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

NucPred

Fetching Q00798 from www.uniprot.org...

The NucPred score for your sequence is 0.86 (see score help below)

   1  MKRGICLAALLCLFNYLGAGHGENAEEDIRNSEGKVNFFSLDSNLKKNKK    50
  51  SKHNRVKRRNAKISNFLSQKAYVKETDNASGKDAEGSRPSHDSSFVNLNG   100
 101  HVDGKSLSYSVHVKESTPHSTTRESTEKGKENEKIQGVLSSFVQSQEGGE   150
 151  SDDLEGMYNSIVDMSEKLKENDKYNLVFDMEIDFVDLQFFNLILELIPKD   200
 201  SQYHTYYEETLKQQVTEYTNSLKTLMDSCISEKDQMIILEYEINYAKRKS   250
 251  IETETLGDKETKLSAVSQAYAKHLESYKGVLKPKLNDIKNNAFSVLKDSY   300
 301  CKDNCGEYVQKYNTMRKNFISSSDQYKMEAYVYIPKSINDYTVLDKILSE   350
 351  SNELGIDIQETVNSLKLLGEEISEVSHLYVINSTLIDDAAKKLESINEED   400
 401  ESAEIDLQKFEDNSKALANNYCIFQYIKTLNEPIKKAYESKVIKSNELLS   450
 451  TIIDTLGKSATALQESTFDQEECNKIKTEAEKVKDDAEDICEKNEQIYYE   500
 501  IPESEDETIDDKINDLQDLIDQMKEYKDEIVNNSEFISNRYKNIYENLKE   550
 551  TYETELNDIGKLENDTSKVNFYLMQIRKINTEKTKIDESLQTVEKFYKEI   600
 601  LDSKEKIYELKIEFEKSVTEINRLQDGESARDLHEEQIKEILDKMAKKVH   650
 651  YLKELLSLKGKSSVYFTEMNELLNTASYDNMEGFSAKKEKADNDINALYN   700
 701  SVYREDINALIEEVEKFVTENKESTLEMLKDEEMEEKLQDAKETFAKLNF   750
 751  VSDDKLTDVYTKMSAEVTNAEGIKKEIAQKQFENVHKKMKEFSDAFSTKF   800
 801  EALQNSMQQYNQEGDAIEKHKQNRSEKEEEYFKNESVEEDLSREETEEQE   850
 851  YTKHKNNFSRRKGEISAEITNMREVINKIESQLNYYGVIEKYFSLIGDQN   900
 901  EVSTAKALKEKIVSDSLRDKIDQYETEFKEKTSAVENTVSTIQSLSKAID   950
 951  SLKRLNGSINNCKKYNTDIDLLRSKIKTLREEVQKEIAETEGDKVVGENT  1000
1001  TALLLKSLRDKMGKINEKLNDGRLNSLDTKKEDLLKFYSESKSKIHLSKD  1050
1051  QKGPQDPLNRIDEWEDIKREVDELNVNYQVISENKVTLFKNNSVTYIEAM  1100
1101  HSHINTVAHGITSNKNEILKSVKEVEDKLNLVEQNEDYKKVKNPENEKQL  1150
1151  EAIRGSMSKLKEVINKHVSEMTQLESTANTLKSNAKGKENEHDLEELNKT  1200
1201  KGQMRDIYEKLKKIAEELKEGTVNELKDANEKANKVELEFERNIIGHVLE  1250
1251  RITVEKDKAGKVVEEMNSLKTKIEKLIQETSDDSQNELVTTSITKHLENA  1300
1301  KGYEDVIKRNEEDSIQLREKAKSLETLDEMKKLVQQVNMNLQSAIQGNAG  1350
1351  ISKELNELKGVIELLISTNYSSILEYVKKNSSESVRFSQLANGEFTKAEG  1400
1401  EEKNASARLAEAEKLKEQIVKDLDYSDIDDKVKKIEGIKREILKMKESAL  1450
1451  TFWEESEKFKQMCSSHMENAKEGKKKIEYLKNNGDGGKANITDSQMEEVG  1500
1501  NYVSKAEHAFHTVEAQVDKTKAFYESIVAYVTKMDNLFNESLMKEVKVKC  1550
1551  EKKNDEAEQIFGQIKTVDGRIKARVSENERKISELKEKAKVEKKESSQLN  1600
1601  DVSTKSLLQIDNCRQQLDSVLSNIGRVKQNALQYFDSADKSMKSVLPISE  1650
1651  LGAEKSLDKVKAAKESYEKNLETVQNEMSRINVEEGSLTDIDKKITDIEN  1700
1701  DLLKMKKQYEEGLLQKIKENADKRKSNFELVGSEINALLDPSTSIFIKLK  1750
1751  LKEYDMTGDLKNYAVKMNEIHGEFTKSYNLIETHLSNATDYSVTFEKAQS  1800
1801  LRELAEKEEEHLRRREEEAIKLLNDIKKVESLKLLKEMMKKVSAEYEGMK  1850
1851  RDHTSVSQLVQDMKTIVDELKTLNDISECSSVLNNVVSIVKKVKESKHAD  1900
1901  YKRDANSMYESMVTLANYFLSDEAKISSGMEFNAEMKSNFKTDLELEIFS  1950
1951  VISNSNELLKKIEQDSNDVIQKERESEQLAKDATDIYNVIKLKNEFNEKL  2000
2001  EEAKNKEEVVSEKVREALKRLSQVEGIRCHFENFHRLLDNTEELENLKKM  2050
2051  VTIYRDKKSEAPKESGLQEMENEMNTYSNSITQLEGIVVSAGESKEDIEK  2100
2101  LERSNEEMRNISEKISTIDSKVIEMNSTIDELYKLGKNCQAHWISLISYT  2150
2151  ANMKTSKKLIMINKEKENTEKCVDYIKDNSSSTDGYVETLKGFYGSKLTF  2200
2201  SSASEIVQNADTYSVNFAKHEKESLNAIRDIKKELYLFHQNSDISIVEGG  2250
2251  VQNMLALYDKLNEEKREMDELYRNISETKLKQMEHSTDVFKPMIELHKGM  2300
2301  NETNNKSLLEKEKKLKSVNDHMHSMEAEMIKNGLKYTPESVQNINNIYSV  2350
2351  IEAEVKTLEEIDRDYGDNYQIVEEHKKQFSILIDRTNALMDDIEIFKKEN  2400
2401  NYNLMEVNTETIHRVNDYIEKITNKLVQAKTEYEQILENIKQNDDMLQNI  2450
2451  FLKKVSIIEYFENVKKKKESILNDLYEQERLLKIGEHLDEIKRNVTETLS  2500
2501  SYEIDQKMEMMSKNLLEKKSKMMNYTSIYELEREANEINRDAKQIKDDDT  2550
2551  ILNSVLEAAIQKRGDMDAIFSQMSADRNPNEYKSAEKYMNEANEIIRQLE  2600
2601  VKLREIGQLVQDSESILSEMNSKKSAIEKEKTARALRTSENNRREEEERA  2650
2651  RVQEMSMNNDPTQSETTHSEGSIGEGKESDSDETGLTHDAGADEDSTSSA  2700
2701  KGAHELEEEETTAPMEETEMNDNTLLGYDTTRSDEPDMHTENTQDGTYQD  2750
2751  TSNSSDEADILNGKFNFNNVKYAGAFVLLCTSAVIGAIIAHKKDDQEELN  2800
2801  NGVEDDKVFEVKKSMHPENKEEIIDDSFVDIEY                   2833

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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