Literature DB >> 27951634

Structure-Kinetic Relationships of Passive Membrane Permeation from Multiscale Modeling.

Callum J Dickson1, Viktor Hornak1, Robert A Pearlstein1, Jose S Duca1.   

Abstract

Passive membrane permeation of small molecules is essential to achieve the required absorption, distribution, metabolism, and excretion (ADME) profiles of drug candidates, in particular intestinal absorption and transport across the blood-brain barrier. Computational investigations of this process typically involve either building QSAR models or performing free energy calculations of the permeation event. Although insightful, these methods rarely bridge the gap between computation and experiment in a quantitative manner, and identifying structural insights to apply toward the design of compounds with improved permeability can be difficult. In this work, we combine molecular dynamics simulations capturing the kinetic steps of permeation at the atomistic level with a dynamic mechanistic model describing permeation at the in vitro level, finding a high level of agreement with experimental permeation measurements. Calculation of the kinetic rate constants determining each step in the permeation event allows derivation of structure-kinetic relationships of permeation. We use these relationships to probe the structural determinants of membrane permeation, finding that the desolvation/loss of hydrogen bonding required to leave the membrane partitioned position controls the membrane flip-flop rate, whereas membrane partitioning determines the rate of leaving the membrane.

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Year:  2016        PMID: 27951634     DOI: 10.1021/jacs.6b11215

Source DB:  PubMed          Journal:  J Am Chem Soc        ISSN: 0002-7863            Impact factor:   15.419


  28 in total

1.  Multiscale Simulations of Biological Membranes: The Challenge To Understand Biological Phenomena in a Living Substance.

Authors:  Giray Enkavi; Matti Javanainen; Waldemar Kulig; Tomasz Róg; Ilpo Vattulainen
Journal:  Chem Rev       Date:  2019-03-12       Impact factor: 60.622

Review 2.  Molecular Dynamics Simulations of Membrane Permeability.

Authors:  Richard M Venable; Andreas Krämer; Richard W Pastor
Journal:  Chem Rev       Date:  2019-02-12       Impact factor: 60.622

3.  Multiscale Methods in Drug Design Bridge Chemical and Biological Complexity in the Search for Cures.

Authors:  Rommie E Amaro; Adrian J Mulholland
Journal:  Nat Rev Chem       Date:  2018-04-11       Impact factor: 34.035

4.  Understanding Cell Penetration of Cyclic Peptides.

Authors:  Patrick G Dougherty; Ashweta Sahni; Dehua Pei
Journal:  Chem Rev       Date:  2019-05-14       Impact factor: 60.622

5.  Prediction of Membrane Permeation of Drug Molecules by Combining an Implicit Membrane Model with Machine Learning.

Authors:  Stephanie A Brocke; Alexandra Degen; Alexander D MacKerell; Bercem Dutagaci; Michael Feig
Journal:  J Chem Inf Model       Date:  2018-12-27       Impact factor: 4.956

6.  PerMM: A Web Tool and Database for Analysis of Passive Membrane Permeability and Translocation Pathways of Bioactive Molecules.

Authors:  Andrei L Lomize; Jacob M Hage; Kevin Schnitzer; Konstantin Golobokov; Mitchell B LaFaive; Alexander C Forsyth; Irina D Pogozheva
Journal:  J Chem Inf Model       Date:  2019-07-01       Impact factor: 4.956

7.  Physics-Based Method for Modeling Passive Membrane Permeability and Translocation Pathways of Bioactive Molecules.

Authors:  Andrei L Lomize; Irina D Pogozheva
Journal:  J Chem Inf Model       Date:  2019-07-01       Impact factor: 4.956

8.  Dynamic Protonation Dramatically Affects the Membrane Permeability of Drug-like Molecules.

Authors:  Zhi Yue; Chenghan Li; Gregory A Voth; Jessica M J Swanson
Journal:  J Am Chem Soc       Date:  2019-08-16       Impact factor: 15.419

9.  In Silico Prediction of the Binding, Folding, Insertion, and Overall Stability of Membrane-Active Peptides.

Authors:  Nicolas Frazee; Violeta Burns; Chitrak Gupta; Blake Mertz
Journal:  Methods Mol Biol       Date:  2021

10.  Thermodynamics and Mechanism of the Membrane Permeation of Hv1 Channel Blockers.

Authors:  Victoria T Lim; J Alfredo Freites; Francesco Tombola; Douglas J Tobias
Journal:  J Membr Biol       Date:  2020-11-16       Impact factor: 1.843

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