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

NucPred

Fetching P98161 from www.uniprot.org...

The NucPred score for your sequence is 0.26 (see score help below)

   1  MPPAAPARLALALGLGLWLGALAGGPGRGCGPCEPPCLCGPAPGAACRVN    50
  51  CSGRGLRTLGPALRIPADATALDVSHNLLRALDVGLLANLSALAELDISN   100
 101  NKISTLEEGIFANLFNLSEINLSGNPFECDCGLAWLPRWAEEQQVRVVQP   150
 151  EAATCAGPGSLAGQPLLGIPLLDSGCGEEYVACLPDNSSGTVAAVSFSAA   200
 201  HEGLLQPEACSAFCFSTGQGLAALSEQGWCLCGAAQPSSASFACLSLCSG   250
 251  PPPPPAPTCRGPTLLQHVFPASPGATLVGPHGPLASGQLAAFHIAAPLPV   300
 301  TATRWDFGDGSAEVDAAGPAASHRYVLPGRYHVTAVLALGAGSALLGTDV   350
 351  QVEAAPAALELVCPSSVQSDESLDLSIQNRGGSGLEAAYSIVALGEEPAR   400
 401  AVHPLCPSDTEIFPGNGHCYRLVVEKAAWLQAQEQCQAWAGAALAMVDSP   450
 451  AVQRFLVSRVTRSLDVWIGFSTVQGVEVGPAPQGEAFSLESCQNWLPGEP   500
 501  HPATAEHCVRLGPTGWCNTDLCSAPHSYVCELQPGGPVQDAENLLVGAPS   550
 551  GDLQGPLTPLAQQDGLSAPHEPVEVMVFPGLRLSREAFLTTAEFGTQELR   600
 601  RPAQLRLQVYRLLSTAGTPENGSEPESRSPDNRTQLAPACMPGGRWCPGA   650
 651  NICLPLDASCHPQACANGCTSGPGLPGAPYALWREFLFSVPAGPPAQYSV   700
 701  TLHGQDVLMLPGDLVGLQHDAGPGALLHCSPAPGHPGPRAPYLSANASSW   750
 751  LPHLPAQLEGTWACPACALRLLAATEQLTVLLGLRPNPGLRLPGRYEVRA   800
 801  EVGNGVSRHNLSCSFDVVSPVAGLRVIYPAPRDGRLYVPTNGSALVLQVD   850
 851  SGANATATARWPGGSVSARFENVCPALVATFVPGCPWETNDTLFSVVALP   900
 901  WLSEGEHVVDVVVENSASRANLSLRVTAEEPICGLRATPSPEARVLQGVL   950
 951  VRYSPVVEAGSDMVFRWTINDKQSLTFQNVVFNVIYQSAAVFKLSLTASN  1000
1001  HVSNVTVNYNVTVERMNRMQGLQVSTVPAVLSPNATLALTAGVLVDSAVE  1050
1051  VAFLWTFGDGEQALHQFQPPYNESFPVPDPSVAQVLVEHNVMHTYAAPGE  1100
1101  YLLTVLASNAFENLTQQVPVSVRASLPSVAVGVSDGVLVAGRPVTFYPHP  1150
1151  LPSPGGVLYTWDFGDGSPVLTQSQPAANHTYASRGTYHVRLEVNNTVSGA  1200
1201  AAQADVRVFEELRGLSVDMSLAVEQGAPVVVSAAVQTGDNITWTFDMGDG  1250
1251  TVLSGPEATVEHVYLRAQNCTVTVGAASPAGHLARSLHVLVFVLEVLRVE  1300
1301  PAACIPTQPDARLTAYVTGNPAHYLFDWTFGDGSSNTTVRGCPTVTHNFT  1350
1351  RSGTFPLALVLSSRVNRAHYFTSICVEPEVGNVTLQPERQFVQLGDEAWL  1400
1401  VACAWPPFPYRYTWDFGTEEAAPTRARGPEVTFIYRDPGSYLVTVTASNN  1450
1451  ISAANDSALVEVQEPVLVTSIKVNGSLGLELQQPYLFSAVGRGRPASYLW  1500
1501  DLGDGGWLEGPEVTHAYNSTGDFTVRVAGWNEVSRSEAWLNVTVKRRVRG  1550
1551  LVVNASRTVVPLNGSVSFSTSLEAGSDVRYSWVLCDRCTPIPGGPTISYT  1600
1601  FRSVGTFNIIVTAENEVGSAQDSIFVYVLQLIEGLQVVGGGRYFPTNHTV  1650
1651  QLQAVVRDGTNVSYSWTAWRDRGPALAGSGKGFSLTVLEAGTYHVQLRAT  1700
1701  NMLGSAWADCTMDFVEPVGWLMVAASPNPAAVNTSVTLSAELAGGSGVVY  1750
1751  TWSLEEGLSWETSEPFTTHSFPTPGLHLVTMTAGNPLGSANATVEVDVQV  1800
1801  PVSGLSIRASEPGGSFVAAGSSVPFWGQLATGTNVSWCWAVPGGSSKRGP  1850
1851  HVTMVFPDAGTFSIRLNASNAVSWVSATYNLTAEEPIVGLVLWASSKVVA  1900
1901  PGQLVHFQILLAAGSAVTFRLQVGGANPEVLPGPRFSHSFPRVGDHVVSV  1950
1951  RGKNHVSWAQAQVRIVVLEAVSGLQVPNCCEPGIATGTERNFTARVQRGS  2000
2001  RVAYAWYFSLQKVQGDSLVILSGRDVTYTPVAAGLLEIQVRAFNALGSEN  2050
2051  RTLVLEVQDAVQYVALQSGPCFTNRSAQFEAATSPSPRRVAYHWDFGDGS  2100
2101  PGQDTDEPRAEHSYLRPGDYRVQVNASNLVSFFVAQATVTVQVLACREPE  2150
2151  VDVVLPLQVLMRRSQRNYLEAHVDLRDCVTYQTEYRWEVYRTASCQRPGR  2200
2201  PARVALPGVDVSRPRLVLPRLALPVGHYCFVFVVSFGDTPLTQSIQANVT  2250
2251  VAPERLVPIIEGGSYRVWSDTRDLVLDGSESYDPNLEDGDQTPLSFHWAC  2300
2301  VASTQREAGGCALNFGPRGSSTVTIPRERLAAGVEYTFSLTVWKAGRKEE  2350
2351  ATNQTVLIRSGRVPIVSLECVSCKAQAVYEVSRSSYVYLEGRCLNCSSGS  2400
2401  KRGRWAARTFSNKTLVLDETTTSTGSAGMRLVLRRGVLRDGEGYTFTLTV  2450
2451  LGRSGEEEGCASIRLSPNRPPLGGSCRLFPLGAVHALTTKVHFECTGWHD  2500
2501  AEDAGAPLVYALLLRRCRQGHCEEFCVYKGSLSSYGAVLPPGFRPHFEVG  2550
2551  LAVVVQDQLGAAVVALNRSLAITLPEPNGSATGLTVWLHGLTASVLPGLL  2600
2601  RQADPQHVIEYSLALVTVLNEYERALDVAAEPKHERQHRAQIRKNITETL  2650
2651  VSLRVHTVDDIQQIAAALAQCMGPSRELVCRSCLKQTLHKLEAMMLILQA  2700
2701  ETTAGTVTPTAIGDSILNITGDLIHLASSDVRAPQPSELGAESPSRMVAS  2750
2751  QAYNLTSALMRILMRSRVLNEEPLTLAGEEIVAQGKRSDPRSLLCYGGAP  2800
2801  GPGCHFSIPEAFSGALANLSDVVQLIFLVDSNPFPFGYISNYTVSTKVAS  2850
2851  MAFQTQAGAQIPIERLASERAITVKVPNNSDWAARGHRSSANSANSVVVQ  2900
2901  PQASVGAVVTLDSSNPAAGLHLQLNYTLLDGHYLSEEPEPYLAVYLHSEP  2950
2951  RPNEHNCSASRRIRPESLQGADHRPYTFFISPGSRDPAGSYHLNLSSHFR  3000
3001  WSALQVSVGLYTSLCQYFSEEDMVWRTEGLLPLEETSPRQAVCLTRHLTA  3050
3051  FGASLFVPPSHVRFVFPEPTADVNYIVMLTCAVCLVTYMVMAAILHKLDQ  3100
3101  LDASRGRAIPFCGQRGRFKYEILVKTGWGRGSGTTAHVGIMLYGVDSRSG  3150
3151  HRHLDGDRAFHRNSLDIFRIATPHSLGSVWKIRVWHDNKGLSPAWFLQHV  3200
3201  IVRDLQTARSAFFLVNDWLSVETEANGGLVEKEVLAASDAALLRFRRLLV  3250
3251  AELQRGFFDKHIWLSIWDRPPRSRFTRIQRATCCVLLICLFLGANAVWYG  3300
3301  AVGDSAYSTGHVSRLSPLSVDTVAVGLVSSVVVYPVYLAILFLFRMSRSK  3350
3351  VAGSPSPTPAGQQVLDIDSCLDSSVLDSSFLTFSGLHAEQAFVGQMKSDL  3400
3401  FLDDSKSLVCWPSGEGTLSWPDLLSDPSIVGSNLRQLARGQAGHGLGPEE  3450
3451  DGFSLASPYSPAKSFSASDEDLIQQVLAEGVSSPAPTQDTHMETDLLSSL  3500
3501  SSTPGEKTETLALQRLGELGPPSPGLNWEQPQAARLSRTGLVEGLRKRLL  3550
3551  PAWCASLAHGLSLLLVAVAVAVSGWVGASFPPGVSVAWLLSSSASFLASF  3600
3601  LGWEPLKVLLEALYFSLVAKRLHPDEDDTLVESPAVTPVSARVPRVRPPH  3650
3651  GFALFLAKEEARKVKRLHGMLRSLLVYMLFLLVTLLASYGDASCHGHAYR  3700
3701  LQSAIKQELHSRAFLAITRSEELWPWMAHVLLPYVHGNQSSPELGPPRLR  3750
3751  QVRLQEALYPDPPGPRVHTCSAAGGFSTSDYDVGWESPHNGSGTWAYSAP  3800
3801  DLLGAWSWGSCAVYDSGGYVQELGLSLEESRDRLRFLQLHNWLDNRSRAV  3850
3851  FLELTRYSPAVGLHAAVTLRLEFPAAGRALAALSVRPFALRRLSAGLSLP  3900
3901  LLTSVCLLLFAVHFAVAEARTWHREGRWRVLRLGAWARWLLVALTAATAL  3950
3951  VRLAQLGAADRQWTRFVRGRPRRFTSFDQVAQLSSAARGLAASLLFLLLV  4000
4001  KAAQQLRFVRQWSVFGKTLCRALPELLGVTLGLVVLGVAYAQLAILLVSS  4050
4051  CVDSLWSVAQALLVLCPGTGLSTLCPAESWHLSPLLCVGLWALRLWGALR  4100
4101  LGAVILRWRYHALRGELYRPAWEPQDYEMVELFLRRLRLWMGLSKVKEFR  4150
4151  HKVRFEGMEPLPSRSSRGSKVSPDVPPPSAGSDASHPSTSSSQLDGLSVS  4200
4201  LGRLGTRCEPEPSRLQAVFEALLTQFDRLNQATEDVYQLEQQLHSLQGRR  4250
4251  SSRAPAGSSRGPSPGLRPALPSRLARASRGVDLATGPSRTPLRAKNKVHP  4300
4301  SST                                                 4303

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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