| >Q9H6E5 (143 residues) MAAVDSDVESLPRGGFRCCLCHVTTANRPSLDAHLGGRKHRHLVELRAARKAQGLRSVFV SGFPRDVDSAQLSEYFLAFGPVASVVMDKDKGVFAIVEMGDVGAREAVLSQSQHSLGGHR LRVRPREQKEFQSPASKSPKGAA |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | MAAVDSDVESLPRGGFRCCLCHVTTANRPSLDAHLGGRKHRHLVELRAARKAQGLRSVFVSGFPRDVDSAQLSEYFLAFGPVASVVMDKDKGVFAIVEMGDVGAREAVLSQSQHSLGGHRLRVRPREQKEFQSPASKSPKGAA |
| Prediction | CCCSSSSSSSCCCCCCSSSSSSSSSCCCHHHHHHHHCCCCCCCCCCCCCCCCCCCCSSSSCCCCCCCCHHHHHHHHHCCCCSSSSSSSCCCCCSSSSSSCCHHHHHHHHHCCCCSSCCSSSSSSSCCCCCCCCCCCCCCCCCC |
| Confidence | 96343146656999816788999967814489997159864333322354334774799869899999999999974127379999967899089999799999999996399488888999985787544577888888889 |
| H:Helix; S:Strand; C:Coil | |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | MAAVDSDVESLPRGGFRCCLCHVTTANRPSLDAHLGGRKHRHLVELRAARKAQGLRSVFVSGFPRDVDSAQLSEYFLAFGPVASVVMDKDKGVFAIVEMGDVGAREAVLSQSQHSLGGHRLRVRPREQKEFQSPASKSPKGAA |
| Prediction | 65324562564564432100020204446336511664624544644554665542100004045714573046247631503402023455210101053561043017467250543405055356475566676555258 |
| 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 | CCCSSSSSSSCCCCCCSSSSSSSSSCCCHHHHHHHHCCCCCCCCCCCCCCCCCCCCSSSSCCCCCCCCHHHHHHHHHCCCCSSSSSSSCCCCCSSSSSSCCHHHHHHHHHCCCCSSCCSSSSSSSCCCCCCCCCCCCCCCCCC MAAVDSDVESLPRGGFRCCLCHVTTANRPSLDAHLGGRKHRHLVELRAARKAQGLRSVFVSGFPRDVDSAQLSEYFLAFGPVASVVMDKDKGVFAIVEMGDVGAREAVLSQSQHSLGGHRLRVRPREQKEFQSPASKSPKGAA | |||||||||||||||||||
| 1 | 5lsbA | 0.11 | 0.10 | 3.83 | 1.63 | SPARKS-K | NPVLRIKYPKDKVLQAYQGYAFIEFYNQGDAQYAIKIMNNTVRLYDRLIKRQVPIAKLFIKNLADSIDSDQLVKIFNKFGKLIEIFYLSK-LKCAYVYFEDFEKADLAIKSLNQLVANNRITVDYAFKNGKGNAKYGDDVDRL | |||||||||||||
| 2 | 4bs2A | 0.19 | 0.17 | 5.66 | 1.40 | MUSTER | FGEVLVQVKKDLKTGHSKGFGFVRFTEYETQVKVMSGRWCDCKLSKQSQDEPLRSRKVFVGRCTEDMTEDELREFFSQYGDVMDVFIPKPFRAFAFVTFADDQIAQSLCGE-DLIIKGISVHISNAEPKHNSNRQ-------- | |||||||||||||
| 3 | 1u1lA | 0.24 | 0.22 | 6.99 | 1.67 | FFAS-3D | -TLTDCVVMRDPNTKRSRGFGFVTYATVEEVDAAMNARPHKVDEDSQRPGAHLTVKKIFVGGIKEDTEEHHLRDYFEQYGKIEVIEISGKKRGFAFVTFDDHDSVDKIVIQKYHTVNGHNCEVRKALSKQEMASAS------- | |||||||||||||
| 4 | 4p6qA | 0.18 | 0.15 | 5.03 | 1.63 | CNFpred | ----------------VPQYAFLQYCDIASVCKAIKKMDGEYLGNNRL-GKSMPTNCVWLDGLSSNVSDQYLTRHFCRYGPVVKVVFDR-LKGMALVLYNEIEYAQAAVKETGRKIGGNKIKVDFANRESQLAFYHCMEKSGQ | |||||||||||||
| 5 | 5x8rv | 0.15 | 0.12 | 3.99 | 1.00 | DEthreader | NIPRNL-------------NNDELRIVAEFGFTPLEGMDATTQAEDS-QFVE-SPYKVYIGNLAKTVTNELLKDFFSEKGKVLGAKVQRTSNGFGFVSFSSEEEVEAAIQANNSVLEGQKIRVNKA----------------- | |||||||||||||
| 6 | 3h2uB | 0.15 | 0.15 | 4.97 | 1.60 | SPARKS-K | HDLLSDYELKYCFVDKYKGTAFVTLLNGEQAEAAINAFHQSRLRERESVQLQPTDALLCVANLPPSLTQQQFEELVRPFGSLEFLVYSERTGGYGFAEYMKKDSAARAKSDLGKPLGPRTLYVHWTDAGQLTPALLHSRCLCV | |||||||||||||
| 7 | 2mjnA | 0.12 | 0.10 | 3.49 | 0.50 | MapAlign | ---SDARVVKDMATGKSKGYGFVSFFNKWDAENAISTYESNTKQLSYDEVVNQSNCTVYCGGVTSGLTEQLMRQTFSPFGQIMEIRVF---PGYSFVRFNSHESAAHAIVVNGTTIEGHVVKCYWGK---------------- | |||||||||||||
| 8 | 1cvjA | 0.14 | 0.13 | 4.32 | 0.28 | CEthreader | GPILSIRVCRDMITRRSLGYAYVNFQQPADAERALDTMNFDVIKGKPPSLRKSGVGNIFIKNLDKSIDNKALYDTFSAFGNILSCKVVCDSKGYGFVHFETQEAAERAIEMNGMLLNDRKVFVGRFKSRKER----------- | |||||||||||||
| 9 | 1u1lA | 0.24 | 0.23 | 7.18 | 1.36 | MUSTER | WGTLDCVVMRDPNTKRSRGFGFVTYATVEEVDAAMNARPHKVDGDSQRPGAHLTVKKIFVGGIKEDTEEHHLRDYFEQYGKIEVIEIMTDRGGFAFVTFDDHDSVDKIVIQKYHTVNGHNCEVRKALSKQEMASAS------- | |||||||||||||
| 10 | 4pkdB | 0.15 | 0.15 | 5.15 | 0.89 | HHsearch | LKKIFSQIILVSRSLKMRGQAFVIFKEVSSATNALRSMQGFPMRIQYAKAQGDAFKTLFVARVNYDTTESKLRREFEVYGPIKRIVYSKRSGKYAFIEYEHERDMHSAYKHAGKKIDGRRVLVDVERGRTVKGWRPRLGGGLG | |||||||||||||
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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. |