Literature DB >> 26891818

Computational studies of transport in ion channels using metadynamics.

Simone Furini1, Carmen Domene2.   

Abstract

Molecular dynamics simulations have played a fundamental role in numerous fields of science by providing insights into the structure and dynamics of complex systems at the atomistic level. However, exhaustive sampling by standard molecular dynamics is in most cases computationally prohibitive, and the time scales accessible remain significantly shorter than many biological processes of interest. In particular, in the study of ion channels, realistic models to describe permeation and gating require accounting for large numbers of particles and accurate interaction potentials, which severely limits the length of the simulations. To overcome such limitations, several advanced methods have been proposed among which is metadynamics. In this algorithm, an external bias potential to accelerate sampling along selected collective variables is introduced. This bias potential discourages visiting regions of the configurational space already explored. In addition, the bias potential provides an estimate of the free energy as a function of the collective variables chosen once the simulation has converged. In this review, recent contributions of metadynamics to the field of ion channels are discussed, including how metadynamics has been used to search for transition states, predict permeation pathways, treat conformational flexibility that underlies the coupling between gating and permeation, or compute free energy of permeation profiles. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.
Copyright © 2016 Elsevier B.V. All rights reserved.

Keywords:  Enhanced sampling; Free energy; K(+) channels; Membrane proteins; Molecular dynamics; Na(+) channels; Simulations

Mesh:

Substances:

Year:  2016        PMID: 26891818     DOI: 10.1016/j.bbamem.2016.02.015

Source DB:  PubMed          Journal:  Biochim Biophys Acta        ISSN: 0006-3002


  8 in total

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2.  Caver Web 1.0: identification of tunnels and channels in proteins and analysis of ligand transport.

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3.  Computational methods and theory for ion channel research.

Authors:  C Guardiani; F Cecconi; L Chiodo; G Cottone; P Malgaretti; L Maragliano; M L Barabash; G Camisasca; M Ceccarelli; B Corry; R Roth; A Giacomello; B Roux
Journal:  Adv Phys X       Date:  2022

4.  Combining theoretical and experimental data to decipher CFTR 3D structures and functions.

Authors:  Brice Hoffmann; Ahmad Elbahnsi; Pierre Lehn; Jean-Luc Décout; Fabio Pietrucci; Jean-Paul Mornon; Isabelle Callebaut
Journal:  Cell Mol Life Sci       Date:  2018-05-19       Impact factor: 9.261

5.  How Do Short Chain Nonionic Detergents Destabilize G-Protein-Coupled Receptors?

Authors:  Sangbae Lee; Allen Mao; Supriyo Bhattacharya; Nathan Robertson; Reinhard Grisshammer; Christopher G Tate; Nagarajan Vaidehi
Journal:  J Am Chem Soc       Date:  2016-11-15       Impact factor: 15.419

6.  Ion Selectivity in the ENaC/DEG Family: A Systematic Review with Supporting Analysis.

Authors:  Cédric Vallée; Brendan Howlin; Rebecca Lewis
Journal:  Int J Mol Sci       Date:  2021-10-12       Impact factor: 5.923

7.  Combined computational and experimental studies of molecular interactions of albuterol sulfate with bovine serum albumin for pulmonary drug nanoparticles.

Authors:  Shao-Hui Lin; Wei Cui; Gui-Ling Wang; Shuai Meng; Ying-Chun Liu; Hong-Wei Jin; Liang-Ren Zhang; Ying Xie
Journal:  Drug Des Devel Ther       Date:  2016-09-15       Impact factor: 4.162

8.  Thermodynamics and Kinetics of Ion Permeation in Wild-Type and Mutated Open Active Conformation of the Human α7 Nicotinic Receptor.

Authors:  Grazia Cottone; Letizia Chiodo; Luca Maragliano
Journal:  J Chem Inf Model       Date:  2020-08-31       Impact factor: 4.956

  8 in total

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