>Q96PQ7 (150 residues) STPRSTVGVAVLSGKLYAVGGRDGSSCLKSVECFDPHTNKWTLCAQMSKRRGGVGVTTWN GLLYAIGGHDAPASNLTSRLSDCVERYDPKTDMWTAVASMSISRDAVGVCLLGDKLYAVG GYDGQAYLNTVEAYDPQTNEWTQVAPLCLG |
Sequence |
20 40 60 80 100 120 140 | | | | | | | STPRSTVGVAVLSGKLYAVGGRDGSSCLKSVECFDPHTNKWTLCAQMSKRRGGVGVTTWNGLLYAIGGHDAPASNLTSRLSDCVERYDPKTDMWTAVASMSISRDAVGVCLLGDKLYAVGGYDGQAYLNTVEAYDPQTNEWTQVAPLCLG |
Prediction | CCCCCCSSSSSSCCSSSSSSCCCCCSSSCSSSSSSCCCCSSSSCCCCCCCCCCSSSSSSCCSSSSSSCCCCCCCCCCCCSCCSSSSSCCCCCSSSSCCCCCCCCCCSSSSSSCCSSSSSSCCCCCSSCCSSSSSSCCCCSSSSCCCCCCC |
Confidence | 987664069999999999936689914027999918999797758987311343899999999999074799998656332659999399997998599987653538999999999992788992344699996999979973898999 |
H:Helix; S:Strand; C:Coil | |
Sequence |
20 40 60 80 100 120 140 | | | | | | | STPRSTVGVAVLSGKLYAVGGRDGSSCLKSVECFDPHTNKWTLCAQMSKRRGGVGVTTWNGLLYAIGGHDAPASNLTSRLSDCVERYDPKTDMWTAVASMSISRDAVGVCLLGDKLYAVGGYDGQAYLNTVEAYDPQTNEWTQVAPLCLG |
Prediction | 734322000001253240004336742121011301654575634544430210000014431210002225445444422420110117544345144144213100000144330000013454212202142275445452475448 |
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 | CCCCCCSSSSSSCCSSSSSSCCCCCSSSCSSSSSSCCCCSSSSCCCCCCCCCCSSSSSSCCSSSSSSCCCCCCCCCCCCSCCSSSSSCCCCCSSSSCCCCCCCCCCSSSSSSCCSSSSSSCCCCCSSCCSSSSSSCCCCSSSSCCCCCCC STPRSTVGVAVLSGKLYAVGGRDGSSCLKSVECFDPHTNKWTLCAQMSKRRGGVGVTTWNGLLYAIGGHDAPASNLTSRLSDCVERYDPKTDMWTAVASMSISRDAVGVCLLGDKLYAVGGYDGQAYLNTVEAYDPQTNEWTQVAPLCLG | |||||||||||||||||||
1 | 3ii7A | 0.34 | 0.34 | 10.17 | 1.50 | DEthreader | PTPRDSLAACAAEGKIYTSGGSEVGNALYLFECYDTRTESWHTKPSMLTQRCSHGMVEANGLIYVCGGSLGN-NVSG-RVLNSCEVYDPATETWTELCPMIEARKNHGLVFVKDKIFAVGGQNGLGGLDNVEYYDIKLNEWKMVSPMPWA | |||||||||||||
2 | 5gqtA3 | 0.24 | 0.23 | 7.08 | 2.15 | SPARKS-K | PGLRCSHGIAQVGNKIYSFGGEFTQPIDKHLYVFDLETRTWSISPAPHLSCLGVRMVSVGSTLYVFGGRD------ASRQYNGFYSFDTTTNEWKLLTPVPTPRSFHSMAADEENVYVFGGVSATARLNTLDSYNIVDKKWFHCSTPGDS | |||||||||||||
3 | 2dyhA | 0.46 | 0.43 | 12.64 | 0.84 | MapAlign | SVPRNRIGVGVIDGHIYAVGGSHGCIHHSSVERYEPERDEWHLVAPMLTRRIGVGVAVLNRLLYAVGGFDG------TNRLNSAECYYPERNEWRMITPMNTIRSGAGVCVLHNCIYAAGGYDGQDQLNSVERYDVETETWTFVAPM--- | |||||||||||||
4 | 2dyhA | 0.43 | 0.41 | 12.12 | 0.59 | CEthreader | QVPRSGLAGCVVGGLLYAVGGRNGNTDSSALDCYNPMTNQWSPCASMSVPRNRIGVGVIDGHIYAVGGSHG------CIHHSSVERYEPERDEWHLVAPMLTRRIGVGVAVLNRLLYAVGGFDGTNRLNSAECYYPERNEWRMITPMNTI | |||||||||||||
5 | 2vpjA | 0.42 | 0.40 | 11.76 | 1.62 | MUSTER | QTAREGAGLVVASGVIYCLGGYDGLNILNSVEKYDPHTGHWTNVTPMATKRSGAGVALLNDHIYVVGGFDGTA------HLSSVEAYNIRTDSWTTVTSMTTPRCYVGATVLRGRLYAIAGYDGNSLLSSIECYDPIIDSWEVVTSMGTQ | |||||||||||||
6 | 5a10A | 0.26 | 0.25 | 7.62 | 1.55 | HHsearch | PAPRSSHGIAVIGDKLYCFGGEDPPSIDNDLYVFDFNTHTWSIAPAVPKTRLGTRMVAVGTKLYVFGGRNKQ------LEFEDFYSYDTVKEEWKFLTKLPEARTFHSMTSDENHVYVFGGVSKGGRFRTIEAYNIAEGKWAQLPDPFEK | |||||||||||||
7 | 4ascA2 | 0.23 | 0.21 | 6.49 | 1.51 | FFAS-3D | ----YGHTVLSHMDLVYVIGGKGSRKCLNKMCVYDPKKFEWKELAPMQTARSLFGATVHDGRIIVAAGVTDTGLTS------SAEVYSITDNKWAPFEAFPQERSSLSLVSLVGTLYAIGGFATLETLNDIWRYNEEEKKWEGVLRE--- | |||||||||||||
8 | 3ii7A | 0.35 | 0.35 | 10.35 | 0.67 | EigenThreader | PTPRDSLAACAAEGKIYTSGGSEVNSALYLFECYDTRTESWHTKPSMLTQRCSHGMVEANGLIYVCGGSLGNN--VSGRVLNSCEVYDPATETWTELCPMIEARKNHGLVFVKDKIFAVGGQNGLGGLDNVEYYDIKLNEWKMVSPMPWK | |||||||||||||
9 | 3vngA | 0.45 | 0.43 | 12.66 | 2.55 | CNFpred | SVPRNRIGVGVIDGHIYAVGGSHGCIHHNSVERYEPERDEWHLVAPMLTRRIGVGVAVLNRLLYAVGGFDGT------NRLNSAECYYPERNEWRMITAMNTIRSGAGVCVLHNCIYAAGGYDGQDQLNSVERYDVETETWTFVAPMKHR | |||||||||||||
10 | 2xn4A | 0.48 | 0.47 | 13.57 | 1.50 | DEthreader | RDRRSTLGAAVLNGLLYAVGGFDGSTGLSSVEAYNIKSNEWFHVAPMNTRRSSVGVGVVGGLLYAVGGYDVA---SR-QCLSTVECYNATTNEWTYIAEMSTRRSGAGVGVLNNLLYAVGGHDGPLVRKSVEVYDPTTNAWRQVADMNMV | |||||||||||||
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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. |