Comments (1)
We haven't thoroughly tested the downstream tasks for dmasif. In principle you could use a similar docking protocol as the one used in masif but replace the descriptors and interface predictions with the ones from dmasif. You will also have to change the patch extraction method in masif since you won't have a mesh to work with anymore, you could do this by approximating the geodesic distances like done in dmasif. The parameters of the docking protocol have to be fine-tuned for dmasif.
We'll try to benchmark these downstream tasks soon.
from dmasif.
Related Issues (20)
- RuntimeError: legacy constructor expects device type: cpubut device type: cuda was passed
- How to perform massif-ligand "type" tasks with this framework.
- Choice of the atom RADII HOT 1
- How to predict the interface characters of single protein? HOT 1
- dMaSIF for interaction prediction, how to find complementary regions? HOT 2
- No save model checkpoints for site prediction HOT 2
- Input seems to require a y value HOT 2
- Running you example does not provide same ROC-AUC as claimed in the paper HOT 14
- Using main_training.py
- Problems regarding loss function and auroc
- Does anyone have a docker image that can run this project? Can you share it with me? HOT 4
- How to replace with my own dataset
- why the interface is computed like this ? HOT 4
- About helper.py
- Pre-trained model in Hugging face
- [Question] Are ligands or PTMs considered
- How to mathematically define the binding surface? HOT 1
- Why "iface_preds " contain NAN when training dmasif_ HOT 7
- Return value in diagonal_ranges function
- embedding example HOT 1
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from dmasif.