Pocket discovery
Pocket discovery is the process of identifying regions on a protein’s surface where small molecules (drugs) are most likely to bind. OpenDDE uses P2Rank, a machine-learning tool developed at the Czech Technical University, to predict these binding pockets.
What is a binding pocket?
Proteins are large, complex 3D molecules. Their surfaces have grooves, clefts, and cavities. A binding pocket is a specific cavity where a drug molecule can physically fit and form chemical interactions (hydrogen bonds, hydrophobic contacts, salt bridges).
Think of it like a lock: the pocket is the keyhole, and the drug is the key. For a drug to work, it must fit snugly into the right pocket on the right protein.
How P2Rank works
P2Rank is a machine-learning method that predicts ligand-binding sites from a protein structure. Here’s how it works:
- Surface point sampling — The protein surface is sampled as a set of points using a Connolly surface algorithm
- Feature extraction — For each point, P2Rank computes chemical and geometric features: hydrophobicity, charge, surface curvature, atom density, etc.
- ML scoring — A random forest classifier scores each point for its likelihood of being part of a binding site
- Clustering — High-scoring points are clustered into discrete pockets, ranked by aggregate score
Understanding druggability scores
Each predicted pocket receives a druggability score between 0 and 1:
| Score range | Interpretation | What it means |
|---|---|---|
0.80 – 1.00 | Highly druggable | Deep, well-defined cavity. Strong candidate for small-molecule binding. |
0.50 – 0.79 | Moderately druggable | Reasonable pocket but may be shallow or partially exposed. |
0.20 – 0.49 | Challenging | Flat or exposed surface. May require fragment-based approaches. |
0.00 – 0.19 | Unlikely | Not a viable drug binding site with current methods. |
How to interpret pocket residues
Each pocket is defined by the amino acid residues that form its walls. OpenDDE shows you the residue composition:
- Hydrophobic residues (Leu, Ile, Val, Phe) — form the “greasy” interior of the pocket. More hydrophobic = better for small-molecule binding.
- Polar residues (Ser, Thr, Asn, Gln) — provide hydrogen bonding partners for drug design.
- Charged residues (Asp, Glu, Lys, Arg) — can form salt bridges with charged drug groups.
- Aromatic residues (Phe, Tyr, Trp) — enable pi-stacking interactions with aromatic drug rings.
Limitations and caveats
- Static structures — P2Rank operates on a single 3D snapshot. Proteins are dynamic; some pockets only open during conformational changes (cryptic sites).
- Allosteric sites — P2Rank focuses on orthosteric (active site) pockets. Allosteric sites may be ranked lower even if therapeutically relevant.
- Predicted structures — When using AlphaFold-predicted structures (vs. experimental crystal structures), pocket predictions may be less reliable in low-confidence regions.
- Protein-protein interfaces — Pockets at protein-protein interaction sites may not be detected as traditional small-molecule binding sites.