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

NucPred

Fetching Q13535 from www.uniprot.org...

The NucPred score for your sequence is 0.89 (see score help below)

   1  MGEHGLELASMIPALRELGSATPEEYNTVVQKPRQILCQFIDRILTDVNV    50
  51  VAVELVKKTDSQPTSVMLLDFIQHIMKSSPLMFVNVSGSHEAKGSCIEFS   100
 101  NWIITRLLRIAATPSCHLLHKKICEVICSLLFLFKSKSPAIFGVLTKELL   150
 151  QLFEDLVYLHRRNVMGHAVEWPVVMSRFLSQLDEHMGYLQSAPLQLMSMQ   200
 201  NLEFIEVTLLMVLTRIIAIVFFRRQELLLWQIGCVLLEYGSPKIKSLAIS   250
 251  FLTELFQLGGLPAQPASTFFSSFLELLKHLVEMDTDQLKLYEEPLSKLIK   300
 301  TLFPFEAEAYRNIEPVYLNMLLEKLCVMFEDGVLMRLKSDLLKAALCHLL   350
 351  QYFLKFVPAGYESALQVRKVYVRNICKALLDVLGIEVDAEYLLGPLYAAL   400
 401  KMESMEIIEEIQCQTQQENLSSNSDGISPKRRRLSSSLNPSKRAPKQTEE   450
 451  IKHVDMNQKSILWSALKQKAESLQISLEYSGLKNPVIEMLEGIAVVLQLT   500
 501  ALCTVHCSHQNMNCRTFKDCQHKSKKKPSVVITWMSLDFYTKVLKSCRSL   550
 551  LESVQKLDLEATIDKVVKIYDALIYMQVNSSFEDHILEDLCGMLSLPWIY   600
 601  SHSDDGCLKLTTFAANLLTLSCRISDSYSPQAQSRCVFLLTLFPRRIFLE   650
 651  WRTAVYNWALQSSHEVIRASCVSGFFILLQQQNSCNRVPKILIDKVKDDS   700
 701  DIVKKEFASILGQLVCTLHGMFYLTSSLTEPFSEHGHVDLFCRNLKATSQ   750
 751  HECSSSQLKASVCKPFLFLLKKKIPSPVKLAFIDNLHHLCKHLDFREDET   800
 801  DVKAVLGTLLNLMEDPDKDVRVAFSGNIKHILESLDSEDGFIKELFVLRM   850
 851  KEAYTHAQISRNNELKDTLILTTGDIGRAAKGDLVPFALLHLLHCLLSKS   900
 901  ASVSGAAYTEIRALVAAKSVKLQSFFSQYKKPICQFLVESLHSSQMTALP   950
 951  NTPCQNADVRKQDVAHQREMALNTLSEIANVFDFPDLNRFLTRTLQVLLP  1000
1001  DLAAKASPAASALIRTLGKQLNVNRREILINNFKYIFSHLVCSCSKDELE  1050
1051  RALHYLKNETEIELGSLLRQDFQGLHNELLLRIGEHYQQVFNGLSILASF  1100
1101  ASSDDPYQGPRDIISPELMADYLQPKLLGILAFFNMQLLSSSVGIEDKKM  1150
1151  ALNSLMSLMKLMGPKHVSSVRVKMMTTLRTGLRFKDDFPELCCRAWDCFV  1200
1201  RCLDHACLGSLLSHVIVALLPLIHIQPKETAAIFHYLIIENRDAVQDFLH  1250
1251  EIYFLPDHPELKKIKAVLQEYRKETSESTDLQTTLQLSMKAIQHENVDVR  1300
1301  IHALTSLKETLYKNQEKLIKYATDSETVEPIISQLVTVLLKGCQDANSQA  1350
1351  RLLCGECLGELGAIDPGRLDFSTTETQGKDFTFVTGVEDSSFAYGLLMEL  1400
1401  TRAYLAYADNSRAQDSAAYAIQELLSIYDCREMETNGPGHQLWRRFPEHV  1450
1451  REILEPHLNTRYKSSQKSTDWSGVKKPIYLSKLGSNFAEWSASWAGYLIT  1500
1501  KVRHDLASKIFTCCSIMMKHDFKVTIYLLPHILVYVLLGCNQEDQQEVYA  1550
1551  EIMAVLKHDDQHTINTQDIASDLCQLSTQTVFSMLDHLTQWARHKFQALK  1600
1601  AEKCPHSKSNRNKVDSMVSTVDYEDYQSVTRFLDLIPQDTLAVASFRSKA  1650
1651  YTRAVMHFESFITEKKQNIQEHLGFLQKLYAAMHEPDGVAGVSAIRKAEP  1700
1701  SLKEQILEHESLGLLRDATACYDRAIQLEPDQIIHYHGVVKSMLGLGQLS  1750
1751  TVITQVNGVHANRSEWTDELNTYRVEAAWKLSQWDLVENYLAADGKSTTW  1800
1801  SVRLGQLLLSAKKRDITAFYDSLKLVRAEQIVPLSAASFERGSYQRGYEY  1850
1851  IVRLHMLCELEHSIKPLFQHSPGDSSQEDSLNWVARLEMTQNSYRAKEPI  1900
1901  LALRRALLSLNKRPDYNEMVGECWLQSARVARKAGHHQTAYNALLNAGES  1950
1951  RLAELYVERAKWLWSKGDVHQALIVLQKGVELCFPENETPPEGKNMLIHG  2000
2001  RAMLLVGRFMEETANFESNAIMKKYKDVTACLPEWEDGHFYLAKYYDKLM  2050
2051  PMVTDNKMEKQGDLIRYIVLHFGRSLQYGNQFIYQSMPRMLTLWLDYGTK  2100
2101  AYEWEKAGRSDRVQMRNDLGKINKVITEHTNYLAPYQFLTAFSQLISRIC  2150
2151  HSHDEVFVVLMEIIAKVFLAYPQQAMWMMTAVSKSSYPMRVNRCKEILNK  2200
2201  AIHMKKSLEKFVGDATRLTDKLLELCNKPVDGSSSTLSMSTHFKMLKKLV  2250
2251  EEATFSEILIPLQSVMIPTLPSILGTHANHASHEPFPGHWAYIAGFDDMV  2300
2301  EILASLQKPKKISLKGSDGKFYIMMCKPKDDLRKDCRLMEFNSLINKCLR  2350
2351  KDAESRRRELHIRTYAVIPLNDECGIIEWVNNTAGLRPILTKLYKEKGVY  2400
2401  MTGKELRQCMLPKSAALSEKLKVFREFLLPRHPPIFHEWFLRTFPDPTSW  2450
2451  YSSRSAYCRSTAVMSMVGYILGLGDRHGENILFDSLTGECVHVDFNCLFN  2500
2501  KGETFEVPEIVPFRLTHNMVNGMGPMGTEGLFRRACEVTMRLMRDQREPL  2550
2551  MSVLKTFLHDPLVEWSKPVKGHSKAPLNETGEVVNEKAKTHVLDIEQRLQ  2600
2601  GVIKTRNRVTGLPLSIEGHVHYLIQEATDENLLCQMYLGWTPYM        2644

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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