Drug-target interactions occur on second-to-minute timescales, but computational methods only reach microseconds. AI is still grappling with static protein structures. This gap hides the transition states that control drug kinetics, forcing trial-and-error optimization. Enhanced sampling methods for atomistic simulations can bridge this timescale gap, achieving 10,000-fold acceleration while maintaining physical accuracy. Applied to multiple drug discovery programs, we reveal previously invisible transition states that enabled rational optimization of drug residence time and selectivity.
Dennis Nenno
Dennis Nenno is a founder and the Chief Executive Officer of Examol, an operating system for computational drug discovery focused on small molecules. He led project teams at BASF, developing software solutions to automate chemical plants worldwide. As a research fellow, he simulated the properties of advanced and unrealized materials at Harvard University and the Max Planck Institute for Chemical Physics of Solids. He holds a Ph.D. in Theoretical Physics. Dennis is an advisor on quantum technologies for venture capital.
Examol Corporation
Website: https://examol.io/
Examol accelerates drug discovery for challenging targets and advanced modalities through physics-based simulations that capture millisecond to minute timescales. Their technology enables binding kinetics predictions, identification of transient druggable pockets, and training data generation for generative AI models that improve drug design. The platform has successfully predicted minute-scale residence times, optimized PROTAC degraders, and revealed transient binding sites invisible to conventional methods.
