Physics-Driven and AI-Accelerated Modeling of Macrocycles and Cyclic Peptides

Accurately sampling bioactive conformations of cyclic peptides and macrocycles and predicting their binding modes is inherently difficult. Sampling errors at this stage propagate to affinity optimization and other downstream tasks. At this event, we’ll discuss practical, in silico approaches engineered to tackle these specific bottlenecks. We’ll focus on two core capabilities: applying specialized flexible docking to reliably capture bioactive conformations, and using rigorous free energy simulations (FEP+) to accurately rank binding affinities before synthesis. We will also offer live demos of our AI co-scientist, Bunsen, and our Live Design informatics platform which simplify and accelerate discovery workflows.  Join us in person to explore how integrating these powerful technologies can de-risk your lead optimization pipeline and deliver meaningful impact on your projects.

Event Highlights

• Lunch & Networking: Join us for lunch before the talks, then stay after the presentations to connect with local industry peers, share insights, and chat with the Schrödinger team over drinks and appetizers.

• End-to-End Peptide Workflow: See how connecting sequence, 3D structure, predictive modeling, and assay data into a single collaborative workspace helps multidisciplinary teams design, iterate, and prioritize candidates faster.

• Bunsen: Get a quick look at our new agentic AI co-scientist tool, designed to lower the barrier to entry and accelerate design cycles by making advanced computational modeling more accessible.