PoxFolds: All-versus-all protein interaction network - MPOX [Data set]. Zenodo.
https://doi.org/10.5281/zenodo.12517508
Please cite this resource if you find it useful. It results from over 100,000 predicted models and several months of computing.
Also, tell your friends about it. Thanks!
Keep in mind that some proteins will need to form high-order oligomers to function. Therefore, the dimeric predictions displayed here might inform on interfaces but they might not represent functional units.
Click and drag to move around, use the mouse wheel to zoom, click nodes to explore proteins and click on edges to explore interactions.
Clicking on the buttons selects the virus interactome. We are trying to add more protein-protein-interaction data to this resource. When they are added you can decide to show the common interactions between the viruses or the unique ones.
The table on the right lists all interactions. Clicking on the column headers will sort the table. Clicking on a node filters the table to show only interactions with that protein. Clicking in the background of the graph deselects the protein and all interactions are shown again. The links in the protein source and target columns will open the prediction website for the monomer with the scores and 3D models. The link in the ipTM column will open the PPI website with the scores and predicted 3D models.
The size (weight) of the connections encodes how well an interaction was predicted by AlphaFold 2. A thicker connection indicates a more likely interaction than a thinner one. Thickness is calculated from AlphaFold Multimer’s ipTM value. Only interactions with an ipTM value greater than 0.47 are shown.
MPOX
This is a project in cooperation with the Topf lab at CSSB.
The predictions are visualized using 3Dmol.js:
Predictions were run with LocalColabFold on the DESY compute cluster.
See also:
The network was created using cytoscape.js, a Graph theory library for visualization and analysis, which was developed by Franz M, Lopes CT, Huck G, Dong Y, Sumer O, Bader GD at the University of Toronto https://js.cytoscape.org/
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