Data & Visualizations
Visualizations for the output job data.
Metrics & Scores
Predictions are ranked by DiffDock's scoring function and ordered from best to worst prediction. Click on a row to display its prediction in the above protein viewer.
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Config
The configuration that was used for this job.
| Configuration Setting | Set Value |
|---|---|
| Dense Sampling | false |
| Docking Mode | Protein-RNA |
| Flexible Backbone | false |
| Ligand Structure | 6487c7540dd6ff4171363619.pdb |
| Receptor Structure | 6487c7530dd6ff4171363618.pdb |
| Simulation Steps | 100 |
Files
The following files were either used as input(s) or produced by this job.
Output Files
Download all as a zip file:
Citations
Please cite the following if you wish to publish data produced from this job.
LightDock: a new multi-scale approach to protein–protein docking Brian Jiménez-García, Jorge Roel-Touris, Miguel Romero-Durana, Miquel Vidal, Daniel Jiménez-González and Juan Fernández-Recio Bioinformatics, Volume 34, Issue 1, 1 January 2018, Pages 49–55, https://doi.org/10.1093/bioinformatics/btx555
LightDock goes information-driven Jorge Roel-Touris, Alexandre M.J.J. Bonvin, Brian Jiménez-García Bioinformatics, btz642; doi: https://doi.org/10.1093/bioinformatics/btz642
Integrative Modeling of Membrane-associated Protein Assemblies Jorge Roel-Touris, Brian Jiménez-García & Alexandre M.J.J. Bonvin Nat Commun 11, 6210 (2020); doi: https://doi.org/10.1038/s41467-020-20076-5
Neurosnap Inc. - Computational Biology Platform for Research. Wilmington, DE, 2022. https://neurosnap.ai/.