Off-Pocket Activity Cliffs: A Puzzling Facet of Molecular Recognition

While accurate quantitative prediction of ligand–protein
binding affinity remains an elusive goal, high-affinity ligands to
therapeutic targets are being designed through heuristic optimization
of ligand–protein contacts. However, herein, through large-scale
data mining and analyses, we demonstrate that a ligand’s binding
can also be strongly affected through modifying its solvent-exposed
portion that does not make contacts with the protein, thus resulting
in “off-pocket activity cliffs” (OAC).
We then exposed the roots of the OAC phenomenon by means of molecular
dynamics (MD) simulations and MD data analyses. We expect
OAC to extend our knowledge of molecular recognition and enhance the
drug designer’s toolkit.