  Deep generative models for structure-based drug design (SBDD), where molecule
generation is conditioned on a 3D protein pocket, have received considerable
interest in recent years. These methods offer the promise of higher-quality
molecule generation by explicitly modelling the 3D interaction between a
potential drug and a protein receptor. However, previous work has primarily
focused on the quality of the generated molecules themselves, with limited
evaluation of the 3D molecule \emph{poses} that these methods produce, with
most work simply discarding the generated pose and only reporting a "corrected"
pose after redocking with traditional methods. Little is known about whether
generated molecules satisfy known physical constraints for binding and the
extent to which redocking alters the generated interactions. We introduce
PoseCheck, an extensive analysis of multiple state-of-the-art methods and find
that generated molecules have significantly more physical violations and fewer
key interactions compared to baselines, calling into question the implicit
assumption that providing rich 3D structure information improves molecule
complementarity. We make recommendations for future research tackling
identified failure modes and hope our benchmark can serve as a springboard for
future SBDD generative modelling work to have a real-world impact.
