RICT 2026
Date & Time - July 1st-3rd, 2026
Location - Paris, France
Schrödinger is excited to be participating in the RICT 2026 – 60th edition of the International Conference on Medicinal Chemistry taking place on July 1st – 3rd in Paris, France. Join us for a workshop by Schrödinger scientists, titled “Accelerating drug discovery through efficient AI/ML integration with LiveDesign ML.”
JUL 3 Accelerating drug discovery through efficient AI/ML integration with LiveDesign ML
Speakers:
Jean-Christophe Mozziconacci, Senior Principal Scientist, Schrödinger
David Papin, Principal Scientist II, Schrödinger
Abstract:
AI/ML models are powerful tools essential for modern drug discovery, enabling the prediction of protein structures, protein-ligand 3D binding poses, de novo design of novel molecules, and the prediction of diverse physical and chemical properties. However, leveraging these tools effectively presents significant challenges. Indeed, the vast landscape of AI/ML algorithms for structural and property predictions necessitates a centralized platform, offering efficient comparison, visualization, and analysis tools for the effective validation and integration of predictions into the design workflow.
LiveDesign ML, a module in Schrödinger’s LiveDesign collaborative enterprise informatics platform, is designed to overcome these hurdles. It enables the generation, optimization, validation, and deployment of state-of-the-art AI/ML models with minimal manual intervention. Model predictive power in evolving chemistry is monitored with confidence via data visualizations and performance metrics. By treating datasets as dynamic information feeds that evolve as scientists explore new chemistry, LiveDesign ML delivers optimized AI/ML models that allow teams to triage newly sketched design ideas or screen hundreds of thousands of compound ideas rapidly.
In this workshop, we will showcase the range of capabilities available within LiveDesign ML, including target enablement tools and de novo design to seamlessly generate, evaluate and optimize compounds, diverse physical and chemical properties predictions including accurate retrosynthesis prediction at scale. This will be demonstrated through a successful case study on the discovery of novel p38/MK2 molecular glue inhibitors. Free Energy Perturbation (FEP+) was successfully applied, with its performance significantly improved by proprietary crystal structures. The lead series shows high potency but needs improved p38/pMK2 selectivity, which highlights the continuous optimization cycle enabled by LiveDesign ML.