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

NucPred

Fetching Q5S006 from www.uniprot.org...

The NucPred score for your sequence is 0.90 (see score help below)

   1  MASGACQGCEEEEEEEALKKLIVRLNNVQEGKQIETLLQLLEDMLVFTYS    50
  51  DRASKLFEDKNFHVPLLIVLDSYMRVASVQQAGWSLLCKLIEVCPGTLQS   100
 101  LIGPQDIGNDWEVLGIHRLILKMLTVHHANVNLSIVGLKALDLLLDSGKL   150
 151  TLLILDEECDIFLLIFDAMHRYSANDEVQKLGCKALHVLFERVSEEQLTE   200
 201  FVENKDYTILLSTFGSFRRDKEIVYHVLCCLHSLAVTCSNVEVLMSGNVR   250
 251  CYNLVVEAMKAFPTNENIQEVSCSLFQKLTLGNFFNILVLNEVHVFVVKA   300
 301  VRQYPENAALQISALSCLALLTETIFLNQDLEERSETQEQSEEEDSEKLF   350
 351  WLEPCYKALVRHRKDKHVQEAACWALNNLLMYQNSLHEKIGDEDGQFPAH   400
 401  REVMLSMLMHSSSKDVFQAAAHALSTLLEQNVNFRKILLAKGVYLNVLEL   450
 451  MQKHAHAPEVAESGCKMLSHLFEGSNPSLDTMAAVVPKILTVMKAHGTSL   500
 501  SVQLEALRAILHFVVPGLLEESREDSQCRPNVLRKQCFRTDIHKLVLVAL   550
 551  NRFIGNPGIQKCGLKVISSLAHLPDATETLSLQGAVDSVLHTLQMYPDDQ   600
 601  EIQCLGLHLMGCLMTKKNFCIGTGHLLAKILASTLQRFKDVAEVQTTGLQ   650
 651  TTLSILELSVSFSKLLVHYSFDVVIFHQMSSSVVEQKDEQFLNLCCKCFA   700
 701  KVAVDDELKNTMLERACDQNNSIMVECLLLLGADANQVKGATSLIYQVCE   750
 751  KESSPKLVELLLNGGCREQDVRKALTVSIQKGDSQVISLLLRKLALDLAN   800
 801  NSICLGGFGIGKIDPSWLGPLFPDKSSNLRKQTNTGSVLARKVLRYQMRN   850
 851  TLQEGVASGSDGKFSEDALAKFGEWTFIPDSSMDSVFGQSDDLDSEGSES   900
 901  SFLVKRKSNSISVGEVYRDLALQRCSPNAQRHSNSLGPVFDHEDLLRRKR   950
 951  KILSSDESLRSSRLPSHMRQSDSSSSLASEREHITSLDLSANELKDIDAL  1000
1001  SQKCCLSSHLEHLTKLELHQNSLTSFPQQLCETLKCLIHLDLHSNKFTSF  1050
1051  PSFVLKMPRITNLDASRNDIGPTVVLDPAMKCPSLKQLNLSYNQLSSIPE  1100
1101  NLAQVVEKLEQLLLEGNKISGICSPLSLKELKILNLSKNHIPSLPGDFLE  1150
1151  ACSKVESFSARMNFLAAMPALPSSITSLKLSQNSFTCIPEAIFSLPHLRS  1200
1201  LDMSHNNIECLPGPAHWKSLNLRELIFSKNQISTLDFSENPHVWSRVEKL  1250
1251  HLSHNKLKEIPPEIGCLENLTSLDVSYNLELRSFPNEMGKLSKIWDLPLD  1300
1301  GLHLNFDFKHVGCKAKDIIRFLQQRLKKAVPYNRMKLMIVGNTGSGKTTL  1350
1351  LQQLMKMKKPELGMQGATVGIDVRDWSIQIRGKRRKDLVLNVWDFAGREE  1400
1401  FYSTHPHFMTQRALYLAVYDLSKGQAEVDAMKPWLFNIKARASSSPVILV  1450
1451  GTHLDVSDEKQRKACISKITKELLNKRGFPTIRDYHFVNATEESDALAKL  1500
1501  RKTIINESLNFKIRDQPVVGQLIPDCYVELEKIILSERKAVPTEFPVINR  1550
1551  KHLLQLVNEHQLQLDENELPHAVHFLNESGVLLHFQDPALQLSDLYFVEP  1600
1601  KWLCKVMAQILTVKVDGCLKHPKGIISRRDVEKFLSKKKRFPKNYMMQYF  1650
1651  KLLEKFQIALPIGEEYLLVPSSLSDHRPVIELPHCENSEIIIRLYEMPYF  1700
1701  PMGFWSRLINRLLEISPFMLSGRERALRPNRMYWRQGIYLNWSPEAYCLV  1750
1751  GSEVLDNRPESFLKITVPSCRKGCILLGRVVDHIDSLMEEWFPGLLEIDI  1800
1801  CGEGETLLKKWALYSFNDGEEHQKILLDELMKKAEEGDLLINPDQPRLTI  1850
1851  PISQIAPDLILADLPRNIMLNNDELEFEEAPEFLLGDGSFGSVYRAAYEG  1900
1901  EEVAVKIFNKHTSLRLLRQELVVLCHLHHPSLISLLAAGIRPRMLVMELA  1950
1951  SKGSLDRLLQQDKASLTRTLQHRIALHVADGLRYLHSAMIIYRDLKPHNV  2000
2001  LLFTLYPNAAIIAKIADYGIAQYCCRMGIKTSEGTPGFRAPEVARGNVIY  2050
2051  NQQADVYSFGLLLHDIWTTGSRIMEGLRFPNEFDELAIQGKLPDPVKEYG  2100
2101  CAPWPMVEKLITKCLKENPQERPTSAQVFDILNSAELICLMRHILIPKNI  2150
2151  IVECMVATNLNSKSATLWLGCGNTEKGQLSLFDLNTERYSYEEVADSRIL  2200
2201  CLALVHLAAEKESWVVCGTQSGALLVINVEEETKRHTLEKMTDSVTCLHC  2250
2251  NSLAKQSKQSNFLLVGTADGNLMIFEDKAVKCKGAAPLKTLHIGDVSTPL  2300
2301  MCLSESLNSSERHITWGGCGTKVFSFSNDFTIQKLIETKTNQLFSYAAFS  2350
2351  DSNIIALAVDTALYIAKKNSPVVEVWDKKTEKLCELIDCVHFLKEVMVKL  2400
2401  NKESKHQLSYSGRVKALCLQKNTALWIGTGGGHILLLDLSTRRVIRTIHN  2450
2451  FCDSVRAMATAQLGSLKNVMLVLGYKRKSTEGIQEQKEIQSCLSIWDLNL  2500
2501  PHEVQNLEKHIEVRTELADKMRKTSVE                         2527

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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