title: Computational studies of transport in ion channels using metadynamics.
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.
authors.affiliation: Department of Medical Biotechnologies, University of Siena, viale Mario Bracci 16, I-53100 Siena, Italy.
authors.forename: Simone
authors.initials: S
authors.lastname: Furini
authors.affiliation: Department of Chemistry, King's College London, Britannia House, 7 Trinity Street, London SE1 1DB, UK; Chemistry Research Laboratory, Mansfield Road, University of Oxford, Oxford OX1 3TA, UK. Electronic address: carmen.domene@kcl.ac.uk.
authors.forename: Carmen
authors.initials: C
authors.lastname: Domene
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D001693:Biological Transport, Active; D004058:Diffusion; D015640:Ion Channel Gating; D007473:Ion Channels / Q000737:chemistry* / Q000648:ultrastructure*; D008051:Lipid Bilayers / Q000737:chemistry*; D008565:Membrane Proteins; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D011487:Protein Conformation
chemical_list: D007473:Ion Channels; D008051:Lipid Bilayers; D008565:Membrane Proteins
keywords: Enhanced sampling; Free energy; K(+) channels; Membrane proteins; Molecular dynamics; Na(+) channels; Simulations