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

NucPred

Fetching Q17551 from www.uniprot.org...

The NucPred score for your sequence is 0.80 (see score help below)

   1  MSFFLREIDGERVCSTSTETSIPEDRKSARRLRKLLYKCAENTCKPDILR    50
  51  VPAHCGKLDKEEEKSKTPLDQQQQINFHDILNSKFVVGPPSPFALVAIAK   100
 101  SILARFGNPEEVSEKEDGSEEEAGTSGADEEGKQYKNTDQLVGASLTCIF   150
 151  EVLEQLSRRDAELCVQALESLLSLIQSMPIDCLQSENRLSMSAMMHVLKT   200
 201  LREDACPSVSSKATSCLVALSVACGEPEHLGSTIRSLICMKKNIRMSADS   250
 251  TYDMIQMPENLRKLLLKVRRKALGGDNTANSPPNWAMVDVHEHSVASSFS   300
 301  LPSLPDSSPSSDTPDDDNRIHSTMACDGTFLYILNYVGLYKLGTGLNETI   350
 351  SGKLYAANQSLQSSKNVQMYLCNGSLYLRRNYSSCISVIDTDSLLDIGEV   400
 401  ILPPSCVQHALFTDGTYFYSATLIANSTLSTIQLNDSFSPSNEPSSRRSH   450
 451  RLTDVKFTIQGDLQVPHQLPEFLPANLHPQTVDLHFTREMAFIQARSGKV   500
 501  YYAGNGTRFGLFETGNNWMELCLPEPIVQISVGIDTIMFRSGAGHGWIAS   550
 551  VDDKKRNGRLRRLVPSNRRKIVHVCASGHVYGYVSENGKIFMGGLHTMRV   600
 601  NVSSQMLNGLDNVMISSLALGKSHGVAVTRNGHLFTWGLNNMNQCGRVES   650
 651  TSTTSSPRHSGRQEYQICPIGEHTWLTDTPSVCAQCGLCSARGVACGRVP   700
 701  RPKGTMCHCGVGESTCLRCGLCRPCGEVTEPAQPGRAQHVQFSSTAAPQR   750
 751  STLHPSRVILSQGPHDVKVSSVSCGNFHTVLLASDRRVFTFGSNCHGQLG   800
 801  VGDTLSKNTPQQVILPSDTVIVQVAAGSNHTILRANDGSVFTFGAFGKGQ   850
 851  LARPAGEKAGWNAIPEKVSGFGPGFNAFAGWIGADGDSSIIHSHTALLSS   900
 901  DNILKAQIVANKTNIFIFPREVGKDYIVIRRKLNVFEHHASDYKCWYTSW   950
 951  ATDPKYDMLWYYNSAEMEIKGYDIFKKSEKSVGDAFDSLTFLAGAEFAVQ  1000
1001  VYDSPAYATSMSLGMQLLSATFSANVINLSEFWKEKHGEREQDHEKTIMD  1050
1051  GYSVANRFDGTGGGWGYSANSVEAIQFKVSKEIRLVGVGLYGGRGEYISK  1100
1101  LKLYRQIGTEADELYVEQITETDETVYDCGAHETATLLFSQPIVIQPNHW  1150
1151  HVVSAKISGPSSDCGANGKRHVECDGVTFQFRKSAVSNNGTDVDVGQIPE  1200
1201  LYYQIVGGSESRDESDSNKQLSISRDMSNLFSPAALKNVTAEGIGNLLIL  1250
1251  LEWALQRVQIDEDTNNQVEGSAENQWSQERAGFVAILSMKLISRFVRTVY  1300
1301  KEKGCHDEPGIDFANKLVNLHSMLLEFFFSTDMTGYENRPLIKKEEKVVE  1350
1351  EGYTLMKCVSEAVKLFISLSHCFMGSRSLMNAHLIAVMNKGNHEALILTS  1400
1401  AIIGSLAKIERFAHQLLCSTTTTERFPMLSSLLLKHFNCEKETLASLTSF  1450
1451  PNILRFLYDQTFMRNAYENTSSLAEAILVKVSRDLAIPTDDTLMGPVVHQ  1500
1501  TSSRFRRRSAQPTWDMSDGCADAIAFRVDSEGIKLHGFGIYLPTEPDRRN  1550
1551  FVGEIMMLSPDSSEKWTCLLRVTAEMSSEEKEVGIVRFPEYVLLSPGVTY  1600
1601  AVKVNMMKNTKTFCGEGGVTQVHLLNGARLFFSGCSMSQNGTTVQRGQLP  1650
1651  YLIYSILDQSNSLQIKQETIYDTFTLLLRLMANKIGAAITEGGALPACCQ  1700
1701  HLMSHINPHVMVYMERFPDKALEMMSTMEQLIPMVSNLNGVERVFHSYDS  1750
1751  DDSGCDTPYSGIVTTVVESQHPYKPNTSSSMVLLFEEADYICVRFSPDCQ  1800
1801  TAQFDDQLTIYLKIDEHSYMPIERCYGSEWPSYPMILPGNCLMFVLDASS  1850
1851  AVEGATSEQMFGYHVTVTGYLVGYNDSTMRLEQDLVWLSANACRIMTQLP  1900
1901  INPSNIEHLSTAEDDTRHLFEKHGSLLKKGLSLSHSPTLSELCTKGQPPP  1950
1951  AQSADLQFLREFLSGHTSTSAGFLAKWLPTGSVVDASKCQLSLSHDDLIV  2000
2001  GKAVTLKLLCKDQYDREVDCPKLQVEVFASLGHRNPSSTIHQNLHIGNLP  2050
2051  SSLLIHQNPFQPIIVNHTRYMNIAAMPAYANYSVEEIRLGFMIEELVKDR  2100
2101  VPLKSSDSSLFSGTWTPTTAGKYRIECKVDGSDISHTYTVEVTERPHRAG  2150
2151  KGTITKPSGSRRGAQMTVARTVSIPFSSDFSGIRMRLGTTLASTSVGVIP  2200
2201  RGALVEFIEEMDNDDGKWIRLTDETALLYGCNQGVGQVWCLAYHRPLQRE  2250
2251  LIPLKADTDREKAVKLRRKEIEKESNGSKHHSVSIDAKETYILSPNDVLQ  2300
2301  VYSTPAPHSMIDGEKIIGPCDLMSSGWLANRHGVWIKLTGVEKYVLQKND  2350
2351  PSSETSLSFSTNGNDEEDLERPIERKKTRLPNALTPSVADCIRAVFAAFV  2400
2401  WHEHLVKDLMAAAAYLRFHQNLHNIWQSCEIPSCTNAPAALQPIVKIWRE  2450
2451  ICEVVETSVEQHLIMPPVSNKAMRAETVKPPSRSGGCELCDANITVPLTV  2500
2501  HLRMAHPGCGGDCLGYGYNSNGKFTTGWSGECGAGGRGQSPWYLLCNTCR  2550
2551  SQYLKKTPAGHHQERTRRWREFRFSTSASDARPEVIIRQNAMFLLDLNSR  2600
2601  LQTESNSSSTATSGWTINLFPTHLSTPSTMPRSQQKRLDVPPNNSVHQNS  2650
2651  YMKLGYSSDPGPKVNVIMSPPNQGADQSASLNRPGPSAINEPAEVLQSPS  2700
2701  AALRTLFSNTNPSTSALLKRPVLAFCVEHHDLKRIKSACVQSVRRAVAFS  2750
2751  HAFRVWNWLLRMVSSEYSVSDIILQYLTTLTSYNRLAEYMFSAKKNSNIL  2800
2801  PHPWRLCFLAGPIAADMVTQLHAFLHTVSIILQSAGVDGRLKSLCFKSWT  2850
2851  LQLTAQEQDLLILTCNILGTVGGILSDTSILDSDNRFVKEMKDITKFADI  2900
2901  TASSRQAMVICLTDESGETFWESGEEDKNRSRSLSVQLDESAHGEILSLF  2950
2951  IDNARDEGYRISSIAFKAILEDGRRKDLTSLTLESAYCGWLKCCIKDISH  3000
3001  IQIQFKGPNPASRIRQLMILGYPAKTTGTPRLAPSTSHHLFFSDTQRDAF  3050
3051  ALFQAISSQAFCGELSEDDTLRERVIDLLFSRVQLYPLQNYVYTQVVQAM  3100
3101  EKEVELLCDKSKRNYSYCCGLMSLLVRICDSRGNMDSFGQRNSVLTSITQ  3150
3151  LLIFSPVVVQRQCLNSLECIFASFTPSNVEVPKIIRNLLVVVGKVIQLQV  3200
3201  RDKAAHTVVTVHLCSSVLNAPQNWRVDKSIDMDIGRQTAVLVENLCNGTY  3250
3251  TPEWSNATKCELANCLLSLIQMPESVSYTETLSTGGKSKAVAVVSSKRFW  3300
3301  TAISSLSLIKDKSWLELSERWKTVQDEEDQEPVLLCENHDDGHTVAQVFC  3350
3351  VDCDVALCKECFTVMHLHKKNRNHGVKNLVQSSTQHDINIHQGCARMKFL  3400
3401  NFLILFHGEALNGMVEVAADTLFPTSTSSIQPAMQSSSAFLGIHPMTCRF  3450
3451  CGNNVPVEDQSLDGTCTHEDCVNYAKTACQVMHTCNHFCGGIRNEEECLP  3500
3501  CMTCKREDAAQDGDDVCVICFTERLGAAPCIRLGCGHMFHFHCVRMILER  3550
3551  RWNGPRIVFRFMQCPLCIQPIEHSGLQDLIEPLKTIRQEVVDKAKMRLEY  3600
3601  DGLLTTPALTDPRSEFYNQPEEYALDRYMYVLCHKCKKAYFGGESRCQAA  3650
3651  LDSSQFNPEELLCGGCSDTSGVQVCPRHGVEYLEYKCRFCCSIAVYFCFG  3700
3701  TTHFCAPCHDDFQRLMSLPKHLLPTCPVGPRSTPMEEQTCPLKMKHPPTG  3750
3751  DEFAMGCGICRNISTF                                    3766

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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