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

NucPred

Fetching Q12955 from www.uniprot.org...

The NucPred score for your sequence is 0.96 (see score help below)

   1  MAHAASQLKKNRDLEINAEEEPEKKRKHRKRSRDRKKKSDANASYLRAAR    50
  51  AGHLEKALDYIKNGVDINICNQNGLNALHLASKEGHVEVVSELLQREANV   100
 101  DAATKKGNTALHIASLAGQAEVVKVLVTNGANVNAQSQNGFTPLYMAAQE   150
 151  NHLEVVKFLLDNGASQSLATEDGFTPLAVALQQGHDQVVSLLLENDTKGK   200
 201  VRLPALHIAARKDDTKAAALLLQNDNNADVESKSGFTPLHIAAHYGNINV   250
 251  ATLLLNRAAAVDFTARNDITPLHVASKRGNANMVKLLLDRGAKIDAKTRD   300
 301  GLTPLHCGARSGHEQVVEMLLDRAAPILSKTKNGLSPLHMATQGDHLNCV   350
 351  QLLLQHNVPVDDVTNDYLTALHVAAHCGHYKVAKVLLDKKANPNAKALNG   400
 401  FTPLHIACKKNRIKVMELLLKHGASIQAVTESGLTPIHVAAFMGHVNIVS   450
 451  QLMHHGASPNTTNVRGETALHMAARSGQAEVVRYLVQDGAQVEAKAKDDQ   500
 501  TPLHISARLGKADIVQQLLQQGASPNAATTSGYTPLHLSAREGHEDVAAF   550
 551  LLDHGASLSITTKKGFTPLHVAAKYGKLEVANLLLQKSASPDAAGKSGLT   600
 601  PLHVAAHYDNQKVALLLLDQGASPHAAAKNGYTPLHIAAKKNQMDIATTL   650
 651  LEYGADANAVTRQGIASVHLAAQEGHVDMVSLLLGRNANVNLSNKSGLTP   700
 701  LHLAAQEDRVNVAEVLVNQGAHVDAQTKMGYTPLHVGCHYGNIKIVNFLL   750
 751  QHSAKVNAKTKNGYTPLHQAAQQGHTHIINVLLQNNASPNELTVNGNTAL   800
 801  GIARRLGYISVVDTLKIVTEETMTTTTVTEKHKMNVPETMNEVLDMSDDE   850
 851  VRKANAPEMLSDGEYISDVEEGEDAMTGDTDKYLGPQDLKELGDDSLPAE   900
 901  GYMGFSLGARSASLRSFSSDRSYTLNRSSYARDSMMIEELLVPSKEQHLT   950
 951  FTREFDSDSLRHYSWAADTLDNVNLVSSPIHSGFLVSFMVDARGGSMRGS  1000
1001  RHHGMRIIIPPRKCTAPTRITCRLVKRHKLANPPPMVEGEGLASRLVEMG  1050
1051  PAGAQFLGPVIVEIPHFGSMRGKERELIVLRSENGETWKEHQFDSKNEDL  1100
1101  TELLNGMDEELDSPEELGKKRICRIITKDFPQYFAVVSRIKQESNQIGPE  1150
1151  GGILSSTTVPLVQASFPEGALTKRIRVGLQAQPVPDEIVKKILGNKATFS  1200
1201  PIVTVEPRRRKFHKPITMTIPVPPPSGEGVSNGYKGDTTPNLRLLCSITG  1250
1251  GTSPAQWEDITGTTPLTFIKDCVSFTTNVSARFWLADCHQVLETVGLATQ  1300
1301  LYRELICVPYMAKFVVFAKMNDPVESSLRCFCMTDDKVDKTLEQQENFEE  1350
1351  VARSKDIEVLEGKPIYVDCYGNLAPLTKGGQQLVFNFYSFKENRLPFSIK  1400
1401  IRDTSQEPCGRLSFLKEPKTTKGLPQTAVCNLNITLPAHKKETESDQDDE  1450
1451  IEKTDRRQSFASLALRKRYSYLTEPGMIERSTGATRSLPTTYSYKPFFST  1500
1501  RPYQSWTTAPITVPGPAKSGFTSLSSSSSNTPSASPLKSIWSVSTPSPIK  1550
1551  STLGASTTSSVKSISDVASPIRSFRTMSSPIKTVVSQSPYNIQVSSGTLA  1600
1601  RAPAVTEATPLKGLASNSTFSSRTSPVTTAGSLLERSSITMTPPASPKSN  1650
1651  INMYSSSLPFKSIITSAAPLISSPLKSVVSPVKSAVDVISSAKITMASSL  1700
1701  SSPVKQMPGHAEVALVNGSISPLKYPSSSTLINGCKATATLQEKISSATN  1750
1751  SVSSVVSAATDTVEKVFSTTTAMPFSPLRSYVSAAPSAFQSLRTPSASAL  1800
1801  YTSLGSSISATTSSVTSSIITVPVYSVVNVLPEPALKKLPDSNSFTKSAA  1850
1851  ALLSPIKTLTTETHPQPHFSRTSSPVKSSLFLAPSALKLSTPSSLSSSQE  1900
1901  ILKDVAEMKEDLMRMTAILQTDVPEEKPFQPELPKEGRIDDEEPFKIVEK  1950
1951  VKEDLVKVSEILKKDVCVDNKGSPKSPKSDKGHSPEDDWIEFSSEEIREA  2000
2001  RQQAAASQSPSLPERVQVKAKAASEKDYNLTKVIDYLTNDIGSSSLTNLK  2050
2051  YKFEDAKKDGEERQKRVLKPAIALQEHKLKMPPASMRTSTSEKELCKMAD  2100
2101  SFFGTDTILESPDDFSQHDQDKSPLSDSGFETRSEKTPSAPQSAESTGPK  2150
2151  PLFHEVPIPPVITETRTEVVHVIRSYDPSAGDVPQTQPEEPVSPKPSPTF  2200
2201  MELEPKPTTSSIKEKVKAFQMKASSEEDDHNRVLSKGMRVKEETHITTTT  2250
2251  RMVYHSPPGGEGASERIEETMSVHDIMKAFQSGRDPSKELAGLFEHKSAV  2300
2301  SPDVHKSAAETSAQHAEKDNQMKPKLERIIEVHIEKGNQAEPTEVIIRET  2350
2351  KKHPEKEMYVYQKDLSRGDINLKDFLPEKHDAFPCSEEQGQQEEEELTAE  2400
2401  ESLPSYLESSRVNTPVSQEEDSRPSSAQLISDDSYKTLKLLSQHSIEYHD  2450
2451  DELSELRGESYRFAEKMLLSEKLDVSHSDTEESVTDHAGPPSSELQGSDK  2500
2501  RSREKIATAPKKEILSKIYKDVSENGVGKVSKDEHFDKVTVLHYSGNVSS  2550
2551  PKHAMWMRFTEDRLDRGREKLIYEDRVDRTVKEAEEKLTEVSQFFRDKTE  2600
2601  KLNDELQSPEKKARPKNGKEYSSQSPTSSSPEKVLLTELLASNDEWVKAR  2650
2651  QHGPDGQGFPKAEEKAPSLPSSPEKMVLSQQTEDSKSTVEAKGSISQSKA  2700
2701  PDGPQSGFQLKQSKLSSIRLKFEQGTHAKSKDMSQEDRKSDGQSRIPVKK  2750
2751  IQESKLPVYQVFAREKQQKAIDLPDESVSVQKDFMVLKTKDEHAQSNEIV  2800
2801  VNDSGSDNVKKQRTEMSSKAMPDSFSEQQAKDLACHITSDLATRGPWDKK  2850
2851  VFRTWESSGATNNKSQKEKLSHVLVHDVRENHIGHPESKSVDQKNEFMSV  2900
2901  TERERKLLTNGSLSEIKEMTVKSPSKKVLYREYVVKEGDHPGGLLDQPSR  2950
2951  RSESSAVSHIPVRVADERRMLSSNIPDGFCEQSAFPKHELSQKLSQSSMS  3000
3001  KETVETQHFNSIEDEKVTYSEISKVSKHQSYVGLCPPLEETETSPTKSPD  3050
3051  SLEFSPGKESPSSDVFDHSPIDGLEKLAPLAQTEGGKEIKTLPVYVSFVQ  3100
3101  VGKQYEKEIQQGGVKKIISQECKTVQETRGTFYTTRQQKQPPSPQGSPED  3150
3151  DTLEQVSFLDSSGKSPLTPETPSSEEVSYEFTSKTPDSLIAYIPGKPSPI  3200
3201  PEVSEESEEEEQAKSTSLKQTTVEETAVEREMPNDVSKDSNQRPKNNRVA  3250
3251  YIEFPPPPPLDADQIESDKKHHYLPEKEVDMIEVNLQDEHDKYQLAEPVI  3300
3301  RVQPPSPVPPGADVSDSSDDESIYQPVPVKKYTFKLKEVDDEQKEKPKAS  3350
3351  AEKASNQKELESNGSGKDNEFGLGLDSPQNEIAQNGNNDQSITECSIATT  3400
3401  AEFSHDTDATEIDSLDGYDLQDEDDGLTESDSKLPIQAMEIKKDIWNTEG  3450
3451  ILKPADRSFSQSKLEVIEEEGKVGPDEDKPPSKSSSSEKTPDKTDQKSGA  3500
3501  QFFTLEGRHPDRSVFPDTYFSYKVDEEFATPFKTVATKGLDFDPWSNNRG  3550
3551  DDEVFDSKSREDETKPFGLAVEDRSPATTPDTTPARTPTDESTPTSEPNP  3600
3601  FPFHEGKMFEMTRSGAIDMSKRDFVEERLQFFQIGEHTSEGKSGDQGEGD  3650
3651  KSMVTATPQPQSGDTTVETNLERNVETPTVEPNPSIPTSGECQEGTSSSG  3700
3701  SLEKSAAATNTSKVDPKLRTPIKMGISASTMTMKKEGPGEITDKIEAVMT  3750
3751  SCQGLENETITMISNTANSQMGVRPHEKHDFQKDNFNNNNNLDSSTIQTD  3800
3801  NIMSNIVLTEHSAPTCTTEKDNPVKVSSGKKTGVLQGHCVRDKQKVLGEQ  3850
3851  QKTKELIGIRQKSKLPIKATSPKDTFPPNHMSNTKASKMKQVSQSEKTKA  3900
3901  LTTSSCVDVKSRIPVKNTHRDNIIAVRKACATQKQGQPEKGKAKQLPSKL  3950
3951  PVKVRSTCVTTTTTTATTTTTTTTTTTTSCTVKVRKSQLKEVCKHSIEYF  4000
4001  KGISGETLKLVDRLSEEEKKMQSELSDEEESTSRNTSLSETSRGGQPSVT  4050
4051  TKSARDKKTEAAPLKSKSEKAGSEKRSSRRTGPQSPCERTDIRMAIVADH  4100
4101  LGLSWTELARELNFSVDEINQIRVENPNSLISQSFMLLKKWVTRDGKNAT  4150
4151  TDALTSVLTKINRIDIVTLLEGPIFDYGNISGTRSFADENNVFHDPVDGW  4200
4201  QNETSSGNLESCAQARRVTGGLLDRLDDSPDQCRDSITSYLKGEAGKFEA  4250
4251  NGSHTEITPEAKTKSYFPESQNDVGKQSTKETLKPKIHGSGHVEEPASPL  4300
4301  AAYQKSLEETSKLIIEETKPCVPVSMKKMSRTSPADGKPRLSLHEEEGSS  4350
4351  GSEQKQGEGFKVKTKKEIRHVEKKSHS                         4377

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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