Chlorpromazine inhibits EAG1 channels by altering the coupling between the PAS, CNBH and pore domains

EAG1 depolarization-activated potassium selective channels are important targets for treatment of cancer and neurological disorders. EAG1 channels are formed by a tetrameric subunit assembly with each subunit containing an N-terminal Per-Arnt-Sim (PAS) domain and C-terminal cyclic nucleotide-binding homology (CNBH) domain. The PAS and CNBH domains from adjacent subunits interact and form an intracellular tetrameric ring that regulates the EAG1 channel gating, including the movement of the voltage sensor domain (VSD) from closed to open states. Small molecule ligands can inhibit EAG1 channels by binding to their PAS domains. However, the allosteric pathways of this inhibition are not known. Here we show that chlorpromazine, a PAS domain small molecule binder, alters interactions between the PAS and CNBH domains and decreases the coupling between the intracellular tetrameric ring and the pore of the channel, while having little effect on the coupling between the PAS and VSD domains. In addition, chlorpromazine binding to the PAS domain did not alter Cole-Moore shift characteristic of EAG1 channels, further indicating that chlorpromazine has no effect on VSD movement from the deep closed to opened states. Our study provides a framework for understanding global pathways of EAG1 channel regulation by small molecule PAS domain binders.

Multiscale Molecular Dynamics Simulations of the Homodimer Accessory Protein ORF7b of SARS-CoV-2

The SARS-CoV-2 ORF7b protein has drawn attention for its potential role in viral pathogenesis, but its structural details and lateral membrane associations remain elusive. In this study, we conducted multiscale molecular dynamics simulations to provide detailed molecular insights of the protein's dimerization, which is crucial for unraveling its structural model of protein-protein interface important to regulating cellular immune response. To gain a deeper understanding of homodimer configurations, we employed a machine learning algorithm for structural-based clustering. Clusters were categorized into three distinct groups for both parallel and antiparallel orientations, highlighting the influence of the initial monomer conformation on dimer configurations. Analysis of hydrogen bonding and π-π and π-cation stacking interactions within clusters revealed variations in interactions between clusters. In parallel dimers, weak stacking interactions in the transmembrane (TM) region were observed. In contrast, antiparallel dimers exhibited strong hydrogen bonding and stacking interactions contributing to tight dimeric packing, both within and outside the TM domain. Overall, our study provides a comprehensive view of the structural dynamics of ORF7b homodimerization in both parallel and antiparallel orientations. These findings shed light on the molecular interactions involved in ORF7b dimerization, which are crucial for understanding its potential roles in SARS-CoV-2 pathogenesis. This knowledge could inform future research and therapeutic strategies targeting this viral protein.

Simulations of naïve and KLA-activated macrophage plasma membrane models

Macrophages (MAs), which play vital roles in human immune responses and lipid metabolisms, are implicated in the development and progression of atherosclerosis, a major contributor to cardiovascular diseases. Specifically, the abnormal lipid metabolism of oxidized low-density lipids (oxLDLs) in MAs is believed to be a crucial factor. However, the precise mechanism by which the MA membrane contributes to this altered lipid metabolism remains unclear. Lipidomic studies have revealed significant differences in membrane composition between various MA phenotypes. This study serves to provide and characterize complex realistic computational models for naïve (M0) and Kdo2-lipid A-activated (M1) state MA. Analyses of surface area per lipid (SA/lip), area compressibility modulus (KA), carbon‑hydrogen order parameter (SCH), electron density profile (EDP), tilt angles, two-dimension radial distribution functions (2D RDFs), mean squared displacement (MSD), hydrogen bonds (H-bonds), lipid clustering, and lipid wobble were conducted for both models. Results indicate that the M1 state MA membrane is more tightly packed, with increased chain order across lipid species, and forms PSM-DOPG-CHOL and PSM-SLPC-CHOL clusters. Importantly, the bilayer thicknesses reported for the models are in good agreement with experimental data for the thicknesses of transmembrane regions for MA integral proteins. These findings validate the described models as physiologically accurate for future computational studies of MA membranes and their residing proteins.

Molecular mechanism of EAG1 channel inhibition by imipramine binding to the PAS domain

Ether-a-go-go (EAG) channels are key regulators of neuronal excitability and tumorigenesis. EAG channels contain an N-terminal Per-Arnt-Sim (PAS) domain that can regulate currents from EAG channels by binding small molecules. The molecular mechanism of this regulation is not clear. Using surface plasmon resonance and electrophysiology we show that a small molecule ligand imipramine can bind to the PAS domain of EAG1 channels and inhibit EAG1 currents via this binding. We further used a combination of molecular dynamics (MD) simulations, electrophysiology, and mutagenesis to investigate the molecular mechanism of EAG1 current inhibition by imipramine binding to the PAS domain. We found that Tyr71, located at the entrance to the PAS domain cavity, serves as a "gatekeeper" limiting access of imipramine to the cavity. MD simulations indicate that the hydrophobic electrostatic profile of the cavity facilitates imipramine binding and in silico mutations of hydrophobic cavity-lining residues to negatively charged glutamates decreased imipramine binding. Probing the PAS domain cavity-lining residues with site-directed mutagenesis, guided by MD simulations, identified D39 and R84 as residues essential for the EAG1 channel inhibition by imipramine binding to the PAS domain. Taken together, our study identified specific residues in the PAS domain that could increase or decrease EAG1 current inhibition by imipramine binding to the PAS domain. These findings should further the understanding of molecular mechanisms of EAG1 channel regulation by ligands and facilitate the development of therapeutic agents targeting these channels.

Conformational Fluctuations in β2-Microglubulin Using Markov State Modeling and Molecular Dynamics

Conformational dynamics in proteins can give rise to aggregation prone states during folding, and these kinetically stable states could form oligomers and aggregates. In this study, we investigate the intermediate states and near-folded states of β2-microglobulin and their physico-chemical properties using molecular dynamics and Markov state modeling. Analysis of hundreds of microseconds simulation show the importance of the edge strands in the misfolded states that give rise to a high exposure of hydrophobic residues in the core of the protein that could initiate oligomerization and aggregate formation. Our study sheds light on the first step of aggregation of β2m monomers and gave a better picture of the landscape of protein misfolding and aggregation.

Understanding how transmembrane domains regulate interactions between human BST-2 and the SARS-CoV-2 accessory protein ORF7a

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID, replicates at intracellular membranes. Bone marrow stromal antigen 2 (BST-2; tetherin) is an antiviral response protein that inhibits transport of viral particles after budding within infected cells. RNA viruses such as SARS-CoV-2 use various strategies to disable BST-2, including use of transmembrane 'accessory' proteins that interfere with BST-2 oligomerization. ORF7a is a small, transmembrane protein present in SARS-CoV-2 shown previously to alter BST-2 glycosylation and function. In this study, we investigated the structural basis for BST-2 ORF7a interactions, with a particular focus on transmembrane and juxtamembrane interactions. Our results indicate that transmembrane domains play an important role in BST-2 ORF7a interactions and mutations to the transmembrane domain of BST-2 can alter these interactions, particularly single-nucleotide polymorphisms in BST-2 that result in mutations such as I28S. Using molecular dynamics simulations, we identified specific interfaces and interactions between BST-2 and ORF7a to develop a structural basis for the transmembrane interactions. Differences in glycosylation are observed for BST-2 transmembrane mutants interacting with ORF7a, consistent with the idea that transmembrane domains play a key role in their heterooligomerization. Overall, our results indicate that ORF7a transmembrane domain interactions play a key role along with extracellular and juxtamembrane domains in modulating BST-2 function.

Drude Polarizable Lipid Force Field with Explicit Treatment of Long-Range Dispersion: Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids

Accurate empirical force fields of lipid molecules are a critical component of molecular dynamics simulation studies aimed at investigating properties of monolayers, bilayers, micelles, vesicles, and liposomes, as well as heterogeneous systems, such as protein-membrane complexes, bacterial cell walls, and more. While the majority of lipid force field-based simulations have been performed using pairwise-additive nonpolarizable models, advances have been made in the development of the polarizable force field based on the classical Drude oscillator model. In the present study, we undertake further optimization of the Drude lipid force field, termed Drude2023, including improved treatment of the phosphate and glycerol linker region of PC and PE headgroups, additional optimization of the alkene group in monounsaturated lipids, and inclusion of long-range Lennard-Jones interactions using the particle-mesh Ewald method. Initial optimization targeted quantum mechanical (QM) data on small model compounds representative of the linker region. Subsequent optimization targeted QM data on larger model compounds, experimental data, and dihedral potentials of mean force from the CHARMM36 additive lipid force field using a parameter reweighting protocol. The use of both experimental and QM target data during the reweighting protocol is shown to produce physically reasonable parameters that reproduce a collection of experimental observables. Target data for optimization included surface area/lipid for DPPC, DSPC, DMPC, and DLPC bilayers and nuclear magnetic resonance (NMR) order parameters for DPPC bilayers. Validation data include prediction of membrane thickness, scattering form factors, electrostatic potential profiles, compressibility moduli, surface area per lipid, water permeability, NMR T₁ relaxation times, diffusion constants, and monolayer surface tensions for a variety of saturated and unsaturated lipid mono- and bilayers. Overall, the agreement with experimental data is quite good, though the results are less satisfactory for the NMR T₁ relaxation times for carbons near the ester groups. Notable improvements compared to the additive C36 force field were obtained for membrane dipole potentials, lipid diffusion coefficients, and water permeability with the exception of monounsaturated lipid bilayers. It is anticipated that the optimized polarizable Drude2023 force field will help generate more accurate molecular simulations of pure bilayers and heterogeneous systems containing membranes, advancing our understanding of the role of electronic polarization in these systems.

Molecular dynamics simulations of the human ocular lens with age and cataract

The human ocular lens consists primarily of elongated, static fibers characterized by high stability and low turnover, which differ dramatically in their composition and properties from other biological membranes. Cholesterol (Chol) and sphingolipids (SL) are present at high concentrations, including saturated SLs, such as dihyrosphingomyelin (DHSM). Past molecular dynamics simulations demonstrated that the presence of DHSM and high Chol concentration contributes to higher order in lipid membranes. This current study simulated more complex models of human lens membranes. Models were developed representing physiological compositions in cataractous lenses aged 74 ± 6 years and in healthy lenses aged 22 ± 4, 41 ± 6, and 69 ± 3 years. With older age, Chol and ceramide concentrations increase and glycerophospholipid concentration decreases. With cataract, ceramide concentration increases and Chol and glycerophospholipid concentrations decrease. Surface area per lipid, deuterium order parameters (S_CD), sterol tilt angle, electron density profiles, bilayer thickness, chain interdigitation, two-dimensional radial distribution functions (2D-RDF), lipid clustering, and hydrogen bonding were calculated for all simulations. All systems exhibited low surface area per lipid and high bilayer thickness, indicative of strong vertical packing. S_CD parameters suggest similarly, with saturated tails in the hydrophobic core of the membrane having elevated order. Vertical packing and acyl tail order increased with both age and cataract condition. Lateral diffusion decreased with age and cataracts, with the older and cataractous models demonstrating increased long-range structure by the 2D-RDF analysis. In future work examining the membrane proteins of the lens, these models can serve as a physiologically accurate representation of the lens lipidome.

Antimicrobial Peptide Mechanism Studied by Scattering-Guided Molecular Dynamics Simulation

In an effort to combat rising antimicrobial resistance, our labs have rationally designed cationic, helical, amphipathic antimicrobial peptides (AMPs) as alternatives to traditional antibiotics since AMPs incur bacterial resistance in weeks, rather than days. One highly positively charged AMP, WLBU2 (+13e), (RRWV RRVR RWVR RVVR VVRR WVRR), has been shown to be effective in killing both Gram-negative (G(-)) and Gram-positive (G(+)) bacteria by directly perturbing the bacterial membrane nonspecifically. Previously, we used two equilibrium experimental methods: synchrotron X-ray diffuse scattering (XDS) providing lipid membrane thickness and neutron reflectometry (NR) providing WLBU2 depth of penetration into three lipid model membranes (LMMs). The purpose of the present study is to use the results from the scattering experiments to guide molecular dynamics (MD) simulations to investigate the detailed biophysics of the interactions of WLBU2 with LMMs of Gram-negative outer and inner membranes, and Gram-positive cell membranes, to elucidate the mechanisms of bacterial killing. Instead of coarse-graining, backmapping, or simulating without bias for several microseconds, all-atom (AA) simulations were guided by the experimental results and then equilibrated for ∼0.5 μs. Multiple replicas of the inserted peptide were run to probe stability and reach a combined time of at least 1.2 μs for G(-) and also 2.0 μs for G(+). The simulations with experimental comparisons help rule out certain structures and orientations and propose the most likely set of structures, orientations, and effects on the membrane. The simulations revealed that water, phosphates, and ions enter the hydrocarbon core when WLBU2 is positioned there. For an inserted peptide, the three types of amino acids, arginine, tryptophan, and valine (R, W, V), are arranged with the 13 Rs extending from the hydrocarbon core to the phosphate group, Ws are located at the interface, and Vs are more centrally located. For a surface state, R, W, and V are positioned relative to the bilayer interface as expected from their hydrophobicities, with Rs closest to the phosphate group, Ws close to the interface, and Vs in between. G(-) and G(+) LMMs are thinned ∼1 Å by the addition of WLBU2. Our results suggest a dual anchoring mechanism for WLBU2 both in the headgroup and in the hydrocarbon region that promotes a defect region where water and ions can flow across the slightly thinned bacterial cell membrane.

Computational Study of the Allosteric Effects of p5 on CDK5-p25 Hyperactivity as Alternative Inhibitory Mechanisms in Neurodegeneration

The cyclin-dependent kinase (CDK5) forms a stable complex with its activator p25, leading to the hyperphosphorylation of tau proteins and to the formation of plaques and tangles that are considered to be one of the typical causes of Alzheimer's disease (AD). Hence, the pathological CDK5-p25 complex is a promising therapeutic target for AD. Small peptides, obtained from the truncation of CDK5 physiological activator p35, have shown promise in inhibiting the pathological complex effectively while also crossing the blood-brain barrier. One such small 24-residue peptide, p5, has shown selective inhibition toward the pathological complex in vivo. Our previous research focused on the characterization of a computationally predicted CDK5-p5 binding mode and of its pharmacophore, which was consistent with competitive inhibition. In continuation of our previous work, herein, we investigate four additional binding modes to explore other possible mechanisms of interaction between CDK5 and p5. The quantitative description of the pharmacophore is consistent with both competitive and allosteric p5-induced inhibition mechanisms of CDK5-p25 pathology. The gained insights can direct further in vivo/in vitro tests and help design small peptides, linear or cyclic, or peptidomimetic compounds as adjuvants of orthosteric inhibitors or as part of a cocktail of drugs with enhanced effectiveness and lower side effects.

A reengineered common chain cytokine augments CD8+ T cell–dependent immunotherapy

Cytokine therapy is limited by undesirable off-target side effects as well as terminal differentiation and exhaustion of chronically stimulated T cells. Here, we describe the signaling properties of a potentially unique cytokine by design, where T cell surface binding and signaling are separated between 2 different families of receptors. This fusion protein cytokine, called OMCPmutIL-2, bound with high affinity to the cytotoxic lymphocyte-defining immunoreceptor NKG2D but signaled through the common γ chain cytokine receptor. In addition to precise activation of cytotoxic T cells due to redirected binding, OMCPmutIL-2 resulted in superior activation of both human and murine CD8⁺ T cells by improving their survival and memory cell generation and decreasing exhaustion. This functional improvement was the direct result of altered signal transduction based on the reorganization of surface membrane lipid rafts that led to Janus kinase-3–mediated phosphorylation of the T cell receptor rather than STAT/AKT signaling intermediates. This potentially novel signaling pathway increased CD8⁺ T cell response to low-affinity antigens, activated nuclear factor of activated T cells transcription factors, and promoted mitochondrial biogenesis. OMCPmutIL-2 thus outperformed other common γ chain cytokines as a catalyst for in vitro CD8⁺ T cell expansion and in vivo CD8⁺ T cell–based immunotherapy.

Modeling the Membrane Binding Mechanism of a Lipid Transport Protein Osh4 to Single Membranes

All atom molecular dynamics simulations are utilized to unravel the binding mechanism of yeast oxysterol binding protein (Osh4) to model membranes with varying anionic lipid concentration using all-atom (AA) and the highly mobile membrane mimetic (HMMM) representations. For certain protein-lipid interactions, an improved force field description is used (CUFIX) to accurately describe lipid-protein electrostatic interactions. Our detailed computational studies have identified a single, β-crease orientated, membrane bound conformation of Osh4 for all anionic membranes. The penetration of the PHE-239 residue below the membrane phosphate plane is the characteristic signature of the membrane-bound state of Osh4. As the phenylalanine loop anchors itself deeply in the membrane; the other regions of the Osh4, namely, ALPS motif, ß6- ß7 loop, ß14- ß15 loop and ß16- ß17 loop, maximize their contact with the membrane. Furthermore, loose lipid packing and higher mobility of HMMM enables stronger association of ALPS motif with the membrane lipids through its hydrophobic surface and after the HMMM is converted to AA and equilibrated the binding is 2-3 times stronger compared to simulations started with the AA representation yielding the major importance of the ALPS motif to binding. Quantitative estimation of binding energy revealed that the phenylalanine loop plays a crucial role in stable membrane attachment of Osh4 and contributes significantly toward overall binding process. The CUFIX parameters provide a more balanced picture of hydrophobic and electrostatic interactions between the protein and the membrane which differs from our past work that showed salt bridges alone stabilized Osh4-membrane contact. Our study provides a comprehensive picture of the binding mechanism of Osh4 with model single membranes and thus, understanding of the initial interactions is important for elucidating the biological function of this protein to shuttle lipids between organelles.

All-Atom Modeling of Complex Cellular Membranes

Cell membranes are composed of a variety of lipids and proteins where they interact with each other to fulfill their roles. The first step in modeling these interactions in molecular simulations is to have reliable mimetics of the membrane's lipid environment. This Feature Article presents our recent efforts to model complex cellular membranes using all-atom force fields. A short review of the CHARMM36 (C36) lipid force field and its recent update to incorporate the long-range dispersion is presented. Key examples of model membranes mimicking various species and organelles are given. These include single-celled organisms such as bacteria (E. coli., chlamydia, and P. aeruginosa) and yeast (plasma membrane, endoplasmic reticulum, and trans-Golgi network) and more advanced ones such as plants (soybean and Arabidopsis thaliana) and mammals (ocular lens, stratum corneum, and peripheral nerve myelin). Leaflet asymmetry in composition has also been applied to some of these models. With the increased lipid diversity in the C36 lipid FF, these complex models can better reflect the structural, mechanical, and dynamic properties of realistic membranes and open an opportunity to study biological processes involving other molecules.

Leaflet Asymmetry Modeling in the Lipid Composition of Escherichia coli Cytoplasmic Membranes

Lipid composition asymmetry between leaflets is important to cell function and plays a key role in the "positive inside" rule in transmembrane proteins. In this work, Escherichia coli inner plasma membrane models reflecting this asymmetry have been investigated at the early-log and stationary stages during the bacterial lifecycle using all-atom molecular dynamics simulations. The CHARMM36 lipid force field is used, and selected membrane properties are tested for variations between two leaflets and whole membranes. Our models include bacterial lipids with a cyclopropane moiety on the sn-2 acyl chain in the stationary membrane model. The PE/PG ratio for two leaflets reflects the "positive inside" rule of membrane proteins, set to 6.8 and 2.8 for the inner and outer leaflets of the two models, respectively. We are the first to model leaflet asymmetry in the lipid composition of E. coli cytoplasmic membranes and observe the effect on membrane properties in leaflets and whole membranes. Specifically, our results show that for the stationary phase bilayer, the surface area per lipid (SA/lipid) is larger, the thickness (2D_C and D_B) is smaller, the tilt angle is larger, the tilt modulus is smaller, and the deuterium order parameters (S_CD) of sn-1 and sn-2 tails are lower, compared to the early-log stage. Moreover, the stationary stage bilayer has a positive spontaneous curvature, while the early-log stage has a near flat spontaneous curvature. For leaflet asymmetry, the inner leaflet has a larger SA/lipid, a smaller thickness, a smaller elastic tilt modulus (a larger tilt angle), and lower S_CD, compared to the outer leaflet in both stages. Moreover, an asymmetric membrane involves a lipid tilt and a lateral extension, varying from a reference state of a pre-equilibrium membrane. This work encourages a more profound exploration of leaflet asymmetry in various other membrane models and how this might affect the structure and function of membrane-associated peptides and proteins.

Variational embedding of protein folding simulations using Gaussian mixture variational autoencoders

Conformational sampling of biomolecules using molecular dynamics simulations often produces a large amount of high dimensional data that makes it difficult to interpret using conventional analysis techniques. Dimensionality reduction methods are thus required to extract useful and relevant information. Here, we devise a machine learning method, Gaussian mixture variational autoencoder (GMVAE), that can simultaneously perform dimensionality reduction and clustering of biomolecular conformations in an unsupervised way. We show that GMVAE can learn a reduced representation of the free energy landscape of protein folding with highly separated clusters that correspond to the metastable states during folding. Since GMVAE uses a mixture of Gaussians as its prior, it can directly acknowledge the multi-basin nature of the protein folding free energy landscape. To make the model end-to-end differentiable, we use a Gumbel-softmax distribution. We test the model on three long-timescale protein folding trajectories and show that GMVAE embedding resembles the folding funnel with folded states down the funnel and unfolded states outside the funnel path. Additionally, we show that the latent space of GMVAE can be used for kinetic analysis and Markov state models built on this embedding produce folding and unfolding timescales that are in close agreement with other rigorous dynamical embeddings such as time independent component analysis.

Symmetric and Asymmetric Models for the Arabidopsis thaliana Plasma Membrane: A Simulation Study

Arabidopsis thaliana is an important model organism, which has attracted many biologists. While most research efforts have been on studying the genetics and proteins of this organism, a systematic study of its lipidomics is lacking. Here, we present a novel, asymmetric model of its cell membrane with its lipid composition consisting of five glycerophospholipids, two glycolipids, and sitosterol determined from multiple independent experiments. A typical lipid type in plant membranes is glycosyl inositol phosphoryl ceramide (GIPC), which accounts for about 10% of the total lipids in the outer leaflet in our model. Two symmetric models representing the inner and outer leaflets of the membrane were built and simulated until equilibrium was reached and then combined to form the asymmetric model. Our results indicate that the outer leaflet is more rigid and tightly packed compared to the inner leaflet. Pressure profiles for the two leaflets are overall similar though the outer leaflet exhibits larger oscillations. A special focus on lipid organization is discussed and the interplay between glycolipids and sitosterols is found to be important. The current model provides a baseline for future modeling of similar membranes and can be used to study partitioning of small molecules in the membrane or further developed to study the interaction between plant membrane proteins and lipids.

Considerations of Recent All-Atom Lipid Force Field Development

Molecular simulations of biological molecules require an accurate description of molecular interactions through a force field (FF). The focus of this Perspective is on all-atom lipid FFs. Recent additions to the CHARMM36 lipid FF continue to expand a researcher's ability to probe membrane structure and function with a wide variety of biologically important lipids. Currently, there is an effort to reduce the assumptions in all-atom lipid FFs. The inclusion of long-range dispersion interaction through particle-mesh Ewald is allowing for more accurate descriptions of lipid bilayer and monolayer properties without additional computational cost. Soon, simulations with lipid FFs will no longer depend on short-range cutoffs and will accurately represent long-range dispersion. This requires efficient FF parametrization with an automated approach due to FF complexity. In addition, polarizable FFs for lipids will be important for the next generation of simulations that accurately represent how molecule interactions respond to a varied environment.

Simulations of Diabetic and Non-Diabetic Peripheral Nerve Myelin Lipid Bilayers

The multilayered myelin sheath is a critical component of both central and peripheral nervous systems, forming a protective barrier against axonal damage and facilitating the movement of nervous impulses. It is primarily composed of cholesterol (CHL1), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), phosphatidylinositol (PI), sphingomyelin (SM), and galactosylceramide (GalCer) lipids. For rat sciatic nerve myelin (part of the peripheral nervous system, PNS), it has been found that cholesterol and unsaturated fatty acid contents are significantly lower in diabetic than in non-diabetic conditions. In this study, lipid compositions from experimental data are used to create four model rat sciatic nerve myelin lipid bilayers: PI-containing (non-diabetic and diabetic) and PS-containing (non-diabetic and diabetic), which were then simulated using the all-atom CHARMM36 force field. Simulation results of diabetic membranes indicate less rigid, more laterally expansive, and thinner bilayers as well as potentially reduced interactions between GalCer on opposing myelin leaflets, supporting a direct role of the cholesterol content decrease in instigating myelin deterioration and diabetic peripheral neuropathy. Compared to PI-lipids, PS-lipids were found to cause higher inter-lipid spacing and decreased order within membranes as a result of their smaller headgroup size and higher inter-lipid hydrogen bonding potential, which allow them to more frequently reside deeper in the membrane plane and produce pushing effects on other lipids. GalCer deuterium order parameters and non-diabetic headgroup-to-headgroup bilayer thicknesses were compared to experimental data, exhibiting close alignment, supporting the future usage of these models to study the PNS myelin sheath.

Impact of PIP2 Lipids, Force Field Parameters, and Mutational Analysis on the Binding of the Osh4's α6-α7 Domain

All-atom molecular dynamics simulations are used with the highly mobile membrane mimetic method to study the α₆-α₇ peptide of the critical yeast Osh4 peripheral membrane protein. This research focuses on the impact of 1-palmitoyl-2-oleoyl-sn-glycero-phosphatidylinoside 4,5-bisphosphate (PIP2) lipids and 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-l-serine on the protein's ability to bind to the membrane. Details of the binding mechanism are described qualitatively and quantitatively by measuring the position of the deepest residues, angle of the peptide during binding, root mean square deviation of the atomic positions within the peptide, and interaction energy, while changing variables, such as the force field used and the presence of the PIP2 lipids. The negatively charged PIP2 has a large head group that is a few Ångstroms above the main membrane phosphates enabling the PIP2 lipids to interact with the peptide before it binds deeper into the membrane. The PIP2 lipids can alter the position of the peptide during binding by recruiting charged residues on the α₇ helix, such as R344 and R347. Residues R347 and R344 are unusual because they are slightly out of the reach of the main membrane phosphates but optimally positioned to interact with the PIP2 lipids. The salt-bridge interactions can also typically occur between cationic peptide residues such as R314, K325, and K336. The force field interaction effect on peptide binding was also investigated by changing the standard CHARMM36m to an improved description between some amino acids and lipid moieties (Phys. Chem. Chem. Phys. 20, 8432-8449). This resulted in the total number of salt bridges and hydrogen bonds being drastically reduced, the interaction energy was also reduced, and there was more balance between electrostatic and nonpolar interactions, but the general bound structure is maintained. This work is an important initial step to understand the effect of the Osh4 protein on the membrane binding and to quantify the effect of PIP2 lipids on this domain.

Location and Conformational Ensemble of Menaquinone and Menaquinol, and Protein-Lipid Modulations in Archaeal Membranes

Halobacteria, a type of archaea in high salt environments, have phytanyl ether phospholipid membranes containing up to 50% menaquinone. It is not understood why a high concentration of menaquinone is required and how it influences membrane properties. In this study, menaquinone-8 headgroup and torsion parameters of isoprenoid tail are optimized in the CHARMM36 force field. Molecular dynamics simulations of archaeal bilayers containing 0 to 50% menaquinone characterize the distribution of menaquinone-8 and menaquinol-8, as well as their effects on mechanical properties and permeability. Menaquinone-8 segregates to the membrane midplane above concentrations of 10%, favoring an extended conformation in a fluid state. Menaquinone-8 increases the bilayer thickness but does not significantly alter the area compressibility modulus and lipid chain ordering. Counterintuitively, menaquinone-8 increases water permeability because it lowers the free energy barrier in the midplane. The thickness increase due to menaquinone-8 may help halobacteria ameliorate hyper-osmotic pressure by increasing the membrane bending constant. Simulations of the archaeal membranes with archaerhodopsin-3 show that the local membrane surface adjusts to accommodate the thick membranes. Overall, this study delineates the biophysical landscape of 50% menaquinone in the archaeal bilayer, demonstrates the mixing of menaquinone and menaquinol, and provides atomistic details about menaquinone configurations.

A replica exchange umbrella sampling (REUS) approach to predict host-guest binding free energies in SAMPL8 challenge

In this study, we report binding free energy calculations of various drugs-of-abuse to Cucurbit-[8]-uril as part of the SAMPL8 blind challenge. Force-field parameters were obtained from force-matching with different quantum mechanical levels of theory. The Replica Exchange Umbrella Sampling (REUS) approach was used with a cylindrical restraint to enhance the sampling of host–guest binding. Binding free energy was calculated by pulling the guest molecule from one side of the symmetric and cylindrical host, then into and through the host, and out the other side (bidirectional) as compared to pulling only to the bound pose inside the cylindrical host (unidirectional). The initial results with force-matched MP2 parameter set led to RMSE of 4.68 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{kcal}}/{\text{mol}}$$\end{document}kcal/mol from experimental values. However, the follow-up study with CHARMM generalized force field parameters and force-matched PM6-D3H4 parameters resulted in RMSEs from experiment of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2.65$$\end{document}2.65 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1.72 {\text{kcal}}/{\text{mol}}$$\end{document}1.72kcal/mol, respectively, which demonstrates the potential of REUS for accurate binding free energy calculation given a more suitable description of energetics. Moreover, we compared the free energies for the so called bidirectional and unidirectional free energy approach and found that the binding free energies were highly similar. However, one issue in the bidirectional approach is the asymmetry of profile on the two sides of the host. This is mainly due to the insufficient sampling for these larger systems and can be avoided by longer sampling simulations. Overall REUS shows great promise for binding free energy calculations.

Molecular dynamics simulations of ethanol permeation through single and double-lipid bilayers

Permeation of small molecules through membranes is a fundamental biological process, and molecular dynamics simulations have proven to be a promising tool for studying the permeability of membranes by providing a precise characterization of the free energy and diffusivity. In this study, permeation of ethanol through three different membranes of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylserine (POPS), PO-phosphatidylethanolamine (POPE), and PO-phosphatidylcholine (POPC) is studied. Permeabilities are calculated and compared with two different approaches based on Fick's first law and the inhomogeneous solubility-diffusion model. Microsecond simulation of double bilayers of these membranes provided a direct measurement of permeability by a flux-based counting method. These simulations show that a membrane of POPC has the highest permeability, followed by POPE and POPS. Due to the membrane-modulating properties of ethanol, the permeability increases as functions of concentration and saturation of the inner leaflet in a double bilayer setting, as opposed to the customary definition as a proportionality constant. This concentration dependence is confirmed by single bilayer simulations at different ethanol concentrations ranging from 1% to 18%, where permeability estimates are available from transition-based counting and the inhomogeneous solubility-diffusion model. We show that the free energy and diffusion profiles for ethanol lack accuracy at higher permeant concentrations due to non-Markovian kinetics caused by collective behavior. In contrast, the counting method provides unbiased estimates. Finally, the permeabilities obtained from single bilayer simulations are combined to represent natural gradients felt by a cellular membrane, which accurately models the non-equilibrium effects on ethanol permeability from single bilayer simulations in equilibrium.

CHARMM36 Lipid Force Field with Explicit Treatment of Long-Range Dispersion: Parametrization and Validation for Phosphatidylethanolamine, Phosphatidylglycerol, and Ether Lipids

Long-range Lennard-Jones (LJ) interactions have been incorporated into the CHARMM36 (C36) lipid force field (FF) using the LJ particle-mesh Ewald (LJ-PME) method in order to remove the inconsistency of bilayer and monolayer properties arising from the exclusion of long-range dispersion [Yu, Y.; Semi-automated Optimization of the CHARMM36 Lipid Force Field to Include Explicit Treatment of Long-Range Dispersion. J. Chem. Theory Comput. 2021, 10.1021/acs.jctc.0c01326. (preceding article in this issue)]. The new FF is denoted C36/LJ-PME. While the first optimization was based on three phosphatidylcholines (PCs), this work extends the validation and parametrization to more lipids including PC, phosphatidylethanolamine (PE), phosphatidylglycerol (PG), and ether lipids. The agreement with experimental structure data is excellent for PC, PE, and ether lipids. C36/LJ-PME also compares favorably with scattering data of PG bilayers but less so with NMR deuterium order parameters of 1,2-dimyristoyl-sn-glycero-3-phospho-(1'-rac-glycerol) (DMPG) at 303.15 K, indicating a need for future optimization regarding PG-specific parameters. Frequency dependence of NMR T1 spin-lattice relaxation times is well-described by C36/LJ-PME, and the overall agreement with experiment is comparable to C36. Lipid diffusion is slower than C36 due to the added long-range dispersion causing a higher viscosity, although it is still too fast compared to experiment after correction for periodic boundary conditions. When using a 10 Å real-space cutoff, the simulation speed of C36/LJ-PME is roughly equal to C36. While more lipids will be incorporated into the FF in the future, C36/LJ-PME can be readily used for common lipids and extends the capability of the CHARMM FF by supporting monolayers and eliminating the cutoff dependence.

Semi-automated Optimization of the CHARMM36 Lipid Force Field to Include Explicit Treatment of Long-Range Dispersion

The development of the CHARMM lipid force field (FF) can be traced back to the early 1990s with its current version denoted CHARMM36 (C36). The parametrization of C36 utilized high-level quantum mechanical data and free energy calculations of model compounds before parameters were manually adjusted to yield agreement with experimental properties of lipid bilayers. While such manual fine-tuning of FF parameters is based on intuition and trial-and-error, automated methods can identify beneficial modifications of the parameters via their sensitivities and thereby guide the optimization process. This work introduces a semi-automated approach to reparametrize the CHARMM lipid FF with consistent inclusion of long-range dispersion through the Lennard-Jones particle-mesh Ewald (LJ-PME) approach. The optimization method is based on thermodynamic reweighting with regularization with respect to the C36 set. Two independent optimizations with different topology restrictions are presented. Targets of the optimizations are primarily liquid crystalline phase properties of lipid bilayers and the compression isotherm of monolayers. Pair correlation functions between water and lipid functional groups in aqueous solution are also included to address headgroup hydration. While the physics of the reweighting strategy itself is well-understood, applying it to heterogeneous, complex anisotropic systems poses additional challenges. These were overcome through careful selection of target properties and reweighting settings allowing for the successful incorporation of the explicit treatment of long-range dispersion, and we denote the newly optimized lipid force field as C36/LJ-PME. The current implementation of the optimization protocol will facilitate the future development of the CHARMM and related lipid force fields.

Estimating localization of various statins within a POPC bilayer

As a class of drugs prescribed to heart disease patients, statins are among the most popular prescription drugs in the world. Over the years, statins have been shown to have beneficial effects on patients via pathways independent of their effect on cholesterol. These pleiotropic effects vary across the different statins, and a growing hypothesis is that they are related to the localization of the statins in and their effect on the membrane. In this study, we use molecular dynamics (MD) simulations with the CHARMM36 all-atom force field to investigate the localization of statins (atorvastatin, cerivastatin, lovastatin, and pravastatin) in a POPC bilayer and how they affect the acyl chain order parameters (S_CD), surface area per lipid (APL), and thicknesses of the bilayer. The data obtained from 500 ns simulations suggests that lovastatin is localized deepest in the membrane, mostly interacting with the hydrophobic core, cerivastatin is slightly closer to the bilayer/solvent interface than lovastatin and interacts with the headgroups via its dihydroxy acid group, and pravastatin is found closest to the bilayer/solvent interface, its hydrophobic rings interacting mostly with the region around the acyl's carbonyl and its dihydroxy acid interacting with the solvent and the headgroups. Consistent binding of atorvastatin to the bilayer is not observed during our simulation due to self-aggregation. The statins differentially alter the S_CD and APL and most of the bilayer thicknesses, but these effects are modest. Overall, as expected, the localization of statins seems to follow their hydrophilicity, and given previous data showing the relationship between statins' hydrophobicity and pleiotropic effects, one would expect statins that localize and interact with different regions of the membrane to have different effects. This research provides some important insight into statin localization in a simplified model of a cellular membrane.

CHARMM-GUI Supports Hydrogen Mass Repartitioning and Different Protonation States of Phosphates in Lipopolysaccharides

Hydrogen mass repartitioning (HMR) that permits time steps of all-atom molecular dynamics simulation up to 4 fs by increasing the mass of hydrogen atoms has been used in protein and phospholipid bilayers simulations to improve conformational sampling. Molecular simulation input generation via CHARMM-GUI now supports HMR for diverse simulation programs. In addition, considering ambiguous pH at the bacterial outer membrane surface, different protonation states, either -2e or -1e, of phosphate groups in lipopolysaccharides (LPS) are also supported in CHARMM-GUI LPS Modeler. To examine the robustness of HMR and the influence of protonation states of phosphate groups on LPS bilayer properties, eight different LPS-type all-atom systems with two phosphate protonation states are modeled and simulated utilizing both OpenMM 2-fs (standard) and 4-fs (HMR) schemes. Consistency in the conformational space sampled by standard and HMR simulations shows the reliability of HMR even in LPS, one of the most complex biomolecules. For systems with different protonation states, similar conformations are sampled with a PO41- or PO42- group, but different phosphate protonation states make slight impacts on lipid packing and conformational properties of LPS acyl chains. Systems with PO41- have a slightly smaller area per lipid and thus slightly more ordered lipid A acyl chains compared to those with PO42-, due to more electrostatic repulsion between PO42- even with neutralizing Ca2+ ions. HMR and different protonation states of phosphates of LPS available in CHARMM-GUI are expected to be useful for further investigations of biological systems of diverse origin.

Critical Sequence Hotspots for Binding of Novel Coronavirus to Angiotensin Converter Enzyme as Evaluated by Molecular Simulations

The novel coronavirus (nCOV-2019) outbreak has put the world on edge, causing millions of cases and hundreds of thousands of deaths all around the world, as of June 2020, let alone the societal and economic impacts of the crisis. The spike protein of nCOV-2019 resides on the virion's surface mediating coronavirus entry into host cells by binding its receptor binding domain (RBD) to the host cell surface receptor protein, angiotensin converter enzyme (ACE2). Our goal is to provide a detailed structural mechanism of how nCOV-2019 recognizes and establishes contacts with ACE2 and its difference with an earlier severe acute respiratory syndrome coronavirus (SARS-COV) in 2002 via extensive molecular dynamics (MD) simulations. Numerous mutations have been identified in the RBD of nCOV-2019 strains isolated from humans in different parts of the world. In this study, we investigated the effect of these mutations as well as other Ala-scanning mutations on the stability of the RBD/ACE2 complex. It is found that most of the naturally occurring mutations to the RBD either slightly strengthen or have the same binding affinity to ACE2 as the wild-type nCOV-2019. This means that the virus had sufficient binding affinity to its receptor at the beginning of the crisis. This also has implications for any vaccine design endeavors since these mutations could act as antibody escape mutants. Furthermore, in silico Ala-scanning and long-timescale MD simulations highlight the crucial role of the residues at the interface of RBD and ACE2 that may be used as potential pharmacophores for any drug development endeavors. From an evolutional perspective, this study also identifies how the virus has evolved from its predecessor SARS-COV and how it could further evolve to become even more infectious.

Membrane permeability of small molecules from unbiased molecular dynamics simulations

Permeation of many small molecules through lipid bilayers can be directly observed in molecular dynamics simulations on the nano- and microsecond timescale. While unbiased simulations provide an unobstructed view of the permeation process, their feasibility for computing permeability coefficients depends on various factors that differ for each permeant. The present work studies three small molecules for which unbiased simulations of permeation are feasible within less than a microsecond, one hydrophobic (oxygen), one hydrophilic (water), and one amphiphilic (ethanol). Permeabilities are computed using two approaches: counting methods and a maximum-likelihood estimation for the inhomogeneous solubility diffusion (ISD) model. Counting methods yield nearly model-free estimates of the permeability for all three permeants. While the ISD-based approach is reasonable for oxygen, it lacks precision for water due to insufficient sampling and results in misleading estimates for ethanol due to invalid model assumptions. It is also demonstrated that simulations using a Langevin thermostat with collision frequencies of 1/ps and 5/ps yield oxygen permeabilities and diffusion constants that are lower than those using Nosé-Hoover by statistically significant margins. In contrast, permeabilities from trajectories generated with Nosé-Hoover and the microcanonical ensemble do not show statistically significant differences. As molecular simulations become more affordable and accurate, calculation of permeability for an expanding range of molecules will be feasible using unbiased simulations. The present work summarizes theoretical underpinnings, identifies pitfalls, and develops best practices for such simulations.

Exploring dynamics and network analysis of spike glycoprotein of SARS-COV-2

The ongoing pandemic caused by coronavirus SARS-COV-2 continues to rage with devastating consequences on human health and global economy. The spike glycoprotein on the surface of coronavirus mediates its entry into host cells and is the target of all current antibody design efforts to neutralize the virus. The glycan shield of the spike helps the virus to evade the human immune response by providing a thick sugar-coated barrier against any antibody. To study the dynamic motion of glycans in the spike protein, we performed microsecond-long MD simulation in two different states that correspond to the receptor binding domain in open or closed conformations. Analysis of this microsecond-long simulation revealed a scissoring motion on the N-terminal domain of neighboring monomers in the spike trimer. Role of multiple glycans in shielding of spike protein in different regions were uncovered by a network analysis, where the high betweenness centrality of glycans at the apex revealed their importance and function in the glycan shield. Microdomains of glycans were identified featuring a high degree of intra-communication in these microdomains. An antibody overlap analysis revealed the glycan microdomains as well as individual glycans that inhibit access to the antibody epitopes on the spike protein. Overall, the results of this study provide detailed understanding of the spike glycan shield, which may be utilized for therapeutic efforts against this crisis.

Update of the CHARMM36 United Atom Chain Model for Hydrocarbons and Phospholipids

Accurate lipid force field (FF) parameters used in molecular dynamics (MD) simulations are crucial for understanding the properties of lipid-containing systems and biological processes related to lipids. The last update of the CHARMM36 united atom chain model (C36UA) was in 2013 [Lee, S. J. Phys. Chem. B 2014, 118, 547 556]; it utilized CHARMM36 (C36) lipid FF parameters for headgroups and OPLS-UA Lennard-Jones (LJ) parameters for tails. Simulations with the FF were able to reproduce many experimental observables of lipid bilayers accurately, but to be more applicable for a wide range of lipids, additional FF parameter optimization was needed. In this work, we present an update of the model, named C36UAr. The parameterization included the LJ parameters for hydrocarbons and related dihedrals. Bulk liquid properties (density, heat of vaporization, isothermal compressibility, and diffusion constant) of model compounds were used as targets for the LJ parameter fitting, and dihedrals were fit to either quantum mechanical (QM) or potential of mean force (PMF) calculations using C36. Thermodynamic reweighting was used to further improve the parameters. Bilayer simulations of various lipid headgroups (phosphatidylcholine, phosphatidylethanolamine, and phosphatidylglycerol) and tails (saturated, monounsaturated, and polyunsaturated) were performed to validate the model, and significant improvements were seen in bilayer properties, including surface area, membrane thicknesses, NMR deuterium order parameters, and density profiles. C36UAr was also compared to the hydrogen mass repartitioning (HMR) method. The high accuracy and competitive efficiency shown in this study make C36UAr one of the best choices for studies of membrane structure and membrane-associated proteins.

Critical Sequence Hot-spots for Binding of nCOV-2019 to ACE2 as Evaluated by Molecular Simulations

The novel coronavirus (nCOV-2019) outbreak has put the world on edge, causing millions of cases and hundreds of thousands of deaths all around the world, as of June 2020, let alone the societal and economic impacts of the crisis. The spike protein of nCOV-2019 resides on the virion's surface mediating coronavirus entry into host cells by binding its receptor binding domain (RBD) to the host cell surface receptor protein, angiotensin converter enzyme (ACE2). Our goal is to provide a detailed structural mechanism of how nCOV-2019 recognizes and establishes contacts with ACE2 and its difference with an earlier coronavirus SARS-COV in 2002 via extensive molecular dynamics (MD) simulations. Numerous mutations have been identified in the RBD of nCOV-2019 strains isolated from humans in different parts of the world. In this study, we investigated the effect of these mutations as well as other Ala-scanning mutations on the stability of RBD/ACE2 complex. It is found that most of the naturally-occurring mutations to the RBD either strengthen or have the same binding affinity to ACE2 as the wild-type nCOV-2019. This may have implications for high human-to-human transmission of coronavirus in regions where these mutations have been found as well as any vaccine design endeavors since these mutations could act as antibody escape mutants. Furthermore, in-silico Ala-scanning and long-timescale MD simulations, highlight the crucial role of the residues at the interface of RBD and ACE2 that may be used as potential pharmacophores for any drug development endeavors. From an evolutional perspective, this study also identifies how the virus has evolved from its predecessor SARS-COV and how it could further evolve to become more infectious.

Rapid, quantitative therapeutic screening for Alzheimer's enzymes enabled by optimal signal transduction with transistors

We show that commercially sourced n-channel silicon field-effect transistors (nFETs) operating above their threshold voltage with closed loop feedback to maintain a constant channel current allow a pH readout resolution of (7.2 ± 0.3) × 10-3 at a bandwidth of 10 Hz, or ≈3-fold better than the open loop operation commonly employed by integrated ion-sensitive field-effect transistors (ISFETs). We leveraged the improved nFET performance to measure the change in solution pH arising from the activity of a pathological form of the kinase Cdk5, an enzyme implicated in Alzheimer's disease, and showed quantitative agreement with previous measurements. The improved pH resolution was realized while the devices were operated in a remote sensing configuration with the pH sensing element off-chip and connected electrically to the FET gate terminal. We compared these results with those measured by using a custom-built dual-gate 2D field-effect transistor (dg2DFET) fabricated with 2D semi-conducting MoS2 channels and a signal amplification of 8. Under identical solution conditions the nFET performance approached the dg2DFETs pH resolution of (3.9 ± 0.7) × 10-3. Finally, using the nFETs, we demonstrated the effectiveness of a custom polypeptide, p5, as a therapeutic agent in restoring the function of Cdk5. We expect that the straight-forward modifications to commercially sourced nFETs demonstrated here will lower the barrier to widespread adoption of these remote-gate devices and enable sensitive bioanalytical measurements for high throughput screening in drug discovery and precision medicine applications.

How Do Ethanolamine Plasmalogens Contribute to Order and Structure of Neurological Membranes?

Ethanolamine plasmalogen (EtnPLA) is a conical-shaped ether lipid and an essential component of neurological membranes. Low stability against oxidation limits its study in experiments. The concentration of EtnPLA in the bilayer varies depending on cell type and disease progression. Here we report on mixed bilayers of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and 1-(1Z-octadecenyl)-2-oleoyl-sn-glycero-3-phosphoethanolamine (C18(Plasm)-18:1PE, PLAPE), an EtnPLA lipid subtype, at mole ratios of 2:1, 1:1, and 1:2. We present X-ray diffuse scattering (XDS) form factors F(qz) from oriented stacks of bilayers, related electron-density profiles, and hydrocarbon chain NMR order parameters. To aid future research on EtnPLA lipids and associated proteins, we have also extended the CHARMM36 all-atom force field to include the PLAPE lipid. The ability of the new force-field parameters to reproduce both X-ray and NMR structural properties of the mixed bilayer is remarkable. Our results indicate a thickening of the bilayer upon incorporation of increasing amounts of PLAPE into mixed bilayers, a reduction of lateral area per molecule, and an increase in lipid tail-ordering. The lateral compressibility modulus (KA) calculated from simulations yielded values for PLAPE similar to POPC.

Microsecond-timescale simulations suggest 5-HT-mediated preactivation of the 5-HT3A serotonin receptor

Aided by efforts to improve their speed and efficiency, molecular dynamics (MD) simulations provide an increasingly powerful tool to study the structure-function relationship of pentameric ligand-gated ion channels (pLGICs). However, accurate reporting of the channel state and observation of allosteric regulation by agonist binding with MD remains difficult due to the timescales necessary to equilibrate pLGICs from their artificial and crystalized conformation to a more native, membrane-bound conformation in silico. Here, we perform multiple all-atom MD simulations of the homomeric 5-hydroxytryptamine 3A (5-HT3A) serotonin receptor for 15 to 20 μs to demonstrate that such timescales are critical to observe the equilibration of a pLGIC from its crystalized conformation to a membrane-bound conformation. These timescales, which are an order of magnitude longer than any previous simulation of 5-HT3A, allow us to observe the dynamic binding and unbinding of 5-hydroxytryptamine (5-HT) (i.e., serotonin) to the binding pocket located on the extracellular domain (ECD) and allosteric regulation of the transmembrane domain (TMD) from synergistic 5-HT binding. While these timescales are not long enough to observe complete activation of 5-HT3A, the allosteric regulation of ion gating elements by 5-HT binding is indicative of a preactive state, which provides insight into molecular mechanisms that regulate channel activation from a resting state. This mechanistic insight, enabled by microsecond-timescale MD simulations, will allow a careful examination of the regulation of pLGICs at a molecular level, expanding our understanding of their function and elucidating key structural motifs that can be targeted for therapeutic regulation.