Webinar - Discovery at Scale: Using Enterprise-level Deployment of ML to Drive Lead Optimization

June 18, 2019

Time: 1:00 PM EDT 
Speaker: Dr. Kyle Konze

The hit-to-lead and lead optimization processes usually involve the design, synthesis, and profiling of thousands of analogs prior to clinical candidate nomination. A hit finding campaign may begin with a virtual screen that explores millions of compounds; if not more. However, this scale of computational profiling is not frequently performed in the hit-to-lead or lead optimization phases of drug discovery. This is likely due to the lack of appropriate computational tools to generate synthetically tractable lead-like compounds in silico, and a lack of computational methods to accurately profile compounds prospectively on a large scale. Recent advances in computational power and methods provide the ability to profile much larger libraries of ligands than previously possible. In this webinar, the integration of synthetically aware enumeration (PathFinder), cloud-based FEP simulations, and active learning will be presented using cyclin-dependent kinase 2 (CDK2) as a model system. Using our approach to optimize R-groups and core hop from known CDK2 inhibitors, we explored > 300,000 ideas, performed > 5,000 FEP simulations, and identified > 100 ligands with a predicted IC 50 < 100 nM; including four unique cores. The rapid turnaround time, and scale of chemical exploration, indicates that this is a useful approach to accelerate the discovery of novel chemical matter in drug discovery campaigns. 

 

Lead Optimization