This workshop presents common molecular modeling and design techniques for identifying, optimizing, and prioritizing small-molecule drug candidates. The workshop begins by describing structure preparation and pocket analysis to understand key protein-ligand interactions. Participants will explore template-based docking of congeneric series and pharmacophore-guide docking (to preserve key interactions) to predict how small molecules bind to a protein target. This workshop also presents a series of de novo fragment-based drug design applications, focusing on scaffold hopping and fragment growing methods to generate novel compound ideas, optimize structures in the pocket, and score them. It also discusses the use of molecular descriptors, protein-ligand interaction fingerprints (PLIFs), and pharmacophore models to guide the drug design process. Finally, a method for generating closely related analogs through bioisosteric replacements is presented.

This workshop explores some essential ligand-based methods for guiding drug discovery projects. Participants will learn how to efficiently use MOEsaic to perform SAR analyses of compound datasets, using approaches such as R-group profiling and matched molecular pairs (MMP) analysis, to identify relationships within chemical series. The session highlights computational strategies for extracting meaningful insights from structure-activity data to support informed decision-making in drug design. The workshop also introduces the CLE application as a powerful tool for streamlining the search of available reagent catalogs using multi-component chemical reactions. It demonstrates how to apply a reaction both as a query and as a transformation to efficiently enumerate all possible product combinations. The session covers methods for inspecting, filtering, and exporting reagents and products, including catalog IDs, for synthesis.