Hit to lead design of novel d-amino-acid oxidase inhibitors using a comprehensive digital chemistry strategy
Overview
Inhibition of D-amino-acid oxidase (DAO) has been hypothesized as a potential therapeutic strategyy for schizophrenia. Schrödinger’s Drug Discovery Team engaged in a discovery effort with a collaborator to identify novel DAO inhibitors with potential best-in-class properties.
Program Challenges
- Identify novel chemical matter while striving for best-in-class molecules that cross the blood-brain-barrier
- Simultaneously optimize drug-like properties, improve CNS exposure, and affinity
Approach
The Drug Discovery Team deployed a large-scale digital chemistry strategy leveraging:
- A centralized project data platform to facilitate knowledge-based medicinal chemistry design collaboration (LiveDesign, AutoQSAR)
- Physics-based methods to predict affinity and prioritize design ideas for synthesis (FEP+)
- Computationally-driven ideation and scoring workflow to amplify common enumeration strategies and screen hundreds of millions of compounds using machine learning coupled with physics-based free energy methods (FEP+, AutoDesigner)
Results
The team discovered a novel class of DAO inhibitors with desirable drug-like properties by confidently exploring synthetically-challenging chemistry. The team also identified a previously unexplored subpocket for further evaluation. The novelty of the compounds, coupled with well-balanced properties, demonstrates the extraordinary power of the approach to unleash project team creativity. By leveraging a digital platform, the team explored vast chemical space while simultaneously optimizing for drug-like properties in a challenging disease area.