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

NucPred

Fetching Q9TTK4 from www.uniprot.org...

The NucPred score for your sequence is 0.97 (see score help below)

   1  MSTDSNSLAREFLTDVNRLCNAVVQRVEAREEEEEETHMATLGQYLVHGR    50
  51  GFLLLTKLNSIIDQALTCREELLTLLLSLLPLVWKIPVQEEKATDFNLPF   100
 101  SAGIILTKEKNSSSQRSTQEKLYLEGSAPAGQVSAKVNVFRKSRRQRKTT   150
 151  HRYSVRDARKTQLSTSDSEVNSDDKSIVMTKYRRSHVLQHFVKQCPKEDH   200
 201  LTAKLNHLSTKEQTPPDTMALENSREIIPREESNTDILSEPAALSTISHM   250
 251  NNSPFDLCHVLLSLLEKVCKFDITLNHNSALAASVVPTLTEFLAGFGDCC   300
 301  NLSDNLEGQMVSAGWTEEPVALIQRMLFRTVLHLMSVDISMAEVMPENLR   350
 351  KNLTELLRAALKIRTFLEKQPDPFAPRQKKTLQEVQDDFVFSKYCHRVLL   400
 401  LPELLEGVLQILICCLQSAASNPFFFSQAMDLVQEFIQHHGFHLFETAVL   450
 451  QMEWLVVRDGVPPEASGHLKALINNVMKIMSTVKKVKSEQLHHSMCTRKR   500
 501  HRRCEYSHFMHHHRDLSGLLVSAFKNQVSKNPFEETADGDVYYPERCCCI   550
 551  AVCAHQCLRLLQQASLSSTCVQILSGVQNIGICCCMDPKSVIVPLLHAFK   600
 601  LPALKSCQQHILNILNKLILDQLGGAEIPQKTKKAACNICTVDSDQLAKL   650
 651  EETLQGSSYNAEPSSGLSSPSYRFQGILPSSGSEDLLWKWDALEAYQNFV   700
 701  FEEDRLQSVQIANHICSLIQKGNVVVQWKLYNCIFNPVLQRGVELAHHCQ   750
 751  QLSISSAQTHVCSHHNQCLPQEVLQIYLKTLPTLLKSRVIRDLFLSCNGV   800
 801  NQIIELNYLDGIRNHSLKAFETLIISLGEQQKDSSIPGIDGIDLEQKELS   850
 851  SLNVGTLYNQQAYSDSQSLSKFYARLKDAYPKKRKSVVQDIHISTINLFL   900
 901  CVAFLCVSKEAESDRESANDSEDTSGYDSTASEPLQHMLPCFSLESLVLP   950
 951  SPRHMHQAADVWSMCRWIYMLSPIFRKQFYRLGGFQVCHKLIFMVIQDLF  1000
1001  RNPEEEQGRKEGDRTMNENQDLNRISQPEITVKEDLLSLTVKIDPTPTEL  1050
1051  SSLKKSADSLGRLESEHLSSINVEQIPAVEAVPEETKVFMSRESETLLQG  1100
1101  IRLLEALLAICLHGTRASQQKLELELPNQNLSVETILLEMRDHLSKSKVT  1150
1151  ETELAKPLFDALLRVALGNHSADFEHDDAMTEKSHQSEEELSSQPGDFSE  1200
1201  EAEDSQCCSFKLLVEEEGYEADSESNPEDSETWDDGVDLKPEAESFIASS  1250
1251  SPNDLLENLSQGEIIYPEICTLELNLLSTGKAKLDVLAHVFESFLKIIRQ  1300
1301  KEKNIFLLMQQGTVKNLLGGFLSILTQTDSDFQACQRVLVDLLVSLMSSR  1350
1351  TCSEELTLLLRIFLEKSPCTEILLLGILKIVESDITMSPSQYLTFPLLHT  1400
1401  PNLSNGVSSQKCPGILNSKAMGLLRRARVSQSKKEGDSESFPQQLLSSWH  1450
1451  IAPVHLPLLGQPHLSEGFSISLWFNVECIHEPESTTEKGKKTRKRNKSLV  1500
1501  LLDSSFDGTENNRLEGAAYVNPGERLIEEGCVHMISLGSKALIIQVWADP  1550
1551  HTGTFIFRVCMDSNDDTKVVLLAQVESQENIFLPSKWQHLVLTYLQQPQG  1600
1601  KKNIHGKISIWISGQRKPDVTLDFMLPRKTSLSSDSNKTFCMIGHCLSSQ  1650
1651  EESLQLAGKWDLGNLLLFNGAKIGSQEAFYLYACGPNHTSIMPCKYGKPV  1700
1701  NDYSKYINTEILQCEQIRELFMTSKDVDIGLLIESLSVVYTTYCPAQYTI  1750
1751  YEPVIRLKGQMKTQLSQRPFSSKEVHNILLEPHHLKNLQPTECKTLQGIL  1800
1801  HEIGGTGIFVFLFARVVELSSCEETQALALRVILSLIKYNQQRIHELENC  1850
1851  NGLSMIHQVLIKQKCIVGFHILKTLLEGCCGEDIIHINENGELKLDVESN  1900
1901  AIIQDVKLLEELLLDWKIWNKAEHGVWETLLAALEVLIRADHQQQMFNIK  1950
1951  QLLKARVVHHFLLTCQVLQEHKEGQLISMPQEVCRSFVKITAEVLGSPPD  2000
2001  LELLTIIFNFLLAVHPPTNTYVCHNPTNFYFSLHIDGKIFQEKVQSIMYL  2050
2051  RHSSSGGKSVTSPGFMIISPSDFTASPPEGNNSSSAVPKQVTASMLRSRS  2100
2101  LPAFPTASPHIKPRKLTGSLGCSIDKLQSFVDDGVASQPEKWSPLRSSET  2150
2151  LEKSKQDAFISSCESAKMVCETEPALLAQASVSDIPKGALELPAVNIDHK  2200
2201  DFGAEPRSDDDSPGDESCPRRPLYLKGLASFQRSHSTIASLGLAFPSQNG  2250
2251  SAAVGRWPSLVDRNADDWENFALSLGYEPHHSRTAGAHSVTEDCLVPICC  2300
2301  GLYELLSGVLLILPDVMLEDVMDRLIQADTLLVLVNHPSPAVQQEVIKLL  2350
2351  DAYFNRASKEQKDKFLKNRGFSLLANQLYLHRGTQELLECFIEMFFGRRI  2400
2401  GLDEEFDLEDVKNMGLFQKWSVIPILGLIETSLYDNVLLHNALLLLLQIL  2450
2451  NSCSKVADMLLDNGLLYVLCNTVATLNGLEKIIPLNEYRLLACDIQQLFI  2500
2501  AVTIHACSSSGSQYFRVIEDLIVLLGYLQNSKNKRTQNMAVALQFRVLQA  2550
2551  AMEFIRTTANHDSENLTDSLQSPSVPHHTMFQKRKSIAGPRKFLLAQTDS  2600
2601  LLMKMRSVASDELHVMMQRRMSQENPVQATETELAQRLQRLTVFAVNRIV  2650
2651  YQEFNPDIIDILSTPESTTQSRTSASQTEISEENIHHEQPSVFNPFQKEM  2700
2701  FMYLVEGFKVSSASGKTSSSKQQWAKILWSCKETFRMQLGRLLVHMLSPA  2750
2751  HPSQERKQIFEIVREPNHQEILRECLSPSLQHGAKLVLYLSELIHNHKDE  2800
2801  LTEEELDTAELLMNALKLCGHKCIPPSASTKSDLIRVIKEEQRKYETEEG  2850
2851  VNKANWQKTVNNNQQSLFQRLDSKSKDISKIAADITQAVSLSQGIERKKV  2900
2901  IQHIRGMYKVDLSASRHWQELIQQLTHDRAVWYDPIYYPTSWQLDPTEGP  2950
2951  NRERRRLQRCYLTIPNKYLLRDRQKSEDVVKPPLSYLFEDKTHSSFSSTV  3000
3001  KDKAASESIRVNRRCISVAPSRETAGELLLGKCGMYFVEDNASDTVECSN  3050
3051  LQGELEPASFSWTYEEIKEVHKRWWQLRDNAVEIFLTNGRTLLLAFDNTK  3100
3101  VRNDVYHSILTNNLPNLLEYGNITALTHLWYTGQITNFEYLTHLNKHAGR  3150
3151  SFNDLMQYPVFPFILADYVSETLDLSDPSVYRNLSKPIAVQYKEKEDRYV  3200
3201  DTYKYLEEEYRKGAREDDPMPPVQPYHYGSHYSNSGTVLHFLVRMPPFTK  3250
3251  MFLAYQDQSFDIPDRTFHSTNTTWRLSSFESMTDVKELIPEFFYLPEFLV  3300
3301  NREGFDFGVRQNGERVNHVNLPPWARNDPRLFILIHRQALESDYVSQNIC  3350
3351  QWIDLVFGYKQKGKASVQAINVFHPATYFGMDVSAVEDPVQRRALETMIK  3400
3401  TYGQTPRQLFQSAHASRPGSKLNIEGELPAAVGLLVQFAFRETREQVKEI  3450
3451  TYPSPLSWIKGLKWGEYVGSPSAPVPVVCFSQPHGERFGSLQALPTRAIC  3500
3501  GLSRNFCLLMTYSKEQGVRSMNSTDIQWSAILSWGYADNILRLKSKQSEP  3550
3551  PINFIQSSQQYQVTSCAWVPDSCQLFTGSKCGVITAYSNRFTSGTPSEIE  3600
3601  MESQIHLYGHTEEISSLFVCKPYSIMISVSRDGTCIIWDLNRLCYVQSLA  3650
3651  GHKSPVTAVSASETTGDIATVCDSAGGGSDLRLWTVNGDLVGHVHCREII  3700
3701  CSVAFSNQPEGISINVIAGGLENGIVRLWSTWDLKPVREITFPKSNKPIV  3750
3751  SLTFSCDGHHLYTANSDGTVIAWCRKDQQRLKHPMFYSFLSSYAAG      3796

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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