Explore and triage vast chemical space with high precision in silico tools
Identifying the best drug candidate — a novel molecule that optimizes key physicochemical properties while maintaining on-target potency and specificity — is the ultimate challenge of lead optimization programs.
Schrödinger’s platform for molecular design empowers project teams to deploy a ‘predict-first’ approach to lead optimization challenges, dramatically expanding the pool of molecules that can be explored through highly interactive, fully in silico design cycles. Teams can confidently spend time and energy exploring new, unknown, and often more complex designs while sending only the top performing molecules for synthesis.
Predict key properties to accelerate ligand optimization
Free energy-based computational assay (FEP+):
Other physics-based predictions:
• Membrane permeability
• hERG inhibition
• CYP inhibition / TDI
• CYP induction (DDI)
• Site of metabolism
• Brain exposure
- Life Science
In this webinar, we highlight key moments from the discovery of this potentially best-in-class selective, allosteric, picomolar inhibitor of TYK2.Watch webinar
- Life Science
In this webinar, scientists from Schrödinger’s therapeutics group describe several recent case studies where de novo design technologies have allowed teams to overcome critical design challenges and accelerate programs.Watch webinar
Software and services to meet your organizational needs
Deploy digital materials discovery workflows with a comprehensive and user-friendly platform grounded in physics-based molecular modeling, machine learning, and team collaboration.
Leverage Schrödinger’s expert computational scientists to assist at key stages in your materials discovery and development process.
Support & Training
Access expert support, educational materials, and training resources designed for both novice and experienced users.