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

NucPred

Fetching P15924 from www.uniprot.org...

The NucPred score for your sequence is 0.99 (see score help below)

   1  MSCNGGSHPRINTLGRMIRAESGPDLRYEVTSGGGGTSRMYYSRRGVITD    50
  51  QNSDGYCQTGTMSRHQNQNTIQELLQNCSDCLMRAELIVQPELKYGDGIQ   100
 101  LTRSRELDECFAQANDQMEILDSLIREMRQMGQPCDAYQKRLLQLQEQMR   150
 151  ALYKAISVPRVRRASSKGGGGYTCQSGSGWDEFTKHVTSECLGWMRQQRA   200
 201  EMDMVAWGVDLASVEQHINSHRGIHNSIGDYRWQLDKIKADLREKSAIYQ   250
 251  LEEEYENLLKASFERMDHLRQLQNIIQATSREIMWINDCEEEELLYDWSD   300
 301  KNTNIAQKQEAFSIRMSQLEVKEKELNKLKQESDQLVLNQHPASDKIEAY   350
 351  MDTLQTQWSWILQITKCIDVHLKENAAYFQFFEEAQSTEAYLKGLQDSIR   400
 401  KKYPCDKNMPLQHLLEQIKELEKEREKILEYKRQVQNLVNKSKKIVQLKP   450
 451  RNPDYRSNKPIILRALCDYKQDQKIVHKGDECILKDNNERSKWYVTGPGG   500
 501  VDMLVPSVGLIIPPPNPLAVDLSCKIEQYYEAILALWNQLYINMKSLVSW   550
 551  HYCMIDIEKIRAMTIAKLKTMRQEDYMKTIADLELHYQEFIRNSQGSEMF   600
 601  GDDDKRKIQSQFTDAQKHYQTLVIQLPGYPQHQTVTTTEITHHGTCQDVN   650
 651  HNKVIETNRENDKQETWMLMELQKIRRQIEHCEGRMTLKNLPLADQGSSH   700
 701  HITVKINELKSVQNDSQAIAEVLNQLKDMLANFRGSEKYCYLQNEVFGLF   750
 751  QKLENINGVTDGYLNSLCTVRALLQAILQTEDMLKVYEARLTEEETVCLD   800
 801  LDKVEAYRCGLKKIKNDLNLKKSLLATMKTELQKAQQIHSQTSQQYPLYD   850
 851  LDLGKFGEKVTQLTDRWQRIDKQIDFRLWDLEKQIKQLRNYRDNYQAFCK   900
 901  WLYDAKRRQDSLESMKFGDSNTVMRFLNEQKNLHSEISGKRDKSEEVQKI   950
 951  AELCANSIKDYELQLASYTSGLETLLNIPIKRTMIQSPSGVILQEAADVH  1000
1001  ARYIELLTRSGDYYRFLSEMLKSLEDLKLKNTKIEVLEEELRLARDANSE  1050
1051  NCNKNKFLDQNLQKYQAECSQFKAKLASLEELKRQAELDGKSAKQNLDKC  1100
1101  YGQIKELNEKITRLTYEIEDEKRRRKSVEDRFDQQKNDYDQLQKARQCEK  1150
1151  ENLGWQKLESEKAIKEKEYEIERLRVLLQEEGTRKREYENELAKVRNHYN  1200
1201  EEMSNLRNKYETEINITKTTIKEISMQKEDDSKNLRNQLDRLSRENRDLK  1250
1251  DEIVRLNDSILQATEQRRRAEENALQQKACGSEIMQKKQHLEIELKQVMQ  1300
1301  QRSEDNARHKQSLEEAAKTIQDKNKEIERLKAEFQEEAKRRWEYENELSK  1350
1351  VRNNYDEEIISLKNQFETEINITKTTIHQLTMQKEEDTSGYRAQIDNLTR  1400
1401  ENRSLSEEIKRLKNTLTQTTENLRRVEEDIQQQKATGSEVSQRKQQLEVE  1450
1451  LRQVTQMRTEESVRYKQSLDDAAKTIQDKNKEIERLKQLIDKETNDRKCL  1500
1501  EDENARLQRVQYDLQKANSSATETINKLKVQEQELTRLRIDYERVSQERT  1550
1551  VKDQDITRFQNSLKELQLQKQKVEEELNRLKRTASEDSCKRKKLEEELEG  1600
1601  MRRSLKEQAIKITNLTQQLEQASIVKKRSEDDLRQQRDVLDGHLREKQRT  1650
1651  QEELRRLSSEVEALRRQLLQEQESVKQAHLRNEHFQKAIEDKSRSLNESK  1700
1701  IEIERLQSLTENLTKEHLMLEEELRNLRLEYDDLRRGRSEADSDKNATIL  1750
1751  ELRSQLQISNNRTLELQGLINDLQRERENLRQEIEKFQKQALEASNRIQE  1800
1801  SKNQCTQVVQERESLLVKIKVLEQDKARLQRLEDELNRAKSTLEAETRVK  1850
1851  QRLECEKQQIQNDLNQWKTQYSRKEEAIRKIESEREKSEREKNSLRSEIE  1900
1901  RLQAEIKRIEERCRRKLEDSTRETQSQLETERSRYQREIDKLRQRPYGSH  1950
1951  RETQTECEWTVDTSKLVFDGLRKKVTAMQLYECQLIDKTTLDKLLKGKKS  2000
2001  VEEVASEIQPFLRGAGSIAGASASPKEKYSLVEAKRKKLISPESTVMLLE  2050
2051  AQAATGGIIDPHRNEKLTVDSAIARDLIDFDDRQQIYAAEKAITGFDDPF  2100
2101  SGKTVSVSEAIKKNLIDRETGMRLLEAQIASGGVVDPVNSVFLPKDVALA  2150
2151  RGLIDRDLYRSLNDPRDSQKNFVDPVTKKKVSYVQLKERCRIEPHTGLLL  2200
2201  LSVQKRSMSFQGIRQPVTVTELVDSGILRPSTVNELESGQISYDEVGERI  2250
2251  KDFLQGSSCIAGIYNETTKQKLGIYEAMKIGLVRPGTALELLEAQAATGF  2300
2301  IVDPVSNLRLPVEEAYKRGLVGIEFKEKLLSAERAVTGYNDPETGNIISL  2350
2351  FQAMNKELIEKGHGIRLLEAQIATGGIIDPKESHRLPVDIAYKRGYFNEE  2400
2401  LSEILSDPSDDTKGFFDPNTEENLTYLQLKERCIKDEETGLCLLPLKEKK  2450
2451  KQVQTSQKNTLRKRRVVIVDPETNKEMSVQEAYKKGLIDYETFKELCEQE  2500
2501  CEWEEITITGSDGSTRVVLVDRKTGSQYDIQDAIDKGLVDRKFFDQYRSG  2550
2551  SLSLTQFADMISLKNGVGTSSSMGSGVSDDVFSSSRHESVSKISTISSVR  2600
2601  NLTIRSSSFSDTLEESSPIAAIFDTENLEKISITEGIERGIVDSITGQRL  2650
2651  LEAQACTGGIIHPTTGQKLSLQDAVSQGVIDQDMATRLKPAQKAFIGFEG  2700
2701  VKGKKKMSAAEAVKEKWLPYEAGQRFLEFQYLTGGLVDPEVHGRISTEEA  2750
2751  IRKGFIDGRAAQRLQDTSSYAKILTCPKTKLKISYKDAINRSMVEDITGL  2800
2801  RLLEAASVSSKGLPSPYNMSSAPGSRSGSRSGSRSGSRSGSRSGSRRGSF  2850
2851  DATGNSSYSYSYSFSSSSIGH                               2871

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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