSKAAAKPREQEAVCPGEGTGSGGLLPQSGAL  2200
2201  DPELKVSPKEAGSMGSRMAELCQWEITDPEGNKIKGTMADICPGEETGVP  2250
2251  SEESGLLALTATRREFFPTAPEKPLCLLVHGPLDHFFPESKIPCPKVSRP  2300
2301  ASTFTLEGVRELQGPSGLEPRTSLAPEPSLQEAESQSSSLTEDSGQVAFE  2350
2351  AQYEEFTPPTVYPWDWE                                   2367

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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