>Q9NW08 (150 residues) KGLVKQHIDSFNYFINVEIKKIMKANEKVTSDADPMWYLKYLNIYVGSAPITVDIEYTRG SQRIIRNALPIGRMAGQLLSLLFEDLFKKFNSEMKKIADQVIPKQRAAQFDVVKHMRQDQ ITNGMVNAISTGNWSLKRFKMDRQGVTQVL |
Sequence |
20 40 60 80 100 120 140 | | | | | | | KGLVKQHIDSFNYFINVEIKKIMKANEKVTSDADPMWYLKYLNIYVGSAPITVDIEYTRGSQRIIRNALPIGRMAGQLLSLLFEDLFKKFNSEMKKIADQVIPKQRAAQFDVVKHMRQDQITNGMVNAISTGNWSLKRFKMDRQGVTQVL |
Prediction | CCHHHHHHHHHHHHHHHHHHHHHHHCCCSCCCCCCCSSSSSSSSSSCCCCCCCCCCCCCCCSSSCCCCCCHHHCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCCCHHHHCCHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCC |
Confidence | 951566666677889989999998145221357985356442222126886566122148644012465211234999999999999999999999999999707877664777414114568888776507864334455667752219 |
H:Helix; S:Strand; C:Coil | |
Sequence |
20 40 60 80 100 120 140 | | | | | | | KGLVKQHIDSFNYFINVEIKKIMKANEKVTSDADPMWYLKYLNIYVGSAPITVDIEYTRGSQRIIRNALPIGRMAGQLLSLLFEDLFKKFNSEMKKIADQVIPKQRAAQFDVVKHMRQDQITNGMVNAISTGNWSLKRFKMDRQGVTQVL |
Prediction | 742342113111201644044015127514253344010301222044441414352333433044574433500230033103300430143024205411655454514024204463025204300011314454464543403146 |
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 | CCHHHHHHHHHHHHHHHHHHHHHHHCCCSCCCCCCCSSSSSSSSSSCCCCCCCCCCCCCCCSSSCCCCCCHHHCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCCCCCHHHHCCHHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCC KGLVKQHIDSFNYFINVEIKKIMKANEKVTSDADPMWYLKYLNIYVGSAPITVDIEYTRGSQRIIRNALPIGRMAGQLLSLLFEDLFKKFNSEMKKIADQVIPKQRAAQFDVVKHMRQDQITNGMVNAISTGNWSLKRFKMDRQGVTQVL | |||||||||||||||||||
1 | 7d58B | 0.91 | 0.90 | 25.29 | 1.17 | DEthreader | GL-VKQHIDSFNYFINVEIKKIMKANEKVTSDADPMWYLKYLNIYVGLPAITVDIEYTRGSQRIIRNAPGRMPIMGQLLSLLFEDLFKKFNSEMKKIADQVIPKQRAAQFDVVKHMRQDQITNGMVNAISTGNWSLKRFKMDRQGVTQLM | |||||||||||||
2 | 7b0yB1 | 0.32 | 0.31 | 9.25 | 1.77 | SPARKS-K | --LVRQQLDSFDEFIQMSVQRIVEDAPPIDLQAPPRYLLKFEQIYLSSAPLYVDITKTVIKEQTQHQKTFIGKIPIMLLAFLFRGMFKNLLKEVRIYAQKFIDRGK--DFNLELAIKTRIISDGLKYSLATGNWGDQKAHQARAGVSQVL | |||||||||||||
3 | 4c2mB1 | 0.14 | 0.14 | 4.77 | 0.92 | MapAlign | QEAVQPHIGSFNALTGGLLNLGVKDIGEKVIFDGNKLSVSVEQVSIARGKLLLKLKWSVNNEENLFEVRDCGGLGGFLYGMILKEKIDEYLQNIIAQVRMDINRGMINFKRVLMRVN-ENIGSKMQYFLSTGNLVSQLDLQQVSGYTVVA | |||||||||||||
4 | 4c2mB1 | 0.15 | 0.15 | 5.14 | 1.02 | CEthreader | QEAVQPHIGSFNALTGGLLNLGVKDIGEKVIFDGKKLSVSVEQVSIARGKLLLKLKWSVNNGENLFEVRDCGGLPGFLYGMILKEKIDEYLQNIIAQVRMDINRGMAINFKRVLMRVNENIGSKMQYFLSTGNLVSQLDLQQVSGYTVVA | |||||||||||||
5 | 4c2mB1 | 0.15 | 0.15 | 4.96 | 0.87 | MUSTER | QEAVQPHIGSFNALTEGPDGGLLNLGGEKVIFDGKQVSIAKPMSNRKRGKLLLKLKWSVNNEENLFEVRDCGLLGGFLYGMILKEKIDEYLQNIIAQVRMDINRGMAINFKDKRYMSNENIGSKMQYFLSTGNLVSQSGLQQVSGYTVVA | |||||||||||||
6 | 7b0yB1 | 0.32 | 0.31 | 9.43 | 2.19 | HHsearch | --LVRQQLDSFDEFIQMSVQRIVEDAPPIDLQAPPRYLLKFEQIYLSSAPLYVDITKTVIKEQTQHQKTFIGKIPGPLLAFLFRGMFKNLLKEVRIYAQKFIDRGK--DFNLELAIKTRIISDGLKYSLATGNWGDQKAHQARAGVSQVL | |||||||||||||
7 | 5svaB1 | 0.29 | 0.29 | 8.73 | 1.26 | FFAS-3D | KGLVSQQLDSFNQFVDYTLQDIICEDSTLIDNISRKYEISFGKIYVTKPMVNERTYEAIDELKYELGKVFIGRLAGPLLAQLFKTLFKKLTKDIFRYMQRTVEEAH--DFNMKLAINAKTITSGLKYALATGNWGEQKKAMSRAGVSQVL | |||||||||||||
8 | 6wvjC2 | 0.13 | 0.13 | 4.41 | 0.88 | EigenThreader | PNLIEIQTSSYQWFLDEGLREMFQDISPIE-DFTGNLSLEFIDYSLGSAPLRVKVRLINKETDQDVFMGDFPIMTLRSVGELLQNQFRIGLSRMERVVRERMSIQDTNNIRPVIASIKEFFGSSLAELTHKRRLSALGPGGLLINSLSVN | |||||||||||||
9 | 3mlqA | 0.14 | 0.12 | 4.12 | 1.13 | CNFpred | --LTEIQVESYKKALQVGIQAAFKETFPIEEGDKGGLVLDFLEYRIGDAPLYARLQLIHKTGLIKEDEVFLGHLPL-TVGELMADQFRVGLARLARGVRERMVMGSPDTLTPAKLVNSRPLEAALREFFSRSQLS--------------- | |||||||||||||
10 | 7a6hB | 0.83 | 0.83 | 23.31 | 1.17 | DEthreader | -GLVKQHIDSFNYFINVEIKKIMKANEKVTSDADPMWYLKYLNIYVGLPAPITVDIEYTRGSRIIRNAPGRMPIMAQLLSLLFEDLFKKFNSEMKKIADQVIPKQRAAQFDVVKHMRQDQITNGMVNAISTGNWSLKRFKMDRQGVTQLM | |||||||||||||
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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. |