Computational chemistry plays an important role in all aspects of a drug discovery campaign. Here, we present cases studies to demonstrate the ability of computational chemistry to impact early stage projects in the pharmaceutical industry. Typically, when one thinks of early stage project evaluations, druggability and/or ligandability assessments come to mind. We have found that the needs of a project vary greatly in the initial stages and as such, the analysis necessary<br/>to make an impact. For all new targets, compilation and analysis of existing structural information is the first step but the available data will drive the subsequent steps. In some cases, structural information may not be available and ligand-based tools or a well-built homology model may be required. Furthermore, it’s not uncommon for a novel compound to have been identified in an early screen against a target, but the binding site is unknown. Pocket identification methods are then necessary to predict potential binding sites. Additionally, knowledge of the conservation of binding site residues across family members or species can help biologists on the project determine which cross-reactivity/off-target assays to employ. Early stage analyses can also inform and identify the most optimal strategies for high-throughput virtual screens. Large scale virtual screens run by computational chemists can then jump start a project with novel chemical matter before experimental techniques such as high-throughput or DNA-encoded library (DEL) screens have been fully optimized. Consequently, computational chemists well versed in early stage project evaluation strategies can provide crucial data that allow the project team to make the best decisions regarding prosecution of the target at hand.

Computational chemistry evaluation strategies in early-stage drug discovery

ACS Spring Meeting 2021

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.