[Home]
[Back to DMFold server]
[Help]
DMFold results for DMF482643047
[Click result.zip to download all results on this page]
Input Sequence In FASTA Format
|
DMF482643047 ( 207 residues )
|
>DYT1_monomer-A MGGGSRFQEPVRMSRRKQVTKEKEEDENFKSPNLEAERRRREKLHCRLMALRSHVPIVTNMTKASIVEDAITYIGELQNNVKNLLETFHEMEEAPPEIDEEQTDPMIKPEVETSDLNEEMKKLGIEENVQLCKIGERKFWLKIITEKRDGIFTKFMEVMRFLGFEIIDISLTTSNGAILISASVQTQELCDVEQTKDFLLEVMRSNP
|
Multiple Sequence Alignments
|
Predicted Contact And Distance Map
|
Contact Map
|
Distance Map
|
Top 5 Final Models From DMFold
|
|
Note: If the JSmol model is not visible, please refresh the page or click the radio buttons
|
(a) | DMFold generates a large set of structural models by different MSAs as inputs. These models are ranked by predicted TM-score (pTM-score for multimer) or predicted LDDT (pLDDT for monomer) and top 5 models are selected with the highest predicted scores. |
|
Residue-level Modeling Quality
|
Proteins With Similar Structure
|
| |
Top 10 structural analogs in PDB (as identified by
TM-align)
Note: If the JSmol model is not visible, please refresh the page or click the radio buttons
(a) | Query structure is shown in cartoon, while the structural analog is displayed using backbone trace. |
(b) | Ranking of proteins is based on TM-score of the structural alignment between the query structure and known structures in the PDB library. |
(c) | RMSDa is the RMSD between residues that are structurally aligned by TM-align. |
(d) | IDENa is the percentage sequence identity in the structurally aligned region. |
(e) | Cov. represents the coverage of the alignment by TM-align and is equal to the number of structurally aligned residues divided by length of the query protein. |
|
[Back to server]
Reference:
Wei Zheng, Qiqige Wuyun, Yang Li, Chengxin Zhang, P Lydia Freddolino, Yang Zhang. Improving deep learning protein monomer and complex structure prediction using DeepMSA2 with huge metagenomics data. Nature Methods, (2024). https://doi.org/10.1038/s41592-023-02130-4.
Wei Zheng, Quancheng Liu, Qiqige Wuyun, P. Lydia Freddolino, Yang Zhang. DMFold: A deep learning platform for protein complex structure and function predictions based on DeepMSA2. In preparation.
Wei Zheng, Qiqige Wuyun, Peter L Freddolino, Yang Zhang. Integrating deep learning, threading alignments, and a multi-MSA strategy for high-quality protein monomer and complex structure prediction in CASP15. 1-20. Proteins. (2023). doi:10.1002/prot.26585.
|
|