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Using Membrane Partitioning Simulations To Predict Permeability of Forty-Nine Drug-Like Molecules.

Callum J DicksonViktor HornakDallas BednarczykJose S Duca
Published in: Journal of chemical information and modeling (2018)
A simple descriptor calculated from molecular dynamics simulations of the membrane partitioning event is found to correlate well with experimental measurements of passive membrane permeation from the high-throughput MDCK-LE assay using a data set of 49 drug-like molecules. This descriptor approximates the energy cost of translocation across the hydrophobic membrane core (flip-flop), which for many molecules limits permeability. Performance is found to be superior in comparison to calculated properties such as clogP, clogD, or polar surface area. Furthermore, the atomistic simulations provide a structural understanding of the partitioned drug-membrane complex, facilitating medicinal chemistry optimization of membrane permeability.
Keyphrases
  • molecular dynamics simulations
  • high throughput
  • molecular dynamics
  • ionic liquid
  • electronic health record
  • machine learning
  • drug induced
  • deep learning
  • monte carlo