| >Q9P2B2 (144 residues) MGRLASRPLLLALLSLALCRGRVVRVPTATLVRVVGTELVIPCNVSDYDGPSEQNFDWSF SSLGSSFVELASTWEVGFPAQLYQERLQRGEILLRRTANDAVELHIKNVQPSDQGHYKCS TPSTDATVQGNYEDTVQVKVLADS |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | MGRLASRPLLLALLSLALCRGRVVRVPTATLVRVVGTELVIPCNVSDYDGPSEQNFDWSFSSLGSSFVELASTWEVGFPAQLYQERLQRGEILLRRTANDAVELHIKNVQPSDQGHYKCSTPSTDATVQGNYEDTVQVKVLADS |
| Prediction | CCCHHHHHHHHHHHHHCCSCCSSSSCCCCCSSSCCCCCSSSSSSSCCCCCCCCCSSSSSSCCCCCCSSSSSSSSCCCCCCHHHHHHSCCCSSSSSSCCCCSSSSSSCCCCCCCCSSSSSSSCCCCCCSSSCSSSSSSSSSSSCC |
| Confidence | 985156999999998523042799837996897189658999996299997410899998279996699998624887550243220451699974269859999924663324899998135885334100448999997289 |
| H:Helix; S:Strand; C:Coil | |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | MGRLASRPLLLALLSLALCRGRVVRVPTATLVRVVGTELVIPCNVSDYDGPSEQNFDWSFSSLGSSFVELASTWEVGFPAQLYQERLQRGEILLRRTANDAVELHIKNVQPSDQGHYKCSTPSTDATVQGNYEDTVQVKVLADS |
| Prediction | 753312231123112233144240433743123346560402030363643541403022454744212102234664646414633643412344166330202046044615140302043454433333414030303468 |
| Values range from 0 (buried residue) to 8 (highly exposed residue) | |
| Rank | PDB hit | ID1 | ID2 | Cov | Norm. Zscore | Downloadalignment | 20 40 60 80 100 120 140 | | | | | | | | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SS Seq | CCCHHHHHHHHHHHHHCCSCCSSSSCCCCCSSSCCCCCSSSSSSSCCCCCCCCCSSSSSSCCCCCCSSSSSSSSCCCCCCHHHHHHSCCCSSSSSSCCCCSSSSSSCCCCCCCCSSSSSSSCCCCCCSSSCSSSSSSSSSSSCC MGRLASRPLLLALLSLALCRGRVVRVPTATLVRVVGTELVIPCNVSDYDGPSEQNFDWSFSSLGSSFVELASTWEVGFPAQLYQERLQRGEILLRRTANDAVELHIKNVQPSDQGHYKCSTPSTDATVQGNYEDTVQVKVLADS | |||||||||||||||||||
| 1 | 3f8uD | 0.13 | 0.11 | 3.87 | 1.17 | DEthreader | --------VECEMSMVSSLLVLTVLTHTPAPRVRLGQDALLDLSFAYMPPPPPFGLEWRRQH-LGKGHLLAATPLNGQMPA-A--Q---EGAVAFAAWDGNGTFWLPRVQPFQEGTYLATIHLP----YLQGQVTLELAVYKPF | |||||||||||||
| 2 | 7k0xD1 | 0.15 | 0.12 | 4.00 | 1.05 | SPARKS-K | -------------------TGVALEQRPISITRNAKQSASLNCKILNPVSD---YVHWYRSQEGRAPERLLVYSR-SKSESVPDPGFSADKVRAYKGADDTCRLIVSDLQVSDSGVYHCASWDG----RVKVFGGTRLIVTESA | |||||||||||||
| 3 | 6oilA | 0.17 | 0.15 | 4.79 | 1.67 | FFAS-3D | ---------------------FKVATPYSLYVCPEGQNVTLTCRLLGPVHDVTFYKTWYRSSRGETFQDLHLHHGGHQAAQTSHDLAQRHGLESASDHHGNFSITMRNLTLLDSGLYCCLVVERHHHSEHRVHGAMELQVQTGK | |||||||||||||
| 4 | 3r8bB | 0.15 | 0.12 | 3.97 | 1.55 | CNFpred | ---------------------AAVTQSPRNKVAVTGEKVTLSCKQTNS---YFNNMYWYRQDTGHELRLIFMSHG----IRNVEKGDIPDGYKASRPSQENFSLILELATPSQTSVYFCASGGG---GTLYFGAGTRLSVLYGS | |||||||||||||
| 5 | 4f9lD | 0.13 | 0.11 | 3.87 | 1.17 | DEthreader | -----RPG-NIP-KL-G--QVQLQESGA-ELVKPG-ASVKLSCKASGYT-FTRYYLYWVKQRPGQGLEWIGEINNGGTKF-N-EKFK--SKATLTVDKSRTTYIQLSSLTSEDSAVYYCSREDDYDG-AMDYWGGTAVTVS-SA | |||||||||||||
| 6 | 1eajA | 0.16 | 0.13 | 4.40 | 1.01 | SPARKS-K | -----------------FARSLSITTPEEMIEKAKGETAYLPCKFTLPEDQGPLDIEWLISPADKVDQVIILYSGDKIYDDYYPDLKGRVHFTSNDLKSGDASINVTNLQLSDIGTYQCKVKKAP----GVANKKIHLVVLV-- | |||||||||||||
| 7 | 3nn8A | 0.18 | 0.15 | 4.75 | 0.53 | MapAlign | --------------------QVQLQQS-GPEDVKPGASVKISCKASGYLSTSGMGVNWVKQSPGKGLEWLAHIYWDDDKR-YN-PSL-KSRATLTVDTSSTVYLELRSLTSEDSSVYYCARRGGSHYYAMDYWGGTTVTVS--- | |||||||||||||
| 8 | 7k0xD | 0.14 | 0.12 | 4.01 | 0.36 | CEthreader | -------------------TGVALEQRPISITRNAKQSASLNCKILNP---VSDYVHWYRSQEGRAPERLLVYSRSKSES-VPDPGFSADKVRAYKGADDTCRLIVSDLQVSDSGVYHCASWDGR---VKVFGEGTRLIVTESA | |||||||||||||
| 9 | 2kh2B2 | 0.16 | 0.15 | 4.84 | 0.93 | MUSTER | ------------GGGSGGGGSEVQLVESGGGLVQPGGSLRLSCAASGFD-FSRYDMSWVRQAPGKRLEWVAYISSGG-GSTYFPDTVKGRFTISRDNAKNTLYLQMNSLRAEDTAVYYCARQNKKLTWFDYWGQGTLVTVSSHH | |||||||||||||
| 10 | 4f80A1 | 0.25 | 0.19 | 6.03 | 0.43 | HHsearch | --------------------QFSVLGPSGPILAMVGEDADLPCHLFPTMSAETMELKWVSSSLR-QVVNVYADGKEVRQSAPYRGRTS---ILRDGITAGKAALRIHNVTASDSGKYLCYFQDGD----FYEKALVELKVA--- | |||||||||||||
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Top 10 structural analogs in PDB (as identified by
TM-align)
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Top 5 enzyme homologs in PDB
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Template proteins with similar binding site:
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| References: | |
| 1. | Wei Zheng, Qiqige Wuyun, Yang Li, Quancheng Liu, Xiaogen Zhou, Yiheng Zhu, P. Lydia Freddolino, Yang Zhang. Integrating deep learning potentials with I-TASSER for single- and multi-domain protein structure prediction. Submitted. 2023. |