| >Q9UI47 (143 residues) MSAETPITLNIDPQDLQVQTFTVEKLLEPLIIQVTTLVNCPQNPSSRKKGRSKRASVLLA SVEEATWNLLDKGEKIAQEATVLKDELTASLEEVRKESEALKVSAERFTDDPCFLPKREA VVQAARALLAAVTRLLILADMID |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | MSAETPITLNIDPQDLQVQTFTVEKLLEPLIIQVTTLVNCPQNPSSRKKGRSKRASVLLASVEEATWNLLDKGEKIAQEATVLKDELTASLEEVRKESEALKVSAERFTDDPCFLPKREAVVQAARALLAAVTRLLILADMID |
| Prediction | CCCCCCCSSCCCCCCCCSSHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHCHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHCCC |
| Confidence | 99999822121688761113569999999999999998168776544678861388999999999999999989997128999999999999999999999999998634887567899999999999999999999864159 |
| H:Helix; S:Strand; C:Coil | |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | MSAETPITLNIDPQDLQVQTFTVEKLLEPLIIQVTTLVNCPQNPSSRKKGRSKRASVLLASVEEATWNLLDKGEKIAQEATVLKDELTASLEEVRKESEALKVSAERFTDDPCFLPKREAVVQAARALLAAVTRLLILADMID |
| Prediction | 76464424040447615331321341034005302400335754456457444515420520340043016304500661650274035005403610530350054147453437424301410341142012000111338 |
| 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 | CCCCCCCSSCCCCCCCCSSHHHHHHHHHHHHHHHHHHHHCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHCHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHCCC MSAETPITLNIDPQDLQVQTFTVEKLLEPLIIQVTTLVNCPQNPSSRKKGRSKRASVLLASVEEATWNLLDKGEKIAQEATVLKDELTASLEEVRKESEALKVSAERFTDDPCFLPKREAVVQAARALLAAVTRLLILADMID | |||||||||||||||||||
| 1 | 1st6A | 0.12 | 0.11 | 3.97 | 1.17 | DEthreader | SDVFSAAAGTANK---DEARKWSSIAAKRMALLMAEMSRLVRGGS----GNKRALIQCAKDIAKASDEVTRLAKEVAKQCTKIRTNLLQVCERIPTISTQLKILSTVKATMLGSEQATEMLVHNAQNLMQSVKETVREAEAAI | |||||||||||||
| 2 | 5xa5A1 | 0.27 | 0.23 | 7.09 | 1.51 | SPARKS-K | --------------IDEVRSKNVLKQITQLINEVT------NITETFPLKPGQTTEGLVATLDAAVANFLQTGSFAISKCPRAIDLLHEALGAVQDTGQVMIQTGRDFVRDSTSTNKRAIATNSGRNLLTAVAKFLILADSID | |||||||||||||
| 3 | 6bfiA | 0.23 | 0.20 | 6.37 | 0.87 | MapAlign | -------------MPVKFHTKTLESVIDPVAQQVGQLVLFHEQAESGLL--KEDLTPLVQGVGIAVTNLVQVAASMVSNDEDFKAELPPSMQEVQQAAVFLSDAARLLKADQGSPEGKRKLLDGARGVINGMSDLLMCADRSE | |||||||||||||
| 4 | 6bfiA1 | 0.23 | 0.20 | 6.37 | 0.59 | CEthreader | -------------MPVKFHTKTLESVIDPVAQQVGQLVLFHEQAESGLLKE--DLTPLVQGVGIAVTNLVQVAASMVSNDEDFKAELPPSMQEVQQAAVFLSDAARLLKADQGSPEGKRKLLDGARGVINGMSDLLMCADRSE | |||||||||||||
| 5 | 5xa5A1 | 0.27 | 0.23 | 7.09 | 1.61 | MUSTER | --------------IDEVRSKNVLKQITQLINEVTNITETFP------LKPGQTTEGLVATLDAAVANFLQTGSFAISKCPRAIDLLHEALGAVQDTGQVMIQTGRDFVRDSTSTNKRAIATNSGRNLLTAVAKFLILADSID | |||||||||||||
| 6 | 5xa5A1 | 0.28 | 0.24 | 7.28 | 3.58 | HHsearch | --------------IDEVRSKNVLKQITQLINEVTNITETF--P----LKPGQTTEGLVATLDAAVANFLQTGSFAISKCPIAIDLLHEALGAVQDTGQVMIQTGRDFVRDSTSTNKRAIATNSGRNLLTAVAKFLILADSID | |||||||||||||
| 7 | 5xa5A1 | 0.27 | 0.23 | 7.08 | 2.22 | FFAS-3D | ----------------EVRSKNVLKQITQLINEVTNITETFPL------KPGQTTEGLVATLDAAVANFLQTGSFAISSDPRAIDLLHEALGAVQDTGQVMIQTGRDFVRDSTSTNKRAIATNSGRNLLTAVAKFLILADSID | |||||||||||||
| 8 | 6bfiA4 | 0.12 | 0.12 | 4.18 | 0.87 | EigenThreader | PLPPKDQNVFREADQWDEKGNDLISLVKQMARKMAMMSKYTRGES----RSKADLIRMAKEIALNAQELLKLARQIANACKRAKTNLLQLLDRIPTISTQLKILATVKATSMGGGDATDMLVGNAENLMRTVKDVIRASEAAC | |||||||||||||
| 9 | 4p9tA | 0.61 | 0.50 | 14.22 | 1.01 | CNFpred | ----------------EIRTLTVERLLEPLVTQVTTLVNT-----------SKKAHVLAASVEQATQNFLEKGEQIAKESQDLKEELVAAVEDVRKQGETMRIASSEFADDPCSSVKRGTMVRAARALLSAVTRLLILADMAD | |||||||||||||
| 10 | 6bfiA1 | 0.23 | 0.20 | 6.37 | 1.17 | DEthreader | ------------MP-VKFHTKTLESVIDPVAQQVGQLVLFHEQAESGL-LKE-DLTPLVQGVGIAVTNLVQVAASMVETSDEFKAELPPSMQEVQQAAVFLSDAARLLKADQGSPEGKRKLLDGARGVINGMSDLLMCADRSE | |||||||||||||
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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. |