Taming Tautomerism in Organic Crystal Structure Prediction

Tautomerism influences the solubility,
stability, efficacy,
and
even toxicity of drug formulations. Computational solid-form screening
is increasingly being used to help identify effective drug formulations
and derisk against undesirable crystal forms. Here, however, we demonstrate
that widely used density functionals predict tautomeric crystal polymorph
energetics poorly, largely due to density-driven delocalization error.
We first show how these DFT models incorrectly identify the preferred
tautomeric polymorphs of 2-thiobarituric acid and the antihelmintic
drug mebendazole and that some functionals substantially underestimate
the barrier to solid-state tautomerization. Surveying 18 additional
examples, we find that tautomeric polymorph energy differences defy
conventional wisdom by exceeding the normal 10 kJ/mol energy window
associated with crystal polymorphism in ∼40% of the cases,
sometimes by tens of kJ/mol. Moreover, the DFT errors in the polymorph
energy differences are strikingly large: they can reach tens of kJ/mol
and produce the wrong qualitative stability ordering in ∼20–30%
of the cases. We address the challenge of predicting tautomeric polymorphs
through a general solution that combines periodic hybrid DFT with
intramolecular coupled-cluster theory corrections to substantially
improve agreement with experiment. Most notably, our refined models
reveal that the experimentally reported crystal structure of mebendazole
form B features the incorrect tautomera prediction that is
confirmed via solid-state NMR analysis.