Dataset Information
Menichetti2019 - Drug−Membrane Permeability across Chemical Space
Ontology highlight
ABSTRACT: 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. Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos2hbd
SUBMITTER: Zainab Ashimiyu-Abdusalam
PROVIDER: MODEL2408070001 | biostudies-other |
SECONDARY ACCESSION(S): 30834317
REPOSITORIES: biostudies-other
Publications
Drug-Membrane Permeability across Chemical Space.
ACS central science 20190108 2
Unraveling the relation between the chemical structure of small druglike compounds and their rate of passive permeation across lipid membranes is of fundamental importance for pharmaceutical applications. The elucidation of a comprehensive structure-permeability relationship expressed in terms of a few molecular descriptors is unfortunately hampered by the overwhelming number of possible compounds. In this work, we reduce a priori the size and diversity of chemical space to solve an analogous-bu ...[more]
