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

NucPred

Fetching P45444 from www.uniprot.org...

The NucPred score for your sequence is 0.81 (see score help below)

   1  MEVASSGVPDGAPTAISQGPLVDADAVVEYLADVLRVTLGALRSELENAG    50
  51  SLLSKTKYSETAQRCLRFASESQVALYVQKDLVASDHTNGTADSEEPPAE   100
 101  YVYTLSAEISSSSTTVASVAFIKRPAAIDPSLPISSQIQVMNLPGPAALN   150
 151  NTQAQQGTSLSPYEILHLLVHHGLSPYFEANTRNQDGAAKAKTDSEVKTG   200
 201  VPGTKKKFAELELGLLHLQQNVEIPALNLPLHEVVQAALVEAEKRGVKPS   250
 251  VDLIDSTLLESSAFINSIQNNVNAWIKSIQTITKMSRDADSGSAAQEINF   300
 301  WLSMETALEGIENQLRGDGVQLTMDILRHAKRYQATLSFVADTGLREATD   350
 351  LVQKYNQLMRDFPLDELLSATSLQKVRESLVLIFNHLNKKLKICPYPIKR   400
 401  ALALVEAISGDLDSQIHSLLNGRTIMHLDYREFRTLMKTAGSIWRTWDDN   450
 451  LKEFTNVARESTRRRNEKFIPIKINARHDKTQERLKYINTFRVNHEQLQR   500
 501  TIANVLGPKSYSAEDAAAGAAADGAVIVEEIGDVDAVEEVAQAYAALKSV   550
 551  DVLDVSPTGTQNWITAEIAYNERTSRVENSIIARLRDRLATAKNANEMFR   600
 601  VFSKFNALLVRPKIRGAIGEYQTQLIDNVKQDISALHERFKQQYGHSEAH   650
 651  AMAQLRDLPPVSGAIVWARQIERQLDGYMRKVEDVLGEDWHLHTEGQKLQ   700
 701  AESNLFRKKLDTRPVFETWLHDVQRRRITISGRLFNIIRNRAAGNTLELA   750
 751  VNFDAQIIALFKEIRNLIWLNFQVPHAVSNISKEAKRVYPYAISLMESVR   800
 801  TLLQTNRSILSMTDVAILLNGYMNDAQSMIVRGIPLRWESFVHSYELHVK   850
 851  QAALVNGALDSVIPSRGESKHVQFVREFAASAAVLQHKTAVLASINDTIQ   900
 901  KAIHELKTCPYEFSAFKQRLDAIQAAVDKLNLENYVNLGFWVHNLNQKIE   950
 951  GILSERLHKAIREWMNSFQESQSGQPMQKVNGNGDTDTTAYNIEFPGLTH  1000
1001  EISMRNQVLHLDPPLQYARATWFSHFDNWLGIICNLEKIKSSRYQISIEV  1050
1051  QKVQLSESCFADLPQHCTNELILVYSAIETRLKEVSEYVDKWLQFQSLWD  1100
1101  LQSEQVYDILGDDLSQWLQLLQEIRKSRATFDTSEVSRSFGNIKIDYEQV  1150
1151  QTRVNAKYDQWQHEILLKFGSKLGNRMREVHSEIATARHDLEGKSLDSAS  1200
1201  TAHAVAFITSVQQCKRKAKVWEPEVDLFRQGQATLVRQRYQFPSDWLHVE  1250
1251  NVDGEWAALNELLGRKGKIVEEQTEALRAKIAAEDKVINDKITEAIAQWN  1300
1301  EEKPVSGTIPPEEASRSLSMFQTRLESLQSEFEMVSKAKEALDLPPSAES  1350
1351  SLPAILEEVQDFMSVWAALSTIWRSLNDLRDTLWTSIQPRKLRQSIDGLI  1400
1401  KMTKEMPSRMRQYAAFEHIQNVLKQLLKVNPLLSDMKSEAVRERHWLKIY  1450
1451  KALKPGMRFSLVSLTLGDVWDLQLAASETVIRNIIAQAQGEMALEEFLKS  1500
1501  VRETWQNYSLDLVNYQNKCRLIRGFDDLFAKCSENLNSLQAMRHSPYYKE  1550
1551  FEEDASSWEDKLNRVHVLFDVWIDVQRQWVYLEGVFTGNADIKHLLPLES  1600
1601  SRFQNINSEFFAVMKKVYKSPFVLDVLAINGVQKSLERLAELLNKIQKAL  1650
1651  GEYLERERVSFPRFYFVGDEDLLEIIGNSNDIFRVAKHFKKMFAGLSGVL  1700
1701  MDDDNNIVGFTSKEGEEVRLKKEVNLVKTPRINDWLTALESNMKLTLAEL  1750
1751  LAEAIEQFEPIYNSAEVDRTAFDDFIANYPAQIVVLASQVVWTNEVQKSL  1800
1801  ENSGTTLPTLYDAQVRILELLAVTVLGDLDPISRKKCEHLITEFVHQRDT  1850
1851  ISKLIASNATSATHYLWLLQMRYVYQADGDFLQRLYVHMANAKLNYGFEY  1900
1901  LGVPERLVRTPLTDRCFLTLTQALCQRLGGSPYGPAGTGKTESVKALGLQ  1950
1951  LGRFTLVFCCDDTFDFQAMGRIFLGICQVGAWGCFDEFNRLEERILSAVS  2000
2001  QQIQNIQIGLRNKETDEKSQIDLVGRRLTVNMNTGIFITMNPGYAGRSNL  2050
2051  PDNLKKLFRSVAMSKPDKELIAEVMLFSQGFKQAKRLSQQTVPFFDHCST  2100
2101  RLSKQAHYDFGLRALKSVLVSSGGLKRARIANSDGDLGPDEIVEPQIIVQ  2150
2151  SLRETIAPKLVREDVATMLQIQEQDFAGVEYVPANYEALTAAIREIAREQ  2200
2201  HFVDSEMWITKILQLYQIQSIHHGVMMVGKSGSGKSSAWKILLQALQRIE  2250
2251  GVEGVSHIIDSKVMSKEALYGSLDSTTREWTDGLFTGILRKIVDNLRGED  2300
2301  TKRHWIVFDGDVDPEWVENLNSVLDDNKLLTLPNGERLNLPPNVRIMFEV  2350
2351  ESLKYATLATVSRCGMVWFNEDTVTPSMIITNYVESLKTKTFEDLDDDSV  2400
2401  PSGQSAVKTQDCQDMLSTILSQLLQTDELVHKSLGEAKKYNHIMEFTEIR  2450
2451  ALNTLFSLLNKACRNILEYNIQHVDFPLEYEQIESYISKKLLLALVWSFT  2500
2501  GDCPLGDRKSFGEFVSGLTTIDLPIETNSSIIDFDVTLPKGTWSSWQSQV  2550
2551  PTIDVNTHSITQTDVVIPTVDTVRHEDVLYSWLAEHKPLLLCGPPGSGKT  2600
2601  MTLFAALRKLPNMEVVGLNFSSATTPDLLIKTFEQYCEYKKTLSGVVMSP  2650
2651  NQIGRWLVIFCDEINLPAPDKYGTQRAISFLRQLVEQNGFWRTSDKTWVS  2700
2701  LDRIQFVGACNPPTDAGRTPLAERFLRHSPLVMVDYPGEISLNQIYGTFN  2750
2751  SAILKILPLLRGYSESLTKAMVQFYLESQQRFTPKIQPHYVYSPRELTRW  2800
2801  VRGVYEAIKPLESLSVEGLVRIWAHEALRLFQDRLVTEEERAWTADAVRR  2850
2851  IALEHFPTIDQEAALKGPILFSNWLSRNYVPVEQEQLRDFVKARLKTFCE  2900
2901  EEVDVPLVLFNDVLEHALRIDRVFRQPQGHLILIGVSGSGKTTLSRFVAW  2950
2951  MNGLKVFQIKVHGKYSSEDFDDDLRSVLRRAGCKGEKICFIMDESNVLDS  3000
3001  GFLERMNTLLANAEVPGLFEGDEFSSLMTACKEGAQRQGLILDSQEELYK  3050
3051  WFTQQIVKNLHVVFTMNPPEEGLSSKAATSPALFNRCVLNWMGDWSDQAL  3100
3101  FQVGSELTQSVDLDKPGFVAPDSIPVAYRELSLPASHRDTVINAMVYIHH  3150
3151  SLQRFNQRLQKQQGKTTYLTPRHYLDFVAQYVKLFNEKREDLEEQQRHLN  3200
3201  VGLEKLRDTVEKVSDLRGSLAQKKMQLEKKDAEANEKLQRMVADQREAEQ  3250
3251  RKAVSLEVQAALEKQEKEVALRKDVVLHDLARAEPAVLEAQKSVSNIKRQ  3300
3301  HLTEVRSMGNPPAGVRLALEAVCTLLGHKVDSWKTIQGIVRRDDFIASIV  3350
3351  NYDNEKQMTKNHRLKMQNEFFSKEDFTYERVNRASKACGPLVQWVEAQVN  3400
3401  YSAILDRVGPLRDEVGQLEEQALQTKAEAQAIENTINDLESSIATYKSEY  3450
3451  AALISETQAIKAEMERVQFKVDRSVRLLDSLSSERTRWEEGSKSFETQIS  3500
3501  TLIGDVLIAAAFLAYAGFYDQQFRKAMTEDWVQHLVQSGISLKPHNPITE  3550
3551  YLSNADERLAWQAHSLPVDDLSTENAIFLKRYNRYPLIIDPSGRVTEFLQ  3600
3601  KESSDRKLTVTSFLDDSFVKQLESALRFGNPILIQDAEHLDPILNHVLNK  3650
3651  EYQKTGGRVLIQLGKQEIDFSPSFKLFLSTRDPSATFAPDVCSRTTFVNF  3700
3701  TITQSSLQIQSLNEVLKSERDDVDRRRSDLVKAQGEFNVHLRQLEKRLLQ  3750
3751  ALNESHGNILDDDNVIETLETLKKEAAEISRKMAETEGVMTEVEEITQRY  3800
3801  SIIARSCSAVFAVLEQLHHINHFYQFSLQYFTDIFESVLHGNPHLENSGL  3850
3851  RKMEDYQQRIQIILRDLFVTTYQRTSLGVIQKDRITLAMLLAQAAPYPMD  3900
3901  KSIIDTILDESVEGTDLSANPEAKVQVMSAFGNMSLFKAHLPSVTAEQWD  3950
3951  QFLGEELAENFVPKVWDENTSELDKLLRSLLLVKLCRMDRFVPAAERFIV  4000
4001  AVFGRELYEGSTDLKDIVGQVTATAPISLSSSPGFDASYKVDALVERTHA  4050
4051  TCANIAMGSNEGLESADKAISNAASAGTWVLVKNVHLAPSWLQSLEKRLA  4100
4101  SLKPHKDFRLFLSMESSPKIPVNLIRASRVLMYEQPAGVRANMKDSLSSL  4150
4151  STRASKAPVEKARVYLLLCFLHAVVQERLRYAPSLGWKGFWEFNDSDYEC  4200
4201  SANIIDHWVDVVAQGRSNVAPQKLPWDMIRTLITEMYGGKVDDSDDFQQL  4250
4251  ERLVHSFLTPATFEADYKLVEGVENDECLILPGETGLPAFVEWVNKLPER  4300
4301  EPPTYLGLPANAEKLLLVGHGKKMISDLARITSLLDEGEQLMIDA       4345

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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