Literature DB >> 28847523

Computational membrane biophysics: From ion channel interactions with drugs to cellular function.

Williams E Miranda1, Van A Ngo1, Laura L Perissinotti1, Sergei Yu Noskov2.   

Abstract

The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Integral membrane proteins; Kinetic cell models; Markov State Models; Molecular dynamics simulations; Protein-ligand interactions

Mesh:

Substances:

Year:  2017        PMID: 28847523      PMCID: PMC5764198          DOI: 10.1016/j.bbapap.2017.08.008

Source DB:  PubMed          Journal:  Biochim Biophys Acta Proteins Proteom        ISSN: 1570-9639            Impact factor:   3.036


  128 in total

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3.  A human ether-á-go-go-related (hERG) ion channel atomistic model generated by long supercomputer molecular dynamics simulations and its use in predicting drug cardiotoxicity.

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4.  Application of Markov State Models to simulate long timescale dynamics of biological macromolecules.

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Journal:  Adv Exp Med Biol       Date:  2014       Impact factor: 2.622

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7.  Convergence and error estimation in free energy calculations using the weighted histogram analysis method.

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Journal:  J Comput Chem       Date:  2011-11-23       Impact factor: 3.376

8.  Improved patch-clamp techniques for high-resolution current recording from cells and cell-free membrane patches.

Authors:  O P Hamill; A Marty; E Neher; B Sakmann; F J Sigworth
Journal:  Pflugers Arch       Date:  1981-08       Impact factor: 3.657

9.  Molecular view of cholesterol flip-flop and chemical potential in different membrane environments.

Authors:  W F Drew Bennett; Justin L MacCallum; Marlon J Hinner; Siewert J Marrink; D Peter Tieleman
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10.  Accurate Estimation of Protein Folding and Unfolding Times: Beyond Markov State Models.

Authors:  Ernesto Suárez; Joshua L Adelman; Daniel M Zuckerman
Journal:  J Chem Theory Comput       Date:  2016-07-11       Impact factor: 6.006

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Review 2.  Permeating disciplines: Overcoming barriers between molecular simulations and classical structure-function approaches in biological ion transport.

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Journal:  Biochim Biophys Acta Biomembr       Date:  2017-12-16       Impact factor: 4.019

Review 3.  Biophysical Psychiatry-How Computational Neuroscience Can Help to Understand the Complex Mechanisms of Mental Disorders.

Authors:  Tuomo Mäki-Marttunen; Tobias Kaufmann; Torbjørn Elvsåshagen; Anna Devor; Srdjan Djurovic; Lars T Westlye; Marja-Leena Linne; Marcella Rietschel; Dirk Schubert; Stefan Borgwardt; Magdalena Efrim-Budisteanu; Francesco Bettella; Geir Halnes; Espen Hagen; Solveig Næss; Torbjørn V Ness; Torgeir Moberget; Christoph Metzner; Andrew G Edwards; Marianne Fyhn; Anders M Dale; Gaute T Einevoll; Ole A Andreassen
Journal:  Front Psychiatry       Date:  2019-08-06       Impact factor: 4.157

  3 in total

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