| >Q9NWH2 (141 residues) METAGAATGQPASGLEAPGSTNDRLFLVKGGIFLGTVAAAGMLAGFITTLSLAKKKSPEW FNKGSMATAALPESGSSLALRALGWGSLYAWCGVGVISFAVWKALGVHSMNDFRSKMQSI FPTIPKNSESAVEWEETLKSK |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | METAGAATGQPASGLEAPGSTNDRLFLVKGGIFLGTVAAAGMLAGFITTLSLAKKKSPEWFNKGSMATAALPESGSSLALRALGWGSLYAWCGVGVISFAVWKALGVHSMNDFRSKMQSIFPTIPKNSESAVEWEETLKSK |
| Prediction | CCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCHHHHHHCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCHHHHHHHHHHHCCCCCCCCCCCHHHHHHHCCC |
| Confidence | 997788888853112345304667788767899999999999999999999986139377751122454467742799999986889999972437999999997799999999999986478999998512589874469 |
| H:Helix; S:Strand; C:Coil | |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | METAGAATGQPASGLEAPGSTNDRLFLVKGGIFLGTVAAAGMLAGFITTLSLAKKKSPEWFNKGSMATAALPESGSSLALRALGWGSLYAWCGVGVISFAVWKALGVHSMNDFRSKMQSIFPTIPKNSESAVEWEETLKSK |
| Prediction | 855645544544543655455653344131122111233322322333213303453463145334444524544230013013312221323331231331222415327403530351134126477335404622578 |
| 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 | CCCCCCCCCCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCHHHHHHCCCCCCCCCCHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHCCCCHHHHHHHHHHHCCCCCCCCCCCHHHHHHHCCC METAGAATGQPASGLEAPGSTNDRLFLVKGGIFLGTVAAAGMLAGFITTLSLAKKKSPEWFNKGSMATAALPESGSSLALRALGWGSLYAWCGVGVISFAVWKALGVHSMNDFRSKMQSIFPTIPKNSESAVEWEETLKSK | |||||||||||||||||||
| 1 | 6bd4A | 0.06 | 0.06 | 2.72 | 0.62 | CEthreader | WMAVWASLCFISTAFTVLTFLIDSSRFSYPERPIIFLSMCYNIYSIAYIVRLTVGRERISCDFEEAAEPVLIQKNTGCAIIFLLLYFFGMASSIWWVILTLTWFLAAGLIPAVKTIVILIMRLVDADELTGLCYVGNQNLD | |||||||||||||
| 2 | 5araT | 0.09 | 0.09 | 3.25 | 0.52 | EigenThreader | LILYLLSKEIYVITPEKYGASVGEFADKLNEQKIAQLEEVKQASIKQIQDAIDMEKSQQALVQKRHYLFDVQRNNIAMALEVLDYHISVQNMMRQKEQEHMINWVEKR---VVQSISAQ----QEKETIAKCIADLKLLSK | |||||||||||||
| 3 | 4i97A2 | 0.12 | 0.09 | 3.26 | 0.60 | FFAS-3D | -----------------PKCPKKRAVINQRLYFDMGTLYQSFANYYYPQVFAKAPADPELYKK------------MEAAVEFLNTFTIADIALLATMSSFEVAGYDFSKVNKWYANAKKVTPGWDENWAGCQEFKKYF--- | |||||||||||||
| 4 | 5ijoJ | 0.04 | 0.04 | 1.95 | 0.71 | SPARKS-K | GTRDSVKTVLQDERQSQALILKIADYYYEERTCILRCVLHLLTYFLVSKYRQQFEELYKTEAPTWETHGNLMTERQVSRWFVQCLREQSMLLEIIFLYYAYFE-MAPSDLLVLTKMFKEQFGSRQTNRLVDETMDPFVDRI | |||||||||||||
| 5 | 5gpjA | 0.17 | 0.12 | 3.95 | 0.69 | CNFpred | ------------------------ITAFRSGAVMGFLLAANGLLVLYIAINLFKIYYGDDWG------------GLFEAITGYGLGGSSMALFGRVGGGIYTKAADV-NPAVIADNVGDNVGDIA------GMGSDLFGSY | |||||||||||||
| 6 | 6bq1A | 0.09 | 0.09 | 3.21 | 0.83 | DEthreader | ------GGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGELRHAQFLVTMCILEAMKWAPTVFVQFEFSLLGRKIYSTAFDFLALAQLPFKNTEAGN------KFVTWHTIDADAPESHHPLTAQYGVKVLRSFA | |||||||||||||
| 7 | 6bd4A | 0.06 | 0.06 | 2.72 | 0.84 | MapAlign | LKCGYDAGLYSRSAKEFTDIWMAVWASLCFISPIIFLSMCYNIYSIAYIVRLTVGRERISCDAAEPVLIQEGLKNTGCAIIFLLLYFFGMASSIWWVILTLTWFLVGNQLDALTGFVVAPLFTYLVIGTLFIAAGLVALFK | |||||||||||||
| 8 | 3vk9A2 | 0.13 | 0.12 | 4.15 | 0.52 | MUSTER | ------------SSL-YPEDPKARALVDQRLYFDIGTLYQRFSDYFYPQVFAGAPADKAKNEKVQEALQLL-EGQKYVAGPNLTVADLSLIASVSSLEASDIDFKKYANVKRWYETVKSTAPGYQE-EKGLEAFKGLVNSM | |||||||||||||
| 9 | 1vt4I3 | 0.13 | 0.11 | 3.69 | 0.55 | HHsearch | -EYANIPKTFDSDDLIPPQYFYSHIHHLKNIEHPERMTLFRMVFLDFRFLEQKIRH--DSTAWNASGS---ILNTLQ------------------QLKFYKPYIC--DNDPKYERLVNAILDFLPKIEEDEAIFEEAHKQV | |||||||||||||
| 10 | 7cgpA | 0.07 | 0.06 | 2.60 | 0.56 | CEthreader | KRQPRLLEPGSLGGIPSPAKSEEQKMIEKAMESCAFKAALACVGGFVLGGAFGVFTAG------------------GQRGMSYAKNFAIVGAMFSCTECLIESYRGTSDWKNSVISGCITGGAIGFRAGLKAGAIGCGGFA | |||||||||||||
| ||||||||||||||||||||
|
Top 10 structural analogs in PDB (as identified by
TM-align)
|
|
Top 5 enzyme homologs in PDB
|
Template proteins with similar binding site:
|
| 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. |