Menichetti2019 - Drug−Membrane Permeability across Chemical Space

Using Coarse Grained (CG) models, where several atoms are aggregated into a single bead, the authors obtain a set of 500,000 compounds with their simulated permeability across a single-component DOPC lipid bilayer. With this approach, the authors are able to cover a large and representative portion of the chemical space. We have used the data generated in this publication to train a simple regression model to predict compound permeability.

Model Type: Predictive machine learning model.
Model Relevance: Predicition of Passive permeability based on simulations
Model Encoded by: Miquel Duran-Frigola (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam

Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos2hbd