scholarly journals A heuristic derived from analysis of the ion channel structural proteome permits the rapid identification of hydrophobic gates

2019 ◽  
Vol 116 (28) ◽  
pp. 13989-13995 ◽  
Author(s):  
Shanlin Rao ◽  
Gianni Klesse ◽  
Phillip J. Stansfeld ◽  
Stephen J. Tucker ◽  
Mark S. P. Sansom
Keyword(s):  
Ion Channel ◽  
Conformational Changes ◽  
Rapid Identification ◽  
Ionic Flux ◽  
Simple Simulation ◽  
Transmembrane Pores ◽  
Ion Channel Proteins ◽  
Phase Water ◽  
Dynamics Simulations ◽  
Channel Structures

Ion channel proteins control ionic flux across biological membranes through conformational changes in their transmembrane pores. An exponentially increasing number of channel structures captured in different conformational states are now being determined; however, these newly resolved structures are commonly classified as either open or closed based solely on the physical dimensions of their pore, and it is now known that more accurate annotation of their conductive state requires additional assessment of the effect of pore hydrophobicity. A narrow hydrophobic gate region may disfavor liquid-phase water, leading to local dewetting, which will form an energetic barrier to water and ion permeation without steric occlusion of the pore. Here we quantify the combined influence of radius and hydrophobicity on pore dewetting by applying molecular dynamics simulations and machine learning to nearly 200 ion channel structures. This allows us to propose a simple simulation-free heuristic model that rapidly and accurately predicts the presence of hydrophobic gates. This not only enables the functional annotation of new channel structures as soon as they are determined, but also may facilitate the design of novel nanopores controlled by hydrophobic gates.

scholarly journals A Heuristic Derived from Analysis of the Ion Channel Structural Proteome Permits the Rapid Identification of Hydrophobic Gates

2018 ◽  
Author(s):  
Shanlin Rao ◽  
Gianni Klesse ◽  
Phillip J. Stansfeld ◽  
Stephen J. Tucker ◽  
Mark S.P. Sansom
Keyword(s):  
Machine Learning ◽  
Ion Channels ◽  
Ion Channel ◽  
Functional State ◽  
Conformational Changes ◽  
Rapid Identification ◽  
Ion Permeation ◽  
Ionic Flux ◽  
Easy Method ◽  
Channel Structures

AbstractIon channel proteins control ionic flux across biological membranes through conformational changes in their transmembrane pores. An exponentially increasing number of channel structures captured in different conformational states are now being determined. However, these newly-resolved structures are commonly classified as either open or closed based solely on the physical dimensions of their pore and it is now known that more accurate annotation of their conductive state requires an additional assessment of the effect of pore hydrophobicity. A narrow hydrophobic gate region may disfavour liquid-phase water, leading to local de-wetting which will form an energetic barrier to water and ion permeation without steric occlusion of the pore. Here we quantify the combined influence of radius and hydrophobicity on pore de-wetting by applying molecular dynamics simulations and machine learning to nearly 200 ion channel structures. This allows us to propose a simple simulation-free heuristic model that rapidly and accurately predicts the presence of hydrophobic gates. This not only enables the functional annotation of new channel structures as soon as they are determined, but may also facilitate the design of novel nanopores controlled by hydrophobic gates.Significance statementIon channels are nanoscale protein pores in cell membranes. An exponentially increasing number of structures for channels means that computational methods for predicting their functional state are needed. Hydrophobic gates in ion channels result in local de-wetting of pores which functionally closes them to water and ion permeation. We use simulations of water behaviour within nearly 200 different ion channel structures to explore how the radius and hydrophobicity of pores determine their hydration vs. de-wetting behaviour. Machine learning-assisted analysis of these simulations enables us to propose a simple model for this relationship. This allows us to present an easy method for the rapid prediction of the functional state of new channel structures as they emerge.

scholarly journals Hydrophobic Gating and Functional Annotation of Ion Channel Structures by Molecular Dynamics Simulations

2017 ◽  
Vol 112 (3) ◽  
pp. 417a
Author(s):  
Gianni Klesse ◽  
Jemma Trick ◽  
Sivapalan Chelvaniththilan ◽  
Prafulla Aryal ◽  
Jayne Wallace ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Ion Channel ◽  
Molecular Dynamics Simulations ◽  
Functional Annotation ◽  
Dynamics Simulations ◽  
Channel Structures

scholarly journals Computational Analysis of the Soluble Form of the Intracellular Chloride Ion Channel Protein CLIC1

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Peter M. Jones ◽  
Paul M. G. Curmi ◽  
Stella M. Valenzuela ◽  
Anthony M. George
Keyword(s):  
Ion Channel ◽  
Binding Site ◽  
Conformational Changes ◽  
Active Site ◽  
Bound States ◽  
Covalent Binding ◽  
Chloride Ion ◽  
Soluble Form ◽  
Active Site Cysteine ◽  
Dynamics Simulations

The chloride intracellular channel (CLIC) family of proteins has the remarkable property of maintaining both a soluble form and an integral membrane form acting as an ion channel. The soluble form is structurally related to the glutathione-S-transferase family, and CLIC can covalently bind glutathione via an active site cysteine. We report approximately 0.6 μs of molecular dynamics simulations, encompassing the three possible ligand-bound states of CLIC1, using the structure of GSH-bound human CLIC1. Noncovalently bound GSH was rapidly released from the protein, whereas the covalently ligand-bound protein remained close to the starting structure over 0.25 μs of simulation. In the unliganded state, conformational changes in the vicinity of the glutathione-binding site resulted in reduced reactivity of the active site thiol. Elastic network analysis indicated that the changes in the unliganded state are intrinsic to the protein architecture and likely represent functional transitions. Overall, our results are consistent with a model of CLIC function in which covalent binding of glutathione does not occur spontaneously but requires interaction with another protein to stabilise the GSH binding site and/or transfer of the ligand. The results do not indicate how CLIC1 undergoes a radical conformational change to form a transmembrane chloride channel but further elucidate the mechanism by which CLICs are redox controlled.

scholarly journals A Newly Available Tool for Functional Annotation of Ion Channel Structures Based on Molecular Dynamics Simulations

2018 ◽  
Vol 114 (3) ◽  
pp. 134a ◽  
Author(s):  
Gianni Klesse ◽  
Shanlin Rao ◽  
Phillip J. Stansfeld ◽  
Mark S.P. Sansom ◽  
Stephen J. Tucker
Keyword(s):  
Molecular Dynamics ◽  
Ion Channel ◽  
Molecular Dynamics Simulations ◽  
Functional Annotation ◽  
Dynamics Simulations ◽  
Channel Structures

scholarly journals Molecular insights from conformational ensembles via machine learning

2019 ◽  
Author(s):  
O. Fleetwood ◽  
M.A. Kasimova ◽  
A.M. Westerlund ◽  
L. Delemotte
Keyword(s):  
Machine Learning ◽  
Ligand Binding ◽  
Ion Channel ◽  
Conformational Changes ◽  
Molecular Simulations ◽  
Principal Component ◽  
Voltage Sensitivity ◽  
Learning Tools ◽  
Biomolecular Systems ◽  
Dynamics Simulations

ABSTRACTBiomolecular simulations are intrinsically high dimensional and generate noisy datasets of ever increasing size. Extracting important features in the data is crucial for understanding the biophysical properties of molecular processes, but remains a big challenge. Machine learning (ML) provides powerful dimensionality reduction tools. However, such methods are often criticized to resemble black boxes with limited human-interpretable insight.We use methods from supervised and unsupervised ML to efficiently create interpretable maps of important features from molecular simulations. We benchmark the performance of several methods including neural networks, random forests and principal component analysis, using a toy model with properties reminiscent of macromolecular behavior. We then analyze three diverse biological processes: conformational changes within the soluble protein calmodulin, ligand binding to a G protein-coupled receptor and activation of an ion channel voltage-sensor domain, unravelling features critical for signal transduction, ligand binding and voltage sensing. This work demonstrates the usefulness of ML in understanding biomolecular states and demystifying complex simulations.STATEMENT OF SIGNIFICANCEUnderstanding how biomolecules function requires resolving the ensemble of structures they visit. Molecular dynamics simulations compute these ensembles and generate large amounts of data that can be noisy and need to be condensed for human interpretation. Machine learning methods are designed to process large amounts of data, but are often criticized for their black-box nature and have historically been modestly used in the analysis of biomolecular systems. We demonstrate how machine learning tools can provide an interpretable overview of important features in a simulation dataset. We develop a protocol to quickly perform data-driven analysis of molecular simulations. This protocol is applied to identify the molecular basis of ligand binding to a receptor and of voltage sensitivity of an ion channel.

scholarly journals CHAP: A versatile tool for the structural and functional annotation of ion channel pores

2019 ◽  
Author(s):  
Gianni Klesse ◽  
Shanlin Rao ◽  
Mark S.P. Sansom ◽  
Stephen J. Tucker
Keyword(s):  
Ion Channel ◽  
Functional Annotation ◽  
Pore Radius ◽  
Computational Tool ◽  
Ion Flow ◽  
Considerable Evidence ◽  
The Past ◽  
Versatile Tool ◽  
Dynamics Simulations ◽  
Channel Structures

AbstractThe regulation of ion channel and transporter function requires the modulation of energetic barriers or ‘gates’ within their transmembrane pathways. However, despite the ever-increasing number of available structures, our understanding of these barriers is often simply determined from calculating the physical dimensions of the pore. Such approaches (e.g. the HOLE program) have worked very well in the past, but there is now considerable evidence that the unusual behaviour of water within the narrow hydrophobic spaces found within many ion channel pores can also produce energetic barriers to ion conduction without requiring physical occlusion of the permeation pathway. Several different classes of ion channels have now been shown to exploit this principle of ‘hydrophobic gating’ to regulate ion flow. However, measurement of pore radius alone is unable to identify such barriers and new tools are required for more accurate functional annotation of an exponentially increasing number of ion channel structures. We have previously shown how molecular dynamics simulations of water behaviour can be used as a proxy to accurately predict hydrophobic gates. Here we now present a new and highly versatile computational tool, the Channel Annotation Package (CHAP) that implements this methodology to predict the conductive status of new ion channel structures.

Molecular Basis of Glucose Transport Mechanism in Plants

2019 ◽  
Author(s):  
Balaji Selvam ◽  
Ya-Chi Yu ◽  
Liqing Chen ◽  
Diwakar Shukla
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulations ◽  
Conformational Changes ◽  
Transport Mechanism ◽  
Conformational Dynamics ◽  
Site Directed Mutagenesis ◽  
Free Energy Barrier ◽  
Transport Cycle ◽  
Dynamics Simulations

<p>The SWEET family belongs to a class of transporters in plants that undergoes large conformational changes to facilitate transport of sugar molecules across the cell membrane. However, the structures of their functionally relevant conformational states in the transport cycle have not been reported. In this study, we have characterized the conformational dynamics and complete transport cycle of glucose in OsSWEET2b transporter using extensive molecular dynamics simulations. Using Markov state models, we estimated the free energy barrier associated with different states as well as 1 for the glucose the transport mechanism. SWEETs undergoes structural transition to outward-facing (OF), Occluded (OC) and inward-facing (IF) and strongly support alternate access transport mechanism. The glucose diffuses freely from outside to inside the cell without causing major conformational changes which means that the conformations of glucose unbound and bound snapshots are exactly same for OF, OC and IF states. We identified a network of hydrophobic core residues at the center of the transporter that restricts the glucose entry to the cytoplasmic side and act as an intracellular hydrophobic gate. The mechanistic predictions from molecular dynamics simulations are validated using site-directed mutagenesis experiments. Our simulation also revealed hourglass like intermediate states making the pore radius narrower at the center. This work provides new fundamental insights into how substrate-transporter interactions actively change the free energy landscape of the transport cycle to facilitate enhanced transport activity.</p>

AMPA and Kainate Receptors

2020 ◽  
Author(s):  
G. Brent Dawe ◽  
Patricia M. G. E. Brown ◽  
Derek Bowie
Keyword(s):  
Ion Channel ◽  
Glutamate Receptor ◽  
Single Channel ◽  
Channel Gating ◽  
Regulatory Proteins ◽  
Kainate Receptors ◽  
Mammalian Brain ◽  
Receptor Field ◽  
Neuronal Excitation ◽  
Ion Channel Proteins

α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and kainate-type glutamate receptors (AMPARs and KARs) are dynamic ion channel proteins that govern neuronal excitation and signal transduction in the mammalian brain. The four AMPAR and five KAR subunits can heteromerize with other subfamily members to create several combinations of tetrameric channels with unique physiological and pharmacological properties. While both receptor classes are noted for their rapid, millisecond-scale channel gating in response to agonist binding, the intricate structural rearrangements underlying their function have only recently been elucidated. This chapter begins with a review of AMPAR and KAR nomenclature, topology, and rules of assembly. Subsequently, receptor gating properties are outlined for both single-channel and synaptic contexts. The structural biology of AMPAR and KAR proteins is also discussed at length, with particular focus on the ligand-binding domain, where allosteric regulation and alternative splicing work together to dictate gating behavior. Toward the end of the chapter there is an overview of several classes of auxiliary subunits, notably transmembrane AMPAR regulatory proteins and Neto proteins, which enhance native AMPAR and KAR expression and channel gating, respectively. Whether bringing an ion channel novice up to speed with glutamate receptor theory and terminology or providing a refresher for more seasoned biophysicists, there is much to appreciate in this summation of work from the glutamate receptor field.

scholarly journals Studies of Conformational Changes of Tubulin Induced by Interaction with Kinesin Using Atomistic Molecular Dynamics Simulations

2021 ◽  
Vol 22 (13) ◽  
pp. 6709
Author(s):  
Xiao-Xuan Shi ◽  
Peng-Ye Wang ◽  
Hong Chen ◽  
Ping Xie
Keyword(s):  
Molecular Dynamics ◽  
High Resolution ◽  
Binding Energy ◽  
Molecular Dynamics Simulations ◽  
Conformational Changes ◽  
Weak Interactions ◽  
Molecular Motor ◽  
Structural Data ◽  
Calculated Binding Energy ◽  
Dynamics Simulations

The transition between strong and weak interactions of the kinesin head with the microtubule, which is regulated by the change of the nucleotide state of the head, is indispensable for the processive motion of the kinesin molecular motor on the microtubule. Here, using all-atom molecular dynamics simulations, the interactions between the kinesin head and tubulin are studied on the basis of the available high-resolution structural data. We found that the strong interaction can induce rapid large conformational changes of the tubulin, whereas the weak interaction cannot. Furthermore, we found that the large conformational changes of the tubulin have a significant effect on the interaction of the tubulin with the head in the weak-microtubule-binding ADP state. The calculated binding energy of the ADP-bound head to the tubulin with the large conformational changes is only about half that of the tubulin without the conformational changes.

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