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

NucPred

Fetching Q91132 from www.uniprot.org...

The NucPred score for your sequence is 0.42 (see score help below)

   1  MERMALYLVAALLIGFPGSSHGALYTLITPAVLRTDTEEQILVEAHGDST    50
  51  PKQLDIFVHDFPRKQKTLFQTRVDMNPAGGMLVTPTIEIPAKEVSTDSRQ   100
 101  NQYVVVQVTGPQVRLEKVVLLSYQSSFLFIQTDKGIYTPGSPVLYRVFSM   150
 151  DHNTSKMNKTVIVEFQTPEGILVSSNSVDLNFFWPYNLPDLVSLGTWRIV   200
 201  AKYEHSPENYTAYFDVRKYVLPSFEVRLQPSEKFFYIDGNENFHVSITAR   250
 251  YLYGEEVEGVAFVLFGVKIDDAKKSIPDSLTRIPIIDGDGKATLKRDTFR   300
 301  SRFPNLNELVGHTLYASVTVMTESGSDMVVTEQSGIHIVASPYQIHFTKT   350
 351  PKYFKPGMPYELTVYVTNPDGSPAAHVPVVSEAFHSMGTTLSDGTAKLIL   400
 401  NIPLNAQSLPITVRTNHGDLPRERQATKSMTAIAYQTQGGSGNYLHVAIT   450
 451  STEIKPGDNLPVNFNVKGNANSLKQIKYFTYLILNKGKIFKVGRQPRRDG   500
 501  QNLVTMNLHITPDLIPSFRFVAYYQVGNNEIVADSVWVDVKDTCMGTLVV   550
 551  KGDNLIQMPGAAMKIKLEGDPGARVGLVAVDKAVYVLNDKYKISQAKIWD   600
 601  TIEKSDFGCTAGSGQNNLGVFEDAGLALTTSTNLNTKQRSAAKCPQPANR   650
 651  RRRSSVLLLDSNASKAAEFQDQDLRKCCEDVMHENPMGYTCEKRAKYIQE   700
 701  GDACKAAFLECCRYIKGVRDENQRESELFLARDDNEDGFIADSDIISRSD   750
 751  FPKSWLWLTKDLTEEPNSQGISSKTMSFYLRDSITTWVVLAVSFTPTKGI   800
 801  CVAEPYEIRVMKVFFIDLQMPYSVVKNEQVEIRAILHNYVNEDIYVRVEL   850
 851  LYNPAFCSASTKGQRYRQQFPIKALSSRAVPFVIVPLEQGLHDVEIKASV   900
 901  QEALWSDGVRKKLKVVPEGVQKSIVTIVKLDPRAKGVGGTQLEVIKARKL   950
 951  DDRVPDTEIETKIIIQGDPVAQIIENSIDGSKLNHLIITPSGCGEQNMIR  1000
1001  MAAPVIATYYLDTTEQWETLGINRRTEAVNQIVTGYAQQMVYKKADHSYA  1050
1051  AFTNRASSSWLTAYVVKVFAMAAKMVAGISHEIICGGVRWLILNRQQPDG  1100
1101  AFKENAPVLSGTMQGGIQGAEEEVYLTAFILVALLESKTICNDYVNSLDS  1150
1151  SIKKATNYLLKKYEKLQRPYTTALTAYALAAADQLNDDRVLMAASTGRDH  1200
1201  WEEYNAHTHNIEGTSYALLALLKMKKFDQTGPIVRWLTDQNFYGETYGQT  1250
1251  QATVMAFQALAEYEIQMPTHKDLNLDITIELPDREVPIRYRINYENALLA  1300
1301  RTVETKLNQDITVTASGDGKATMTILTFYNAQLQEKANVCNKFHLNVSVE  1350
1351  NIHLNAMGAKGALMLKICTRYLGEVDSTMTIIDISMLTGFLPDAEDLTRL  1400
1401  SKGVDRYISRYEVDNNMAQKVAVIIYLNKVSHSEDECLHFKILKHFEVGF  1450
1451  IQPGSVKVYSYYNLDEKCTKFYHPDKGTGLLNKICIGNVCRCAGETCSSL  1500
1501  NHQERIDVPLQIEKACETNVDYVYKTKLLRIEEQDGNDIYVMDVLEVIKQ  1550
1551  GTDENPRAKTHQYISQRKCQEALNLKVNDDYLIWGSRSDLLPTKDKISYI  1600
1601  ITKNTWIERWPHEDECQEEEFQKLCDDFAQFSYTLTEFGCPT          1642

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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