Docking + Active Site Design

[Anonymous]

Hi,

I have posted this question in my Enzyme design thread earlier and it seems it has remained unnoticed. Therefore, I am asking the same query again. I would like to know whether its possible to combine docking + mutation of residues forming the active site. More specifically, I am looking for a protocol where I can combine docking with mutation of active site residues to all 20 amino acids to get best designed active sites based on docking socre. I know this can be done using enzyme design protocol, but is it still possible when we don’t have TS for the intermediate and can work with the substrate alone? Hope my query is clear.

Regards
B

[Anonymous]

I just responded to your other post – https://www.rosettacommons.org/comment/8166#comment-8166

Regarding enzyme design, there really isn’t anything special about a “transition state” in enzyme design, as far as Rosetta is concerned. It’s just another ligand. It may be chemically unrealistic, but with the correct input settings that’s not much of a concern to Rosetta. At that stage in the process, Rosetta is functioning almost solely on the transition state stabilization theory for enzyme activity, so it’s not a big leap to change the protocol slightly in order to design for binding of a chemically realizable compound instead of a transition state. In fact, it’s a little bit simpler as you don’t have to worry about the active site catalytic constraints. (Although you can certainly put them in for binding interactions instead, if you want.)

See Tinberg et al. Nature. 2013 Sep 12;501(7466):212-6. for an example of using the enzyme design machinery to redesign for small molecule binding.

[Anonymous]

Hi,

Could you please tell me some easy to use clustering tool for clustering the docked complexes from Rosetta docking? I tried using 3dLigandSite, but it seems the server does not take all the docked complexes…

I have docked two types of ligands to the same active and I am interested in analyzing the orientational preference of functional groups of these two ligands. Is it possible and how ?

[Anonymous]

I have started using the rosetta scripts for docking and design. I am getting the following error:
protocols.jd2.DockDesignerParser: Defined mover named “start_from” of type StartFrom
Segmentation fault (core dumped)

My pdb doesn’t have chain ID so I replaced it with an alphabet A using Pymol and I ran this command :
rosetta_scripts.linuxgccrelease @options.txt -database /home/rosetta-3.5/rosetta_database/

Pls find all the files attached herewith. I also checked whether after renaming PDB is opening in pymol or not and even that opens fine too.

When I tried docking with the same starting coordinates without using xml script, it worked fine. I don’t know where the problem is ??

Also when I tried docking (without xml script) and using resfile for mutation of residues around active. I dont’t get any residue mutated in the docked, which I specifically made to mutate to Alanine. Why is it so?

I tried again the docking protocol using xml script and this time I am getting a different error:
protocols.jd2.DockDesignerParser: Defined mover named “start_from” of type StartFrom
ERROR: Exit from: src/core/pose/util.cc line:2191

—
M

[Anonymous]

Hi,

I have solved the problem which I posted in my last post. I was providing the wrong chain ID and that’s why I was getting error from start_from mover. I was supposed to use the chain ID of the ligand and not that of protein’s chain ID. Now, I am successfully able to generate mutants of my active site as well.

I have a question regarding analyzing the result. I would like to know which score is important is it the total_score or interface_delta_X? Which score should be considered for a better binding mutants? For eg:
total_score interface_delta_X
Mutant 1 -1566.97 -8.14
Mutant 2 -1555.79 -8.02
Mutant 3 -1555.09 -6.94
Mutant 4 -1564.99 -2.087 (this model has the least total_score but its interface_delta_X score is not the lowest)

Among these four models which one should be considered the best for testing in wet-lab??

[Anonymous]

Generally for ligand docking and enzyme design the binding energy of the ligand to the protein (roughly interface_delta_X) is the primary energy for optimization. The reason for this is that there can be a lot of noise in the total energy due to movement of protein sidechains which wouldn’t affect the binding energy at all.

The caveat to this is if you go just on the binding energy, you can theoretically cause the protein to unfold or make clashes with itself to get a better interaction with the ligand. You want to avoid this, so often there’s a multi-stage analysis involved, where you first do a filter on total score to throw out all the bad-scoring outliers (which may have clashes or other bad geometry.) From these reasonable structures you then rank by interaction energy and pick the structures which best optimize it.

[Anonymous]

Thank you for providing the answer.

Bh

[Anonymous]

The “select_best_unique_ligand_poses” application (https://www.rosettacommons.org/docs/latest/ligand-dock.html#Clustering-ligand-poses) is probably my recommendation.

This doesn’t do full-on clustering in the K-means naive sense, but instead takes an energy-based approach. It takes the lowest energy ligand, and labels that as a cluster center. It then runs up the list of structure sorted by energy until it finds a structure which has a ligand rmsd outside the provided cutoff radius, and then labels that as a new cluster center. It continues this until it’s found a given number of cluster centers, or it exhausts the number of structures available.

If you use the version in a weekly release, it should take the standard “jd2” option for input.

One drawback is that it’s set up just to give you cluster centers, not to say which cluster non-centers are part of. It should be easy enough to alter the program to spit that information out, though.

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