Computational approaches for the identification of novel metal-binding pharmacophores: advances and challenges

Metalloenzymes are important therapeutic targets for a variety of human diseases. Computational approaches have recently emerged as effective tools to understand metal-ligand interactions and expand the structural diversity of both metalloenzyme inhibitors (MIs) and metal-binding pharmacophores (MBPs). In this review, we highlight key advances in currently available fine-tuning modeling methods and data-driven cheminformatic approaches. We also discuss major challenges to the recognition of novel MBPs and MIs. The evidence provided herein could expedite future computational efforts to guide metalloenzyme-based drug discovery.