Hi,

I am having some issues looking through test_sets_pdb:

original (undocked) structures are in: db5_test_random_transform with ligands (part that moves) being in random_transformed, receptor (not movable) being in complexes and results in db5_equidock_results.

So for example if we take from db5_equidock_results the following pose: 1AVX_l_b_EQUIDOCK.pdb this means that 1AVX_l_b.pdb was used as ligand (movable) and 1AVX_r_b_complex.pdb as receptor (not moved). This means that if I superimposse in pymol 1AVX_l_b_EQUIDOCK.pdb and `1AVX_r_b_complex.pdb' I should get a nicely docked complex, however this is not the case. There are many many clashes.

Can you help?

Best, Liviu

hello, when I run the command: python preprocess_raw_data.py -n_jobs 20 -data db5 -graph_nodes residues -graph_cutoff 30 -graph_max_neighbor 10 -graph_residue_loc_is_alphaC -pocket_cutoff 8

I got the following error:

Processing split 1 Processing ./cache/db5_residues_maxneighbor_10_cutoff_30.0_pocketCut_8.0/cv_1\label_val.pkl Traceback (most recent call last): File "C:\Users\equidock_public-main\src\preprocess_raw_data.py", line 37, in Unbound_Bound_Data(args, reload_mode='val', load_from_cache=False, raw_data_path=raw_data_path, File "C:\Users\equidock_public-main\src\utils\db5_data.py", line 78, in init with open(os.path.join(split_files_path, reload_mode + '.txt'), 'r') as f: FileNotFoundError: [Errno 2] No such file or directory: './data/benchmark5.5/cv/cv_0\cv_1\val.txt'

Any suggestions?

Thanks

as we can see in the DISP_Plus, the author said: about make dips dataset #7 https://github.com/BioinfoMachineLearning/DIPS-Plus/issues/7

"deadlock of sorts after a certain number of complexes have been processed." when run for a long time, it will appeare By chance， but for few files , it always run success, so i Split up to process the make_dataset

first mkdir six different fold like tmp1 tmp2 .... mkdir tmp1 than cd in pdb and move the files to the new fold mv ls | head -200 ../tmp6 run make_dataset.py seperate: python3 make_dataset.py project/datasets/DIPS/raw/tmp1 project/datasets/DIPS/interim --num_cpus 24 --source_type rcsb --bound

add a -W to ignore check，

rsync -rlpt -v -W -z --delete --port=33444 rsync.rcsb.org::ftp_data/biounit/coordinates/divided/ ./DIPS/raw/pdb

hope it useful

Hi, I created a virtual environment and tried to pip install the dependencies listed in README.md. However, I'm not able to install some of them (e.g. cuda & dgl==0.7.0). Can I request for a requirements.txt to install the dependencies?

Thank you! :)

Hello!

I was working with your code and found out that the best validation score used in the project (val_complex_rmsd_median) differs from what is enunciated in the article presenting EquiDock (val_ligand_rmsd_median). Is there any reason behind this choice or am I misinterpreting something ?

https://github.com/octavian-ganea/equidock_public/blob/ac2c754399bf20b50a27d86dbff4f6669788d47f/src/train.py#L372

Hi there,

I'd like to report a bug on installation. So far my workaround was to use dgl==0.9.0 rather than the dgl==0.7.0 you have in the requirements.

Also, is there an easy way to interface with the models for a custom set of PDBs? I'd prefer to avoid having to fiddle with the inference_rigid.py but from what it seems there's no way to pass custom sets other than perhaps inserting them as test data?

Hi, dear authors of Equidock, I feel really sad to hear the news that Ganea passed away without fully showing his extraordinary genius.

I came across the calculation of the Kabsh Model and found that the computation of the rotation matrix is somehow misleading. To be specific, U, S, Vt = np.linalg.svd(H) gives us the U, S, V^T, which corresponds to U2, S, U1^T in the paper. Next, the rotation matrix is obtained via R = Vt.T @ U.T, which is different from what is described in the text. Instead, R = U2 @ U^T, which should be R = U @ Vt in the code. Do you agree with me?

Thank you for this great tool. I am starting to install it on Ubuntu 20.04, and met with multiple FileNotFound Errors. Are there any dependencies not listed? Here are the errors: (base) nc1@nc1-UA9C-R38:~/equidock_public-main$ # Extract the raw PDB files: (base) nc1@nc1-UA9C-R38:~/equidock_public-main$ python3 project/datasets/builder/extract_raw_pdb_gz_archives.py project/datasets/DIPS/raw/pdb python3: can't open file '/home/nc1/equidock_public-main/project/datasets/builder/extract_raw_pdb_gz_archives.py': [Errno 2] No such file or directory (base) nc1@nc1-UA9C-R38:~/equidock_public-main$ (base) nc1@nc1-UA9C-R38:~/equidock_public-main$ # Process the raw PDB data into associated pair files: (base) nc1@nc1-UA9C-R38:~/equidock_public-main$ python3 project/datasets/builder/make_dataset.py project/datasets/DIPS/raw/pdb project/datasets/DIPS/interim --num_cpus 28 --source_type rcsb --bound python3: can't open file '/home/nc1/equidock_public-main/project/datasets/builder/make_dataset.py': [Errno 2] No such file or directory (base) nc1@nc1-UA9C-R38:~/equidock_public-main$ (base) nc1@nc1-UA9C-R38:~/equidock_public-main$ # Apply additional filtering criteria: (base) nc1@nc1-UA9C-R38:~/equidock_public-main$ python3 project/datasets/builder/prune_pairs.py project/datasets/DIPS/interim/pairs project/datasets/DIPS/filters project/datasets/DIPS/interim/pairs-pruned --num_cpus 28 python3: can't open file '/home/nc1/equidock_public-main/project/datasets/builder/prune_pairs.py': [Errno 2] No such file or directory

Hi, thanks for the great work!! I have a question regarding the following point in the paper:

On p.7 it is stated that:

we unfortunately do not know the actual alignment between points in $Y_l$ and $P_l$ , for every $l ∈ {1, 2}$. This can be recovered using an additional optimal transport loss

However, in the code here : https://github.com/octavian-ganea/equidock_public/blob/main/src/train.py#L128 The optimal transport matrix (the 2nd returned variable) is ignored:

ot_dist, _ = compute_ot_emd(cost_mat_ligand + cost_mat_receptor, args['device'])

In my understanding, the matrix should be used to recovered the alignment. So I am now confused how the points alignment can be recovered without this optimal transport matrix?

Thank you so much again!

Hello ! It is a bit unclear to me which hyper parameters you used to train your model, could you provide a complete list of your best models for DIPS and DB5? In particular, I am not sure whether node and edge features were used. Moreover, the hyperparameters you mention in the paper are not the same as your best model's checkpoints. Thanks :)