Citrus Sinensis ID: 006884


Local Sequence Feature Prediction

Prediction and MethodResult
Residue Number Marker
Protein Sequence ?
Secondary Structure (Consensus) ?
Disordered Region (Consensus) ?
Transmembrane Helix (Consensus) ?
Signal Peptide (Consensus) ?
Coiled Coil (COILS) ?
 
--------10--------20--------30--------40--------50--------60--------70--------80--------90-------100-------110-------120-------130-------140-------150-------160-------170-------180-------190-------200-------210-------220-------230-------240-------250-------260-------270-------280-------290-------300-------310-------320-------330-------340-------350-------360-------370-------380-------390-------400-------410-------420-------430-------440-------450-------460-------470-------480-------490-------500-------510-------520-------530-------540-------550-------560-------570-------580-------590-------600-------610-------620-------
MKLQISMVVPIFLFTVLPIFPTVVADLNSDKQALLDFADAVPHARKLNWNAAAPVCSSWIGVTCNVNRSRVIGIHLPGIGFTGPIPANSIGKLDALKILSLRSNYLNGTLPSDITSISSLQYVYLQNNYFSGVLPAFRSLQLNALDLSFNAFTGNIPPGFQNLTRLHLLNLQNNSISGAIPPLNLPRLKILNFSNNNLNGSIPDSLQTFPNSSFVGNSMLCGLPLTPCSTVSSSPSPSPSYFPTISPHKNASRKKLNSGSIIAIAVGGCAVLFLLLALFFLCCLKKLDRQGSGVLKGKGTAEKPKDFGSGVQEAEKNKLCFLDGSYFNFDLEDLLRASAEVLGKGSYGSTYKAILEDGTTVVVKRLREVAATKREFEQQMEVVGTIGKHSNVVPVRAYYYSKDEKLVVYSYMPAGSLFMLLHRNRSDGGTALDWNSRMKIALGTARGIAFIHSEGGAKFTHGNIKSSNVLLTQDLNGCISDVGLAHLINFPTTATRTIGYRAPEVTETRKASQKSDVYSFGVLLLEMLTGKAPLQHSGHDDVVDLPRWVRSVVREEWTAEVFDVELLKYQDVEEEMVQMLQIALSCVAKVPDSRPKMDDVVRMIEQIQQPELRNRASSGTESNVQTP
cccccHHHHHHHHHHHHHHccccccccHHHHHHHHHHHHHccccccccccccccccccccEEEEccccccEEEEEccccccccccccccccccccccEEEcccccccccccccccccccccEEEcccccccccccccccccccEEEcccccccccccHHHccccccccEEccccccCCcccccccccccEEEcccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccHHHHHHHHHHHHHHHHHHHHHHHHHHHHHccccccccccccccccccccccccccccccccEEEEccccccccHHHHHHHHcccccccccccEEEEEEccccEEEEEEcccccccHHHHHHHHHHHccccccccccccEEEECcccCEEEEEcccccccHHHHHHcccccccccccHHHHHHHHHHHHHHHHHHHccccccccccccccccEEEcccccCEEcccccccccccccccccccccccccccccccccccccEEcHHHHHHHHHccccccccccccccccHHHHHHHHHHHccccEEEccccccccccHHHHHHHHHHHHccccccccccccHHHHHHHHHHccccccccccccccccccccc
****ISMVVPIFLFTVLPIFPTVVADLNSDKQALLDFADAVPHARKLNWNAAAPVCSSWIGVTCNVNRSRVIGIHLPGIGFTGPIPANSIGKLDALKILSLRSNYLNGTLPSDITSISSLQYVYLQNNYFSGVLPAFRSLQLNALDLSFNAFTGNIPPGFQNLTRLHLLNLQNNSISGAIPPLNLPRLKILNFSNNNLNGSIPDSLQTFPNSSFVGNSMLCGLPLT********************************GSIIAIAVGGCAVLFLLLALFFLCCLKKLD****************************NKLCFLDGSYFNFDLEDLLRASAEVLGKGSYGSTYKAILEDGTTVVVKRLREVAATKREFEQQMEVVGTIGKHSNVVPVRAYYYSKDEKLVVYSYMPAGSLFMLLHRNRSDGGTALDWNSRMKIALGTARGIAFIHSEGGAKFTHGNIKSSNVLLTQDLNGCISDVGLAHLINFPTTATRTIGYRAPEVTETRKASQKSDVYSFGVLLLEMLTGKAPLQHSGHDDVVDLPRWVRSVVREEWTAEVFDVELLKYQDVEEEMVQMLQIALSCVAKVPDSRPKMDDVVRM************************
xxxxHHHHHHHHHHHHHHHHHHHHHxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxHHHHHHHHHHHHHHHHHHHHHHHHxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
SSSSSSSSSSSSSSSxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
MKLQISMVVPIFLFTVLPIFPTVVADLNSDKQALLDFADAVPHARKLNWNAAAPVCSSWIGVTCNVNRSRVIGIHLPGIGFTGPIPANSIGKLDALKILSLRSNYLNGTLPSDITSISSLQYVYLQNNYFSGVLPAFRSLQLNALDLSFNAFTGNIPPGFQNLTRLHLLNLQNNSISGAIPPLNLPRLKILNFSNNNLNGSIPDSLQTFPNSSFVGNSMLCGLPLTPCSTVSSSPSPSPSYFPTISPHKNASRKKLNSGSIIAIAVGGCAVLFLLLALFFLCCLKKLDRQGSGVLKGKGTAEKPKDFGSGVQEAEKNKLCFLDGSYFNFDLEDLLRASAEVLGKGSYGSTYKAILEDGTTVVVKRLREVAATKREFEQQMEVVGTIGKHSNVVPVRAYYYSKDEKLVVYSYMPAGSLFMLLHRNRSDGGTALDWNSRMKIALGTARGIAFIHSEGGAKFTHGNIKSSNVLLTQDLNGCISDVGLAHLINFPTTATRTIGYRAPEVTETRKASQKSDVYSFGVLLLEMLTGKAPLQHSGHDDVVDLPRWVRSVVREEWTAEVFDVELLKYQDVEEEMVQMLQIALSCVAKVPDSRPKMDDVVRMIEQIQQPELRNRASSGTESNVQTP

Function Prediction

Annotation transfered from Closely Related SWISS-PROT Entries ?

Annotation ?Function Description ?Confidence Level ?Reference Protein ?
Probable inactive receptor kinase At5g58300 probableQ9LVM0

Prediction of Enzyme Commission Number ?

No confident prediction of EC number!


Spatial Structural Prediction

Structural Models Based on Templates

Template: 1ZIW, chain A
Confidence level:very confident
Coverage over the Query: 70-225
View the alignment between query and template
View the model in PyMOL
Template: 3RGZ, chain A
Confidence level:very confident
Coverage over the Query: 25-216
View the alignment between query and template
View the model in PyMOL
Template: 3OJA, chain A
Confidence level:very confident
Coverage over the Query: 375-403
View the alignment between query and template
View the model in PyMOL
Template: 3VHE, chain A
Confidence level:very confident
Coverage over the Query: 429-561,572-610
View the alignment between query and template
View the model in PyMOL
Template: 3UIM, chain A
Confidence level:very confident
Coverage over the Query: 327-608
View the alignment between query and template
View the model in PyMOL
Template: 3TL8, chain A
Confidence level:confident
Coverage over the Query: 325-605
View the alignment between query and template
View the model in PyMOL
Template: 2KS1, chain B
Confidence level:probable
Coverage over the Query: 259-289
View the alignment between query and template
View the model in PyMOL