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

NucPred

Fetching Q2QLF8 from www.uniprot.org...

The NucPred score for your sequence is 0.96 (see score help below)

   1  MATDGASCEPDLSRAPEDAAGAAAEAAKKEFDVDTLSKSELRMLLSVMEG    50
  51  ELEARDLVIEALRARRKEVFIQERYGRFNLNDPFLALQRDYEAGAGDKEK   100
 101  PVCTNPLSILEAVMAHCRKMQERMSAQLAAAESRQKKLEMEKLQLQALEQ   150
 151  EHKKLAARLEEERGKNKQVVLMLVKECKQLSGRVIEEAQKLEDIMAKLEE   200
 201  EKKKTNELEEELSAEKRRSSEMEAQMEKQLSEFDTEREQLRAKLNREEAH   250
 251  TTDLKEEIDKMKKMIEQLKRGSDSKPSLSLPRKTKDRRLVSISVGTEGTV   300
 301  MRSVACQTDLVTESADHVKKLPLTMPVKPSTGSPLASANAKGSVCSSAAM   350
 351  ARPGIDRQASHGDLIGVSVPAFPPSSANRIEENGPSTGSTPDPTSSIPPL   400
 401  PSNAAPSTAQTPGITPQNSQAPPMHSLHSPCANASLHPGLNPRIQAARFR   450
 451  FQGNANDPDQNGNTTQSPPSRDVSPTSRDNLVAKQLARNTVTQALSRFTG   500
 501  PQAGAPPRPGAPPTGDVSTHPSVGRTSVKTHGIARVDRGNPPPIPPKKPG   550
 551  LSQTPSPPHPQLKVIIDSSRASNTGAKGDNKTVASPPSSLPQGNRVINEE   600
 601  NLPKSSSPQLPPKPSIDLTVAPAGCAVSALATSQVGAWPAATPGLNQPAC   650
 651  SDSSLIIPTTIAFCSSINPVSASSCRPGASDSLLVTASGWSPSLTPLLMS   700
 701  GGPAPLAGRPTLLQQAAAQGNVTLLSMLLNEEGLDINYSCEDGHSALYSA   750
 751  AKNGHTDCVRLLLSAEAQVNAADKNGFTPLCAAAAQGHFECVELLIAYDA   800
 801  NINHAADGGQTPLYLACKNGNKECIRLLLEAGTDRSVKTTDGWTPVHAAV   850
 851  DTGNVDSLKLLMYHRVPAHGNSFSEEESESGVFDLDEGEESPEGKSKPVV   900
 901  TADFINHANREGWTAAHIAASKGFKNCLEILCRHGGLETERRDKCNRTVH   950
 951  DVATDDCKHLLENLNALKIPLRISVGEIEPSNYGSDDFECENTICALNIR  1000
1001  KQTSWDDFSKAVSQALTNHFQAISSDGWWSLEDMTCNNTTDSNIGLSARS  1050
1051  IRSITLGNVPWSVGQSFVQSPWDFMIKNKAEHITVLLSGPQEGCLSSVTY  1100
1101  ASMIPLKMMQNYLRLVEQYHNVIFHGPEGSLQDYIVHQLALCLKHRQMAA  1150
1151  GFSCEIVKAEVDAGFSKKQLLDLFISSACLIPVKQSPVKKKIIIILENLE  1200
1201  KSSLFELLRDFLAPLENRSTESPCTFHKGNGMSECYYFHENCFLMGTIAK  1250
1251  ACLQGSDLLVQQHFRWVQLRWDGEPMQGLLQRFLRRKVVNKFRGQVPPPC  1300
1301  DPVCKIVDWALSVWRQLNSCLSRLGTPEALLGPKYFLSCPVVPGHAQVTV  1350
1351  KWMSKLWNGVITPRVQEAILSRASVKRQAGFRQTIAKRHPSQGQQAVVKA  1400
1401  ALSILLNKAVLHGCPLPRAELEQHRADFKGGSFPLSIVSSYNSCSKKKGE  1450
1451  SGAWRKVNTSPRRKSGRFSLPTWNKPDLSTEGIKNKTLSQLNCNRNASLS  1500
1501  KQMSLENDVSLTLNLDQRLSLGSDDEADLVKELQSMCSSKSESDISKIAD  1550
1551  SRDDLRMFDSSGNNPVFSATINNLRMPVSQKEVCPLSSHHTTECSNSKSK  1600
1601  TELGVSRVKSFLPVPRSKVTQCSQNTKRSSSSSNTRQIEINNNSKEENWN  1650
1651  LHKNEHLEKPNK                                        1662

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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