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

NucPred

Fetching P11722 from www.uniprot.org...

The NucPred score for your sequence is 0.43 (see score help below)

   1  MPGRGGLRLALLALCLGAAAAGGGDGQRRGGKNRRQAQTASVPQATPAQG    50
  51  KQTCFDNGRYYQINQQWERIYLGNTLVCTCYGGSRGFNCESKPEPEETCF   100
 101  DKYTGSTYRVGETYERPKDSMIWDCTCIGAGRGRISCTIANRCHEGGKSY   150
 151  KIGDTWRRPHETGGYLLECVCLGNGKGEWTCKPLAERCYDNTAGTSYVVG   200
 201  ETWEKPYQGWMMVDCTCLGEGSGRITCTSRNRCNDQDTKTSYRIGDTWSK   250
 251  KDNRGNLLQCICTGNGRGEWKCERHTSLHTTSTGSGSPSFTNVQTALYQP   300
 301  QPQQPQPQPHGHCVTDNGVVYSLGMQWLKTQGSQQMLCTCLGNGVSCQEI   350
 351  AVTQTYGGNSDGEACVLPFTYNGRTFYSCTTEGRTDGHLWCSTTSNFEQD   400
 401  RRYSFCTEQNVLVQTRGGNSNGALCHFPFLYNNRNYTDCTSEGRRDNMKW   450
 451  CGTTENYDADQKFGFCPMAAHEEICTTNDGIMYRVGDQWDKQHDMGHMMR   500
 501  CTCVGNGRGEWTCIAYSQLRDQCIVDGITYDVNQTFHKRHDEGHMLNCTC   550
 551  FGQGRGRWKCDPVDQCQDSETRTFYQIGDSWEKYVHGVRYQCYCYGRGIG   600
 601  EWHCQPLQAYAGATGPVQVIITESTNQPNSHPIQWNAPKTSHISKYILRW   650
 651  RPKISGRHWKEATIPGHLNSYTISGLKPGVVYEGQLISVQQHGPKEVTRF   700
 701  DFTTTSTTAVTSNTVSGETTLLPPMVATSESVTEITASSFVVSWVSASDT   750
 751  VSGFRVEYELSEEGDEPQYLDLPSTATSVNIPDLLPGRKYIVNVYQISEE   800
 801  GEQNLILSTSQTTAPDAPPEHSVESVDDTSIVISWSRPQAPITGYRIVYT   850
 851  PSVEGSSTELNLPDTATSVTLSDLMPGVQYNISIYAVEEHQESTPVFIQQ   900
 901  ETTGVPRTDEVPSPKDLQFVEVSDVKVTIMWTPPQSQVSGYRVEAIPVNR   950
 951  PGQHGQRLPITRSSFAEVVDLLPGTTYLFKIFAVSHGRESKPLTGEQTTK  1000
1001  LDAPTNLRFINTTEHSVLVLWTRPRAIISGYRLTAGPTRGGQPRTYNVGP  1050
1051  SATKYLLRNLQPGTEYTVYLVAVKEDLQSARETGVFTTYQPVGSVPPFNT  1100
1101  EVTETSIVITWTPAPRIGFKLGVRPSQGGEAPREVISDSGSIVISGLTPG  1150
1151  VEYTYSLTVLMDGQERETPIIRRVTTPLSPPTNLRLEPNPDTGILIVSWD  1200
1201  RSTTPGISGYRVTTAPTNGQQGSTLEEVVGADQTSCTFENLNPGVEYNVS  1250
1251  VYAVKDDQESIPISKTITQEVPQLTDLSFVDITDSSIGLRWTPLNASTII  1300
1301  GYRITVVAAGESVPIFEDFVDSSVGYYTVTGLEPGIDYDISVITLINGGE  1350
1351  SAPTTLTQQTAVPPPTDLRFTNVGPDTMRVTWTAPTSIVLSSFLVRYSPV  1400
1401  KKEEDVAELTISPSDNVVVLTNLLPGTEYLVRVYSVAEQHESAPLSGIQK  1450
1451  TGLDSPTGLDFSDITANSFTVHWIAPRATITGYKIRHHPEHGVGRPKEDR  1500
1501  VPPSRNSITLTNLLPGTEYVVSIIAVNGREESVPLVGQQTTVSDVPRDLE  1550
1551  VNPTSPTSLEISWDAPAVTVRYYRITYGETGGSSPVQEFTVPGTMSRATI  1600
1601  TGLKPGVDYTITVYAVTGRGDSPASSKPVTVTYKTEIDTPSQMQVTDVQD  1650
1651  NSISIRWLPSSSPVTGYRVTAVPKKGHGPTKTKNVPPDQTQVTIEGLQPT  1700
1701  VEYMVSVYAQNQNGESLPLVETAVTNIDRPKGLTFTEVDVDSIKIAWESP  1750
1751  QGQVTRYRVTYSSPEDGIHELLPAPGGEEDTAELHGLRPGSEYTINIVAI  1800
1801  YDDMESLPLTGTQSTAIPPPTNLKFTQVTPTSLTVNWNAPNVRLTGYRVR  1850
1851  VNPKEKTGPMKEINLSPDSTSAVVSGLMVATKYEVSVYALKDSLTSRPAQ  1900
1901  GVVTTLENVSPPRRARVTDATETTITITWRTKTETITGFQIDAIPAASGQ  1950
1951  NPIQRTISPDVRTYTITGLQPGNDYKIYLYTLNENARSSPVVIDASTAID  2000
2001  APSNLRFLTTTTNSLLASWQPPRAKITGYIIRYDKPGSPAKELLPRPRPG  2050
2051  TTEATITGLEPGTEYTIYIIAVKNNQKSEPLVGRKRTDDLPTLITGPHPN  2100
2101  QPDMLDVPSVDEGTPYLTNNRYDNGNGIQLPGTSGHPQTIGHQGQQVFFE  2150
2151  EHGYRRPVPTTATPLRPGSRRQPPNVDEAIEIPGYQVPIIVVPSYPHSRE  2200
2201  PRRNDTTGQEALSQTTISWRPLLESTEYIISCQPVSQDEDTLQFRVPGTS  2250
2251  SSATLTGLTRGATYNIIVEALKDHRRQKVLEEVVTVGNTVSEGLNQPADD  2300
2301  TCYDTYTGSFYSIGEEWERLSETGFKLWCQCLGFGSGHFRCDSSKWCHDN  2350
2351  GVNYKIGEKWDRQGENGQMMSCTCLGNGKGEFKCEPHETTCYDDGKMYQV  2400
2401  GEQWQKEYFGAICSCTCYGGQQGWRCDNCRRPSVEVAPEGSAGHTYPQFT  2450
2451  QRYHQATNTNVNCPIECFMPLDVQADTQHPRGK                   2483

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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