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

NucPred

Fetching Q19317 from www.uniprot.org...

The NucPred score for your sequence is 0.90 (see score help below)

   1  MEISETSHNESGPPVQENGIVEIPVEEGEEVNDEESNMETVDLGLDDSAA    50
  51  DASSPSVFKNIDDEAPGDPSDAAKKEEDSEEIVVPSVLAPTPSQEVSPPN   100
 101  AIESLPPLPEGKELELEDDVTSSLPRLLSKTTLIHSNEEGADETIQRLVT   150
 151  VLHSNSPNTDRTQVVDNLFNLLVGGHFDQESKFVIEDAANVDHMLTLLSH   200
 201  CDYDLQNEIWSLFLAVMKKSNRNLEACTRVGLISKVLDILPEAPPLLADL   250
 251  LVQIIAALVAYSINVKQTKHLLRALKSTKEQWPPNSLKLLHVLKEMPQHD   300
 301  SADVFFSFPGKDQSGIILPPIKTMPYQQGWTFATWLRMEPLNSVTFEKEQ   350
 351  PVLYSFRTSKGVGYSCHFTGNCLVVNVEKTKGKEQSRCVRAELGARKWHH   400
 401  IAIAHCYSRWGRSDIKCFIDGQLAETIELSWVVTSATNWDRCSIGVSADG   450
 451  TANSAFCGQMGAMYLFAEALTLQQANSLFCLGPVYQSTFKHDSETSLPEG   500
 501  YKKHLFDGHLHSSLVFAYCPKNCHGQLCLYTPPKTAASTYFVQIPHAVMK   550
 551  EGVEVITTHSIHKSLQSVGGIQILLPLFAQIDLPSSNDNSIDGEVCQTLL   600
 601  SLIALLLSSSQSSQQQLFHSKGFLIISSCLQKASPSHLSMKVLEQLIHIA   650
 651  KFLLRCPAGGPLLKHLFDYILFNPKLWIRARPEVQVHLYQYLATDFLANN   700
 701  NFSQMLRRVPTVIEMCHTLKHFYWLALPQTVSDYTIEERPENFATADIVA   750
 751  IRSSILTFINRIIIASAGPEEEERVRDQEVHTLLNLLATVREDDNLYDVL   800
 801  ALVTRLLAEHPAIMIPAIDKNKALGIIFNLLAAPNELIRIPALKILGFFL   850
 851  SRSTLKRKTESMGNQNLFSLIGERLLSHKKVLSLPTYNVLLEILVEQMTP   900
 901  TFTYACHQPAQPEWKFENPHLLKVIAHVISQCEESENIVQIKKCFLIDII   950
 951  NLCRESKENRRTILQMSVWQDWLIGLAYVFHTTESQNEVSELVWEAFSIL  1000
1001  LHHALRNEYGGWRVWVDTLAIAHSKVSFEKFKRKLAEAKIKAERSESGGE  1050
1051  EAKMEPTPIYRAPEFAWSDVHVRLLADLLSGIERVVDEWKVAECGISDQC  1100
1101  NASENQVFVGNVVHVVSQLSDSLIMACGGLLPLLASATAPNNDMEIVDPC  1150
1151  QQQLPISVSAGFLMRFARLVDTFVLASGVSFSELEQEKNMPAGGVLRQSL  1200
1201  RISATVTVRHILASRIQQPDTPRYETNSTKKNQCIMEFVREALEKRSPDG  1250
1251  LENVERLVQDSDITRIKGVVYRDMVEENRQAQFLALSVIYLVSVLMVSRY  1300
1301  RDILEPPSSPSPFFDSTTQKQENSENVNSETSPENGSNGKLANGGDNLSI  1350
1351  KNGIESNGNDGEEEENGEEGQGDDGGRIAAIKVANADMKRGDGNEYDEEE  1400
1401  LSKMHQSNGRRPSTMMPVQQTAERRAYLTTKLQTALETCAPLLREMMSDF  1450
1451  RGYLQKTLLGTHGQEIMNDTKVLETLRNRNASVIELVMLLCSQEWQTSLQ  1500
1501  KHAGLAFIELVNEGRLMAHATRDHVLRVANEADFILNRLRAEDVSKHAQF  1550
1551  EAESREQLAARHEEYGRCDLLIASGRLRDSINATRLLEKMSAILSDQDDS  1600
1601  KSGTQFWKLDVWEDDSRRRKRFVPNAYGSRHEEANLPEGEKNEEPEISEQ  1650
1651  EKIRKVLKGLFSKRQNSSGSHELVDESDIDKWAQEVDPTPSSQSACFSTT  1700
1701  AKLIAPGVVVPGTLSVTANDLFFDANESDPNYKKQCAQVLRYCEALHARW  1750
1751  NLQEIRAIFLRRYLLQNTALELFLASRTAIMFAFDSEDAVKKVVYQLPRV  1800
1801  GVGVKYGLPQSRKTSLMTPRQLFKHSDMCAKWQKREISNFDYLMFLNTVA  1850
1851  GRTFNDLSQYPVFPWILTNYTSDTLDLSVASNFRDLSKPIGALSEARRKF  1900
1901  FNDRYTSWDDDQVPAFHYGTHYSTPAFTLNWLLRVEPFASMFINLHDGKF  1950
1951  DHPDRITHSIKDSWDRCQRDSHDVKELIPELFYLPEMFRNSSKFNLGRRA  2000
2001  DGTPVDDVVLPPWAESPEHFVLMHRQALESDLVSCQLNQWIDLIFGYKQR  2050
2051  GAEAVRATNVFYHLTYEGTVTPKMAETPGQVAAIEQQILSFGQTPSQLLT  2100
2101  EAHPPRHSIMSMAPTMFRRHDEDLCMMMKYISNSPVVYLAANTFHQLPQP  2150
2151  TVVGVAQNLVFSLNKWDNSYSYGASQRSALSMDPSNAEGQVSLPLTADAQ  2200
2201  LASAASTTPVARRHLGDAFDQRLTVQCSNFVTTTDSKFIFACGYPDYSFR  2250
2251  IVDTDSGRVRQAVYGHGDVVTCIARSETSLFSDCYVVTGSMDCTVVLWHW  2300
2301  NGTTGFIAGEYNQPGEVPSPRSILTGHEASISALCVSAEHGLVVSGCEDG  2350
2351  VILIHTTSSDLLRRIRGHGIVTQLSMSRECILLSLFDSKRMVTYSATAKK  2400
2401  LDEVLVDDKIECVTVTRDGEFAVTGAVNGRINIWRMFPLTKLYTYQPLNS  2450
2451  AVRSVAVVASHRFILGGLDSGAIVVFNADFNRWHYEYKHRYIQNTSAAKP  2500
2501  VQQSPQK                                             2507

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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