Literature DB >> 26574394

Bias-Exchange Metadynamics Simulations: An Efficient Strategy for the Analysis of Conduction and Selectivity in Ion Channels.

Carmen Domene1,2, Paolo Barbini3, Simone Furini3.   

Abstract

Conduction through ion channels possesses two interesting features: (i) different ionic species are selected with high-selectivity and (ii) ions travel across the channel with rates approaching free-diffusion. Molecular dynamics simulations have the potential to reveal how these processes take place at the atomic level. However, analysis of conduction and selectivity at atomistic detail is still hampered by the short time scales accessible by computer simulations. Several algorithms have been developed to "accelerate" sampling along the slow degrees of freedom of the process under study and thus to probe longer time scales. In these algorithms, the slow degrees of freedom need to be defined in advance, which is a well-known shortcoming. In the particular case of ion conduction, preliminary assumptions about the number and type of ions participating in the permeation process need to be made. In this study, a novel approach for the analysis of conduction and selectivity based on bias-exchange metadynamics simulations was tested. This approach was compared with umbrella sampling simulations, using a model of a Na(+)-selective channel. Analogous conclusions resulted from both techniques, but the computational cost of bias-exchange simulations was lower. In addition, with bias-exchange metadynamics it was possible to calculate free energy profiles in the presence of a variable number and type of permeating ions. This approach might facilitate the definition of the set of collective variables required to analyze conduction and selectivity in ion channels.

Mesh:

Substances:

Year:  2015        PMID: 26574394     DOI: 10.1021/ct501053x

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  10 in total

1.  Ion-triggered selectivity in bacterial sodium channels.

Authors:  Simone Furini; Carmen Domene
Journal:  Proc Natl Acad Sci U S A       Date:  2018-05-07       Impact factor: 11.205

2.  IR Spectroscopy Can Reveal the Mechanism of K+ Transport in Ion Channels.

Authors:  Steven E Strong; Nicholas J Hestand; Alexei A Kananenka; Martin T Zanni; J L Skinner
Journal:  Biophys J       Date:  2019-11-20       Impact factor: 4.033

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.  Nanobody Paratope Ensembles in Solution Characterized by MD Simulations and NMR.

Authors:  Monica L Fernández-Quintero; Eugene F DeRose; Scott A Gabel; Geoffrey A Mueller; Klaus R Liedl
Journal:  Int J Mol Sci       Date:  2022-05-12       Impact factor: 6.208

5.  Molecular Dynamics of Ion Conduction through the Selectivity Filter of the NaVAb Sodium Channel.

Authors:  Karen M Callahan; Benoît Roux
Journal:  J Phys Chem B       Date:  2018-10-29       Impact factor: 2.991

6.  Energetics of Ion Permeation in an Open-Activated TRPV1 Channel.

Authors:  Christian Jorgensen; Simone Furini; Carmen Domene
Journal:  Biophys J       Date:  2016-09-20       Impact factor: 4.033

7.  A noncanonical binding site of linezolid revealed via molecular dynamics simulations.

Authors:  G I Makarov; T M Makarova
Journal:  J Comput Aided Mol Des       Date:  2019-12-12       Impact factor: 3.686

8.  Determinants of conductance of a bacterial voltage-gated sodium channel.

Authors:  Ada Y Chen; Bernard R Brooks; Ana Damjanovic
Journal:  Biophys J       Date:  2021-06-30       Impact factor: 3.699

Review 9.  Binding Mechanisms of Intrinsically Disordered Proteins: Theory, Simulation, and Experiment.

Authors:  Luca Mollica; Luiza M Bessa; Xavier Hanoulle; Malene Ringkjøbing Jensen; Martin Blackledge; Robert Schneider
Journal:  Front Mol Biosci       Date:  2016-09-09

10.  Ion Permeation Mechanism in Epithelial Calcium Channel TRVP6.

Authors:  Serzhan Sakipov; Alexander I Sobolevsky; Maria G Kurnikova
Journal:  Sci Rep       Date:  2018-04-09       Impact factor: 4.379

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.