Citrus Sinensis ID: 000962

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-------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------121
MAELVVSLVVQPIVEKAIEAAVSLIKEEVGSVLGVKSEVEKLLSKLTSIKAVLEDAEERQLKVPQLKDWLGKLRNAAYDAEDILETFATQVAMHKRKQKLRRVRTPISGNKISYQYDAAQRIKKILDRLDVITEEKEKFHLSSGVNNNSGNSRNHNQDQELPLTGSFIDTANVFGRDDDKERILHMLLSDEFDEEDDAFVIPIIGMPGLGKTTLAQLLFNEERVREHFESRMWVCVTVDYDLPRILKGMIEFHSKMEQSTSSISLLETRLLEFLTGQRFLLVLDDVWNEDYRKWEPLQQLLKQGHKGSRVLVTSRTARVSQIMGIRSPYLLEYLPEDQCWSIFKKIAFNQGNFSSRMQQQNLEAIGREIVGKCKGLPLAVKAIAGFLRKYDDVNKWRKILSSDIWELEEGSSNGPHILPPLKLSYDHLPPFLKHCFSLCSIFPKSYAFDKAEMVKFWMAEALIQSRGGGRQEREEEIGIEYFDELLGRSFFQSSNIDDKVKYQMHDLFHDLAQFVSSPYGHVCQVKDDRSSCSSCCSPETRHVSLLCKHVEKPALSVVENSKKLRTFLVPSFGEHLKDFGRALDKIFHQLKYLRLLDLSSSTLTVLPDSVEELKLLRYLDLSRTEIKVLPNSICNLYNLQTLKLIGCIWIMELPKDLANLVKLRNLELEEMFWFKCSTLPAGIGKLTNLHNLHVFRVGSKSGYRIEELKELPYLTGKLHISKLENAVNGGEAKLSEKESLHKLVFEWSNNRDSSPQSQDVSGDEERLLEDLQPHPNLEELQIFNYFGNSLPQWMRDGRLQNLVSLTLKGCTNCRILSLGQLSSLRVLNIKGMLELEKWPNDEDCRFLGRLKISNCPRLNELPECMPNLTVMKIKKCCSLKALPVTPFLQFLILVDNLELENWNERCLRVIPTSDNGQGQHLLLHSFQTLLEMKAINCPKLRGLPQIFAPQKLEISGCDLLSTLPNSEFSQRLQLLALEGCPDGTLVRAIPETSSLNFLILSKISNLDSFPRWPNLPGLKALYIRDCKDLVSLSGEGALQSLTSLNLLSIRGCPKLETLPDEGLPTSLKCLIIASCSGLKSLGPRGTLKSLNSLKDFYIEDCPLLQSFPEDGLPENLQHLVIQNCPLLTQQCRDGEAEGPEWPKIKDIPDLEIDFICNRSPIMPEKKKASWYRPLVGRGGLKGRKQMEQGEPSGLAGCSKYSILLLHFA
cHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHccHHHHHHHHHHHHHHHHHHHHHHHHccccHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHccccccccccccccccHHHHHHHHHHHHHHHHHHHHHHHHcccccccccccccccccccccccccccccccccccccccHHHHHHHHHHcccccccccccEEEEEECcccccHHHHHHHHHccHHHHcccccEEEEEEcccccHHHHHHHHHHHccccccccccHHHHHHHHHHHHcccEEEEEEccccccccccHHHHHHHHHccccccEEEEccccHHHHHHHcccccCCcccccHHHHHHHHHHHHcccccccccccccHHHHHHHHHHHHccccHHHHHHHHHHHcccccHHHHHHHHHcccccccccccccccccccHHcccccccccccccccccccccccccccHHHHHHHHHHccccccccccccccHHHHHHHHHHHHHHccccCECccccccEEEEccHHHHHHHHHHcccccEEECccccccccccccccEEEEEEEEcccccccccccccccccEEEEccccccccccHHHHHHHHHcccccccEEEccccccccccccccccccccccccccccccccccHHHccccccEEccccccccccccHHccccccccEEEEccccccccccccccccccccccccccEECccccccccHHHccccccccEEEEcccccccccccccccccccccEEEEEEccccccccccccccccHHHHHcccccccccccEEEEEcccccccccccccccccEEEEEECcccccccccccccccccEEEEcccccEEEcccccccccccEEEECccccccccccccccccEEEECcccccccccccccccEEEEEcccccccccHHcccccccccccccccccccccccccEEEEccccccccccccccccEEEEcccccccccccccccccccEEEECccccccccccccccccccEEEEEccccccccccccccccccEEEEEcccccccccccccccccccccEEEECccccccccccccccccccEEEEEEccccccccccccccccccccEEEECccccccccccccccccccEEEEcccHHHHHHHHccccccccccccccccEEEEccCCcccccccccccccccccccccccccccccccccccccccccHHHHHHHHHcc
MAELVVSLVVQPIVEKAIEAAVSLIKEEVGSVLGVKSEVEKLLSKLTSIKAVLEDAEERQLKVPQLKDWLGKLRNAAYDAEDILETFATQVAMHK******RVRTPISGNKISYQYDAAQRIKKILDRLDVITEEKEKFHLS************************FIDTANVFGRDDDKERILHMLLSDEFDEEDDAFVIPIIGMPGLGKTTLAQLLFNEERVREHFESRMWVCVTVDYDLPRILKGMIEFHSKME**TSSISLLETRLLEFLTGQRFLLVLDDVWNEDYRKWEPLQQLLKQGHKGSRVLVTSRTARVSQIMGIRSPYLLEYLPEDQCWSIFKKIAFNQGNFSSRMQQQNLEAIGREIVGKCKGLPLAVKAIAGFLRKYDDVNKWRKILSSDIWELEEGSSNGPHILPPLKLSYDHLPPFLKHCFSLCSIFPKSYAFDKAEMVKFWMAEALIQSRG*****REEEIGIEYFDELLGRSFFQSSNIDDKVKYQMHDLFHDLAQFVSSPYGHVCQVKDDR*****CCSPETRHVSLLCKHVEKPALSVVENSKKLRTFLVPSFGEHLKDFGRALDKIFHQLKYLRLLDLSSSTLTVLPDSVEELKLLRYLDLSRTEIKVLPNSICNLYNLQTLKLIGCIWIMELPKDLANLVKLRNLELEEMFWFKCSTLPAGIGKLTNLHNLHVFRVGSKSGYRIEELKELPYLTGKLHISKLENAVNGGEAKLSEKESLHKLVFEWSNNRDS*P******GDEERLLEDLQPHPNLEELQIFNYFGNSLPQWMRDGRLQNLVSLTLKGCTNCRILSLGQLSSLRVLNIKGMLELEKWPNDEDCRFLGRLKISNCPRLNELPECMPNLTVMKIKKCCSLKALPVTPFLQFLILVDNLELENWNERCLRVIPTSDNGQGQHLLLHSFQTLLEMKAINCPKLRGLPQIFAPQKLEISGCDLLSTLPNSEFSQRLQLLALEGCPDGTLVRAIPETSSLNFLILSKISNLDSFPRWPNLPGLKALYIRDCKDLVSLSGEGALQSLTSLNLLSIRGCPKLETLPDEGLPTSLKCLIIASCSGLKSLGPRGTLKSLNSLKDFYIEDCPLLQSFPEDGLPENLQHLVIQNCPLLTQQCRDGEAEGPEWPKIKDIPDLEIDFICNRSPIMPEKKKASWYRPLVG*****************LAGCSKYSILLLHFA
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MAELVVSLVVQPIVEKAIEAAVSLIKEEVGSVLGVKSExxxxxxxxxxxxxxxxxxxxxQLKVPQLKDWLGKLRNAAYDAEDILETFATQVAMHKRKQKLRRVRTPISGNKISYQYDAAQRIKKILDRLDVITEEKEKFHLSSGVNNNSGNSRNHNQDQELPLTGSFIDTANVFGRDDDKERILHMLLSDEFDEEDDAFVIPIIGMPGLGKTTLAQLLFNEERVREHFESRMWVCVTVDYDLPRILKGMIEFHSKMEQSTSSISLLETRLLEFLTGQRFLLVLDDVWNEDYRKWEPLQQLLKQGHKGSRVLVTSRTARVSQIMGIRSPYLLEYLPEDQCWSIFKKIAFNQGNFSSRMQQQNLEAIGREIVGKCKGLPLAVKAIAGFLRKYDDVNKWRKILSSDIWELEEGSSNGPHILPPLKLSYDHLPPFLKHCFSLCSIFPKSYAFDKAEMVKFWMAEALIQSRGGGRQEREEEIGIEYFDELLGRSFFQSSNIDDKVKYQMHDLFHDLAQFVSSPYGHVCQVKDDRSSCSSCCSPETRHVSLLCKHVEKPALSVVENSKKLRTFLVPSFGEHLKDFGRALDKIFHQLKYLRLLDLSSSTLTVLPDSVEELKLLRYLDLSRTEIKVLPNSICNLYNLQTLKLIGCIWIMELPKDLANLVKLRNLELEEMFWFKCSTLPAGIGKLTNLHNLHVFRVGSKSGYRIEELKELPYLTGKLHISKLENAVNGGEAKLSEKESLHKLVFEWSNNRDSSPQSQDVSGDEERLLEDLQPHPNLEELQIFNYFGNSLPQWMRDGRLQNLVSLTLKGCTNCRILSLGQLSSLRVLNIKGMLELEKWPNDEDCRFLGRLKISNCPRLNELPECMPNLTVMKIKKCCSLKALPVTPFLQFLILVDNLELENWNERCLRVIPTSDNGQGQHLLLHSFQTLLEMKAINCPKLRGLPQIFAPQKLEISGCDLLSTLPNSEFSQRLQLLALEGCPDGTLVRAIPETSSLNFLILSKISNLDSFPRWPNLPGLKALYIRDCKDLVSLSGEGALQSLTSLNLLSIRGCPKLETLPDEGLPTSLKCLIIASCSGLKSLGPRGTLKSLNSLKDFYIEDCPLLQSFPEDGLPENLQHLVIQNCPLLTQQCRDGEAEGPEWPKIKDIPDLEIDFICNRSPIMPEKKKASWYRPLVGRGGLKGRKQMEQGEPSGLAGCSKYSILLLHFA

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: 3RGZ, chain A
Confidence level:very confident
Coverage over the Query: 538-755,770-901,919-1126,1137-1158,1176-1200
View the alignment between query and template
View the model in PyMOL
Template: 3SFZ, chain A
Confidence level:very confident
Coverage over the Query: 169-460,475-519
View the alignment between query and template
View the model in PyMOL
Template: 1ZIW, chain A
Confidence level:very confident
Coverage over the Query: 542-882,919-1155
View the alignment between query and template
View the model in PyMOL
Template: 2A5Y, chain B
Confidence level:very confident
Coverage over the Query: 174-519
View the alignment between query and template
View the model in PyMOL
Template: 3QFL, chain A
Confidence level:confident
Coverage over the Query: 13-93
View the alignment between query and template
View the model in PyMOL
Template: 4G8A, chain A
Confidence level:confident
Coverage over the Query: 562-751,764-883,923-1126,1159-1202
View the alignment between query and template
View the model in PyMOL
Template: 3FXI, chain A
Confidence level:probable
Coverage over the Query: 587-865,882-1123
View the alignment between query and template
View the model in PyMOL