Abstract

Permeation of compounds through membranes is important in biological and engineering processes, e.g., drug delivery through lipid bilayers, anesthetics, or chemical reactor design. Simulations at the atomic scale can provide insight in the diffusive pathways and they give estimates of the membrane permeability based on counting membrane transitions or on the inhomogeneous solubility-diffusivity model described by the Smoluchowski equation. For many permeants, permeation through a membrane is too slow to gather sufficient statistics with conventional molecular dynamics simulations, i.e., permeation is a rare event. Recent attempts to improve the description of the dynamics of such rare permeation events have been based on milestoning, which allows the study of processes at timescales beyond those achievable by straightforward molecular dynamics. The approach is not relying on an overdamped description, but, still, it uses a Markovian approximation which is only valid for small permeants that are not disruptive to the membrane structure. To overcome this fundamental limitation, we show here how replica exchange transition interface sampling (RETIS) can effectively be used on this problem by deriving an effective set of equations that relate the outcome of RETIS simulations and the permeability coefficient. In addition, we introduce two new path Monte Carlo (MC) moves specifically for permeation dynamics, that are used in combination with the ordinary path generating moves, which considerably increase the efficiency. The advantage of our method is that it gives exact results, identical to brute force molecular dynamics, but orders of magnitude faster.

Highlights

  • Permeation of compounds through another medium is essential in both biological and engineering processes

  • A second common approach is to run equilibrium molecular dynamics (MD) simulations and to analyze these assuming the validity of the inhomogeneous solution-diffusivity (ISD) model, where transport is modeled by position-dependent Brownian diffusion (diffusion profile D(z)) on a free energy landscape (profile F (z)), as governed by the Smoluchowski equation [15]

  • Path sampling methods seem to provide a natural solution to the permeation problem since they are designed to maintain the natural dynamics of the process as much as possible, while still allowing the sampling of events that happen on long timescales

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Summary

INTRODUCTION

Permeation of compounds through another medium is essential in both biological and engineering processes. A first standard approach to derive the permeability P from MD simulations is the counting method, which is based on measuring the rate of membrane transitions per unit of time and area [10,11,12]. Another standard approach is Bayesian analysis (BA) using the Smoluchowski equation, which assumes a position-dependent concentration profile as well as a position-dependent diffusion profile across the membrane [12,13,14,15,16,17]. The central assumption underlying milestoning is that the set of first hitting points, of the trajectories originating from one surface with a hypersurface left or right from it, is again distributed according to the equilibrium distribution.

Direct counting
Smoluchowski equation
Path sampling approaches
REPLICA EXCHANGE TRANSITION INTERFACE SAMPLING
PERMEABILITY FROM RETIS SIMULATIONS
Connecting permeability and rate
RC FOR PERMEATION WITH PERIODIC BOUNDARY CONDITIONS
NEW MC MOVES IN PATH SPACE
Target swap move
Mirror move
NUMERICAL RESULTS
One-dimensional system setup
Analysis of permeability
Two-channel membrane system setup
Two-channel membrane: analysis
VIII. CONCLUSION

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