| >Q17R31 (143 residues) MRAAGVGLVDCHCHLSAPDFDRDLDDVLEKAKKANVVALVAVAEHSGEFEKIMQLSERYN GFVLPCLGVHPVQGLPPEDQRSVTLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTG EQKEEQRQVLIRQIQLAKRLNLP |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | MRAAGVGLVDCHCHLSAPDFDRDLDDVLEKAKKANVVALVAVAEHSGEFEKIMQLSERYNGFVLPCLGVHPVQGLPPEDQRSVTLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTGEQKEEQRQVLIRQIQLAKRLNLP |
| Prediction | CCCCCCCSSSSSSCCCCHHHHCCHHHHHHHHHHHCCCSSSSSCCCHHHHHHHHHHHHHCCCCSSSSSSCCCCCCCCCCHHHHHHHHHHHHHHHHHHHCCCCSSSSSSSSCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHCCC |
| Confidence | 98899856997518998366141999999999929998998318966899999999975996699983675658878723799999999999999962997899986315666222578763999999999999999996969 |
| H:Helix; S:Strand; C:Coil | |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | MRAAGVGLVDCHCHLSAPDFDRDLDDVLEKAKKANVVALVAVAEHSGEFEKIMQLSERYNGFVLPCLGVHPVQGLPPEDQRSVTLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTGEQKEEQRQVLIRQIQLAKRLNLP |
| Prediction | 66547141010203432650373154015203734562000001337306302500661372000002010230452565425304403412532544554000000000011354345763362245045300400463768 |
| 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 | CCCCCCCSSSSSSCCCCHHHHCCHHHHHHHHHHHCCCSSSSSCCCHHHHHHHHHHHHHCCCCSSSSSSCCCCCCCCCCHHHHHHHHHHHHHHHHHHHCCCCSSSSSSSSCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHCCC MRAAGVGLVDCHCHLSAPDFDRDLDDVLEKAKKANVVALVAVAEHSGEFEKIMQLSERYNGFVLPCLGVHPVQGLPPEDQRSVTLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTGEQKEEQRQVLIRQIQLAKRLNLP | |||||||||||||||||||
| 1 | 2y1hA | 0.98 | 0.91 | 25.48 | 1.33 | DEthreader | -M-G-VGLVDCHCHLSAPDFDRDLDDVLEKAKKANVVALVAVAEHSGEFEKIMQLSERYNGFVLPCLGVHPVQ--R-----SVTLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTGEQKEEQRQVLIRQIQLAKRLNLP | |||||||||||||
| 2 | 2y1hA | 0.99 | 0.92 | 25.85 | 1.35 | SPARKS-K | ---MGVGLVDCHCHLSAPDFDRDLDDVLEKAKKANVVALVAVAEHSGEFEKIMQLSERYNGFVLPCLGVHPVQ-------RSVTLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTGEQKEEQRQVLIRQIQLAKRLNLP | |||||||||||||
| 3 | 2y1hA | 0.98 | 0.90 | 25.27 | 0.84 | MapAlign | -----VGLVDCHCHLSAPDFDRDLDDVLEKAKKANVVALVAVAEHSGEFEKIMQLSERYNGFVLPCLGVHPVQRS-------VTLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTGEQKEEQRQVLIRQIQLAKRLNLP | |||||||||||||
| 4 | 2y1hA | 0.98 | 0.91 | 25.48 | 0.79 | CEthreader | ---MGVGLVDCHCHLSAPDFDRDLDDVLEKAKKANVVALVAVAEHSGEFEKIMQLSERYNGFVLPCLGVHPVQRS-------VTLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTGEQKEEQRQVLIRQIQLAKRLNLP | |||||||||||||
| 5 | 2y1hA | 0.99 | 0.92 | 25.85 | 1.38 | MUSTER | ---MGVGLVDCHCHLSAPDFDRDLDDVLEKAKKANVVALVAVAEHSGEFEKIMQLSERYNGFVLPCLGVHPVQ-------RSVTLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTGEQKEEQRQVLIRQIQLAKRLNLP | |||||||||||||
| 6 | 2y1hA | 0.97 | 0.90 | 25.29 | 1.74 | HHsearch | ---MGVGLVDCHCHLSAPDFDRDLDDVLEKAKKANVVALVAVAEHSGEFEKIMQLSERYNGFVLPCLGVHPVQRSV-------TLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTGEQKEEQRQVLIRQIQLAKRLNLP | |||||||||||||
| 7 | 2y1hA | 0.98 | 0.91 | 25.48 | 1.80 | FFAS-3D | ---MGVGLVDCHCHLSAPDFDRDLDDVLEKAKKANVVALVAVAEHSGEFEKIMQLSERYNGFVLPCLGVHPVQRS-------VTLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTGEQKEEQRQVLIRQIQLAKRLNLP | |||||||||||||
| 8 | 2y1hA | 0.95 | 0.87 | 24.52 | 0.55 | EigenThreader | ---MGVGLVDCHCHLSAPDFDRDLDDVLEKAKKA--NVVVAVAEHSGEFEKIMQLSERYNGFVLPCLGVHPVQRS-------VTLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTGEQKEEQRQVLIRQIQLAKRLNLP | |||||||||||||
| 9 | 2y1hA | 1.00 | 0.92 | 25.85 | 1.56 | CNFpred | ----GVGLVDCHCHLSAPDFDRDLDDVLEKAKKANVVALVAVAEHSGEFEKIMQLSERYNGFVLPCLGVHPVQ-------RSVTLKDLDVALPIIENYKDRLLAIGEVGLDFSPRFAGTGEQKEEQRQVLIRQIQLAKRLNLP | |||||||||||||
| 10 | 1zzmA | 0.30 | 0.27 | 8.27 | 1.33 | DEthreader | -MICR--FIDTHCHFDFPPFSGDEEASLQRAAQAGVGKIIVPATEAENFARVLALAENYQ-PLYAALGLHPGML------EKHSDVSLEQLQQALERRPAKVVAVGEIGLDLFG---DDP-QFERQQWLLDEQLKLAKRYDLP | |||||||||||||
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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. |