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DiffDock for Protein-Small-Molecule Docking

DiffDock is a diffusion-based ML model for the docking of a protein to a small molecule. DiffDock reports a confidence score (-inf, inf) where a larger number is better, and scores below -1.5 can be considered low confidence. Note the confidence score does not predict the affinity, aka strength of the biochemical attraction, of the complex.

DiffDock Examples and Docking Scripts​

Dock asparagine into A0A1L9RXX7

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Docking

Load the protein structure for uniprot ID P08100, load the small molecule retinal, and then dock the two together

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Retinal

Dock biotin into P22629

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Biotin

Inputs​

PDB file: specifies the protein structure in 3D.
SMILE string: specifies the identity of the small molecule.

Outputs​

PDB file: specifies the predicted structure of the protein + small molecule docked together.
Confidence score: model confidence in the dock

Evaluating Protein-Small-Molecule Docking Results​

High quality computational evaluation of docking results is an underdeveloped area.

  • Comparison to Experiment: Alignment to and root-mean-square deviation (RMSD) evaluation of the docked structure to experimental data would be the gold-standard metric. However, in the vast majority of cases experimental data is unavailable.
  • Visual Inspection: Use of a molecule visualizer with expert knowledge to check if docked structure makes sense with biochemistry or data that is not a full experimental structure. For example, checking if there is a strong bonding pattern and shape complementarity at the interface. Or for example, checking if the interface involves residues known to be important for the interaction, perhaps from mutational scanning experiments.