About this session
In lead optimization, every synthesis decision counts, so reliable binding affinity predictions can mean the difference between a wasted cycle and a real breakthrough. However, traditional free energy methods are often too slow or compute-intensive to keep pace with today's project timelines.
Join us to discover FE-NES, a nonequilibrium alchemical method that delivers high-throughput relative binding free energy (RBFE) calculations with far less sampling than equilibrium approaches like FEP or TI. We will also present a reduced-sampling variant, Rapid FE-NES, that produces affinity predictions 3x faster than default FE-NES, enabling scaling into thousands of molecules with ease. We'll share insights on how Rapid FE-NES can effectively balance accuracy and scale, and show how adaptive compute allocation can help you prioritize the right molecules faster than ever.