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Simulation-Based Approaches for Determining Membrane Permeability of Small Compounds

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Department of Chemistry and Biochemistry, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093-0340, United States
Nanotechnology Innovation Center of Kansas State, Institute of Computational Comparative Medicine, Department of Anatomy and Physiology, Kansas State University, P-213 Mosier Hall, Manhattan, Kansas 66506, United States
§ School of Physics, Georgia Institute of Technology, 837 State Street, Atlanta, Georgia 30332, United States
Department of Physics, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
Department of Chemistry, Memorial University of Newfoundland, St. John’s, NL A1B 3X7 Canada
# Laboratoire International Associé Centre National de la Recherche Scientifique and University of Illinois at Urbana−Champaign, UMR n° 7565, Université de Lorraine, B.P. 70239, 54506 Vandœuvre-lès-Nancy, France
Beckman Institute for Advanced Science and Technology and Department of Physics, University of Illinois at Urbana−Champaign, 405 North Mathews, Urbana, Illinois 61801, United States
Shenzhen Research Institute, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
School of Chemistry and Biochemistry, Georgia Institute of Technology, 901 Atlantic Drive NW, Atlanta, Georgia 30332, United States
*E-mail: [email protected] (J. Comer).
*E-mail: [email protected] (R.E. Amaro).
*E-mail: [email protected] (C. Chipot).
*E-mail: [email protected] (Y. Wang).
*E-mail: [email protected] (J.C. Gumbart).
Cite this: J. Chem. Inf. Model. 2016, 56, 4, 721–733
Publication Date (Web):April 4, 2016
https://doi.org/10.1021/acs.jcim.6b00022
Copyright © 2016 American Chemical Society

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    Abstract

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    Predicting the rate of nonfacilitated permeation of solutes across lipid bilayers is important to drug design, toxicology, and signaling. These rates can be estimated using molecular dynamics simulations combined with the inhomogeneous solubility-diffusion model, which requires calculation of the potential of mean force and position-dependent diffusivity of the solute along the transmembrane axis. In this paper, we assess the efficiency and accuracy of several methods for the calculation of the permeability of a model DMPC bilayer to urea, benzoic acid, and codeine. We compare umbrella sampling, replica exchange umbrella sampling, adaptive biasing force, and multiple-walker adaptive biasing force for the calculation of the transmembrane PMF. No definitive advantage for any of these methods in their ability to predict the membrane permeability coefficient Pm was found, provided that a sufficiently long equilibration is performed. For diffusivities, a Bayesian inference method was compared to a generalized Langevin method, both being sensitive to chosen parameters and the slow relaxation of membrane defects. Agreement within 1.5 log units of the computed Pm with experiment is found for all permeants and methods. Remaining discrepancies can likely be attributed to limitations of the force field as well as slowly relaxing collective movements within the lipid environment. Numerical calculations based on model profiles show that Pm can be reliably estimated from only a few data points, leading to recommendations for calculating Pm from simulations.

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    • Theoretical details of application of the Bayesian scheme to MD and analysis of membrane structure from MD simulations. (PDF)

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