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
read the case study
Related Products
Learn more about the related computational technologies available to progress your research projects.
Publications
Browse the list of peer-reviewed publications using Schrödinger technology in related application areas.
Training & Resources
Online certification courses
Level up your skill set with hands-on, online molecular modeling courses. These self-paced courses cover a range of scientific topics and include access to Schrödinger software and support.
Tutorials
Learn how to deploy the technology and best practices of Schrödinger software for your project success. Find training resources, tutorials, quick start guides, videos, and more.
Other Resources