| >Q9NV72 (142 residues) KPYKCEECDKVFSRKSHLERHRRIHTGEKPYKCKVCDKAFRRDSHLAQHTVIHTGEKPYK CNECGKTFVQNSSLVMHKVIHTGEKRYKCNECGKVFNHKSNLACHRRLHTGEKPYKCNEC GKVFNRKSNLERHHRLHTGKKS |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | KPYKCEECDKVFSRKSHLERHRRIHTGEKPYKCKVCDKAFRRDSHLAQHTVIHTGEKPYKCNECGKTFVQNSSLVMHKVIHTGEKRYKCNECGKVFNHKSNLACHRRLHTGEKPYKCNECGKVFNRKSNLERHHRLHTGKKS |
| Prediction | CCCCCCCCCCSSCCCCCCCCSCCCCCCCCCSCCCCCCCSSCCCCCCCCSCCCSCCCCCSCCCCCCCSSCCCCCCCCSCCCSCCCCCSCCCCCCCSSCCCCCCCCSCCCSCCCCCSCCCCCCCSSCCCCCCHHHHCCCCCCCC |
| Confidence | 9845788876654423320000320689882168788653443342100032358898127888764245445111003215889812788886524423311010322588981178787650442331111033268587 |
| H:Helix; S:Strand; C:Coil | |
| Sequence |
20 40 60 80 100 120 140 | | | | | | | KPYKCEECDKVFSRKSHLERHRRIHTGEKPYKCKVCDKAFRRDSHLAQHTVIHTGEKPYKCNECGKTFVQNSSLVMHKVIHTGEKRYKCNECGKVFNHKSNLACHRRLHTGEKPYKCNECGKVFNRKSNLERHHRLHTGKKS |
| Prediction | 7525474433003341414413331321231447442300233141441333132133144734220023324044133312223314473413003331404413331231331447342310223141441333134558 |
| 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 | CCCCCCCCCCSSCCCCCCCCSCCCCCCCCCSCCCCCCCSSCCCCCCCCSCCCSCCCCCSCCCCCCCSSCCCCCCCCSCCCSCCCCCSCCCCCCCSSCCCCCCCCSCCCSCCCCCSCCCCCCCSSCCCCCCHHHHCCCCCCCC KPYKCEECDKVFSRKSHLERHRRIHTGEKPYKCKVCDKAFRRDSHLAQHTVIHTGEKPYKCNECGKTFVQNSSLVMHKVIHTGEKRYKCNECGKVFNHKSNLACHRRLHTGEKPYKCNECGKVFNRKSNLERHHRLHTGKKS | |||||||||||||||||||
| 1 | 2i13A | 0.50 | 0.45 | 13.07 | 1.17 | DEthreader | KCPE------CGKSFLRHQRTHT-G-E-KPYKCPECGKSFSQRANLRAHQRTHTGEKPYACPECGKSFSQLAHLRAHQRTHTGEKPYKCPECGKSFSREDNLHTHQRTHTGEKPYKCPECGKSFSRRDALNVHQRTH----- | |||||||||||||
| 2 | 6ml2A | 0.45 | 0.44 | 12.76 | 4.83 | SPARKS-K | KSFTCDQCGKYFSQKRQLKSHYRVHTS--LPECSHCHRKFMDVSQLKKHLRTHTGEKPFTCEICGKSFTAKSSLQTHIRIHRGEKPYSCSICGKCFSDSSAKRRHCILHTGKKPFSCPECGLQFARLDNLKAHLKIHSKE-- | |||||||||||||
| 3 | 5v3gD | 0.57 | 0.57 | 16.40 | 1.03 | MapAlign | KPYVCRECGRGFSNKSHLLRHQRTHTGEKPYVCRECGRGFRDKSHLLSHQRTHTGEKPYVCRECGRGFRDKSNLLSHQRTHTGEKPYVCRECGRGFSWQSVLLRHQRTHTGEKPYVCRECGRGFRDKSNLLSHQRTHTGERN | |||||||||||||
| 4 | 2i13A | 0.59 | 0.57 | 16.37 | 0.84 | CEthreader | KPYKCPECGKSFSDKKDLTRHQRTHTGEKPYKCPECGKSFSQRANLRAHQRTHTGEKPYACPECGKSFSQLAHLRAHQRTHTGEKPYKCPECGKSFSREDNLHTHQRTHTGEKPYKCPECGKSFSRRDALNVHQRTH----- | |||||||||||||
| 5 | 5v3jE | 0.52 | 0.52 | 15.07 | 3.35 | MUSTER | RRFECKDCDKVYSCASQLALHQMSHTGEKPHKCKECGKGFISDSHLLRHQSVHTGETPYKCKECGKGFRRGSELARHQRAHSGDKPYKCKECGKSFTCTTELFRHQKVHTGDRPHKCKECGKAFIRRSELTHHERSHSGEKP | |||||||||||||
| 6 | 5v3jE | 0.52 | 0.52 | 15.07 | 1.61 | HHsearch | RRFECKDCDKVYSCASQLALHQMSHTGEKPHKCKECGKGFISDSHLLRHQSVHTGETPYKCKECGKGFRRGSELARHQRAHSGDKPYKCKECGKSFTCTTELFRHQKVHTGDRPHKCKECGKAFIRRSELTHHERSHSGEKP | |||||||||||||
| 7 | 5v3gD | 0.58 | 0.58 | 16.59 | 2.15 | FFAS-3D | KPYVCRECGRGFSNKSHLLRHQRTHTGEKPYVCRECGRGFRDKSHLLSHQRTHTGEKPYVCRECGRGFRDKSNLLSHQRTHTGEKPYVCRECGRGFSWQSVLLRHQRTHTGEKPYVCRECGRGFRDKSNLLSHQRTHTGEKP | |||||||||||||
| 8 | 5t0uA | 0.30 | 0.30 | 9.17 | 1.30 | EigenThreader | -THKCHLCGRAFRTVTLLRNHLNTHTGTRPHKCPDCDMAFVTSGELVRHRRYKHTHEKPFCSMCDYASVEVSKLKRHIRSHTGERPFQCSLCSYASRDTYKLKRHMRTHSGEKPYECYICHARFTQSGTMKMHILQKHTENV | |||||||||||||
| 9 | 5v3gA | 0.58 | 0.58 | 16.59 | 6.36 | CNFpred | KPYVCRECGRGFSNKSHLLRHQRTHTGEKPYVCRECGRGFRDKSHLLSHQRTHTGEKPYVCRECGRGFRDKSNLLSHQRTHTGEKPYVCRECGRGFSWQSVLLRHQRTHTGEKPYVCRECGRGFRDKSNLLSHQRTHTGEKP | |||||||||||||
| 10 | 5t0uA | 0.35 | 0.33 | 9.89 | 1.17 | DEthreader | HKCHL-----CGRAFTLLRNHLNTHTGTRPHKCPDCDMAFVTSGELVRHRRYHTHEKPFKCSMCDYASVEVSKLKRHIRSHTGERPFQCSLCSYASRDTYKLKRHMRTHSGEKPYECYICHARFTQSGTMKMHILKHTE-V- | |||||||||||||
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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. |