| >P69905 (142 residues) MVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHG KKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTP AVHASLDKFLASVSTVLTSKYR |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | MVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYR |
| Prediction | CCCCHHHHHHHHHHHHHHHCCHHHHHHHHHHHHHHHCCHHHHHCCCCCCCCCCHHHHHHHHHHHHHHHHHHHCCCCHHHHHHHHHHHHHHHHCCCHHHHHHHHHHHHHHHHHHCCCCCCHHHHHHHHHHHHHHHHHHHHHCC |
| Confidence | 9999999999999999986358999999999999969127776224276789978999999999999999960253899999999972532099979986899999999998355579999999999999999999998729 |
| H:Helix; S:Strand; C:Coil | |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | MVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYR |
| Prediction | 7613662252046026304641551023003300442263463054164356354144103300300240053245155104500631064260436305302300010023235641233013004301210031026528 |
| 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 | CCCCHHHHHHHHHHHHHHHCCHHHHHHHHHHHHHHHCCHHHHHCCCCCCCCCCHHHHHHHHHHHHHHHHHHHCCCCHHHHHHHHHHHHHHHHCCCHHHHHHHHHHHHHHHHHHCCCCCCHHHHHHHHHHHHHHHHHHHHHCC MVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYR | |||||||||||||||||||
| 1 | 1jebA | 0.60 | 0.59 | 16.96 | 1.50 | DEthreader | -SLTKTERTIIVSMWAKISTQADTIGTETLERLFLSHPQTKTYFPHFDLHPGSAQLRAHGSKVVAAVGDAVKSIDDIGGALSKLSELHAYILRVDPVNFKLLSHCLLVTLAARFPADFTAEAHAAWDKFLSVVSSVLTEKYR | |||||||||||||
| 2 | 1c7dA2 | 0.99 | 0.99 | 27.81 | 1.71 | SPARKS-K | GVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYR | |||||||||||||
| 3 | 5jggA | 0.59 | 0.58 | 16.77 | 0.89 | MapAlign | -TLTSADKSHVKSIWSKASGKAEELGAEALGRMLEVFPNTKTYFSHYDLSVTSGQVHTHGKKILDAITTAVNHIDDITGVLTALSTLHAKTLRVDPANFKILSHTILVVLALYFPADFTPEVHLACDKFLASVSHTLATKY- | |||||||||||||
| 4 | 5jggA | 0.60 | 0.59 | 16.96 | 0.59 | CEthreader | -TLTSADKSHVKSIWSKASGKAEELGAEALGRMLEVFPNTKTYFSHYDLSVTSGQVHTHGKKILDAITTAVNHIDDITGVLTALSTLHAKTLRVDPANFKILSHTILVVLALYFPADFTPEVHLACDKFLASVSHTLATKYR | |||||||||||||
| 5 | 1c7dA2 | 0.99 | 0.99 | 27.81 | 1.69 | MUSTER | GVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYR | |||||||||||||
| 6 | 1c7dA | 0.99 | 0.99 | 27.81 | 1.34 | HHsearch | GVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYR | |||||||||||||
| 7 | 1c7dA2 | 1.00 | 0.99 | 27.80 | 2.12 | FFAS-3D | -VLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYR | |||||||||||||
| 8 | 1c7dA2 | 0.99 | 0.99 | 27.81 | 1.00 | EigenThreader | GVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYR | |||||||||||||
| 9 | 1y09A | 0.99 | 0.98 | 27.42 | 1.17 | CNFpred | -MLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVAFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYR | |||||||||||||
| 10 | 1lhtA | 0.26 | 0.26 | 8.03 | 1.50 | DEthreader | -GLSDDEWNHVLGIWAKVEPDLSAHGQEVIIRLFQLHPETQERFAKFNLLKSSEEVKKHGTTVLTALGRILKQKNNHEQELKPLAESHATKHKIPVKYLEFICEIIVKVIAEKHPSDFGADSQAAMKKALELFRNDMASKYQ | |||||||||||||
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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. |