Classical Molecular Dynamics with Mobile Protons

Lazaridis, Themis; Hummer, Gerhard

doi:10.1021/acs.jcim.7b00603

Cited by 19 publications

(23 citation statements)

References 116 publications

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“…This remains a valuable test system for the direct simulation of proton conduction, for example, via multistate EVB simulations 423 or by combining classical MD simulations with a stochastic model for proton hopping. 424 EVB simulations have also been used to explore proton transport through water-filled CNTs, 159 and yield similar results to ab initio MD simulations. Proton-conducting water wires are rather more complex in a number of proton-permeable ion channels for which structural data have recently become available, including the voltage-gated proton channel Hv1 and the low-pH-activated proton channel M2 from influenza A.…”

Section: Ion Channelsmentioning

confidence: 89%

Water in Nanopores and Biological Channels: A Molecular Simulation Perspective

2020

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This Review explores the dynamic behavior of water within nanopores and biological channels in lipid bilayer membranes. We focus on molecular simulation studies, alongside selected structural and other experimental investigations. Structures of biological nanopores and channels are reviewed, emphasizing those high-resolution crystal structures, which reveal water molecules within the transmembrane pores, which can be used to aid the interpretation of simulation studies. Different levels of molecular simulations of water within nanopores are described, with a focus on molecular dynamics (MD). In particular, models of water for MD simulations are discussed in detail to provide an evaluation of their use in simulations of water in nanopores. Simulation studies of the behavior of water in idealized models of nanopores have revealed aspects of the organization and dynamics of nanoconfined water, including wetting/dewetting in narrow hydrophobic nanopores. A survey of simulation studies in a range of nonbiological nanopores is presented, including carbon nanotubes, synthetic nanopores, model peptide nanopores, track-etched nanopores in polymer membranes, and hydroxylated and functionalized nanoporous silica. These reveal a complex relationship between pore size/geometry, the nature of the pore lining, and rates of water transport. Wider nanopores with hydrophobic linings favor water flow whereas narrower hydrophobic pores may show dewetting. Simulation studies over the past decade of the behavior of water in a range of biological nanopores are described, including porins and β-barrel protein nanopores, aquaporins and related polar solute pores, and a number of different classes of ion channels. Water is shown to play a key role in proton transport in biological channels and in hydrophobic gating of ion channels. An overall picture emerges, whereby the behavior of water in a nanopore may be predicted as a function of its hydrophobicity and radius. This informs our understanding of the functions of diverse channel structures and will aid the design of novel nanopores. Thus, our current level of understanding allows for the design of a nanopore which promotes wetting over dewetting or vice versa. However, to design a novel nanopore, which enables fast, selective, and gated flow of water de novo would remain challenging, suggesting a need for further detailed simulations alongside experimental evaluation of more complex nanopore systems.

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Section: Ion Channelsmentioning

confidence: 89%

Water in Nanopores and Biological Channels: A Molecular Simulation Perspective

2020

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“…However, the correct combination of protonation changes at each pH, as well as their coupling to the conformational change, remain unknown. This could potentially be improved by inclusion of a constant pH MD algorithm, although sampling sufficient phase space to capture all possible combinations of protonation states remains intractable. Second, the coarse‐grained space in which the study was predicated, has been reliant on observations from experimental structural determination, without knowledge of the relative importance, interdependencies, crystal‐packing artifacts or completeness of the set.…”

Section: Discussionmentioning

confidence: 99%

Simulating ion channel activation mechanisms using swarms of trajectories

Lev

Allen

2019

J Comput Chem

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Atomic-level studies of protein activity represent a significant challenge as a result of the complexity of conformational changes occurring on wide-ranging timescales, often greatly exceeding that of even the longest simulations. A prime example is the elucidation of protein allosteric mechanisms, where localized perturbations transmit throughout a large macromolecule to generate a response signal. For example, the conversion of chemical to electrical signals during synaptic neurotransmission in the brain is achieved by specialized membrane proteins called pentameric ligand-gated ion channels. Here, the binding of a neurotransmitter results in a global conformational change to open an ion-conducting pore across the nerve cell membrane. X-ray crystallography has produced static structures of the open and closed states of the proton-gated GLIC pentameric ligand-gated ion channel protein, allowing for atomistic simulations that can uncover changes related to activation. We discuss a range of enhanced sampling approaches that could be used to explore activation mechanisms. In particular, we describe recent application of an atomistic string method, based on Roux's "swarms of trajectories" approach, to elucidate the sequence and interdependence of conformational changes during activation. We illustrate how this can be combined with transition analysis and Brownian dynamics to extract thermodynamic and kinetic information, leading to understanding of what controls ion channel function.

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“… 67 Efficient constant pH algorithms are therefore likely to be of considerable interest. 68 , 69 A second challenge is to improve on tools to streamline the MD workflow. Automated topology builders (CgenFF, 70 , 71 SwissParam, 72 LigParGen, 73 PRODRG, 74 ATB, 75 Charmm-GUI, 76 H++, 77 among others) are playing an increasingly important role in the opportunity to rapidly set-up self-assembly simulations and screen larger groups of input molecules.…”

Section: Molecular Simulation Techniquesmentioning

confidence: 99%