Membrane Permeability
Physics-based solution for rapid and accurate prediction of passive membrane permeability
Evaluate membrane permeability with unmatched accuracy
Membrane Permeability is a robust solution to accurately predict passive membrane permeability of small molecules across diverse chemistries. By considering conformation dependent phenomena such as internal hydrogen-bonding, which can have a dramatic effect on permeability, it offers tremendous advantages over QSAR and machine learning-based approaches.
Key Capabilities
Accelerate hit-to-lead and lead optimization by rapidly scoring and prioritizing large sets of idea compounds based on predicted permeability, prior to running advanced modeling such as FEP+
Predict partition energy for inserting a small molecule into the membrane using a physics-based approach
Benefit from automatic detection and sampling of macrocycles using an advanced sampling algorithm
Featured Case Study
Design of a novel potent CDC7 inhibitor development candidate with high ligand efficiency and optimized properties
See how Membrane Permeability enabled the Schrödinger team to prioritize designs in the discovery of a novel, potent CDC7 inhibitor development candidate with high ligand efficiency and optimized properties
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