igashov / difflinker Goto Github PK

delinker_utils/sascorer.py is calling a module of RDKit that was removed in Release_2024.03.1
See change log: https://github.com/rdkit/rdkit/blob/master/ReleaseNotes.md#code-removed-in-this-release-1

I encountered this when trying to run one of your case studies:

$ python ./DiffLinker/generate_with_protein.py \
    --fragments 3hz1_modified_fragments_obabel.sdf \
    --protein 3hz1_protein.pdb \
    --output samples \
    --model models/pockets_difflinker_full_given_anchors.ckpt \
    --linker_size models/zinc_size_gnn.ckpt \
    --anchors 12,22 \
    --n_samples 1000 \
    --max_batch_size 16 \
    --random_seed 1
Traceback (most recent call last):
  File "[...]/DiffLinker/generate_with_protein.py", line 14, in <module>
    from src.lightning import DDPM
  File "[...]/DiffLinker/src/lightning.py", line 7, in <module>
    from src import metrics, utils, delinker
  File "[...]/DiffLinker/src/delinker.py", line 7, in <module>
    from src.delinker_utils import sascorer, calc_SC_RDKit
  File "[...]/DiffLinker/src/delinker_utils/sascorer.py", line 22, in <module>
    from rdkit.six.moves import cPickle
ModuleNotFoundError: No module named 'rdkit.six'

Hi,

Thanks for your amazing work!

I am particularly interested in the metric of "steric clashes" as described in your paper

I am attempting to implement this metric in my project, but I did not find specific code in your repository for calculating this metric. Could you please provide it, or guide me on how to implement it?

Thank you for your time and consideration!

@igashov

Your work is especially helpful! I found that the two fragments in the SDF file you provided are complete molecules with 3D structures. If I have two fragments, must they also be complete molecules and 3D structures? And I want to ask are fragments from ligands in the original PDB protein structure broken up?
My fragment molecule for example: c1ccc((=O)(O)NC(C)(C)C)cc1”，c1nnn1

and I can not use browser to link the https which you give.

After using your weights and trying to find the linker of the fragment with the following code:

generate.main(
        input_path = "...generator_0.sdf",
        model = "models/geom_difflinker.ckpt",
        output_dir = "difflinker/output",
        n_samples = 2,
        n_steps = None,
        linker_size = "...difflinker/models/geom_size_gnn.ckpt",
        anchors = None)

I got the following error:

File "difflinker/src/egnn.py", line 134, in init
self.device = device
File "lib/python3.7/site-packages/torch/nn/modules/module.py", line 1317, in setattr
super().setattr(name, value)
AttributeError: can't set attribute

It was happening when I was trying to load the weights. After commenting parts with self.device = device in several files from src it started compiling properly. Please let me know I misunderstand smth or if you have experienced the same. Just in case I'm working with cuda if it might matter

hi,

if using generate_with_protein.py or generate_with_pocket.py method, the para --anchors is necessary. however,
In order to take into account the diversity of compounds generated, is there any approach that takes into account the combination and limitation of pockets but doesn't limit the location of the anchors for the fragment links?

many many thanks,

Sh-Y

Hi, you guys did a good job about connecting diffusion model and de novo design based on fragments.
I'm now working on design small molecules, I want to use this model to work, but after I run the code I met some problems.

1. Accroding to the help instructions, If I got 3 mol fragments, should I put them into one pdb file? And how the format of this kind of PDB file looks like, is there any example input file?
2. the argument anchor, is that mean the atoms id in the PDB file that link the fragments?
   I'm looking forward to your help ~

Hey, is it possible to run cpu mode? I saw it's possible from the generate.py, but when I tried I got this error:

python -W ignore /home/softwares/DiffLinker/generate.py --fragments frag.sdf --model models/geom_difflinker.ckpt --linker_size models/geom_size_gnn.ckpt --anchors 9,19
Will generate linkers with sampled numbers of atoms
Sampling...
  0%|                                                                                                  | 0/1 [00:01<?, ?it/s]
Traceback (most recent call last):
  File "/home/softwares/DiffLinker/generate.py", line 187, in <module>
    main(
  File "/home/softwares/DiffLinker/generate.py", line 156, in main
    chain, node_mask = ddpm.sample_chain(data, sample_fn=sample_fn, keep_frames=1)
  File "/home/softwares/DiffLinker/src/lightning.py", line 449, in sample_chain
    chain = self.edm.sample_chain(
  File "/home/softwares/mambaforge3/envs/difflinker/lib/python3.10/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/home/softwares/DiffLinker/src/edm.py", line 152, in sample_chain
    z = self.sample_p_zs_given_zt_only_linker(
  File "/home/softwares/DiffLinker/src/edm.py", line 188, in sample_p_zs_given_zt_only_linker
    eps_hat = self.dynamics.forward(
  File "/home/softwares/DiffLinker/src/egnn.py", line 383, in forward
    edges = self.get_edges(n_nodes, bs)  # (2, B*N)
  File "/home/softwares/DiffLinker/src/egnn.py", line 464, in get_edges
    return self.get_edges(n_nodes, batch_size)
  File "/home/softwares/DiffLinker/src/egnn.py", line 459, in get_edges
    edges = [torch.LongTensor(rows).to(self.device), torch.LongTensor(cols).to(self.device)]
  File "/home/softwares/mambaforge3/envs/difflinker/lib/python3.10/site-packages/torch/cuda/__init__.py", line 216, in _lazy_init
    torch._C._cuda_init()
RuntimeError: No CUDA GPUs are available

hi,

thank you to provide so interesting and powful tool to generate linkers.

while I try to repeat your model, run into the error

the below command line I used to run the model om_difflinker_given_anchors.ckpt

!python -W ignore generate_with_protein.py --fragments fragments/frags_3hz1.sdf \
--protein proteins/pro_3hz1_protein.pdb --model models/geom_difflinker_given_anchors.ckpt \
--linker_size 3 --anchors 14,11

• frags_3hz1.sdf , this file is downloaded from the address (https://huggingface.co/spaces/igashov/DiffLinker/tree/main/examples)
• pro_3hz1_protein.pdb, this pdb file is also from the above address.

and the anchors were set as you mentioned in other issues.

but the error:

Will generate linkers with 3 atoms
[15:28:10] Can't kekulize mol.  Unkekulized atoms: 0 1 2 3 4 5 6 7 8

could you please provide some suggesitions about how to fix it and make it work?
many thanks,

Sh-Y

Hi,

How do you sample with protein??

thanks

I am currently conducting research on structure-based drug design using proteins.

I find the concept of fragmentation linking to be a valuable approach in drug design, and I am particularly impressed with your work's ability to consider the conditioning on the protein pocket. Thank you for hard working on it!

I have a few questions regarding your research:

1. First, I attempted to reproduce the results from your paper using the Sampling section (https://github.com/igashov/DiffLinker#sampling). However, I noticed that the results for the ZINC and GEOM datasets differ significantly from the paper's reported results, especially concerning the SA score. While the paper's SA score is approximately 3.x, my results yielded a score of 6.x. I'm unsure why these results are different. Is there an additional step required to accurately reproduce the paper's findings?

2. Unfortunately, as mentioned in the readme, there is no pocket linker prediction model available. Therefore, I was unable to conduct experiments with the Pocket dataset. Could you provide some suggestions on how I can reproduce the paper's results without this model? Additionally, I am curious about the linker prediction model used in the Table 5 pocket section.

3. I came across Figure 2 in the paper, which showcases examples of linkers sampled by DiffLinker conditioned on pocket atoms. I attempted to replicate these results using the same molecule fragments from the MOAD dataset and the awesome hugging face. However, I couldn't achieve the same results as presented in the paper, even when utilizing the same protein anchors. Could you please guide me on how to accurately reproduce the results shown in Figure 2?

4. I am interested in reproducing the results shown in Figure 4 and 5 from the paper. However, I encountered a challenge as there is no index provided in the paper, which prevents me from attempting the test. Could you kindly provide me with the necessary information about the fragments used in the Figure 4 and 5 datasets? This would be immensely helpful in my efforts to replicate the results accurately

If you require any specific information or have any additional questions to aid in reproducing my experiments, please let me know, and I will promptly provide the requested details.

Thank you for your time and consideration.

@igashov