Shape-Restrained Modeling of Protein–Small-Molecule Complexes with High Ambiguity Driven DOCKing

Small-molecule docking
remains one of the most valuable computational
techniques for the structure prediction of protein–small-molecule
complexes. It allows us to study the interactions between compounds
and the protein receptors they target at atomic detail in a timely
and efficient manner. Here, we present a new protocol in HADDOCK (High
Ambiguity Driven DOCKing), our integrative modeling platform, which
incorporates homology information for both receptor and compounds.
It makes use of HADDOCK’s unique ability to integrate information
in the simulation to drive it toward conformations, which agree with
the provided data. The focal point is the use of shape restraints
derived from homologous compounds bound to the target receptors. We
have developed two protocols: in the first, the shape is composed
of dummy atom beads based on the position of the heavy atoms of the
homologous template compound, whereas in the second, the shape is
additionally annotated with pharmacophore data for some or all beads.
For both protocols, ambiguous distance restraints are subsequently
defined between those beads and the heavy atoms of the ligand to be
docked. We have benchmarked the performance of these protocols with
a fully unbound version of the widely used DUD-E (Database of Useful
Decoys-Enhanced) dataset. In this unbound docking scenario, our template/shape-based
docking protocol reaches an overall success rate of 81% when a reliable
template can be identified (which was the case for 99 out of 102 complexes
in the DUD-E dataset), which is close to the best results reported
for bound docking on the DUD-E dataset.