| >Q9BZR9 (143 residues) MAENWKNCFEEELICPICLHVFVEPVQLPCKHNFCRGCIGEAWAKDSGLVRCPECNQAYN QKPGLEKNLKLTNIVEKFNALHVEKPPAALHCVFCRRGPPLPAQKVCLRCEAPCCQSHVQ THLQQPSTARGHLLVEADDVRAW |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | MAENWKNCFEEELICPICLHVFVEPVQLPCKHNFCRGCIGEAWAKDSGLVRCPECNQAYNQKPGLEKNLKLTNIVEKFNALHVEKPPAALHCVFCRRGPPLPAQKVCLRCEAPCCQSHVQTHLQQPSTARGHLLVEADDVRAW |
| Prediction | CCCCHHHHHHHHCSCHHHHHHCCCCSSCCCCCCHHHHHHHHHHHHCCCCSSCCCCCCSSCCCCCCCCCHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCSSSCCCCCHHHCHHHHHHHHCCCCCCCCCSSCCHHHHHCC |
| Confidence | 97422678276102753635627971428996130999998986258844256645232588888664759999999998333467777656336889973108991346821317771343245323478435138985159 |
| H:Helix; S:Strand; C:Coil | |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | MAENWKNCFEEELICPICLHVFVEPVQLPCKHNFCRGCIGEAWAKDSGLVRCPECNQAYNQKPGLEKNLKLTNIVEKFNALHVEKPPAALHCVFCRRGPPLPAQKVCLRCEAPCCQSHVQTHLQQPSTARGHLLVEADDVRAW |
| Prediction | 84654362047303331134305413303001210240045215557442434404432444463423320340043047355666856341521663562503222432552045313530473444446240331653576 |
| 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 | CCCCHHHHHHHHCSCHHHHHHCCCCSSCCCCCCHHHHHHHHHHHHCCCCSSCCCCCCSSCCCCCCCCCHHHHHHHHHHHHHCCCCCCCCCCCCCCCCCCCCCCSSSCCCCCHHHCHHHHHHHHCCCCCCCCCSSCCHHHHHCC MAENWKNCFEEELICPICLHVFVEPVQLPCKHNFCRGCIGEAWAKDSGLVRCPECNQAYNQKPGLEKNLKLTNIVEKFNALHVEKPPAALHCVFCRRGPPLPAQKVCLRCEAPCCQSHVQTHLQQPSTARGHLLVEADDVRAW | |||||||||||||||||||
| 1 | 7l3lA | 0.17 | 0.12 | 3.92 | 0.83 | DEthreader | -FV--ERLE-ERYKCAFCHSVLHNPHQTGCGHRFCQHCILSLRELNT-VPICPVDKEVIKSQ-EVFKDNCCKREVLNL--YVYCSAPGCNA----LQQCQPV----------LRKDLKEHLSAS------------------- | |||||||||||||
| 2 | 5olmA | 0.29 | 0.24 | 7.45 | 2.24 | SPARKS-K | ASAARLTMMWEEVTCPICLDPFVEPVSIECGHSFCQECISQVGKS-----VCPVCRQRFLL-KNLRPNRQLANMVNNLKEISQEARGER--CAVHG----ERLHLFCEKDGKALCWVCAQS-----RKHRDHAMVPLE----- | |||||||||||||
| 3 | 5olmA | 0.30 | 0.24 | 7.42 | 0.97 | MapAlign | --AARLTMMWEEVTCPICLDPFVEPVSIECGHSFCQECISQVG-----KSVCPVCRQRFLL-KNLRPNRQLANMVNNLKEI--SQEARGERCAVH----GERLHLFCEKDGKALCWVCAQKH-------RDHAMVPL------ | |||||||||||||
| 4 | 6wi7A | 0.22 | 0.21 | 6.64 | 0.77 | CEthreader | EIVVSPRSLHSELMCPICLDMLKNTMTTKCLHRFCADCIITALRS--GNKECPTCRKKLVSKRSLRPDPNFDALISKIYPSRTTRIKITLMCVLCG--GYFIDATTIIECLHSFCKTCIVRYLETSKYVQVHKTRPLLNIRSD | |||||||||||||
| 5 | 5olmA | 0.29 | 0.24 | 7.45 | 1.95 | MUSTER | ASAARLTMMWEEVTCPICLDPFVEPVSIECGHSFCQECISQVGKSV------PVCRQRFLLK-NLRPNRQLANMVNNLKEISQEARGE-----RCAVH-GERLHLFCEKDGKALCWVCAQS-----RKHRDHAMVPLE----- | |||||||||||||
| 6 | 4kblA | 0.20 | 0.19 | 6.03 | 1.55 | HHsearch | KEKLMERYFDGNMPCQICYLNYPYFTGLECGHKFCMQCWSEYLTTKEETISCPAHGCDILVDDNTVMRLITSKVKLKYQHLIVECNRLLKWCPACHHVYPDAKPVRC-KCGRQFCFNCG---------ENWHDPVKCKWLKKW | |||||||||||||
| 7 | 5olmA | 0.26 | 0.22 | 6.89 | 1.25 | FFAS-3D | MASARLTMMWEEVTCPICLDPFVEPVSIECGHSFCQECISQVGKSVCPV------CRQRFLLKNLRPNRQLANMVNNLKEISQEARGE------RCAVHGERLHLFCEKDGKALCWVCAQSRKH-----RDHAMVPLE----- | |||||||||||||
| 8 | 6wi7A | 0.23 | 0.21 | 6.57 | 0.98 | EigenThreader | SLHS-------ELMCPICLDMLKNTTTKECLHRFCADCIITALRSGNK--ECPTCRKKLVSKRSLRPDPNFDALISKIY---PSRTTPHLMCVLC--GGYFIDATTIECLHSFCKTCIVRYLETSKYCPICDVQVRRRDFYAA | |||||||||||||
| 9 | 5olmA | 0.30 | 0.25 | 7.63 | 2.45 | CNFpred | ASAARLTMMWEEVTCPICLDPFVEPVSIECGHSFCQECISQVGK-----SVCPVCRQRFLLK-NLRPNRQLANMVNNLKEISQE----GERCAVHGER----LHLFCEKDGKALCWVCAQSRK-----HRDHAMVPLE----- | |||||||||||||
| 10 | 4wz3B | 0.17 | 0.12 | 3.90 | 0.83 | DEthreader | LEANLSH-TTPTLTCPIDSGFLKDPVITPEGFVYNKSSILKWLETK---KEDPQSRKPLTAK-DLQPFPELLIIVNRFVETQTNYELKNRL----------VQNAR-----------------------------VAAQYEIP | |||||||||||||
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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, 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. |