>Q9BVJ7 (150 residues) MGVQPPNFSWVLPGRLAGLALPRLPAHYQFLLDLGVRHLVSLTERGPPHSDSCPGLTLHR LRIPDFCPPAPDQIDRFVQIVDEANARGEAVGVHCALGFGRTGTMLACYLVKERGLAAGD AIAEIRRLRPGSIETYEQEKAVFQFYQRTK |
Sequence |
20 40 60 80 100 120 140 | | | | | | | MGVQPPNFSWVLPGRLAGLALPRLPAHYQFLLDLGVRHLVSLTERGPPHSDSCPGLTLHRLRIPDFCPPAPDQIDRFVQIVDEANARGEAVGVHCALGFGRTGTMLACYLVKERGLAAGDAIAEIRRLRPGSIETYEQEKAVFQFYQRTK |
Prediction | CCCCCCCCSSSSCCSSSSSCCCCCHHHHHHHHHCCCCSSSSCCCCCCCCHHHCCCCSSSSSSCCCCCCCCHHHHHHHHHHHHHHHHHCCSSSSSCCCCCCCHHHHHHHHHHHHHCCCHHHHHHHHHHHCCCCCCCHHHHHHHHHHHHHHC |
Confidence | 998999971785995897389998689999999099899984899987135228977999662799999999999999999999981995999868899836999999999980999999999999979999999999999999999839 |
H:Helix; S:Strand; C:Coil | |
Sequence |
20 40 60 80 100 120 140 | | | | | | | MGVQPPNFSWVLPGRLAGLALPRLPAHYQFLLDLGVRHLVSLTERGPPHSDSCPGLTLHRLRIPDFCPPAPDQIDRFVQIVDEANARGEAVGVHCALGFGRTGTMLACYLVKERGLAAGDAIAEIRRLRPGSIETYEQEKAVFQFYQRTK |
Prediction | 873634411202222000011232552152037354511021146243563434404113010434301226204410410340276542000003234411000000000343704053015203732452253650150035117548 |
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 | | | | | | | | |||||||||||||
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SS Seq | CCCCCCCCSSSSCCSSSSSCCCCCHHHHHHHHHCCCCSSSSCCCCCCCCHHHCCCCSSSSSSCCCCCCCCHHHHHHHHHHHHHHHHHCCSSSSSCCCCCCCHHHHHHHHHHHHHCCCHHHHHHHHHHHCCCCCCCHHHHHHHHHHHHHHC MGVQPPNFSWVLPGRLAGLALPRLPAHYQFLLDLGVRHLVSLTERGPPHSDSCPGLTLHRLRIPDFCPPAPDQIDRFVQIVDEANARGEAVGVHCALGFGRTGTMLACYLVKERGLAAGDAIAEIRRLRPGSIETYEQEKAVFQFYQRTK | |||||||||||||||||||
1 | 2imgA | 1.00 | 0.99 | 27.63 | 1.50 | DEthreader | -GVQPPNFSWVLPGRLAGLALPRLPAHYQFLLDLGVRHLVSLTERGPPHSDSCPGLTLHRLRIPDFCPPAPDQIDRFVQIVDEANARGEAVGVHCALGFGRTGT-LACYLVKERGLAAGDAIAEIRRLRPGSIETYEQEKAVFQFYQRTK | |||||||||||||
2 | 2imgA | 1.00 | 0.99 | 27.63 | 2.45 | SPARKS-K | -GVQPPNFSWVLPGRLAGLALPRLPAHYQFLLDLGVRHLVSLTERGPPHSDSCPGLTLHRLRIPDFCPPAPDQIDRFVQIVDEANARGEAVGVHCALGFGRTGT-LACYLVKERGLAAGDAIAEIRRLRPGSIETYEQEKAVFQFYQRTK | |||||||||||||
3 | 2imgA | 1.00 | 0.97 | 27.25 | 0.82 | MapAlign | --VQPPNFSWVLPGRLAGLALPRLPAHYQFLLDLGVRHLVSLTERGPPHSDSCPGLTLHRLRIPDFCPPAPDQIDRFVQIVDEANARGEAVGVHCALGFGRTGT-LACYLVKERGLAAGDAIAEIRRLRPGSIETYEQEKAVFQFYQRT- | |||||||||||||
4 | 2imgA | 1.00 | 0.99 | 27.63 | 0.64 | CEthreader | -GVQPPNFSWVLPGRLAGLALPRLPAHYQFLLDLGVRHLVSLTERGPPHSDSCPGLTLHRLRIPDFCPPAPDQIDRFVQIVDEANARGEAVGVHCALGFGRTGT-LACYLVKERGLAAGDAIAEIRRLRPGSIETYEQEKAVFQFYQRTK | |||||||||||||
5 | 2imgA | 0.97 | 0.96 | 26.91 | 2.15 | MUSTER | -GVQPPNFSWVLPGRLAGLALPRLPAHYQFLLDLGVRHLVSLTERGPPHSDSCPGLTLHRLRIPDFCPPAPDQIDRFVQIVDEANARGEAVGVHCALGFG-RTGTLACYLVKERGLAAGDAIAEIRRLRPGSIETYEQEKAVFQFYQRTK | |||||||||||||
6 | 2imgA | 1.00 | 0.99 | 27.63 | 1.66 | HHsearch | -GVQPPNFSWVLPGRLAGLALPRLPAHYQFLLDLGVRHLVSLTERGPPHSDSCPGLTLHRLRIPDFCPPAPDQIDRFVQIVDEANARGEAVGVHCALGFGRTGT-LACYLVKERGLAAGDAIAEIRRLRPGSIETYEQEKAVFQFYQRTK | |||||||||||||
7 | 2imgA | 0.99 | 0.97 | 27.27 | 2.46 | FFAS-3D | -GVQPPNFSWVLPGRLAGLALPRLPAHYQFLLDLGVRHLVSLTERGPPHSDSCPGLTLHRLRIPDFCPPAPDQIDRFVQIVDEANARGEAVGVHCALGFGRTGTLA-CYLVKERGLAAGDAIAEIRRLRPGSIETYEQEKAVFQFYQRTK | |||||||||||||
8 | 1fq1A | 0.20 | 0.20 | 6.40 | 0.97 | EigenThreader | DEQTPIHISWLNCSQFGLCALPGCKKDTEELKSCGIQDIFVFCTPNLLDLYQQCGIITHHHPIADGGTPDIASCCEIMEELTTCLKNYRKTLIHSYGGLGRSCLVAACLLLYLSDISPEQAIDSLRDLRGGAIQTIKQYNYLHEFRDKLA | |||||||||||||
9 | 4ercA | 1.00 | 1.00 | 28.00 | 1.64 | CNFpred | MGVQPPNFSWVLPGRLAGLALPRLPAHYQFLLDLGVRHLVSLTERGPPHSDSCPGLTLHRLRIPDFCPPAPDQIDRFVQIVDEANARGEAVGVHCALGFGRTGTMLACYLVKERGLAAGDAIAEIRRLRPGSIETYEQEKAVFQFYQRTK | |||||||||||||
10 | 3aweA1 | 0.19 | 0.19 | 6.02 | 1.50 | DEthreader | DGFDL-DLTYVTD-HVIAMSFPSIGEVSRFFKTKHKFRIYNLCSERGYDETKFD-NHVYRVMIDDHNVPTLVDLLKFIDDAKVWMTSDHVIAIHCKGGKGRTGTLVSSWLLEDGFDTAKEALEYFGSRRTQGVETASQIRYVGYFEKIKK | |||||||||||||
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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, Chengxin Zhang, Yang Li, Robin Pearce, Eric W. Bell, Yang Zhang. Folding non-homology proteins by coupling deep-learning contact maps with I-TASSER assembly simulations. In preparation, 2020. |