Small molecule drug discovery requires identification of ligands manifesting highly potent and selective binding, while maintaining a wide variety of other ligand properties required for safety and biological efficacy.  We will present how a variety of technological and scientific advances may now be used to readily enumerate and accurately evaluate billions of synthetically-feasible project-relevant small molecules to facilitate more rapid identification of those molecules most likely to be of greatest value.  Essential to the success of these approaches is the integration of active-learning free energy calculation methods, which combine the accuracy of physics-based computational modeling with the addressable scale of modern machine learning methods.  We will further present multiple case studies from active drug discovery projects highlighting how these technologies, rather than simply being used to evaluate ligand design ideas, are being used to directly ideate novel ligand matter likely to advance discovery efforts.

Accelerating drug discovery via ultra large scale enumeration and multi-parameter evaluation of project relevant chemical space

Fall 2022 abstracts, posters, and presentations will launch in mid-September.

ACS Fall 2022

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