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rdkit cannot load some mol2 files #13
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Convert the mol2 files into sdf files with some external tools (e.g., convert.py in OpenEye), and then load them into the RDkit using "Chem.MolFromMolFile". |
Thank you for your reply. I have other following questions. First, I saw you uploaded the processed graphs at https://zenodo.org/record/6859325#.Y6KpS3ZBxD-. I found that each data point is stored in a heterogeneous graph object. I guess I should convert it into two separate protein and ligand graphs before feeding it to RTMScore. Alternatively, I can also modify the model to make it possible to process heterogeneous graphs. Am I right? Second, the heterogeneous graph contains three types of distance (cadist, cedist, and mindist). Is mindist equal to the result returned by the function “compute_euclidean_distances_matrix” at model2.py? Do these three types of distance lead to similar performance? Third, do the two auxiliary tasks matter? Do you test the model performance by removing the two auxiliary tasks? To my understanding, the model is just trained to recover the information already included in the input features for the auxiliary tasks. I am looking forward to your reply. Thank you. |
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Thank you for your reply. I might have the following question. To my understanding, RTMScore is trained to predict a Gaussian-like distribution where mu is supposed to be at a position close to the true distance (i.e., y in the source code). However, when I check the prediction of the trained RTMScore I found that the predicted mu is far away from the true distance y. Is that normal, or perhaps I misunderstood the algorithm? |
sigma and mu are all a group of parameters to determine the distribution of the distance, and the final distribution of a specific residue-atom pair shall be the mixtures of multiple Gaussians. Hence there shall be no relation between a single mu and the correponding y. It should be noticed that mu and y have different dimentions. |
Thank you very much for your reply. I tried to apply for a license for OpenEye, but I haven’t received any feedback yet. Could you please upload the processed graphs or converted sdf files for CASF2016 decoys_docking set? |
The following are the scores of the poses in CASF-2016 docking set predicted by our models, and I think they are enough to show the performance of our methodology. rtmscore2_casf2016_docking.tar.gz |
Dear Dr. Shen, thank you for sharing the source code of RTMScore. I’m trying to process decoys_docking set of CASF-2016, but I found that there are some mol2 files that cannot be successfully read by RDkit (fail to be sanitized and return None when executing “ligand_mol2 = Chem.MolFromMol2File(ligand_mol2_path, removeHs=True)”). Are there any solutions to solve this problem, or you just skipped those mol2 files that cannot be successfully loaded?
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