Citrus Sinensis ID: 000635

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------1170------1180------1190------1200------1210------1220------1230------1240------1250------1260------1270------1280------1290------1300------1310------1320------1330------1340------1350------1360------1370------1380

MVEIIINVVFEVAKWLAAPIGRQVSYLSKSNYTSSFENLKKEVEKLRGERESMRQRVEEAERNRQEIEKNVEKWLERVNKIIDETVKITGDEETATKHCIKGLCPNLKTRYQLSKKAATLVKDIVELREEASKFPKVSYRTIPEDIWFHSIKGYEAFESRLSTLKSIRNALTDPNVSIIGVYGMGGIGKTTLAKEVARRAKEDNIFDAVAFSEVSQTPDIKNIQGEIAEKLGLTLREESESRRASSLYERLKKEKKILVVLDNLWKSLDLETTIGIPYGDDHKGCKVLLTTRDRSVLLSMGSKENFPIGVLNEQEAWRLFKLTADDDVENRRLKSIATQVAKACGGLPIALTTIAKALRKKSVPEWENALQELRRPSMESFQGVPKEAYSTIELSYKYLEGEKLKKMFLLCSLMPNPCYTLDLLKYCMGLGMFQRVHKLEDARTKMHAWVHELVDSCLLLVDDSGDNFSMHDVVRDVAISIACRDEHTFLVRNEDVWDWPDEDEKKECYAISVRDSSIHELPEGLKCPQLQFLTIANSKDSFLEIDVPEDFFTGMRKLRVVHFSGMRLASLPYSIGLLQNLQTLCLERSTVGDIAIIGKLKNLEVLSFLQSDIVMLPKEIGQLTKLRLLDLTDCFKLKVIATNVLSSLTRLEALYMHNCYVEWEVETRGSEKRSASLDEFLHLPRLTTLEIEVRNDDILPEGFFTKKLARFKISVGDESFSTPFYFVESWFSSRPNFMIGKHESLRTLKLKLSSKPIGSKELQGVNNVEYLCLDELPGVKTVLFELDTKGFSQLKHLHIQNNPDLLCIVDSRDRETYDAFPLLESLTLQNLIRLERTCMDRLKVESFNELKIIKVENCDELTNIFWLSNTKCLHKLERIAVIDCKKMEEVFAIGGEADVGNKNAIEKIEFAQLKSLSLGMLPKVTNFFREVKTPPASPNRRESEEDELDTSIQLLNEKVVLPNLEALELRDINIDKIWHYNELPAMFPGSQSLTRLILWDCNKLKYIFSATMIRSFEQLQRLEISNCMVLQEIISKDRAEADQRTTPCFVFPRLTTLILLGLPELKCFYPGMHTSEWPALKILNVIFPNLEDLALSGEDVEMILMGDFPHHLFGCLKQVAVATDESECFPLGLLERFLNMEDLYLRACSYKEIFSSNDEYLEKDVRNFALIKRLHLVELDDLKHLWKPNSKLEHILQYLEKLFVSYCQSLLILLPSASISFRNLTELQVTNCKKLINLVTSSVAKSLVGLLMLNIYGCRAMTEVVTGDENGAANPKEEIVFTKLKSISLVDLDSLTSFCSANYTFNFPSLQDLEVIGCPKMTIFTTVELCTPPRVNVWYGEGNLWRSDDGGVNTTIQHLHDEKLLEGSSSHIAYDWIRDI

cccHHHHHHHHHHHHHHHHHHHHHHHHHccHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHccccHHHHHHHHHHHHHHHHHHHHHHccHHHHHccccccccccccHHHHHHHHHHHHHHHHHHHHHHHcccccccccccccccccccccccccHHcHHHHHHHHHHHHcccccEEEEEECcccccHHHHHHHHHHHccccccccEEEEEEEcccccHHHHHHHHHHHHccccccccHHHHHHHHHHHHHcccEEEEEEccccccccccccccccccccccccEEEEEEccHHHHHHccccccCCcccccHHHHHHHHHHHcccccccccHHHHHHHHHHHccccHHHHHHHHHHHccccHHHHHHHHHHHcccccccccccccccHHHHHHHccccccccHHHHHHHccccccccccHHHHHHHHHcccccccccHHHHHHHHHHHHHHHHHccccccccccccEEEccHHHHHHHHHHccccEEEEEEccccccccccccCEEEEEEEECccccccccccccccccEEEEccccccccccccccHHHHcccccEEEEEccccccccccccccccccccEEEcccccccccccccccccccEEEcccccccccHHHccccccccEEEcccccccccccccccccccccccccccccEEEEEEECccccccccccccccccccccCEEEEECccccccccccccccccEEEECcccccccccccccccccccccccccccccccEEEEEccccccccccccccccccEEEEccccccCEEcccccccccccccEEEECcccccccccccccccccccccccccccccccccccccccccccccccccccEEEECcccccccccccccccccccccEEEEEcccccHHHHcccccccccccccHHHHccccccccccccccccccccccccccccccccccccccHHHHHHHHcccccccccccCEEECccccccccccccccccccccccccEEEEEcccccccccccccccccccccEEEEEcccccHHHcccccccccccccccccccccccccccccccccccccccccccccccCEEECcccccccccccccccHHHHccccccccccccEEEEECcccccccccHHHcccccccEEEEEcccccEEEccccccccccccccccccEEEEccccccccccccccccccccccccEEEEEccccccccccccccccccccEEEEEcccccccccccccccccccccEEEEEcccccEEECccccccccccccccccccccEEccccccccccccccccccccccccEEEECccccccccccccccccccEEEEEcccccccccccccccHHHHHccccccccccccccccccccc

MVEIIINVVFEVAKWLAAPIGRQVSYLSKSNYTSSFENLKKEVEKLRGERESMRQRVEEAERNRQEIEKNVEKWLERVNKIIDETVKITGDEETATKHCIKGLCPNLKTRYQLSKKAATLVKDIVELREEASKF*****************KGYEAFESRLSTLKSIRNALTDPNVSIIGVYGMGGIGKTTLAKEVARRAKEDNIFDAVAFSEVSQTPDIKNIQGEIAEKLG***************YERLKKEKKILVVLDNLWKSLDLETTIGIPYGDDHKGCKVLLTTRDRSVLLSMGSKENFPIGVLNEQEAWRLFKLTADDDVENRRLKSIATQVAKACGGLPIALTTIAKALRKKSVPEWENALQELRR**********KEAYSTIELSYKYLEGEKLKKMFLLCSLMPNPCYTLDLLKYCMGLGMFQRVHKLEDARTKMHAWVHELVDSCLLLVDDSGDNFSMHDVVRDVAISIACRDEHTFLVRNEDVWDWPDEDEKKECYAISVRDSSIHELPEGLKCPQLQFLTIANSKDSFLEIDVPEDFFTGMRKLRVVHFSGMRLASLPYSIGLLQNLQTLCLERSTVGDIAIIGKLKNLEVLSFLQSDIVMLPKEIGQLTKLRLLDLTDCFKLKVIATNVLSSLTRLEALYMHNCYVEWEVETRGSEKRSASLDEFLHLPRLTTLEIEVRNDDILPEGFFTKKLARFKISVGDESFSTPFYFVESWFSSRPNFMIGKHESLRTLKLKLSSKPIGSKELQGVNNVEYLCLDELPGVKTVLFELDTKGFSQLKHLHIQNNPDLLCIVDSRDRETYDAFPLLESLTLQNLIRLERTCMDRLKVESFNELKIIKVENCDELTNIFWLSNTKCLHKLERIAVIDCKKMEEVFAIGGEADVGNKNAIEKIEFAQLKSLSLGMLPKVTNFFREVKTPPASPNRRESEEDELDTSIQLLNEKVVLPNLEALELRDINIDKIWHYNELPAMFPGSQSLTRLILWDCNKLKYIFSATMIRSFEQLQRLEISNCMVLQEIISKDRAEADQRTTPCFVFPRLTTLILLGLPELKCFYPGMHTSEWPALKILNVIFPNLEDLALSGEDVEMILMGDFPHHLFGCLKQVAVATDESECFPLGLLERFLNMEDLYLRACSYKEIFSSNDEYLEKDVRNFALIKRLHLVELDDLKHLWKPNSKLEHILQYLEKLFVSYCQSLLILLPSASISFRNLTELQVTNCKKLINLVTSSVAKSLVGLLMLNIYGCRAMTEVVTGDENGAANPKEEIVFTKLKSISLVDLDSLTSFCSANYTFNFPSLQDLEVIGCPKMTIFTTVELCTPPRVNVWYGEGNLWRSDDGGVNTTIQHLHDEKLLEGSSSHIAYDWIRDI

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MVEIIINVVFEVAKWLAAPIGRQVSYLSxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxTVKITGDEETATKHCIKGLCPNLKTRYQLSKKAATLVKDIVELREEASKFPKVSYRTIPEDIWFHSIKGYEAFESRLSTLKSIRNALTDPNVSIIGVYGMGGIGKTTLAKEVARRAKEDNIFDAVAFSEVSQTPDIKNIQGEIAEKLGLTLREESESRRASSLYERLKKEKKILVVLDNLWKSLDLETTIGIPYGDDHKGCKVLLTTRDRSVLLSMGSKENFPIGVLNEQEAWRLFKLTADDDVENRRLKSIATQVAKACGGLPIALTTIAKALRKKSVPEWENALQELRRPSMESFQGVPKEAYSTIELSYKYLEGEKLKKMFLLCSLMPNPCYTLDLLKYCMGLGMFQRVHKLEDARTKMHAWVHELVDSCLLLVDDSGDNFSMHDVVRDVAISIACRDEHTFLVRNEDVWDWPDEDEKKECYAISVRDSSIHELPEGLKCPQLQFLTIANSKDSFLEIDVPEDFFTGMRKLRVVHFSGMRLASLPYSIGLLQNLQTLCLERSTVGDIAIIGKLKNLEVLSFLQSDIVMLPKEIGQLTKLRLLDLTDCFKLKVIATNVLSSLTRLEALYMHNCYVEWEVETRGSEKRSASLDEFLHLPRLTTLEIEVRNDDILPEGFFTKKLARFKISVGDESFSTPFYFVESWFSSRPNFMIGKHESLRTLKLKLSSKPIGSKELQGVNNVEYLCLDELPGVKTVLFELDTKGFSQLKHLHIQNNPDLLCIVDSRDRETYDAFPLLESLTLQNLIRLERTCMDRLKVESFNELKIIKVENCDELTNIFWLSNTKCLHKLERIAVIDCKKMEEVFAIGGEADVGNKNAIEKIEFAQLKSLSLGMLPKVTNFFREVKTPPASPNRRESEEDELDTSIQLLNEKVVLPNLEALELRDINIDKIWHYNELPAMFPGSQSLTRLILWDCNKLKYIFSATMIRSFEQLQRLEISNCMVLQEIISKDRAEADQRTTPCFVFPRLTTLILLGLPELKCFYPGMHTSEWPALKILNVIFPNLEDLALSGEDVEMILMGDFPHHLFGCLKQVAVATDESECFPLGLLERFLNMEDLYLRACSYKEIFSSNDEYLEKDVRNFALIKRLHLVELDDLKHLWKPNSKLEHILQYLEKLFVSYCQSLLILLPSASISFRNLTELQVTNCKKLINLVTSSVAKSLVGLLMLNIYGCRAMTEVVTGDENGAANPKEEIVFTKLKSISLVDLDSLTSFCSANYTFNFPSLQDLEVIGCPKMTIFTTVELCTPPRVNVWYGEGNLWRSDDGGVNTTIQHLHDEKLLEGSSSHIAYDWIRDI

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: 3SFZ, chain A
Confidence level:confident
Coverage over the Query: 157-493
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View the model in PyMOL

Template: 2A5Y, chain B
Confidence level:confident
Coverage over the Query: 58-485
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Template: 3ZYI, chain A
Confidence level:probable
Coverage over the Query: 547-659,673-705
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View the model in PyMOL

Template: 1ZIW, chain A
Confidence level:probable
Coverage over the Query: 511-1026
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Template: 3J0A, chain A
Confidence level:probable
Coverage over the Query: 517-927,959-1033,1046-1059
View the alignment between query and template
View the model in PyMOL

Template: 4ECN, chain A
Confidence level:probable
Coverage over the Query: 518-662,676-831,846-916
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Template: 2P1M, chain B
Confidence level:probable
Coverage over the Query: 783-1036,1051-1100,1123-1259
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View the model in PyMOL

Template: 3J0A, chain A
Confidence level:probable
Coverage over the Query: 517-927,959-1033,1046-1059
View the alignment between query and template
View the model in PyMOL

Template: 2Z63, chain A
Confidence level:probable
Coverage over the Query: 517-662,676-689
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Template: 3OGK, chain B
Confidence level:probable
Coverage over the Query: 791-1036,1048-1100,1123-1260
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Template: 3LVG, chain D
Confidence level:probable
Coverage over the Query: 35-95
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View the model in PyMOL