Taming Tautomerism in Organic Crystal Structure Prediction

Abstract

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.