How to tell if our ligand-protein docking is good from AutoDock Vina's result
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Entering edit mode
14 months ago
gundalav ▴ 370

I have perform a ligand-protein docking using Autodock Vina. The result of the docking looks like this:

WARNING: The search space volume > 27000 Angstrom^3 (See FAQ)
Detected 8 CPUs
Setting up the scoring function ... done.
Analyzing the binding site ... done.
Using random seed: -1553787135
Performing search ... done.
Refining results ... done.

mode |   affinity | dist from best mode
| (kcal/mol) | rmsd l.b.| rmsd u.b.
-----+------------+----------+----------
1         -5.9      0.000      0.000.  Pose 1
2         -5.7     22.945     25.492.  Pose 2
3         -5.5      1.426      2.046.  Pose 3
4         -5.5     23.669     25.616
5         -5.4     25.783     29.152.  .....
6         -5.3     21.146     23.357
7         -5.2     20.323     22.545
8         -5.2     23.864     26.064
9         -5.1     23.422     26.585.  Pose 9


As far as I understand from these statistics Mode 1(Pose 1) is the best. However when I actually visualize them in Pymol, Pose 1 has no hydrogen bonding at all but Pose 2 has.

My question is how can we judge if which of those two Pose is the best to use?

Note in figure below Pose 2 has dashed line (Hydrogen bond).

protein-structure vina autodock docking pdb • 613 views
1
Entering edit mode
14 months ago
Mensur Dlakic ★ 20k

I always consider two criteria when evaluating similar results: binding affinity and biological relevance. Pose 1 is the best according to binding energy, and it doesn't matter that there are no hydrogen bonds in PyMol. There are other contributions to binding energy beyond hydrogen bonds.

Your Pose 1 & 2 solutions are wildly different, at least according to their RMSD. Which one makes more biological sense as a docking site? If Pose 2 makes more sense, I would consider that to be a tiebreaker, because the energy difference is relatively small. By the way, you may want to consider heeding that warning on the first line, and define a smaller search space. You are more likely to get several meaningful docking solutions.