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The value of pursuing a structure-based drug discovery strategy has amplified in recent years as new highly predictive, physics-based methods have evolved and demonstrated the ability to accelerate the discovery of novel clinical compounds. However, these approaches are limited by the availability of high-quality structural models of the target protein.

Recent advances in structural biology such as cryo-EM and computationally predicted protein models (using machine learning and physics-based methods) have the potential to open a new world of targets to pursue. This webcast will describe how new advances in computational workflows are enabling structure-based drug discovery on these historically challenging targets and off-targets.

• How new computational approaches can assist in building and validating high-quality protein structural models in the absence of experimental X-ray crystal structures
• How these methods can be used to guide structure-based drug discovery programs, such as progressing hits from high-throughput screens, dialing out off-target liabilities, and improving on-target potency
• What this means for the future of structure-based drug discovery amidst advances in structural biology