Passive permeability of a drug-like molecule is a critical assay early in a drug discovery campaign that informs a medicinal chemist how well a compound can traverse biological membranes, such as gastrointestinal epithelial or restrictive organ barriers, so it can perform a specific therapeutic function. However, the challenge that remains is the development of a method, experimental or computational, which can both determine the permeation rate and provide mechanistic insights into the transport process to help with the rational design for any given molecule. Typically, one of three methods are used to measure membrane permeability: (1) experimental permeation assays acting on either artificial or natural membranes; (2) quantitative structure-permeability relationship (QSPR) models that rely on experimental values of permeability or related pharmacokinetic properties of a range of molecules to infer those for new molecules; (3) estimates of permeability from the Smoluchowski equation, where free energy and diffusion profiles along the membrane normal are taken as input from large-scale molecular dynamics simulations. While all these methods provide estimates of permeation coefficients, they provide very little information for guiding rational drug design. In this study, we employ a highly parallelizable weighted ensemble (WE) path sampling strategy, empowered by cloud computing techniques, to generate unbiased permeation pathways and permeability coefficients for a set of drug-like molecules across a neat 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC) membrane bilayer. Our WE method predicts permeability coefficients that compare well to experimental values from an MDCK-LE cell line and PAMPA assays for a set of drug-like amines of varying size, shape, and flexibility. Our method also yields a series of continuous permeation pathways weighted and ranked by their associated probabilities. Taken together, the ensemble of reactive permeation pathways, along with the estimate of the permeability coefficient, provides a clearer picture of the microscopic underpinnings of small molecule membrane permeation.
Mechanistic Insights into Passive Membrane Permeability of Drug-Like Molecules from a Weighted Ensemble of Trajectories
20 December 2021, Version 1
This content is a preprint and has not undergone peer review at the time of posting.