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Hi Joel. The receptor should only include the protein itself. DeepFrag provides an "Automatically remove all protein atoms?" link you can use if your protein does include a ligand.
The ligand file is separate but must represent the ligand in the receptor-bound pose. DeepFrag isn’t a docking program, so it can’t position the ligand for you. But if the ligand is positioned in the bound conformation, DeepFrag can recommend fragment additions.
This tutorial might be helpful: https://www.youtube.com/playlist?list=PLR7O6-it-8SOpQTV8oSVHMg8-_R_4gZRV
Take care,
Jacob
Hi Chandan. Is the text you provided in your question the original PDB text? I ask because that PDB text isn’t valid, though it could be a problem that arose when you pasted the PDB file into the forum text box.
Entries in PDB files are determined by column, so it’s critical to put all the spaces in the right places. They are not simply space-delimited fields, if that makes sense.
Hope this answer helps. Take care.
~Jacob
Hi Paul and Santiago. Can you send me copies of your protein and ligand files? That would help a lot with debugging. I’ll email you separately. Thanks. ~Jacob
Hi Pete. When you press the "Save" button in the web app, the resulting ZIP file contains a VMD directory with a VMD state file. Hope this helps. ~Jacob
Hi Daniel. Sincere apologies for the confusion. I just realized that I accidentally uploaded the beta version of the app to the production site. The original version (2.1) should now be restored, with the extract-ligand option. Take care. ~Jacob
Hi Srdan. I’ve never tried it with membranes before, but it’s worth taking a look. I can’t think of any reason it wouldn’t work! Take care. ~Jacob
Hi Wenchang. Thanks for your interest in AutoGrow4! We don’t currently have anyone in the lab working on AutoGrow4, so we don’t plan to add any new features in the short term (just bug fixes). But the program is open source, so please feel free to add to it if you like! Take care.
Hi Christian. Thanks for your interest in ProteinVR. I tested your protein on the Oculus browser. The frame rate wasn’t as high as I hoped, but it did work. I wonder if your device might be underpowered in terms of memory. What kind of Oculus headset do you have? Thanks.
Hi Cory! I recently saw the Vina 1.2 update, which seems to have a lot of great additions. I agree with you that the multiple-ligand docking feature could be great for fragment growing!
One of the advantages of having AutoGrow use an executable rather than python bindings is broad compatibility. Most docking programs don’t have Python bindings, but all have executable files.
Given your interest in fragment-growing strategies, have you had a chance to look at our lab’s DeepFrag program? https://durrantlab.pitt.edu/deepfrag/ We’re very excited about machine-learning approaches to drug discovery.
Anyway, I just wanted to thank you for your interest! It’s always great to engage with people who like to think about these kinds of things.
Hi Sarath. Much thanks for your interest in BINANA, and for pointing out the need for this new feature. I added an issue to the BINANA repo as a reminder for a future version. Not sure when the next version will be released (we actually just released a new one a few weeks ago), but that issue should keep it on my radar. Here are some BINANA-related links, in case you’re interested:
Version 2.0 (just released): https://git.durrantlab.pitt.edu/jdurrant/binana
Web app: https://durrantlab.pitt.edu/binana/Thanks!
Hi Brandon. Much thanks for your interest in AutoGrow4. Without seeing your files, I can’t say for certain what the problem is. But for what it’s worth, I don’t think the SDF files contain the docked compounds. If I’m not mistaken, the docked poses end in ".pdbqt.vina" and are PDBQT formatted. I hope this helps. ~Jacob
Hi Alok. Much thanks for your interest in AutoGrow4. To answer your question, there unfortunately isn’t a video describing AutoGrow4 use. But here’s some documentation that might help:
https://git.durrantlab.pitt.edu/jdurrant/autogrow4/-/blob/4.0.3/README.md
https://git.durrantlab.pitt.edu/jdurrant/autogrow4/-/blob/4.0.3/tutorial/TUTORIAL.md
By default, I believe AutoGrow4 uses AutoDock Vina for docking under the hood. I don’t know how well Vina performs when using DNA as the receptor, but in principle it might work. At least some folks have tried it: http://www.chem.hope.edu/~discus/muccc/muccc30/MUCCC30-Haugen.pdf
Hope this answer helps. Take care.
Hi Ben. Much thanks for your interest in DeepFrag! Just to clarify, DeepFrag doesn’t actually position the fragments it recommends in 3D space. It only suggests which fragments to add.
As a helper program for the DeepFrag browser app, we created a separate app called Fuser that can be used to add the DeepFrag-recommended fragment to a source molecule. The output is a 3D model for use in docking studies. Are you referring to the Fuser app in your question, by chance?
If so, it’s important to note that the 3D ligand made in Fuser isn’t meant to be in any sense "docked" into the protein receptor. DeepFrag doesn’t position the fragment (it only recommends what fragment to use), and Fuser is a step removed from DeepFrag.
Hope this helps. Take care..
Hi Luciano. Much thanks for your interest in AutoGrow4. Looks like you might need to use the ‘custom_docking_script’ parameter. Here’s a description:
The name and path to a python script that is used to dock ligands. This is required for Custom docking choices. Must be a list of strings [name_custom_conversion_class, Path/to/name_custom_conversion_class.py]
More information here: https://git.durrantlab.pitt.edu/jdurrant/autogrow4/-/blob/4.0.3/tutorial/TUTORIAL.md#running-custom-docking-scripts
Hi Xiaoqing. Much thanks for your interest in AutoGrow4. It’s difficult to know what exactly is causing the problem based on the provided information, but let me give a few suggestions in case they help. The error might occur when none of the compounds of one generation pass the user-specified filters. You could try increasing the number of crossovers, mutants, etc., to give the program more chances to generate acceptable compounds for advancing to the next generation.
It could also be that it’s not possible to add fragments to your starting compounds because your fragments (or starting compounds) lack the reactive groups that the AutoGrow4 reaction library requires.
Another thing to try is to remove the -LipinskiLenientFilter parameter, which could allow more evolving compounds to advance to the next generation.
Hope this helps,
Jacob
