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

NucPred

Fetching P24043 from www.uniprot.org...

The NucPred score for your sequence is 0.71 (see score help below)

   1  MPGAAGVLLLLLLSGGLGGVQAQRPQQQRQSQAHQQRGLFPAVLNLASNA    50
  51  LITTNATCGEKGPEMYCKLVEHVPGQPVRNPQCRICNQNSSNPNQRHPIT   100
 101  NAIDGKNTWWQSPSIKNGIEYHYVTITLDLQQVFQIAYVIVKAANSPRPG   150
 151  NWILERSLDDVEYKPWQYHAVTDTECLTLYNIYPRTGPPSYAKDDEVICT   200
 201  SFYSKIHPLENGEIHISLINGRPSADDPSPELLEFTSARYIRLRFQRIRT   250
 251  LNADLMMFAHKDPREIDPIVTRRYYYSVKDISVGGMCICYGHARACPLDP   300
 301  ATNKSRCECEHNTCGDSCDQCCPGFHQKPWRAGTFLTKTECEACNCHGKA   350
 351  EECYYDENVARRNLSLNIRGKYIGGGVCINCTQNTAGINCETCTDGFFRP   400
 401  KGVSPNYPRPCQPCHCDPIGSLNEVCVKDEKHARRGLAPGSCHCKTGFGG   450
 451  VSCDRCARGYTGYPDCKACNCSGLGSKNEDPCFGPCICKENVEGGDCSRC   500
 501  KSGFFNLQEDNWKGCDECFCSGVSNRCQSSYWTYGKIQDMSGWYLTDLPG   550
 551  RIRVAPQQDDLDSPQQISISNAEARQALPHSYYWSAPAPYLGNKLPAVGG   600
 601  QLTFTISYDLEEEEEDTERVLQLMIILEGNDLSISTAQDEVYLHPSEEHT   650
 651  NVLLLKEESFTIHGTHFPVRRKEFMTVLANLKRVLLQITYSFGMDAIFRL   700
 701  SSVNLESAVSYPTDGSIAAAVEVCQCPPGYTGSSCESCWPRHRRVNGTIF   750
 751  GGICEPCQCFGHAESCDDVTGECLNCKDHTGGPYCDKCLPGFYGEPTKGT   800
 801  SEDCQPCACPLNIPSNNFSPTCHLDRSLGLICDGCPVGYTGPRCERCAEG   850
 851  YFGQPSVPGGSCQPCQCNDNLDFSIPGSCDSLSGSCLICKPGTTGRYCEL   900
 901  CADGYFGDAVDAKNCQPCRCNAGGSFSEVCHSQTGQCECRANVQGQRCDK   950
 951  CKAGTFGLQSARGCVPCNCNSFGSKSFDCEESGQCWCQPGVTGKKCDRCA  1000
1001  HGYFNFQEGGCTACECSHLGNNCDPKTGRCICPPNTIGEKCSKCAPNTWG  1050
1051  HSITTGCKACNCSTVGSLDFQCNVNTGQCNCHPKFSGAKCTECSRGHWNY  1100
1101  PRCNLCDCFLPGTDATTCDSETKKCSCSDQTGQCTCKVNVEGIHCDRCRP  1150
1151  GKFGLDAKNPLGCSSCYCFGTTTQCSEAKGLIRTWVTLKAEQTILPLVDE  1200
1201  ALQHTTTKGIVFQHPEIVAHMDLMREDLHLEPFYWKLPEQFEGKKLMAYG  1250
1251  GKLKYAIYFEAREETGFSTYNPQVIIRGGTPTHARIIVRHMAAPLIGQLT  1300
1301  RHEIEMTEKEWKYYGDDPRVHRTVTREDFLDILYDIHYILIKATYGNFMR  1350
1351  QSRISEISMEVAEQGRGTTMTPPADLIEKCDCPLGYSGLSCEACLPGFYR  1400
1401  LRSQPGGRTPGPTLGTCVPCQCNGHSSLCDPETSICQNCQHHTAGDFCER  1450
1451  CALGYYGIVKGLPNDCQQCACPLISSSNNFSPSCVAEGLDDYRCTACPRG  1500
1501  YEGQYCERCAPGYTGSPGNPGGSCQECECDPYGSLPVPCDPVTGFCTCRP  1550
1551  GATGRKCDGCKHWHAREGWECVFCGDECTGLLLGDLARLEQMVMSINLTG  1600
1601  PLPAPYKMLYGLENMTQELKHLLSPQRAPERLIQLAEGNLNTLVTEMNEL  1650
1651  LTRATKVTADGEQTGQDAERTNTRAKSLGEFIKELARDAEAVNEKAIKLN  1700
1701  ETLGTRDEAFERNLEGLQKEIDQMIKELRRKNLETQKEIAEDELVAAEAL  1750
1751  LKKVKKLFGESRGENEEMEKDLREKLADYKNKVDDAWDLLREATDKIREA  1800
1801  NRLFAVNQKNMTALEKKKEAVESGKRQIENTLKEGNDILDEANRLADEIN  1850
1851  SIIDYVEDIQTKLPPMSEELNDKIDDLSQEIKDRKLAEKVSQAESHAAQL  1900
1901  NDSSAVLDGILDEAKNISFNATAAFKAYSNIKDYIDEAEKVAKEAKDLAH  1950
1951  EATKLATGPRGLLKEDAKGCLQKSFRILNEAKKLANDVKENEDHLNGLKT  2000
2001  RIENADARNGDLLRTLNDTLGKLSAIPNDTAAKLQAVKDKARQANDTAKD  2050
2051  VLAQITELHQNLDGLKKNYNKLADSVAKTNAVVKDPSKNKIIADADATVK  2100
2101  NLEQEADRLIDKLKPIKELEDNLKKNISEIKELINQARKQANSIKVSVSS  2150
2151  GGDCIRTYKPEIKKGSYNNIVVNVKTAVADNLLFYLGSAKFIDFLAIEMR  2200
2201  KGKVSFLWDVGSGVGRVEYPDLTIDDSYWYRIVASRTGRNGTISVRALDG  2250
2251  PKASIVPSTHHSTSPPGYTILDVDANAMLFVGGLTGKLKKADAVRVITFT  2300
2301  GCMGETYFDNKPIGLWNFREKEGDCKGCTVSPQVEDSEGTIQFDGEGYAL  2350
2351  VSRPIRWYPNISTVMFKFRTFSSSALLMYLATRDLRDFMSVELTDGHIKV  2400
2401  SYDLGSGMASVVSNQNHNDGKWKSFTLSRIQKQANISIVDIDTNQEENIA  2450
2451  TSSSGNNFGLDLKADDKIYFGGLPTLRNLSMKARPEVNLKKYSGCLKDIE  2500
2501  ISRTPYNILSSPDYVGVTKGCSLENVYTVSFPKPGFVELSPVPIDVGTEI  2550
2551  NLSFSTKNESGIILLGSGGTPAPPRRKRRQTGQAYYAILLNRGRLEVHLS  2600
2601  TGARTMRKIVIRPEPNLFHDGREHSVHVERTRGIFTVQVDENRRYMQNLT  2650
2651  VEQPIEVKKLFVGGAPPEFQPSPLRNIPPFEGCIWNLVINSVPMDFARPV  2700
2701  SFKNADIGRCAHQKLREDEDGAAPAEIVIQPEPVPTPAFPTPTPVLTHGP  2750
2751  CAAESEPALLIGSKQFGLSRNSHIAIAFDDTKVKNRLTIELEVRTEAESG  2800
2801  LLFYMARINHADFATVQLRNGLPYFSYDLGSGDTHTMIPTKINDGQWHKI  2850
2851  KIMRSKQEGILYVDGASNRTISPKKADILDVVGMLYVGGLPINYTTRRIG  2900
2901  PVTYSIDGCVRNLHMAEAPADLEQPTSSFHVGTCFANAQRGTYFDGTGFA  2950
2951  KAVGGFKVGLDLLVEFEFRTTTTTGVLLGISSQKMDGMGIEMIDEKLMFH  3000
3001  VDNGAGRFTAVYDAGVPGHLCDGQWHKVTANKIKHRIELTVDGNQVEAQS  3050
3051  PNPASTSADTNDPVFVGGFPDDLKQFGLTTSIPFRGCIRSLKLTKGTGKP  3100
3101  LEVNFAKALELRGVQPVSCPAN                              3122

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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