Citrus Sinensis ID: 001064

Local Sequence Feature Prediction

Prediction and Method	Result

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-------630-------640-------650-------660-------670-------680-------690-------700-------710-------720-------730-------740-------750-------760-------770-------780-------790-------800-------810-------820-------830-------840-------850-------860-------870-------880-------890-------900-------910-------920-------930-------940-------950-------960-------970-------980-------990------1000------1010------1020------1030------1040------1050------1060------1070------1080------1090------1100------1110------1120------1130------1140------1150------1160------117

MDPNAVMQQAPGVGAPGSGDNVATSENEAMGSSQAAGYNSMNGNVVNEAGNATSTENGTSLGIESGAAAGQELVDGSAMSGEEDRLWNIVKANSSDFSAWTALLEETEKLAQDNIVKIRRVYDAFLAEFPLCYGYWKKYADHEARVGSMDKVVEVYERAVQGVTYSVDIWLHYCIFAINTYGDPETIRRLFERGLAYVGTDYLSFPLWDKYIEYEYMQQEWSRVAMIYTRILENPIQQLDRYFSSFKEFAASRPLSELRTAEEVDAAAVAVAAAPSETGAEVKANEEEVQPDATEQTSKPVSAGLTEAEELEKYIAVREEMYKKAKEFDSKIIGFETAIRRPYFHVKPLSVTELENWHNYLDFIERDGDFNKVVKLYERCLIACANYPEYWIRYVLCMEASGSMDLAHNALARATHVFVKRLPEIHLFAARFKEQNGDIDGARAAYQLVHTETSPGLLEAIIKHANMERRLGNLEDAFSLYEQAIAIEKGKEHSQTLPMLYAQYSRFLHLVSRNAEKARQILVDSLDHVQLSKPLLEALIHFESIQSSPKQIDFLEQLVDKFLMSNSDSPSTANAAEREELSCVFLEFLGLFGDAQLIKKAEDRHARLFLPHRSTSELRKRHAEDFLASERAKMAKSYSGAPSPAQSLMGAYPSSQNPWAAGYGVQPQTWPPATQAQAQQWNQQAAYGAYSAYGSSYPTPQTSVPQNAAYGAYPPAYPAQVGSYFVGQYYQVLQQQPDLVHQFYSDASSMIRVDGDSTESASSMLDIHSLVISLNFTAIEIKTINSLGSWNGGVLVMVSGSVKTKEFCRRRKFVQTFFLAPQEKGYFVLNDIFHFLDEEPVYQHPAPVLSENKFDVQHDASSPIPEQAGLAASDYVLEEEAREYVSSVHIEDDATDNYSLPEQQQDEEPESEEVDEEIPAEEIPASFQTDVSPVQPPPAPAVEEPVDEPQRKTYASILRVSKSQSTSFVATQPSFTKTASTTSDWNPAPQPTTQQSNYTSSFVPESGVSSHMPESGFEAVDDSLGLDEGEVKSVYVRNLPSTVTAFEIEEEFQNFGRIKPDGVFVRNRKDVVGVCYAFVEFEDISGVQNAIQASPIQLAGRQVYIEERRPNTGSTSRGGRRGRGRGSYQTDAPRGRFGGRGLGRGSAQDGGDYNRSRGNGFYQRGSQ

ccccHHHcccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccHHHHHHHHHHHHccccHHHHHHHHHHHHHHcHHHHHHHHHHHHHHHHHccccHHHHHHHHHHHHHcccHHHHHHHHHHHHHcccccHHHHHHHHHHHHHHcccHHHHHHHHHHHHHHccccccccHHHHHHHHHHHHHHHHHHHHHHHHHHHHcccccHHHHHHHHHHHHHccccHHHccHHHHHHHHHHHHHccccccHHHHHcccccccccccccccccccccHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHccccccccccccHHHHHHHHHHHHHHHHccccHHHHHHHHHHHHHccccHHHHHHHHHHHHHcccHHHHHHHHHHHHHHHHcccHHHHHHHHHHHHHcccHHHHHHHHHHHHHHccccHHHHHHHHHHHHHHHccHHHHHHHHHHHHHHHHcccccccHHHHHHHHHHHHHHHHccHHHHHHHHHHHHHcccccHHHHHHHHHHHHHccccHHHHHHHHHHHHHHHccccccccccHHHHHHHHHHHHHHHHHcccHHHHHHHHHHHHHHccccccHHHHHHHHHcHHHHHHHHHHHcccccccccccccccccccccccccccccccccccccccHHHHHHHHHHHcccccccccccccccccccccccccccccccccccccccHHHHHHHHHHHccccccccccccccEEEcccccccccccHHHHHHHHHHcccccEEEEEEcccccccccEEEEEEEEEEcccccccccEEEEEEEEECcccEEEEcccEEEcccccccccccccccccccccccccccccccccccccccccHHHHHHcccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccHHHHHccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccEEEEEcccccccHHHHHHHHHHccccccccEEEEEccccccccEEEEEEccHHHHHHHHHHcccEEccEEEEEEEcccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc

************************************************************************************RLWNIVKANSSDFSAWTALLEETEKLAQDNIVKIRRVYDAFLAEFPLCYGYWKKYADHEARVGSMDKVVEVYERAVQGVTYSVDIWLHYCIFAINTYGDPETIRRLFERGLAYVGTDYLSFPLWDKYIEYEYMQQEWSRVAMIYTRILENPIQQLDRYFSSFKEFAASRPLSELRTAEEVDAAAVAVAAAPSETGAEVKANEEEVQPDATEQTSKPVSAGLTEAEELEKYIAVREEMYKKAKEFDSKIIGFETAIRRPYFHVKPLSVTELENWHNYLDFIERDGDFNKVVKLYERCLIACANYPEYWIRYVLCMEASGSMDLAHNALARATHVFVKRLPEIHLFAARFKEQNGDIDGARAAYQLVHTETSPGLLEAIIKHANMERRLGNLEDAFSLYEQAIAIEKGKEHSQTLPMLYAQYSRFLHLVSRNAEKARQILVDSLDHVQLSKPLLEALIHFESIQSSPKQIDFLEQLVDKFLMSNSD******AAEREELSCVFLEFLGLFGDAQLIKKAEDRHARLFLPHR**********************************************AAGYGV**QTWPPATQAQAQQWNQQAAYGAYSAYGSSYPTPQT****NAAYGAYPPAYPAQVGSYFVGQYYQVLQQQPDLVHQFYSDASSMIRVDGDSTESASSMLDIHSLVISLNFTAIEIKTINSLGSWNGGVLVMVSGSVKTKEFCRRRKFVQTFFLAPQEKGYFVLNDIFHFLDEEPVYQHPA**************************************************************************************************************************************************************************************GEVKSVYVRNLPSTVTAFEIEEEFQNFGRIKPDGVFVRNRKDVVGVCYAFVEFEDISGVQNAIQASPIQLAGRQVYI**************************************************************

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MDPNAVMQQAPGVGAPGSGDNVATSENEAMGSSQAAGYNSMNGNVVNEAGNATSTENGTSLGIESGAAAGQELVDGSAMSGEEDRLWNIVKANSSDFSAWTALLEETEKLAQDNIVKIRRVYDAFLAEFPLCYGYWKKYADHEARVGSMDKVVEVYERAVQGVTYSVDIWLHYCIFAINTYGDPETIRRLFERGLAYVGTDYLSFPLWDKYIEYEYMQQEWSRVAMIYTRILENPIQQLDRYFSSFKEFAASRPLSELRTAEEVDAAAVAVAAAPSETGAEVKANEEEVQPDATEQTSKPVSAGLTEAEELEKYIAVREEMYKKAKEFDSKIIGFETAIRRPYFHVKPLSVTELENWHNYLDFIERDGDFNKVVKLYERCLIACANYPEYWIRYVLCMEASGSMDLAHNALARATHVFVKRLPEIHLFAARFKEQNGDIDGARAAYQLVHTETSPGxxxxxxxxxxxxxxxxxxxxxxxxxxxxIAIEKGKEHSQTLPMLYAQYSRFLHLVSRNAEKARQILVDSLDHVQLSKPLLEALIHFESIQSSPKQIDFLEQLVDKFLMSNSDSPSTANAAEREELSCVFLEFLGLFGDAQLIKKAEDRHARLFLPHRSTSELRKRHAEDFLASERAKMAKSYSGAPSPAQSLMGAYPSSQNPWAAGYGVQPQTWPPATQAQAQQWNQQAAYGAYSAYGSSYPTPQTSVPQNAAYGAYPPAYPAQVGSYFVGQYYQVLQQQPDLVHQFYSDASSMIRVDGDSTESASSMLDIHSLVISLNFTAIEIKTINSLGSWNGGVLVMVSGSVKTKEFCRRRKFVQTFFLAPQEKGYFVLNDIFHFLDEEPVYQHPAPVLSENKFDVQHDASSPIPEQAGLAASDYVLEEEAREYVSSVHIEDDATDNYSLPEQQQDEEPESEEVDEEIPAEEIPASFQTDVSPVQPPPAPAVEEPVDEPQRKTYASILRVSKSQSTSFVATQPSFTKTASTTSDWNPAPQPTTQQSNYTSSFVPESGVSSHMPESGFEAVDDSLGLDEGEVKSVYVRNLPSTVTAFEIEEEFQNFGRIKPDGVFVRNRKDVVGVCYAFVEFEDISGVQNAIQASPIQLAGRQVYIEERRPNTGSTSRGGRRGRGRGSYQTDAPRGRFGGRGLGRGSAQDGGDYNRSRGNGFYQRGSQ

Function Prediction

Annotation transfered from Closely Related SWISS-PROT Entries

No confident close homologs for annotation transfering were detected in SWISSPROT

Prediction of Enzyme Commission Number

No confident prediction of EC number!

Spatial Structural Prediction

Structural Models Based on Templates

Template: 2OOE, chain A
Confidence level:very confident
Coverage over the Query: 86-268,312-643
View the alignment between query and template
View the model in PyMOL

Template: 2UY1, chain A
Confidence level:very confident
Coverage over the Query: 116-131,147-260,311-564,578-650
View the alignment between query and template
View the model in PyMOL

Template: 2OOE, chain A
Confidence level:very confident
Coverage over the Query: 76-231,247-252,272-278,290-567
View the alignment between query and template
View the model in PyMOL

Template: 3Q90, chain A
Confidence level:very confident
Coverage over the Query: 717-839
View the alignment between query and template
View the model in PyMOL

Template: 2GHP, chain A
Confidence level:very confident
Coverage over the Query: 1030-1111
View the alignment between query and template
View the model in PyMOL

Template: 4E6H, chain A
Confidence level:very confident
Coverage over the Query: 48-260,273-570
View the alignment between query and template
View the model in PyMOL

Template: 1M2V, chain B
Confidence level:probable
Coverage over the Query: 751-766
View the alignment between query and template
View the model in PyMOL