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

NucPred

Fetching P42859 from www.uniprot.org...

The NucPred score for your sequence is 0.74 (see score help below)

   1  MATLEKLMKAFESLKSFQQQQQQQPPPQAPPPPPPPPPQPPQPPPQGQPP    50
  51  PPPPPLPGPAEEPLHRPKKELSATKKDRVNHCLTICENIVAQSLRNSPEF   100
 101  QKLLGIAMELFLLCSNDAESDVRMVADECLNKVIKALMDSNLPRLQLELY   150
 151  KEIKKNGAPRSLRAALWRFAELAHLVRPQKCRPYLVNLLPCLTRTSKRPE   200
 201  ESVQETLAAAVPKIMASFGNFANDNEIKVLLKAFIANLKSSSPTVRRTAA   250
 251  GSAVSICQHSRRTQYFYNWLLNVLLGLLVPMEEEHSTLLILGVLLTLRCL   300
 301  VPLLQQQVKDTSLKGSFGVTRKEMEVSPSTEQLVQVYELTLHHTQHQDHN   350
 351  VVTGALELLQQLFRTPPPELLQALTTPGGLGQLTLVQEEARGRGRSGSIV   400
 401  ELLAGGGSSCSPVLSRKQKGKVLLGEEEALEDDSESRSDVSSSAFAASVK   450
 451  SEIGGELAASSGVSTPGSVGHDIITEQPRSQHTLQADSVDLSGCDLTSAA   500
 501  TDGDEEDILSHSSSQFSAVPSDPAMDLNDGTQASSPISDSSQTTTEGPDS   550
 551  AVTPSDSSEIVLDGADSQYLGMQIGQPQEDDEEGAAGVLSGEVSDVFRNS   600
 601  SLALQQAHLLERMGHSRQPSDSSIDKYVTRDEVAEASDPESKPCRIKGDI   650
 651  GQPNDDDSAPLVHCVRLLSASFLLTGEKKALVPDRDVRVSVKALALSCIG   700
 701  AAVALHPESFFSRLYKVPLNTTESTEEQYVSDILNYIDHGDPQVRGATAI   750
 751  LCGTLVYSILSRSRLRVGDWLGNIRTLTGNTFSLVDCIPLLQKTLKDESS   800
 801  VTCKLACTAVRHCVLSLCSSSYSDLGLQLLIDMLPLKNSSYWLVRTELLD   850
 851  TLAEIDFRLVSFLEAKAESLHRGAHHYTGFLKLQERVLNNVVIYLLGDED   900
 901  PRVRHVAATSLTRLVPKLFYKCDQGQADPVVAVARDQSSVYLKLLMHETQ   950
 951  PPSHFSVSTITRIYRGYSLLPSITDVTMENNLSRVVAAVSHELITSTTRA  1000
1001  LTFGCCEALCLLSAAFPVCTWSLGWHCGVPPLSASDESRKSCTVGMASMI  1050
1051  LTLLSSAWFPLDLSAHQDALILAGNLLAASAPKSLRSSWTSEEEANSAAT  1100
1101  RQEEIWPALGDRTLVPLVEQLFSHLLKVINICAHVLDDVTPGPAIKAALP  1150
1151  SLTNPPSLSPIRRKGKEKEPGEQASTPMSPKKVGEASAASRQSDTSGPVT  1200
1201  ASKSSSLGSFYHLPSYLKLHDVLKATHANYKVTLDLQNSTEKFGGFLRSA  1250
1251  LDVLSQILELATLQDIGKCVEEVLGYLKSCFSREPMMATVCVQQLLKTLF  1300
1301  GTNLASQFDGLSSNPSKSQCRAQRLGSSSVRPGLYHYCFMAPYTHFTQAL  1350
1351  ADASLRNMVQAEQERDASGWFDVLQKVSAQLKTNLTSVTKNRADKNAIHN  1400
1401  HIRLFEPLVIKALKQYTTTTSVQLQKQVLDLLAQLVQLRVNYCLLDSDQV  1450
1451  FIGFVLKQFEYIEVGQFRESEAIIPNIFFFLVLLSYERYHSKQIIGIPKI  1500
1501  IQLCDGIMASGRKAVTHAIPALQPIVHDLFVLRGTNKADAGKELETQKEV  1550
1551  VVSMLLRLIQYHQVLEMFILVLQQCHKENEDKWKRLSRQVADIILPMLAK  1600
1601  QQMHIDSHEALGVLNTLFEILAPSSLRPVDMLLRSMFITPSTMASVSTVQ  1650
1651  LWISGILAILRVLISQSTEDIVLCRIQELSFSPHLLSCPVINRLRGGGGN  1700
1701  VTLGECSEGKQKSLPEDTFSRFLLQLVGILLEDIVTKQLKVDMSEQQHTF  1750
1751  YCQELGTLLMCLIHIFKSGMFRRITAAATRLFTSDGCEGSFYTLESLNAR  1800
1801  VRSMVPTHPALVLLWCQILLLINHTDHRWWAEVQQTPKRHSLSCTKSLNP  1850
1851  QKSGEEEDSGSAAQLGMCNREIVRRGALILFCDYVCQNLHDSEHLTWLIV  1900
1901  NHIQDLISLSHEPPVQDFISAIHRNSAASGLFIQAIQSRCENLSTPTTLK  1950
1951  KTLQCLEGIHLSQSGAVLTLYVDRLLGTPFRALARMVDTLACRRVEMLLA  2000
2001  ANLQSSMAQLPEEELNRIQEHLQNSGLAQRHQRLYSLLDRFRLSTVQDSL  2050
2051  SPLPPVTSHPLDGDGHTSLETVSPDKDWYLQLVRSQCWTRSDSALLEGAE  2100
2101  LVNRIPAEDMNDFMMSSEFNLSLLAPCLSLGMSEIANGQKSPLFEAARGV  2150
2151  ILNRVTSVVQQLPAVHQVFQPFLPIEPTAYWNKLNDLLGDTTSYQSLTIL  2200
2201  ARALAQYLVVLSKVPAHLHLPPEKEGDTVKFVVMTVEALSWHLIHEQIPL  2250
2251  SLDLQAGLDCCCLALQVPGLWGVLSSPEYVTHACSLIHCVRFILEAIAVQ  2300
2301  PGDQLLGPESRSHTPRAVRKEEVDSDIQNLSHVTSACEMVADMVESLQSV  2350
2351  LALGHKRNSTLPSFLTAVLKNIVISLARLPLVNSYTRVPPLVWKLGWSPK  2400
2401  PGGDFGTVFPEIPVEFLQEKEILKEFIYRINTLGWTNRTQFEETWATLLG  2450
2451  VLVTQPLVMEQEESPPEEDTERTQIHVLAVQAITSLVLSAMTVPVAGNPA  2500
2501  VSCLEQQPRNKPLKALDTRFGRKLSMIRGIVEQEIQEMVSQRENTATHHS  2550
2551  HQAWDPVPSLLPATTGALISHDKLLLQINPEREPGNMSYKLGQVSIHSVW  2600
2601  LGNNITPLREEEWDEEEEEESDVPAPTSPPVSPVNSRKHRAGVDIHSCSQ  2650
2651  FLLELYSRWILPSSAARRTPVILISEVVRSLLVVSDLFTERTQFEMMYLT  2700
2701  LTELRRVHPSEDEILIQYLVPATCKAAAVLGMDKTVAEPVSRLLESTLRS  2750
2751  SHLPSQIGALHGILYVLECDLLDDTAKQLIPVVSDYLLSNLKGIAHCVNI  2800
2801  HSQQHVLVMCATAFYLMENYPLDVGPEFSASVIQMCGVMLSGSEESTPSI  2850
2851  IYHCALRGLERLLLSEQLSRLDTESLVKLSVDRVNVQSPHRAMAALGLML  2900
2901  TCMYTGKEKASPGRASDPSPATPDSESVIVAMERVSVLFDRIRKGFPCEA  2950
2951  RVVARILPQFLDDFFPPQDVMNKVIGEFLSNQQPYPQFMATVVYKVFQTL  3000
3001  HSAGQSSMVRDWVMLSLSNFTQRTPVAMAMWSLSCFLVSASTSPWVSAIL  3050
3051  PHVISRMGKLEQVDVNLFCLVATDFYRHQIEEEFDRRAFQSVFEVVAAPG  3100
3101  SPYHRLLACLQNVHKVTTC                                 3119

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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