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

NucPred

Fetching Q7RZT9 from www.uniprot.org...

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

   1  MAPATETVDFKKLIVTLNGKTITGRTSALKSLISYFKGDETGSQAESHSQ    50
  51  KLFDDKTYHYVYEALFTCALTEKADYFSCLKSSKSDSVRNSCVKRLEGCA   100
 101  EALRLAVQHGAYKIKRKTATAIADHITQTLLDSDDNFFEPLLKGYVKVLS   150
 151  AFLNIQVNVENLAAFGGEKWESSIDLCLNAISRFLEAAEHDSGTSVRASP   200
 201  APGTPATSRAGSVGPLSASVQVNGQLAIEFLACVKALTSASNAPVLRRAK   250
 251  RISQLVLRLLTLRHIKLGELQRDSFSILNNILVRVQTESIALTNTITTAL   300
 301  VPVLSHCWQPRSLSRDAMSTSLKDEMLKTLYGIHLYLESLLREATDDKLL   350
 351  QDTEDLLDSLWSEYSRRDDKTRLQLGDVTFSAMQLHPDHPLTMVFGLRPY   400
 401  HLAGEQNWALLENIALLEIVYAKNSQRDRQHLEDEPDKPRKRRRVIGSSN   450
 451  RIHQKLMSQDPAVQLTALQLIPFLSALKHPSLEEVKGALVDLSQFISAKQ   500
 501  GLVASWAMIACSSLAAHKTSRDPSLSAMWKQAWHIGIRSLSLPSTSRSAC   550
 551  VLLNWILKAKLLSDHEIAGDVNQIITTADISGPAMLVDSAPVLMLTLLRI   600
 601  RNAIFPNASQSTSSHVIRWVFLKWNPCESAYASVHGVHAAPVDLINLLRA   650
 651  CYEMPPLRMNTSLTVFDGPVAQFRAVQKQRHAMLRYLLLLEDEAPPEDSH   700
 701  KATSTDQPKREEIRAADSSSSHSAKRLILELLFPKLDELLQMVELWHKRG   750
 751  ESDSAAPVSTDRLVSVASTCIVGAFIMPELVGLNSSMSRDLEKTVFGIVE   800
 801  GMIKAIAESPQSEDFFNLVLEVSAPYIPTLGEAELTHFKREEPYALRLFA   850
 851  TVSNSLLEKTRRESPTDSDPASMDLDDEFDSQETRKSTTAGKRFLSRRDI   900
 901  TLKHTPEAFYLDTSLRLHLLRIIRADDGELGRVPDPIVDHLLELSDEDLL   950
 951  SCRLFMQELFASDVVTPVDLAIRMIERIAATISNNQYTCCEAAMCTVMDI  1000
1001  MEGFITMWTDEELEISNLVGDIYDHLIKRALPNNSLSSTAQIWFSRLLFR  1050
1051  LLEVNPMFASQVLKLPSTRSTLLTILRDAPMDVKFFIGINLPRIFGMHVL  1100
1101  QTHDDIIVEILEVLPGEGMEGIAFRLFVLAELACKWPTLLRRCAYHIFET  1150
1151  PGKNQTSASHATSCLKRVSRCLNLSSPQELFTIFAPQILYTWLAIDSIDE  1200
1201  IPYSIFGFSNLAELLSKSQSEAVGIMIMRGHETDARELAKTLKLSIQELV  1250
1251  TQNFSKIVAYSIAQDSSLPNEVTGESRVRRIIGAEPYSSNIILNFADILA  1300
1301  IFFEICDQEYPIEDSFRKDAANFAYAADIMDKIKAFGHLDTMLPPNQQPS  1350
1351  YKAKFLKRQILHLVKRTNYELHDIWTPALVVFVARKLLNTIHPALGPLHA  1400
1401  CSVLRKIRVLICLAGDTALYGYPLEMLLHSLRAFVVDPECADDALGITQY  1450
1451  LITEGSDHLIRFPSFLAGYALSCLADLRVFLESSQSSTTQESQFKATKSK  1500
1501  AQLFHAWFSKYLANYTTNAWKDKTQKEAFEAITQSAANIRVMGNAEKGTH  1550
1551  ESKLLLEILKDWGRQHQLLNGPARSVALSILCGSFNVPPPSRLDVIQSDE  1600
1601  EALAHGAAVWMSCGSKKLSSEYLAWAGRVIGRSYAASGDVPPELLRESRL  1650
1651  QEYRKKSPVNFDFMESEEALLSLIEALTASSDGFRAGLAEAALRVAVSDA  1700
1701  LHENDRPLITACQKSLSESLLVASEWGELRIPRSDRFSVEHPNETEIFSA  1750
1751  EFLESPEWAQQLTTLLAQSVPGSVALRVLPPILTKVKGFAEQAFPFIVHN  1800
1801  VLEYELDQTQGMKQKLSEALKEWLTSTSPAARDNQKLLINTILYLRTQAN  1850
1851  PNETSIADRLHWLEVNFSIAAAAATRCGMYKVALLFAELASTEITRQSRR  1900
1901  SSAIQGLGDTSEILLDIFENIDDPDAYYGLTQDASLSTVLARLEYENDGT  1950
1951  KSLAFRGAQYDSHLRRRDVASQQDGQALIKALSSLGLAGLSNSLLQTQQS  2000
2001  LDGSSTSLDSTFITARRLEIWNLPAPAATENWAVTVYKAYQSMHQASDIN  2050
2051  MVRSAVHDGLTKTLKHLTGKSLNTLTLRHQLGALATLAELDDVLNTGDLS  2100
2101  ELNGIIEDFQARSKWMMSGQYDDVSRILSCRETTLSLWSQRHNLRPARLT  2150
2151  PANARLAQIRGMLVSSDIYRFHRATQETLNLSTTLTDLIRPSEQMGLAVD  2200
2201  AAIRMETANSLWDQGEMISSIRMLQNIDKESPLEKQTVPVSRSDLLSKIG  2250
2251  YQVSVARLESPDTIQKNYLEPALKELKGKSEGKEAGRVYHQFAMFCDEQL  2300
2301  QNPDGLEDLARLQNLERGKNDEVTQLKALIASTRDSQLKNKYSSHLSKAK  2350
2351  QWLDLDQQELRRVEQTRSEFVRLSLQNYLLSLAASDEYNNDALRFTALWL  2400
2401  ECSEDDMVNEVVKRYLSKVPTRKFAPLINQLSSRLQHQEGLFQITLIGLV  2450
2451  YSICLDHPYHGMYQIWSGVKARSIKNDEVALSRQKATDKIARAIKKSGAS  2500
2501  AAKIYLAINATSKVYHNLAMDRDAKKYKAGHKMNIKDSKAGLEFLAAFAE  2550
2551  FPIPPPTMQMPLLASCDYSQVPMIVKFEPQMSIASGVSAPKIITAIGSDG  2600
2601  RQYKQLVKGGNDDLRQDAIMEQVFAAVSELLKHHRATRQRNLGIRTYKVL  2650
2651  PLTETTGVIEFVSNTIPLHEYLMPAHEIYYPKDLKGSHCRKEIMNAQSKS  2700
2701  VDTRVAVYRKVTERFHPVMRYFFMEWFPDPDEWFARRTAYTRTTAAISML  2750
2751  GHVLGLGDRHGHNILLDTKTGEVVHIDLGVAFELGRILPVPELVPFRLTR  2800
2801  DIVDGMGITKTEGVFRRCCEFTLDALREETYSIMTILDVLRYDPLYSWSM  2850
2851  SPLRMARLQNVRVGAGEDDVVEAEDERRAGDKKSTKNLNEPSEADRALEV  2900
2901  VRKKLSKTLSVMATVNDLINQATDERNLAVLFCGWAAYA             2939

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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