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

NucPred

Fetching Q9R0M0 from www.uniprot.org...

The NucPred score for your sequence is 0.66 (see score help below)

   1  MRSRAASAPLPTPLLPLLLLLLLLPPSPLLGDQVGPCRSLGSGGRSSSGA    50
  51  CAPVGWLCPASASNLWLYTSRCRESGIELTGHLVPHHDGLRVWCPESGAH   100
 101  IPLPPSSEGCPWSCRLLGIGGHLSPQGTLTLPEEHPCLKAPRLRCQSCKL   150
 151  AQAPGLRAGEGSPEESLGGRRKRNVNTAPQFQPPSYQATVPENQPAGTSV   200
 201  ASLRAIDPDEGEAGRLEYTMDALFDSRSNHFFSLDPITGVVTTAEELDRE   250
 251  TKSTHVFRVTAQDHGMPRRSALATLTILVTDTNDHDPVFEQQEYKESLRE   300
 301  NLEVGYEVLTVRATDGDAPPNANILYRLLEGAGGSPSDAFEIDPRSGVIR   350
 351  TRGPVDREEVESYKLTVEASDQGRDPGPRSSTAIVFLSVEDDNDNAPQFS   400
 401  EKRYVVQVREDVTPGAPVLRVTASDRDKGSNALVHYSIMSGNARGQFYLD   450
 451  AQTGALDVVSPLDYETTKEYTLRIRAQDGGRPPLSNVSGLVTVQVLDIND   500
 501  NAPIFVSTPFQATVLESVPLGYLVLHVQAIDADAGDNARLEYSLAGVGHD   550
 551  FPFTINNGTGWISVAAELDREEVDFYSFGVEARDHGTPALTASASVSVTI   600
 601  LDVNDNNPTFTQPEYTVRLNEDAAVGTSVVTVSAVDRDAHSVITYQITSG   650
 651  NTRNRFSITSQSGGGLVSLALPLDYKLERQYVLAVTASDGTRQDTAQIVV   700
 701  NVTDANTHRPVFQSSHYTVNVNEDRPAGTTVVLISATDEDTGENARITYF   750
 751  MEDSIPQFRIDADTGAVTTQAELDYEDQVSYTLAITARDNGIPQKSDTTY   800
 801  LEILVNDVNDNAPQFLRDSYQGSVYEDVPPFTSVLQISATDRDSGLNGRV   850
 851  FYTFQGGDDGDGDFIVESTSGIVRTLRRLDRENVAQYVLRAYAVDKGMPP   900
 901  ARTPMEVTVTVLDVNDNPPVFEQDEFDVFVEENSPIGLAVARVTATDPDE   950
 951  GTNAQIMYQIVEGNIPEVFQLDIFSGELTALVDLDYEDRPEYVLVIQATS  1000
1001  APLVSRATVHVRLLDRNDNPPVLGNFEILFNNYVTNRSSSFPGGAIGRVP  1050
1051  AHDPDISDSLTYSFERGNELSLVLLNASTGELRLSRALDNNRPLEAIMSV  1100
1101  LVSDGVHSVTAQCSLRVTIITDEMLTHSITLRLEDMSPERFLSPLLGLFI  1150
1151  QAVAATLATPPDHVVVFNVQRDTDAPGGHILNVSLSVGQPPGPGGGPPFL  1200
1201  PSEDLQERLYLNRSLLTAISAQRVLPFDDNICLREPCENYMRCVSVLRFD  1250
1251  SSAPFIASSSVLFRPIHPVGGLRCRCPPGFTGDYCETEVDLCYSRPCGPH  1300
1301  GRCRSREGGYTCLCLDGYTGEHCEASTHSGRCTPGVCKNGGTCVNLLVGG  1350
1351  FKCDCPSGDFEKPFCQVTTRSFPARSFITFRGLRQRFHFTLALSFATKER  1400
1401  NGLLLYNGRFNEKHDFVALEVIQEQVQLTFSAGESTTTVSPFVPGGVSDG  1450
1451  QWHTVQLKYYNKPLLGQTGLPQGPSEQKVAVVSVDGCDTGVALRFGAMLG  1500
1501  NYSCAAQGTQGGSKKSLDLTGPLLLGGVPDLPESFPVRMRHFVGCMKDLQ  1550
1551  VDSRHIDMADFIANNGTVPGCPTKKIVCDSSICHNGGTCVNQWNAFSCEC  1600
1601  PLGFGGKSCAQEMANPQRFLGSSLVAWHGLSLPISQPWHLSLMFRTRQAD  1650
1651  GVLLQAVTRGRSTITLQLRAGHVVLSVEGTGLQASSLRLEPGRANDGDWH  1700
1701  HAQLALGASGGPGHAILSFDYGQQKAEGNLGPRLHGLHLSNITVGGVPGP  1750
1751  ASGVARGFRGCLQGVRVSETPEGISSLDPSRGESINVEPGCSWPDPCDSN  1800
1801  PCPTNSYCSNDWDSYSCSCVLGYYGDNCTNVCDLNPCEHQSVCTRKPNTP  1850
1851  HGYICECLPNYLGPYCETRIDQPCPRGWWGHPTCGPCNCDVSKGFDPDCN  1900
1901  KTSGECHCKENHYRPPGSPTCLLCDCYPTGSLSRVCDPEDGQCPCKPGVI  1950
1951  GRQCDRCDNPFAEVTTNGCEVNYDSCPRAIEAGIWWPRTRFGLPAAAPCP  2000
2001  KGSFGTAVRHCDEHRGWLPPNLFNCTSVTFSELKGFAERLQRNESGLDSG  2050
2051  RSQRLALLLRNATQHTSGYFGSDVKVAYQLATRLLAHESAQRGFGLSATQ  2100
2101  DVHFTENLLRVGSALLDAANKRHWELIQQTEGGTAWLLQHYEAYASALAQ  2150
2151  NMRHTYLSPFTIVTPNIVISVVRLDKGNFAGTKLPRYEALRGERPPDLET  2200
2201  TVILPESVFREMPSMVRSAGPGEAQETEELARRQRRHPELSQGEAVASVI  2250
2251  IYHTLAGLLPHNYDPDKRSLRVPKRPVINTPVVSISVHDDEELLPRALDK  2300
2301  PVTVQFRLLETEERTKPICVFWNHSILVSGTGGWSARGCEVVFRNESHVS  2350
2351  CQCNHMTSFAVLMDMSRRENGEILPLKTLTYVALGVTLAALMLTFLFLTL  2400
2401  LRALRSNQHGIRRNLTAALGLAQLVFLLGINQADLPFACTVIAILLHFLY  2450
2451  LCTFSWALLEALHLYRALTEVRDVNASPMRFYYMLGWGVPAFITGLAVGL  2500
2501  DPEGYGNPDFCWLSVYDTLIWSFAGPVAFAVSMSVFLYILSARASCAAQR  2550
2551  QGFEKKGPVSGLRSSFTVLLLLSATWLLALLSVNSDTLLFHYLFAACNCV  2600
2601  QGPFIFLSYVVLSKEVRKALKFACSRKPSPDPALTTKSTLTSSYNCPSPY  2650
2651  ADGRLYQPYGDSAGSLHSASRSGKSQPSYIPFLLREESTLNPGQVPPGLG  2700
2701  DPSGLFLEGQAQQHDPDTDSDSDLSLEDDQSGSYASTHSSDSEEEEEEAA  2750
2751  FPGEQGWDSLLGPGAERLPLHSTPKDGGPGSGKVPWLGDFGTTTKENSGS  2800
2801  GPLEERPRENGDALTREGSLGPLPGPSTQPHKGILKKKCLPTISEKSSLL  2850
2851  RLPLEQGTGSSRGSSISEGSRHGPPPRPPPRQSLQEQLNGVMPVAMSIKA  2900
2901  GTVDEDSSGSEFLFFNFLH                                 2919

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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