Computational studies of transport in ion channels using metadynamics

Challenges of Protein-Protein Docking of the Membrane Proteins

Despite the recent advances in the determination of high-resolution membrane protein (MP) structures, the structural and functional characterization of MPs remains extremely challenging, mainly due to the hydrophobic nature, low abundance, poor expression, purification, and crystallization difficulties associated with MPs. Whereby the major challenges/hurdles for MP structure determination are associated with the expression, purification, and crystallization procedures. Although there have been significant advances in the experimental determination of MP structures, only a limited number of MP structures (approximately less than 1% of all) are available in the Protein Data Bank (PDB). Therefore, the structures of a large number of MPs still remain unresolved, which leads to the availability of widely unplumbed structural and functional information related to MPs. As a result, recent developments in the drug discovery realm and the significant biological contemplation have led to the development of several novel, low-cost, and time-efficient computational methods that overcome the limitations of experimental approaches, supplement experiments, and provide alternatives for the characterization of MPs. Whereby the fine tuning and optimizations of these computational approaches remains an ongoing endeavor.Computational methods offer a potential way for the elucidation of structural features and the augmentation of currently available MP information. However, the use of computational modeling can be extremely challenging for MPs mainly due to insufficient knowledge of (or gaps in) atomic structures of MPs. Despite the availability of numerous in silico methods for 3D structure determination the applicability of these methods to MPs remains relatively low since all methods are not well-suited or adequate for MPs. However, sophisticated methods for MP structure predictions are constantly being developed and updated to integrate the modifications required for MPs. Currently, different computational methods for (1) MP structure prediction, (2) stability analysis of MPs through molecular dynamics simulations, (3) modeling of MP complexes through docking, (4) prediction of interactions between MPs, and (5) MP interactions with its soluble partner are extensively used. Towards this end, MP docking is widely used. It is notable that the MP docking methods yet few in number might show greater potential in terms of filling the knowledge gap. In this chapter, MP docking methods and associated challenges have been reviewed to improve the applicability, accuracy, and the ability to model macromolecular complexes.

Recent Advances in Computer-Aided Structure-Based Drug Design on Ion Channels

Ion channels play important roles in fundamental biological processes, such as electric signaling in cells, muscle contraction, hormone secretion, and regulation of the immune response. Targeting ion channels with drugs represents a treatment option for neurological and cardiovascular diseases, muscular degradation disorders, and pathologies related to disturbed pain sensation. While there are more than 300 different ion channels in the human organism, drugs have been developed only for some of them and currently available drugs lack selectivity. Computational approaches are an indispensable tool for drug discovery and can speed up, especially, the early development stages of lead identification and optimization. The number of molecular structures of ion channels has considerably increased over the last ten years, providing new opportunities for structure-based drug development. This review summarizes important knowledge about ion channel classification, structure, mechanisms, and pathology with the main focus on recent developments in the field of computer-aided, structure-based drug design on ion channels. We highlight studies that link structural data with modeling and chemoinformatic approaches for the identification and characterization of new molecules targeting ion channels. These approaches hold great potential to advance research on ion channel drugs in the future.

Computational methods and theory for ion channel research

Ion channels are fundamental biological devices that act as gates in order to ensure selective ion transport across cellular membranes; their operation constitutes the molecular mechanism through which basic biological functions, such as nerve signal transmission and muscle contraction, are carried out. Here, we review recent results in the field of computational research on ion channels, covering theoretical advances, state-of-the-art simulation approaches, and frontline modeling techniques. We also report on few selected applications of continuum and atomistic methods to characterize the mechanisms of permeation, selectivity, and gating in biological and model channels.

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

The Epithelial Sodium Channel/Degenerin (ENaC/DEG) family is a superfamily of sodium-selective channels that play diverse and important physiological roles in a wide variety of animal species. Despite their differences, they share a high homology in the pore region in which the ion discrimination takes place. Although ion selectivity has been studied for decades, the mechanisms underlying this selectivity for trimeric channels, and particularly for the ENaC/DEG family, are still poorly understood. This systematic review follows PRISMA guidelines and aims to determine the main components that govern ion selectivity in the ENaC/DEG family. In total, 27 papers from three online databases were included according to specific exclusion and inclusion criteria. It was found that the G/SxS selectivity filter (glycine/serine, non-conserved residue, serine) and other well conserved residues play a crucial role in ion selectivity. Depending on the ion type, residues with different properties are involved in ion permeability. For lithium against sodium, aromatic residues upstream of the selectivity filter seem to be important, whereas for sodium against potassium, negatively charged residues downstream of the selectivity filter seem to be important. This review provides new perspectives for further studies to unravel the mechanisms of ion selectivity.

The key role of the central cavity in sodium transport through ligand-gated two-pore channels

Subcellular and organellar mechanisms have manifested a prominent importance for a broad variety of processes that maintain cellular life at its most basic level. Mammalian two-pore channels (TPCs) appear to be cornerstones of these processes in endo-lysosomes by controlling delicate ion-concentrations in their interiors. With evolutionary remarkable architecture and one-of-a-kind selectivity filter, TPCs are an extremely attractive topic per se. In the light of the current COVID-19 pandemic, hTPC2 emerges to be more than attractive. As a key regulator of the endocytosis pathway, it is potentially essential for diverse viral infections in humans, as demonstrated. Here, by means of multiscale molecular simulations, we propose a model of sodium transport from the lumen to the cytosol where the central cavity works as a reservoir. Since the inhibition of hTPC2 is proven to stop SARS-CoV2 in vitro, shedding light on the hTPC2 function and mechanism is the first step towards the selection of potential inhibiting candidates.

Ion Conduction Mechanism as a Fingerprint of Potassium Channels

K⁺-channels are membrane proteins that regulate the selective conduction of potassium ions across cell membranes. Although the atomic mechanisms of K⁺ permeation have been extensively investigated, previous work focused on characterizing the selectivity and occupancy of the binding sites, the role of water molecules in the conduction process, or the identification of the minimum energy pathways enabling permeation. Here, we exploit molecular dynamics simulations and the analytical power of Markov state models to perform a comparative study of ion conduction in three distinct channel models. Significant differences emerged in terms of permeation mechanisms and binding site occupancy by potassium ions and/or water molecules from 100 μs cumulative trajectories. We found that, at odds with the current paradigm, each system displays a characteristic permeation mechanism, and thus, there is not a unique way by which potassium ions move through K⁺-channels. The high functional diversity of K⁺-channels can be attributed in part to the differences in conduction features that have emerged from this work. This study provides crucial information and further inspiration for wet-lab chemists designing new synthetic strategies to produce versatile artificial ion channels that emulate membrane transport for their applications in diagnosis, sensors, the next generation of water treatment technologies, etc., as the ability of synthetic channels to transport molecular ions across a bilayer in a controlled way is usually governed through the choice of metal ions, their oxidation states, or their coordination geometries.

Electrophysiological Properties from Computations at a Single Voltage: Testing Theory with Stochastic Simulations

We use stochastic simulations to investigate the performance of two recently developed methods for calculating the free energy profiles of ion channels and their electrophysiological properties, such as current–voltage dependence and reversal potential, from molecular dynamics simulations at a single applied voltage. These methods require neither knowledge of the diffusivity nor simulations at multiple voltages, which greatly reduces the computational effort required to probe the electrophysiological properties of ion channels. They can be used to determine the free energy profiles from either forward or backward one-sided properties of ions in the channel, such as ion fluxes, density profiles, committor probabilities, or from their two-sided combination. By generating large sets of stochastic trajectories, which are individually designed to mimic the molecular dynamics crossing statistics of models of channels of trichotoxin, p7 from hepatitis C and a bacterial homolog of the pentameric ligand-gated ion channel, GLIC, we find that the free energy profiles obtained from stochastic simulations corresponding to molecular dynamics simulations of even a modest length are burdened with statistical errors of only 0.3 kcal/mol. Even with many crossing events, applying two-sided formulas substantially reduces statistical errors compared to one-sided formulas. With a properly chosen reference voltage, the current–voltage curves can be reproduced with good accuracy from simulations at a single voltage in a range extending for over 200 mV. If possible, the reference voltages should be chosen not simply to drive a large current in one direction, but to observe crossing events in both directions.

Voltage-Dependent Transport of Neutral Solutes through Nanopores: A Molecular View

The permeation of (neutral) molecules through nanopores in the presence of external voltages depends on several factors including pore electrostatics, electrophoretic force, and electro-osmotic drag. In earlier single-channel electrophysiology experiments, voltage-dependent asymmetric transport of neutral α-cyclodextrin (α-CD) molecules through the biological nanopore ΔCymA was observed. The voltage-dependent ion-associated flow of water, the so-called electro-osmotic flow, has been suggested to be the key factor behind the observed asymmetric behavior. The influence of pore electrostatics and electrophoretic force and their interplay with the electro-osmotic drag with varying buffers and voltages has not yet been analyzed at the molecular level. Hence, the detailed physical mechanism behind this intriguing permeation process is in part still unclear. In the present study, we have performed 36 μs all-atom free energy calculations by combining applied-field molecular dynamics simulations with metadynamics techniques. The influence of several ionic conditions as well as external voltages on the permeation of α-CD molecules across the ΔCymA pore has been investigated. To decipher the thermodynamic and kinetic details, the lowest energy paths and the permeation times for α-CD translocation have been estimated. In the presence of KCl or MgCl₂ salts, the charge of the cations is found to control the direction and magnitude of the electro-osmotic flow, which in turn strongly affects α-CD permeation. Overall, the present findings significantly improve the fundamental understanding of the voltage-dependent transport of neutral solutes across nanopores.

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

Molecular studies of human pentameric ligand-gated ion channels (LGICs) expressed in neurons and at neuromuscular junctions are of utmost importance in the development of therapeutic strategies for neurological disorders. We focus here on the nicotinic acetylcholine receptor nAChR-α7, a homopentameric channel widely expressed in the human brain, with a proven role in a wide spectrum of disorders including schizophrenia and Alzheimer’s disease. By exploiting an all-atom structural model of the full (transmembrane and extracellular) protein in the open, agonist-bound conformation we recently developed, we evaluate the free energy and the mean first passage time of single-ion permeation using molecular dynamics simulations and the milestoning method with Voronoi tessellation. The results for the wild-type channel provide the first available mapping of the potential of mean force in the full-length α7 nAChR, reveal its expected cationic nature, and are in good agreement with simulation data for other channels of the LGIC family and with experimental data on nAChRs. We then investigate the role of a specific mutation directly related to ion selectivity in LGICs, the E-1′ → A-1′ substitution at the cytoplasmatic selectivity filter. We find that the mutation strongly affects sodium and chloride permeation in opposite directions, leading to a complete inversion of selectivity, at variance with the limited experimental results available that classify this mutant as cationic. We thus provide structural determinants for the observed cationic-to-anionic inversion, revealing a key role of the protonation state of residue rings far from the mutation, in the proximity of the hydrophobic channel gate.

Quantum Mechanical Coherence of K+ Ion Wave Packets Increases Conduction in the KcsA Ion Channel

We simulate the transmission of K+ ions through the KcsA potassium ion channel filter region at physiological temperatures, employing classical molecular dynamics (MD) at the atomic scale together with a quantum mechanical version of MD simulation (QMD), treating single ions as quantum wave packets. We provide a direct comparison between both concepts, embedding the simulations into identical force fields and thermal fluctuations. The quantum simulations permit the estimation of coherence times and wave packet dispersions of a K+ ion over a range of 0.5 nm (a range that covers almost 50% of the filter domains longitudinal extension). We find that this observed extension of particle delocalization changes the mean orientation of the coordinating carbonyl oxygen atoms significantly, transiently suppressing their ‘caging action’ responsible for selective ion coordination. Compared to classical MD simulations, this particular quantum effect allows the K+ ions to ‘escape’ more easily from temporary binding sites provided by the surrounding filter atoms. To further elucidate the role of this observation for ion conduction rates, we compare the temporal pattern of single conduction events between classical MD and quantum QMD simulations at a femto-sec time scale. A finding from both approaches is that ion permeation follows a very irregular time pattern, involving flushes of permeation interrupted by non-conductive time intervals. However, as compared with classical behavior, the QMD simulation shortens non-conductive time by more than a half. As a consequence, and given the same force-fields, the QMD-simulated ion current appears to be considerably stronger as compared with the classical current. To bring this result in line with experimentally observed ion currents and the predictions based on Nernst–Planck theories, the conclusion is that a transient short time quantum behavior of permeating ions can successfully compromise high conduction rates with ion selectivity in the filter of channel proteins.

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

Caver Web 1.0 is a web server for comprehensive analysis of protein tunnels and channels, and study of the ligands’ transport through these transport pathways. Caver Web is the first interactive tool allowing both the analyses within a single graphical user interface. The server is built on top of the abundantly used tunnel detection tool Caver 3.02 and CaverDock 1.0 enabling the study of the ligand transport. The program is easy-to-use as the only required inputs are a protein structure for a tunnel identification and a list of ligands for the transport analysis. The automated guidance procedures assist the users to set up the calculation in a way to obtain biologically relevant results. The identified tunnels, their properties, energy profiles and trajectories for ligands’ passages can be calculated and visualized. The tool is very fast (2–20 min per job) and is applicable even for virtual screening purposes. Its simple setup and comprehensive graphical user interface make the tool accessible for a broad scientific community. The server is freely available at https://loschmidt.chemi.muni.cz/caverweb.

Exploration of Free Energy Surfaces Across a Membrane Channel Using Metadynamics and Umbrella Sampling

To reach their site of action, it is essential for antibiotic molecules to cross the bacterial outer membrane. The progress of enhanced sampling techniques in molecular dynamics simulations enables us to understand these translocations at an atomic level. To this end, calculations of free energy surfaces for these permeation processes are of key importance. Herein, we investigate the translocation of a variety of anionic solutes through the outer membrane pore OprO of the Gram-negative bacterium Pseudomonas aeruginosa using the metadynamics and umbrella sampling techniques at the all-atom level. Free energy calculations have been performed employing these two distinct methods in order to illustrate the difference in computed free energies, if any. The investigated solutes range from a single atomic chloride ion over a multiatomic monophosphate ion to a more bulky fosmidomycin antibiotic. The role of complexity of the permeating solutes in estimating accurate free energy profiles is demonstrated by performing extensive convergence analysis. For simple monatomic ions, good agreement between the well-tempered metadynamics and the umbrella sampling approaches is achieved, while for the permeation of the monophosphate ion differences start to appear. In the case of larger molecules such as fosmidomycin it is a tough challenge to achieve converged free energy profiles. This issue is mainly due to neglecting orthogonal degrees of freedom during the free energy calculations. Nevertheless, the freely driven metadynamics approach leads to clearly advantageous results. Additionally, atomistic insights of the translocation mechanisms of all three solutes are discussed.

Metadynamics to Enhance Sampling in Biomolecular Simulations

Molecular dynamics is a powerful simulation method to provide detailed atomic-scale insight into a range of biological processes including protein folding, biochemical reactions, ligand binding, and many others. Over the last several decades, enhanced sampling methods have been developed to address the large separation in time scales between a molecular dynamics simulation (usually microseconds or shorter) and the time scales of biological processes (often orders of magnitude longer). This chapter specifically focuses on the metadynamics family of methods, which achieves enhanced sampling through the introduction of a history-dependent bias potential that is based on one or more slow degrees of freedom, called collective variables. We introduce the method and its recent variants related to biomolecular studies and then discuss frontier areas of the method. A large part of this chapter is devoted to helping new users of the method understand how to choose metadynamics parameters properly and apply the method to their system of interest.

Role of the Interaction Motif in Maintaining the Open Gate of an Open Sodium Channel

Voltage-gated sodium channels undergo transitions between open, closed, and inactivated states, enabling regulation of the translocation of sodium ions across membranes. A recently published crystal structure of the full-length prokaryotic NavMs crystal structure in the activated open conformation has revealed the presence of a novel motif consisting of an extensive network of salt bridges involving residues in the voltage sensor, S4-S5 linker, pore, and C-terminal domains. This motif has been proposed to be responsible for maintaining an open conformation that enables ion translocation through the channel. In this study, we have used long-time molecular dynamics calculations without artificial restraints to demonstrate that the interaction network of full-length NavMs indeed prevents a rapid collapse and closure of the gate, in marked difference to earlier studies of the pore-only construct in which the gate had to be restrained to remain open. Interestingly, a frequently discussed "hydrophobic gating" mechanism at nanoscopic level is also observed in our simulations, in which the discontinuous water wire close to the gate region leads to an energetic barrier for ion conduction. In addition, we demonstrate the effects of in silico mutations of several of the key residues in the motif on the open channel's stability and functioning, correlating them with existing functional studies on this channel and homologous disease-associated mutations in human sodium channels; we also examine the effects of truncating/removing the voltage sensor and C-terminal domains in maintaining an open gate.

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

Cryo-electron microscopy (cryo-EM) has recently provided invaluable experimental data about the full-length cystic fibrosis transmembrane conductance regulator (CFTR) 3D structure. However, this experimental information deals with inactive states of the channel, either in an apo, quiescent conformation, in which nucleotide-binding domains (NBDs) are widely separated or in an ATP-bound, yet closed conformation. Here, we show that 3D structure models of the open and closed forms of the channel, now further supported by metadynamics simulations and by comparison with the cryo-EM data, could be used to gain some insights into critical features of the conformational transition toward active CFTR forms. These critical elements lie within membrane-spanning domains but also within NBD1 and the N-terminal extension, in which conformational plasticity is predicted to occur to help the interaction with filamin, one of the CFTR cellular partners.

Kinetics of Huperzine A Dissociation from Acetylcholinesterase via Multiple Unbinding Pathways

The dissociation of huperzine A (hupA) from Torpedo californica acetylcholinesterase ( TcAChE) was investigated by 4 μs unbiased and biased all-atom molecular dynamics (MD) simulations in explicit solvent. We performed our study using memetic sampling (MS) for the determination of reaction pathways (RPs), metadynamics to calculate free energy, and maximum-likelihood estimation (MLE) to recover kinetic rates from unbiased MD simulations. Our simulations suggest that the dissociation of hupA occurs mainly via two RPs: a front door along the axis of the active-site gorge (pwf) and through a new transient side door (pws), i.e., formed by the Ω-loop (residues 67-94 of TcAChE). An analysis of the inhibitor unbinding along the RPs suggests that pws is opened transiently after hupA and the Ω-loop reach a low free-energy transition state characterized by the orientation of the pyridone group of the inhibitor directed toward the Ω-loop plane. Unlike pws, pwf does not require large structural changes in TcAChE to be accessible. The estimated free energies and rates agree well with available experimental data. The dissociation rates along the unbinding pathways are similar, suggesting that the dissociation of hupA along pws is likely to be relevant. This indicates that perturbations to hupA- TcAChE interactions could potentially induce pathway hopping. In summary, our results characterize the slow-onset inhibition of TcAChE by hupA, which may provide the structural and energetic bases for the rational design of the next-generation slow-onset inhibitors with optimized pharmacokinetic properties for the treatment of Alzheimer's disease.

Ligand diffusion in proteins via enhanced sampling in molecular dynamics

Computational simulations in biophysics describe the dynamics and functions of biological macromolecules at the atomic level. Among motions particularly important for life are the transport processes in heterogeneous media. The process of ligand diffusion inside proteins is an example of a complex rare event that can be modeled using molecular dynamics simulations. The study of physical interactions between a ligand and its biological target is of paramount importance for the design of novel drugs and enzymes. Unfortunately, the process of ligand diffusion is difficult to study experimentally. The need for identifying the ligand egress pathways and understanding how ligands migrate through protein tunnels has spurred the development of several methodological approaches to this problem. The complex topology of protein channels and the transient nature of the ligand passage pose difficulties in the modeling of the ligand entry/escape pathways by canonical molecular dynamics simulations. In this review, we report a methodology involving a reconstruction of the ligand diffusion reaction coordinates and the free-energy profiles along these reaction coordinates using enhanced sampling of conformational space. We illustrate the above methods on several ligand-protein systems, including cytochromes and G-protein-coupled receptors. The methods are general and may be adopted to other transport processes in living matter.

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

Stability of detergent-solubilized G-protein-coupled receptors (GPCRs) is crucial for their purification in a biologically relevant state, and it is well-known that short chain detergents such as octylglucoside are more denaturing than long chain detergents such as dodecylmaltoside. However, the molecular basis for this phenomenon is poorly understood. To gain insights into the mechanism of detergent destabilization of GPCRs, we used atomistic molecular dynamics simulations of thermostabilized adenosine receptor (A2AR) mutants embedded in either a lipid bilayer or detergent micelles of alkylmaltosides and alkylglucosides. A2AR mutants in dodecylmaltoside or phospholipid showed low flexibility and good interhelical packing. In contrast, A2AR mutants in either octylglucoside or nonylglucoside showed decreased α-helicity in transmembrane regions, decreased α-helical packing, and the interpenetration of detergent molecules between transmembrane α-helices. This was not observed in octylglucoside containing phospholipid. Cholesteryl hemisuccinate in dodecylmaltoside increased the energetic stability of the receptor by wedging into crevices on the hydrophobic surface of A2AR, increasing packing interactions within the receptor and stiffening the detergent micelle. The data suggest a three-stage process for the initial events in the destabilization of GPCRs by octylglucoside: (i) highly mobile detergent molecules form small micelles around the receptor; (ii) loss of α-helicity and decreased interhelical packing interactions in transmembrane regions are promoted by increased receptor thermal motion; (iii) transient separation of transmembrane helices allowed penetration of detergent molecules into the core of the receptor. The relative hydration of the headgroup and alkyl chain correlates with detergent harshness and suggests new avenues to develop milder versions of octylglucoside for receptor crystallization.

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

Albumin-based nanoparticles (NPs) are a promising technology for developing drug-carrier systems, with improved deposition and retention profiles in lungs. Improved understanding of these drug–carrier interactions could lead to better drug-delivery systems. The present study combines computational and experimental methods to gain insights into the mechanism of binding of albuterol sulfate (AS) to bovine serum albumin (BSA) on the molecular level. Molecular dynamics simulation and surface plasmon resonance spectroscopy were used to determine that there are two binding sites on BSA for AS: the first of which is a high-affinity site corresponding to AS1 and the second of which appears to represent the integrated functions of several low-affinity sites corresponding to AS2, AS3, and AS8. AS1 was the strongest binding site, established via electrostatic interaction with Glu243 and Asp255 residues in a hydrophobic pocket. Hydrogen bonds and salt bridges played a main role in the critical binding of AS1 to BSA, and water bridges served a supporting role. Based upon the interaction mechanism, BSA NPs loaded with AS were prepared, and their drug-loading efficiency, morphology, and -release profiles were evaluated. Successful clinical development of AS-BSA-NPs may improve therapy and prevention of bronchospasm in patients with reversible obstructive airway disease, and thus provide a solid basis for expanding the role of NPs in the design of new drug-delivery systems.