Investigation of the Effect of Peptide p5 Targeting CDK5-p25 Hyperactivity on Munc18-1 (P67) Regulating Neuronal Exocytosis Using Molecular Simulations.

Munc18-1 is an SM (sec1/munc-like) family protein involved in vesicle fusion and neuronal exocytosis. Munc18-1 is known to regulate the exocytosis process by binding with closed- and open-state conformations of Syntaxin1, a protein belonging to the SNARE family established to be central to the exocytosis process. Our previous work studied peptide p5 as a promising drug candidate for CDK5-p25 complex, an Alzheimer's disease (AD) pathological target. Experimental in vivo and in vitro studies suggest that Munc18-1 promotes p5 to selectively inhibit the CDK5-p25 complex without affecting the endogenous CDK5 activity, a characteristic of remarkable therapeutic implications. In this paper, we identify several binding modes of p5 with Munc18-1 that could potentially affect the Munc18-1 binding with SNARE proteins and lead to off-target effects on neuronal communication using molecular dynamics simulations. Recent studies indicate that disruption of Munc18-1 function not only disrupts neurotransmitter release but also results in neurodegeneration, exhibiting clinical resemblance to other neurodegenerative conditions such as AD, causing diagnostic and treatment challenges. We characterize such interactions between p5 and Munc18-1, define the corresponding pharmacophores, and provide guidance for the in vitro validation of our findings to improve therapeutic efficacy and safety of p5.

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.

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.

Modeling the membrane binding mechanism of a lipid transport protein Osh4 to single membranes.

All-atom (AA) molecular dynamics simulations are used to unravel the binding mechanism of yeast oxysterol binding protein (Osh4) to model membranes with varying anionic lipid concentration using AA and the highly mobile membrane mimetic (HMMM) representations. For certain protein-lipid interactions, an improved forcefield description is used (CUFIX) to accurately describe lipid-protein electrostatic interactions. Our detailed computational studies have identified a single, ß-crease oriented, 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 enable stronger association of the ALPS motif with the membrane lipids through its hydrophobic surface. After the HMMM is converted to AA and equilibrated, the binding is two to three times stronger compared with 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.

GraphVAMPNet, using graph neural networks and variational approach to Markov processes for dynamical modeling of biomolecules.

Finding a low dimensional representation of data from long-timescale trajectories of biomolecular processes, such as protein folding or ligand-receptor binding, is of fundamental importance, and kinetic models, such as Markov modeling, have proven useful in describing the kinetics of these systems. Recently, an unsupervised machine learning technique called VAMPNet was introduced to learn the low dimensional representation and the linear dynamical model in an end-to-end manner. VAMPNet is based on the variational approach for Markov processes and relies on neural networks to learn the coarse-grained dynamics. In this paper, we combine VAMPNet and graph neural networks to generate an end-to-end framework to efficiently learn high-level dynamics and metastable states from the long-timescale molecular dynamics trajectories. This method bears the advantages of graph representation learning and uses graph message passing operations to generate an embedding for each datapoint, which is used in the VAMPNet to generate a coarse-grained dynamical model. This type of molecular representation results in a higher resolution and a more interpretable Markov model than the standard VAMPNet, enabling a more detailed kinetic study of the biomolecular processes. Our GraphVAMPNet approach is also enhanced with an attention mechanism to find the important residues for classification into different metastable states.

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

The ongoing pandemic caused by severe acute respiratory syndrome coronavirus 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 molecular dynamics 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. The roles of multiple glycans in shielding of spike protein in different regions were uncovered by a network analysis, in which 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 intracommunication 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.

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.

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 [Formula: see text] 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 [Formula: see text] and [Formula: see text], 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.

Developing and Testing of Lipid Force Fields with Applications to Modeling Cellular Membranes.

The amphipathic nature of the lipid molecule (hydrophilic head and hydrophobic tails) enables it to act as a barrier between fluids with various properties and to sustain an environment where the processes critical to life may proceed. While computer simulations of biomolecules primarily investigate protein conformation and binding to drug-like molecules, these interactions often occur in the context of a lipid membrane. Chemical specificity of lipid models is essential to accurately represent the complex environment of the lipid membrane. This review discusses the development and performance of currently used chemically specific lipid force fields (FF) such as the CHARMM, AMBER, GROMOS, OPLS, and MARTINI families. Considerations in lipid FF development including lipid diversity, temperature dependence, phase behavior, and effects of atomic polarizability are considered, as well as methods and goals of parametrization. Applications of these FFs to complex and diverse models for cellular membranes are summarized. Lastly, areas for future development, such as efficient inclusion of long-range Lennard-Jones interactions (significant in transitions from polar to apolar media), accurate transmembrane dipole potential, and diffusion under periodic boundary conditions are considered.

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.

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.

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.

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.

Physical Properties of Bacterial Outer Membrane Models: Neutron Reflectometry & Molecular Simulation.

The outer membrane (OM) of Gram-negative bacteria is an asymmetric bilayer having phospholipids in the inner leaflet and lipopolysaccharides in the outer leaflet. This unique asymmetry and the complex carbohydrates in lipopolysaccharides make it a daunting task to study the asymmetrical OM structure and dynamics, its interactions with OM proteins, and its roles in translocation of substrates, including antibiotics. In this study, we combine neutron reflectometry and molecular simulation to explore the physical properties of OM mimetics. There is excellent agreement between experiment and simulation, allowing experimental testing of the conclusions from simulations studies and also atomistic interpretation of the behavior of experimental model systems, such as the degree of lipid asymmetry, the lipid component (tail, head, and sugar) profiles along the bilayer normal, and lateral packing (i.e., average surface area per lipid). Therefore, the combination of both approaches provides a powerful new means to explore the biological and biophysical behavior of the bacterial OM.

Molecular Structure of the Long Periodicity Phase in the Stratum Corneum.

All-atom models of the long periodicity phase (LPP) in the stratum corneum (SC) are studied using bilayer-slab-bilayer (sandwich) structures and multi-microsecond simulations. Linoleate promotes melting of the interior slab, which contains ceramide (Cer) in the posturing chain conformation, a structurally distinct conformation from full chain extension. The mechanism of Cer transitioning into full extension is characterized by initial anchoring of the head-proximal carbons and occurs over tens of nanoseconds. Free fatty acids translocate through the interior over hundreds of nanoseconds, while Cer and cholesterol take around a microsecond or longer to translocate. Electron density and neutron scattering length density profiles from simulation agree with experiment, and the high disorder of linoleate in CerEOS supports experiments with infrared spectroscopy and nuclear magnetic resonance. Lateral organization demonstrates dependence on lipid composition and bilayer thickness. To further validate the LPP model, umbrella sampling was used to calculate ethanol permeability in comparison with experiment (log(P) values obtained from modeling the SC's multiple LPP layers are -7.6 and -6.6 cm/s, and that from experiment on cadaver skin is -6.65 cm/s). A "leapfrog" mechanism for ethanol permeation is proposed which is associated with its role as a topical enhancer. These models, the first experimentally verified atomistic sandwich models of the LPP, will aid in the design and optimization of transdermal drug delivery.

CHARMM-GUI Nanodisc Builder for modeling and simulation of various nanodisc systems.

Nanodiscs are discoidal protein-lipid complexes that have wide applications in membrane protein studies. Modeling and simulation of nanodiscs are challenging due to the absence of structures of many membrane scaffold proteins (MSPs) that wrap around the membrane bilayer. We have developed CHARMM-GUI Nanodisc Builder (http://www.charmm-gui.org/input/nanodisc) to facilitate the setup of nanodisc simulation systems by modeling the MSPs with defined size and known structural features. A total of 11 different nanodiscs with a diameter from 80 to 180 Å are made available in both the all-atom CHARMM and two coarse-grained (PACE and Martini) force fields. The usage of the Nanodisc Builder is demonstrated with various simulation systems. The structures and dynamics of proteins and lipids in these systems were analyzed, showing similar behaviors to those from previous all-atom and coarse-grained nanodisc simulations. We expect the Nanodisc Builder to be a convenient and reliable tool for modeling and simulation of nanodisc systems. © 2019 Wiley Periodicals, Inc.

The Role of Lipid Interactions in Simulations of the α-Hemolysin Ion-Channel-Forming Toxin.

Molecular dynamics simulations were performed to describe the function of the ion-channel-forming toxin α-hemolysin (αHL) in lipid membranes that were composed of either 1,2-diphytanoyl-sn-glycero-3-phospho-choline or 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-choline. The simulations highlight the importance of lipid type in maintaining αHL structure and function, enabling direct comparison to experiments for biosensing applications. We determined that although the two lipids studied are similar in structure, 1,2-diphytanoyl-sn-glycero-3-phospho-choline membranes better match the hydrophobic thickness of αHL compared to 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-choline membranes. This hydrophobic match is essential to maintaining proper alignment of ß-sheet loops at the trans entrance of αHL, which, when disrupted, creates an additional constriction to ion flow that decreases the channel current below experimental values and creates greater variability in channel conductance. Agreement with experiments was further improved with sufficient lipid membrane equilibration and allowed the discrimination of subtle αHL conduction states with lipid type. Finally, we explore the effects of truncating the extramembrane cap of αHL and its role in maintaining proper alignment of αHL in the membrane and channel conductance. Our results demonstrate the essential role of lipid type and lipid-protein interactions in simulations of αHL and will considerably improve the interpretation of experimental data.

Investigation of phase transitions of saturated phosphocholine lipid bilayers via molecular dynamics simulations.

Lipid bilayers play an important role in biological systems as they protect cells against unwanted chemicals and provide a barrier for material inside a cell from leaking out. In this paper, nearly 30 µs of molecular dynamics (MD) simulations were performed to investigate phase transitions of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) and 1,2-dipalmitoyl-sn-glycero-phosphocholine (DPPC) lipid bilayers from the liquid crystalline (Lα) to the ripple (Pß) and to the gel phase (Lß). Our MD simulations accurately predict the main transition temperature for the single-component bilayers. A key focus of this work is to quantify the structure of the Pß phase for DMPC and compare with measures from x-ray experiments. The Pß major arm has similar structure to that of the Lß, while the thinner minor arm has interdigitated chains and the transition region between these two regions has large chain splay and disorder. At lower temperatures, our MD simulations predict the formation of the Lß phase with tilted fatty acid chains. The Pß and Lß phases are studied for mixtures of DMPC and DPPC and compare favorably with experiment. Overall, our MD simulations provide evidence for the relevancy of the CHARMM36 lipid force field for structures and add to our understanding of the less-defined Pß phase.

Perspective: Computational modeling of accurate cellular membranes with molecular resolution.

Modeling lipid bilayers using molecular simulations has progressed from short simulations of single-component lipids to currently having the ability to model complex cellular membranes with nearly 100 different lipid types on a µs time scale. This perspective article presents a review of how the chemical physics field has provided insight into the structure and dynamics of accurate cellular membrane models. A short review of lipid force fields is presented, and how lower-resolution models can allow for assemblies and time scales not attainable with all-atom models. Key examples on membranes that mimic the lipid diversity seen in nature are provided for all-atom and coarse-grained lipid force fields. The article concludes with an outlook for the field on where there exist certain challenges (lipid diversity and leaflet concentration asymmetry) over the next several years. This is an exciting time to be a researcher in the field of modeling cellular membranes with ultimate goals to model not just an accurate cell membrane but in the future modeling a whole cell.