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

NucPred

Fetching Q60847 from www.uniprot.org...

The NucPred score for your sequence is 0.40 (see score help below)

   1  MQTRLPRALAALGVALLLSSIEAEVDPPSDLNFKIIDENTVHMSWERPVD    50
  51  PIVGYRITVDPTTDGPTKEFTLAASTTETLLSDLIPETQYVVTITSYNEV   100
 101  EESVPVIGQLTIQTGGPTKPGEKKPGKTEIQKCSVSAWTDLVFLVDGSWS   150
 151  VGRNNFKYILDFIVALVSAFDIGEEKTRVGVVQYSSDTRTEFNLNQYYRR   200
 201  EDLLAAVKKIPYKGGNTMTGDAIDYLVKNTFTESAGSRAGFPKVAIIITD   250
 251  GKSQDEVEIPARELRNIGVEVFSLGIKAADAKELKQIASTPSLNHVFNVA   300
 301  NFDAIVDIQNEIISQVCSGVDEQLGELVSGEEVIEPPSNLVVTELSSKYI   350
 351  RLSWDPSPSAVTGYKILLTPMAAGSRHHALSVGPQTTTLNVRDLTADTEY   400
 401  QISVFAMKGLTSSEPTSVMEKTQPMKVQVECSRGVDIKADIVFLVDGSYS   450
 451  IGIANFVKVRAFLEVLAKSFEISPNRVQISLVQYSRDPHTEFTLKEFNRV   500
 501  EDIIKAINTFPYRGGSTNTGKAMTYVREKIFVPNKGSRSNVPKVMILITD   550
 551  GKSSDAFRDPAIKLRNSDVEIFAVGVKDAVRSELEAIASPPAETHVFTVE   600
 601  DFDAFQRISFELTQSICLRIEQELAAIKKKAYVPPKDLRFTQVTANSFKA   650
 651  EWSPPGDNVFSYHVTYKDANGDDEVTVVEPASSTSVVLNNLRPETLYLVN   700
 701  VTAEYEDGFSVPITGEETTAEVKGVPRNLKVTDETTDSFKLTWSQAPGRV   750
 751  LRYRIRYRPVSGGESKEVSTPANQRRKTLENLTPDTKYEISVIAEYSSGP   800
 801  GSPLTGNAATEEVRGNPRDLRVSDATTSTLKLSWSRAPGKVKQYLVTYTP   850
 851  AAGGETQEVTVRGDTTTTMLRKLKEGTQYDLSVTALYASGAGEALSGKGS   900
 901  TLEERGSPQNLVTKDITDTSIGAYWTSAPGMVRGYRVSWKSLYDDIEAGE   950
 951  TTLPGDAIHTMIENLQPETKYKISVFATYSSGEGEPVTGDATTELSQDSK  1000
1001  ILRVDEETEHTMRVTWKAAPGKVVNYRVVYRPQGGGRQMVAKVPPTVTST  1050
1051  VLKRLQPQTTYDITVLPMYKTGEGKLRQGSGTTASRFKSPRNLKTSDPTM  1100
1101  SSFRVTWEPAPGEVKGYKVTFHPTGDDRRLGELVLGPYDNTVVLEELRAG  1150
1151  TTYRVNVFGMFDGGESLPLVGQEMTTLSDTTVTPFLSSGMDCLTRAEADI  1200
1201  VLLVDGSWSIGRANFRTVRSFISRIVEVFEIGPKRVQIALAQYSGDPRTE  1250
1251  WQLNAHRDKKSLLQAVANLPYKGGNTLTGMALNFIRQQSFKTQAGMRPRA  1300
1301  RKIGVLITDGKSQDDVEAPSKKLKDEGVELFAIGIKNADEVELKMIATDP  1350
1351  DDTHAYNVADFESLSKIVDDLTINLCNSVKGPGDLEAPTNLVISERTHRS  1400
1401  FRVSWTPPSDSVDRYKVEYYPVSGGKRQEFYVSRLDTSTVLKDLKPETDY  1450
1451  VVNVYSVVEDEYSEPLKGTEKTLPVPVVSLNIYDVGPTTMHVQWQPVGGA  1500
1501  TGYTVSYQPTRSPEGTKPKEMRVGPTVNDVQLTGLLPNTEYEVTVQAVLY  1550
1551  DLTSEPAKAREVTLPLPRPQDVKLRDVTHSTMNVVWEPVLGKVRKYIVRY  1600
1601  KTPDEEFKEVEVDRSRASTILKDLSSQTQYTVSVSAVYDEGTSPPATAYD  1650
1651  TTRRVPAPTNLQFTEVTPESFRGTWDHGASDVSLYRITWAPVGNPDKMET  1700
1701  ILNGDENTLVFENLNPNTPYEVSITAIYPDESESEDLSGTERTLRLIPLT  1750
1751  TQAPKSGPRNLQVYNATSNSLTVKWDPASGRVQKYRITYQPSTGEGNEQT  1800
1801  ITVGGRQNSVLLQKLKPDTPYTITVYSQYPDGEGGRMTGRGKTKPLNTVR  1850
1851  NLRVYDPSTSSLSVRWDHAEGNPRQYKLFYAPTSGGPEELVPIPGNTNYA  1900
1901  ILRNLQPDTPYTITVVPVYTEGDGGRTSDTGRTLVRGLARNIQVYNPTPN  1950
1951  SLDVRWDPAPGPVQQYRIVYSPVAGTRPSESIVVPGNTRTVHLERLIPDT  2000
2001  PYSVNIVALYSDGEGNPSPSQGRTLPRSGPRNIRVFGETTNSLSVAWDHA  2050
2051  DGPVQQYRIIYSPTVGDPIDEYTTVPGRRNNVILQPLQPDTPYKITVIAI  2100
2101  YEDGDGGHLTGNGRTVGLLPPQNIHIFDEWYTRFRVSWDPSPSPVLGYKI  2150
2151  VYKPVGSNEPMEAFVGEVTSYTLHNLNPSTTYDVSVYAQYDSGLSVPLTD  2200
2201  QGTTLYLNVTDLKTYQVGWDTFCVKWSPHRAATSYRLKLSPADGTRGQEI  2250
2251  TVRGSETSHCFTGLSPEAEYGVTVFVQTPNLEGPGVPIKEQTTVKPTEAP  2300
2301  TEPPTPSPPPTIPPARDVCKGAKADIVFLTDASWSIGDDNFNKVVKFIFN  2350
2351  TVGAFDEVNPAGIQVSFVQYSDEVKSEFKLNTYNDKALALGALQNIRYRG  2400
2401  GNTRTGKALTFIKEKVLTWESGMRKNVPKVLVVVTDGRSQDEVKKAAFVI  2450
2451  QQSGFSVFVVGVADVDYNELANIASKPSERHVFIVDDFESFEKIEDNLIT  2500
2501  FVCETATSSCPLIYLDGYTSPGFKMLEAYNLTEKNFASVQGVSLESGSFP  2550
2551  SYSAYRLQKNAFINQPTAELHPNGLPPSYTIILLFRLLPETPSDPFAIWQ  2600
2601  ITDRDYRPQVGVIADPSSKTLSFFNKDTRGEVQTVTFDTDEVKTLFYGSF  2650
2651  HKVHIVVTSKSVKIYIDCYEIIEKDIKEAGNITTDGYEILGKLLKGERKS  2700
2701  ATFQIQSFDIVCSPVWTSRDRCCDIPSRRDEAKCPALPNACTCTQDSVGP  2750
2751  PGPPGPAGGPGAKGPRGERGINGAVGPPGPRGDTGPPGPQGPPGPQGPNG  2800
2801  LSIPGEQGRQGMKGDAGEPGLPGRTGTPGLPGPPGPMGPPGDRGFTGKDG  2850
2851  AMGPRGPPGPPGSPGSPGVTGPSGKPGKPGDHGRPGQSGLKGEKGDRGDI  2900
2901  ASQNMMRAVARQVCEQLISGQMSRFNQMLNQIPNDYHSSRNQPGPPGPPG  2950
2951  PPGSAGARGEPGPGGRPGFPGTPGMQGPPGERGLPGEKGERGTGSQGPRG  3000
3001  PPGPPGPQGESRTGPPGSTGSRGPPGPPGRPGNSGIRGPPGPPGYCDSSQ  3050
3051  CASIPYNGQGYPEPYVPEGGAYLPEREPFIVPVEPERTAEYEDDYGADEP  3100
3101  DQQHPDHMRWRRALRPGPAE                                3120

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.)

Go back to the NucPred Home Page.