BUMPy: A Model-Independent Tool for Constructing Lipid Bilayers of Varying Curvature and Composition

Exploring the Properties of Curved Lipid Membranes: Comparative Analysis of Atomistic and Coarse-Grained Force Fields

Curvature emerges as a fundamental membrane characteristic crucial for diverse biological processes, including vesicle formation, cell signaling, and membrane trafficking. Increasingly valuable insights into atomistic details governing curvature-dependent membrane properties are provided by computer simulations. Nevertheless, the underlying force field models are conventionally calibrated and tested in relation to experimentally derived parameters of planar bilayers, thereby leaving uncertainties concerning their consistency in reproducing curved lipid systems. In this study we compare the depiction of buckled phosphatidylcholine (POPC) and POPC-cholesterol membranes by four popular force field models. Aside from agreement with respect to general trends in curvature dependence of a number of parameters, we observe a few qualitative differences. Among the most prominent ones is the difference between atomistic and coarse grained force fields in their representation of relative compressibility of the polar headgroup region and hydrophobic lipid core. Through a number of downstream effects, this discrepancy can influence the way in which curvature modulates the behavior of membrane bound proteins depending on the adopted simulation model.

The Secret Ballet Inside Multivesicular Bodies

Lipid bilayers possess the capacity for self-assembly due to the amphipathic nature of lipid molecules, which have both hydrophobic and hydrophilic regions. When confined, lipid bilayers exhibit astonishing versatility in their forms, adopting diverse shapes that are challenging to observe through experimental means. Exploiting this adaptability, lipid structures motivate the development of bio-inspired mechanomaterials and integrated nanobio-interfaces that could seamlessly merge with biological entities, ultimately bridging the gap between synthetic and biological systems. In this work, we demonstrate how, in numerical simulations of multivesicular bodies, a fascinating evolution unfolds from an initial semblance of order toward states of higher entropy over time. We observe dynamic rearrangements in confined vesicles that reveal unexpected limit shapes of distinct geometric patterns. We identify five structures as the basic building blocks that systematically repeat under various conditions of size and composition. Moreover, we observe more complex and less frequent shapes that emerge in confined spaces. Our results provide insights into the dynamics of multivesicular systems, offering a richer understanding of how confined lipid bodies spontaneously self-organize.

Diffusion Analyses along Mean and Gaussian-Curved Membranes with CurD

Curved cellular membranes are both abundant and functionally relevant. While novel tomography approaches reveal the structural details of curved membranes, their dynamics pose an experimental challenge. Curvature especially affects the diffusion of lipids and macromolecules, yet neither experiments nor continuum models distinguish geometric effects from those caused by curvature-induced changes in membrane properties. Molecular simulations could excel here, yet despite community interest toward curved membranes, tools for their analysis are still lacking. Here, we satisfy this demand by introducing CurD, our novel and openly available implementation of the Vertex-oriented Triangle Propagation algorithm to the study of lipid diffusion along membranes with mean and/or Gaussian curvature. This approach, aided by our highly optimized implementation, computes geodetic distances significantly faster than conventional implementations of path-finding algorithms. Our tool, applied to coarse-grained simulations, allows for the first time the analysis of curvature effects on diffusion at size scales relevant to physiological processes such as endocytosis. Our analyses with different membrane geometries reveal that Gaussian curvature plays a surprisingly small role on lipid motion, whereas mean curvature; i.e., the packing of lipid headgroups largely dictates their mobility.

Curvature sensing lipid dynamics in a mitochondrial inner membrane model

Membrane curvature is essential for many cellular structures and processes, and factors such as leaflet asymmetry, lipid composition, and proteins all play important roles. Cardiolipin is the signature lipid of mitochondrial membranes and is essential for maintaining the highly curved shapes of the inner mitochondrial membrane (IMM) and the spatial arrangement of membrane proteins. In this study, we investigate the partitioning behavior of various lipids present in the IMM using coarse-grained molecular dynamics simulations. This study explores curved bilayer systems containing phosphatidylcholine (PC), phosphatidylethanolamine (PE), and cardiolipin (CDL) in binary and ternary component mixtures. Curvature properties such as mean and Gaussian curvatures, as well as the distribution of lipids into the various curved regions of the cristae models, are quantified. Overall, this work represents an advance beyond previous studies on lipid curvature sensing by simulating these systems in a geometry that has the morphological features and scales of curvature consistent with regions of the IMM. We find that CDL has a stronger preference for accumulating in regions of negative curvature than PE lipids, in agreement with previous results. Furthermore, we find lipid partitioning propensity is dominated by sensitivity to mean curvature, while there is a weaker correlation with Gaussian curvature.

Expression of the readthrough transcript CiDRE in alveolar macrophages boosts SARS-CoV-2 susceptibility and promotes COVID-19 severity

Lung infection during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via the angiotensin-I-converting enzyme 2 (ACE2) receptor induces a cytokine storm. However, the precise mechanisms involved in severe COVID-19 pneumonia are unknown. Here, we showed that interleukin-10 (IL-10) induced the expression of ACE2 in normal alveolar macrophages, causing them to become vectors for SARS-CoV-2. The inhibition of this system in hamster models attenuated SARS-CoV-2 pathogenicity. Genome-wide association and quantitative trait locus analyses identified a IFNAR2-IL10RB readthrough transcript, COVID-19 infectivity-enhancing dual receptor (CiDRE), which was highly expressed in patients harboring COVID-19 risk variants at the IFNAR2 locus. We showed that CiDRE exerted synergistic effects via the IL-10-ACE2 axis in alveolar macrophages and functioned as a decoy receptor for type I interferons. Collectively, our data show that high IL-10 and CiDRE expression are potential risk factors for severe COVID-19. Thus, IL-10R and CiDRE inhibitors might be useful COVID-19 therapies.

Understanding Virus Structure and Dynamics through Molecular Simulations

Viral outbreaks remain a serious threat to human and animal populations and motivate the continued development of antiviral drugs and vaccines, which in turn benefits from a detailed understanding of both viral structure and dynamics. While great strides have been made in characterizing these systems experimentally, molecular simulations have proven to be an essential, complementary approach. In this work, we review the contributions of molecular simulations to the understanding of viral structure, functional dynamics, and processes related to the viral life cycle. Approaches ranging from coarse-grained to all-atom representations are discussed, including current efforts at modeling complete viral systems. Overall, this review demonstrates that computational virology plays an essential role in understanding these systems.

CHARMM-GUI Membrane Builder: Past, Current, and Future Developments and Applications

Molecular dynamics simulations of membranes and membrane proteins serve as computational microscopes, revealing coordinated events at the membrane interface. As G protein-coupled receptors, ion channels, transporters, and membrane-bound enzymes are important drug targets, understanding their drug binding and action mechanisms in a realistic membrane becomes critical. Advances in materials science and physical chemistry further demand an atomistic understanding of lipid domains and interactions between materials and membranes. Despite a wide range of membrane simulation studies, generating a complex membrane assembly remains challenging. Here, we review the capability of CHARMM-GUI Membrane Builder in the context of emerging research demands, as well as the application examples from the CHARMM-GUI user community, including membrane biophysics, membrane protein drug-binding and dynamics, protein-lipid interactions, and nano-bio interface. We also provide our perspective on future Membrane Builder development.

Nanoscale membrane curvature sorts lipid phases and alters lipid diffusion

The precise spatiotemporal control of nanoscale membrane shape and composition is the result of a complex interplay of individual and collective molecular behaviors. Here, we employed single-molecule localization microscopy and computational simulations to observe single-lipid diffusion and sorting in model membranes with varying compositions, phases, temperatures, and curvatures. Supported lipid bilayers were created over 50-nm-radius nanoparticles to mimic the size of naturally occurring membrane buds, such as endocytic pits and the formation of viral envelopes. The curved membranes recruited liquid-disordered lipid phases while altering the diffusion and sorting of tracer lipids. Disorder-preferring fluorescent lipids sorted to and experienced faster diffusion on the nanoscale curvature only when embedded in a membrane capable of sustaining lipid phase separation at low temperatures. The curvature-induced sorting and faster diffusion even occurred when the sample temperature was above the miscibility temperature of the planar membrane, implying that the nanoscale curvature could induce phase separation in otherwise homogeneous membranes. Further confirmation and understanding of these results are provided by continuum and coarse-grained molecular dynamics simulations with explicit and spontaneous curvature-phase coupling, respectively. The curvature-induced membrane compositional heterogeneity and altered dynamics were achieved only with a coupling of the curvature with a lipid phase separation. These cross-validating results demonstrate the complex interplay of lipid phases, molecular diffusion, and nanoscale membrane curvature that are critical for membrane functionality.

Molecular Dynamics Simulations of Curved Lipid Membranes

Eukaryotic cells contain membranes with various curvatures, from the near-plane plasma membrane to the highly curved membranes of organelles, vesicles, and membrane protrusions. These curvatures are generated and sustained by curvature-inducing proteins, peptides, and lipids, and describing these mechanisms is an important scientific challenge. In addition to that, some molecules can sense membrane curvature and thereby be trafficked to specific locations. The description of curvature sensing is another fundamental challenge. Curved lipid membranes and their interplay with membrane-associated proteins can be investigated with molecular dynamics (MD) simulations. Various methods for simulating curved membranes with MD are discussed here, including tools for setting up simulation of vesicles and methods for sustaining membrane curvature. The latter are divided into methods that exploit scaffolding virtual beads, methods that use curvature-inducing molecules, and methods applying virtual forces. The variety of simulation tools allow researcher to closely match the conditions of experimental studies of membrane curvatures.

AI-based structure prediction empowers integrative structural analysis of human nuclear pores

INTRODUCTION The eukaryotic nucleus pro-tects the genome and is enclosed by the two membranes of the nuclear envelope. Nuclear pore complexes (NPCs) perforate the nuclear envelope to facilitate nucleocytoplasmic transport. With a molecular weight of ∼120 MDa, the human NPC is one of the larg-est protein complexes. Its ~1000 proteins are taken in multiple copies from a set of about 30 distinct nucleoporins (NUPs). They can be roughly categorized into two classes. Scaf-fold NUPs contain folded domains and form a cylindrical scaffold architecture around a central channel. Intrinsically disordered NUPs line the scaffold and extend into the central channel, where they interact with cargo complexes. The NPC architecture is highly dynamic. It responds to changes in nuclear envelope tension with conforma-tional breathing that manifests in dilation and constriction movements. Elucidating the scaffold architecture, ultimately at atomic resolution, will be important for gaining a more precise understanding of NPC function and dynamics but imposes a substantial chal-lenge for structural biologists. RATIONALE Considerable progress has been made toward this goal by a joint effort in the field. A synergistic combination of complementary approaches has turned out to be critical. In situ structural biology techniques were used to reveal the overall layout of the NPC scaffold that defines the spatial reference for molecular modeling. High-resolution structures of many NUPs were determined in vitro. Proteomic analysis and extensive biochemical work unraveled the interaction network of NUPs. Integra-tive modeling has been used to combine the different types of data, resulting in a rough outline of the NPC scaffold. Previous struc-tural models of the human NPC, however, were patchy and limited in accuracy owing to several challenges: (i) Many of the high-resolution structures of individual NUPs have been solved from distantly related species and, consequently, do not comprehensively cover their human counterparts. (ii) The scaf-fold is interconnected by a set of intrinsically disordered linker NUPs that are not straight-forwardly accessible to common structural biology techniques. (iii) The NPC scaffold intimately embraces the fused inner and outer nuclear membranes in a distinctive topol-ogy and cannot be studied in isolation. (iv) The conformational dynamics of scaffold NUPs limits the resolution achievable in structure determination. RESULTS In this study, we used artificial intelligence (AI)-based prediction to generate an exten-sive repertoire of structural models of human NUPs and their subcomplexes. The resulting models cover various domains and interfaces that so far remained structurally uncharac-terized. Benchmarking against previous and unpublished x-ray and cryo-electron micros-copy structures revealed unprecedented accu-racy. We obtained well-resolved cryo-electron tomographic maps of both the constricted and dilated conformational states of the hu-man NPC. Using integrative modeling, we fit-ted the structural models of individual NUPs into the cryo-electron microscopy maps. We explicitly included several linker NUPs and traced their trajectory through the NPC scaf-fold. We elucidated in great detail how mem-brane-associated and transmembrane NUPs are distributed across the fusion topology of both nuclear membranes. The resulting architectural model increases the structural coverage of the human NPC scaffold by about twofold. We extensively validated our model against both earlier and new experimental data. The completeness of our model has enabled microsecond-long coarse-grained molecular dynamics simulations of the NPC scaffold within an explicit membrane en-vironment and solvent. These simulations reveal that the NPC scaffold prevents the constriction of the otherwise stable double-membrane fusion pore to small diameters in the absence of membrane tension. CONCLUSION Our 70-MDa atomically re-solved model covers >90% of the human NPC scaffold. It captures conforma-tional changes that occur during dilation and constriction. It also reveals the precise anchoring sites for intrinsically disordered NUPs, the identification of which is a prerequisite for a complete and dy-namic model of the NPC. Our study exempli-fies how AI-based structure prediction may accelerate the elucidation of subcellular ar-chitecture at atomic resolution. [Figure: see text].

Assembly and Analysis of Cell-Scale Membrane Envelopes

The march toward exascale computing will enable routine molecular simulation of larger and more complex systems, for example, simulation of entire viral particles, on the scale of approximately billions of atoms─a simulation size commensurate with a small bacterial cell. Anticipating the future hardware capabilities that will enable this type of research and paralleling advances in experimental structural biology, efforts are currently underway to develop software tools, procedures, and workflows for constructing cell-scale structures. Herein, we describe our efforts in developing and implementing an efficient and robust workflow for construction of cell-scale membrane envelopes and embedding membrane proteins into them. A new approach for construction of massive membrane structures that are stable during the simulations is built on implementing a subtractive assembly technique coupled with the development of a structure concatenation tool (fastmerge), which eliminates overlapping elements based on volumetric criteria rather than adding successive molecules to the simulation system. Using this approach, we have constructed two "protocells" consisting of MARTINI coarse-grained beads to represent cellular membranes, one the size of a cellular organelle and another the size of a small bacterial cell. The membrane envelopes constructed here remain whole during the molecular dynamics simulations performed and exhibit water flux only through specific proteins, demonstrating the success of our methodology in creating tight cell-like membrane compartments. Extended simulations of these cell-scale structures highlight the propensity for nonspecific interactions between adjacent membrane proteins leading to the formation of protein microclusters on the cell surface, an insight uniquely enabled by the scale of the simulations. We anticipate that the experiences and best practices presented here will form the basis for the next generation of cell-scale models, which will begin to address the addition of soluble proteins, nucleic acids, and small molecules essential to the function of a cell.

CellSys: An open-source tool for building initial structures for bio-membranes and drug-delivery systems

Since phospholipids are the most important components in the structure of biomembranes, they deserve to be considered with a lot of attention in both experimental and computational theoretical studies using molecular simulation methods related to the research in the fields of drug design and drug delivery where they involve knowledge about the interactions of drug molecules with cell membranes. To employ the molecular simulation approach for this purpose the essential requirement is having information about the initial structure of phospholipids and how they interact with the drugs. Therefore in this article, we introduce an open-source software package in Python programming language for utilizing data manipulation for generation and developing the initial structure of biomolecular cells to provide the needed information for investigation in drug delivery systems. In addition, the proposed software package can be used for the efficient storage of membrane structural data to be exploited in designing new drug delivery systems. To verify the performance of the code and the results of the simulations, several analyses have been done, such as the calculation of area per lipid and self-diffusion coefficient, in addition to lipid order parameter. The results were in complete agreement with the references.

Anisotropic diffusion of membrane proteins at experimental timescales

Single-particle tracking (SPT) experiments of lipids and membrane proteins provide a wealth of information about the properties of biomembranes. Careful analysis of SPT trajectories can reveal deviations from ideal Brownian behavior. Among others, this includes confinement effects and anomalous diffusion, which are manifestations of both the nanoscale structure of the underlying membrane and the structure of the diffuser. With the rapid increase in temporal and spatial resolution of experimental methods, a new aspect of the motion of the particle, namely, anisotropic diffusion, might become relevant. This aspect that so far received only little attention is the anisotropy of the diffusive motion and may soon provide an additional proxy to the structure and topology of biomembranes. Unfortunately, the theoretical framework for detecting and interpreting anisotropy effects is currently scattered and incomplete. Here, we provide a computational method to evaluate the degree of anisotropy directly from molecular dynamics simulations and also point out a way to compare the obtained results with those available from SPT experiments. In order to probe the effects of anisotropic diffusion, we performed coarse-grained molecular dynamics simulations of peripheral and integral membrane proteins in flat and curved bilayers. In agreement with the theoretical basis, our computational results indicate that anisotropy can persist up to the rotational relaxation time [τ=(2D_r)^-1], after which isotropic diffusion is observed. Moreover, the underlying topology of the membrane bilayer can couple with the geometry of the particle, thus extending the spatiotemporal domain over which this type of motion can be detected.

Simulating realistic membrane shapes

Biological membranes exhibit diversity in their shapes and complexity in chemical compositions that are linked to many cellular functions. These two central features of biomembranes have been the subject of numerous simulation studies, using a diverse range of computational techniques. Currently, the field is able to capture this complexity at increasing levels of realism and connect the microscopic view on protein-lipid interactions to cellular morphologies at the level of entire organelles. Here we highlight recent advances in this topic, identify current bottlenecks, and sketch possible ways ahead.

Membrane packing defects in synaptic vesicles recruit complexin and synuclein

Complexin-1 (Cpx) and α-synuclein (α-Syn) are involved in neurotransmitter release through an interaction with synaptic vesicles (SVs). Recent studies demonstrated that Cpx and α-Syn preferentially associate with highly curved membranes, like SVs, to correctly position them for fusion. Here, based on recent experimental results, to further propose a possible explanation for this mechanism, we performed in silico simulations probing interactions between Cpx or α-Syn and membranes of varying curvature. We found that the preferential association is attributed to smaller, curved membranes containing more packing defects that expose hydrophobic acyl tails, which may favorably interact with hydrophobic residues of Cpx and α-Syn. The number of membrane defects is proportional to the curvature and the size can be regulated by cholesterol.

Wrapping Up Viruses at Multiscale Resolution: Optimizing PACKMOL and SIRAH Execution for Simulating the Zika Virus

Simulating huge biomolecular complexes of million atoms at relevant biological time scales is becoming accessible to the broad scientific community. That proves to be crucial for urgent responses against emergent diseases in real time. Yet, there are still issues to sort regarding the system setup so that molecular dynamics (MD) simulations can be run in a simple and standard way. Here, we introduce an optimized pipeline for building and simulating enveloped virus-like particles (VLP). First, the membrane packing problem is tackled with new features and optimized options in PACKMOL. This allows preparing accurate membrane models of thousands of lipids in the context of a VLP within a few hours using a single CPU. Then, the assembly of the VLP system is done within the multiscale framework of the coarse-grained SIRAH force field. Finally, the equilibration protocol provides a system ready for production MD simulations within a few days on broadly accessible GPU resources. The pipeline is applied to study the Zika virus as a test case for large biomolecular systems. The VLP stabilizes at approximately 0.5 μs of MD simulation, reproducing correlations greater than 0.90 against experimental density maps from cryo-electron microscopy. Detailed structural analysis of the protein envelope also shows very good agreement in root-mean-square deviations and B-factors with the experimental data. The level of details attained shows for the first time a possible role for anionic phospholipids in stabilizing the envelope. Combining an efficient and reliable setup procedure with an accurate coarse-grained force field provides a valuable pipeline for simulating arbitrary viral systems or subcellular compartments, paving the way toward whole-cell simulations.

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.

Backmapping triangulated surfaces to coarse-grained membrane models

Many biological processes involve large-scale changes in membrane shape. Computer simulations of these processes are challenging since they occur across a wide range of spatiotemporal scales that cannot be investigated in full by any single current simulation technique. A potential solution is to combine different levels of resolution through a multiscale scheme. Here, we present a multiscale algorithm that backmaps a continuum membrane model represented as a dynamically triangulated surface (DTS) to its corresponding molecular model based on the coarse-grained (CG) Martini force field. Thus, we can use DTS simulations to equilibrate slow large-scale membrane conformational changes and then explore the local properties at CG resolution. We demonstrate the power of our method by backmapping a vesicular bud induced by binding of Shiga toxin and by transforming the membranes of an entire mitochondrion to near-atomic resolution. Our approach opens the way to whole cell simulations at molecular detail.

Computer simulations of large-scale changes in membrane shape are challenging since they occur across a wide range of spatiotemporal scales. Here, authors present a multiscale algorithm that backmaps a continuum membrane model represented as a dynamically triangulated surface to its corresponding molecular model based on the coarse-grained Martini force field.

Understanding the synergistic effect of physicochemical properties of nanoparticles and their cellular entry pathways

Gaining precise control over the cellular entry pathway of nanomaterials is key in achieving cytosolic delivery, accessing subcellular environments, and regulating toxicity. However, this precise control requires a fundamental understanding of the behavior of nanomaterials at the bio-nano interface. Herein, we report a computational study investigating the synergistic effect of several key physicochemical properties of nanomaterials on their cellular entry pathways. By examining interactions between monolayer-protected nanoparticles and model cell membranes in a three-dimensional parameter space of size, surface charge/pKa, and ligand chemistry, we observed four different types of nanoparticle translocation for cellular entry which are: outer wrapping, free translocation, inner attach, and embedment. Nanoparticle size, surface charge/pKa, and ligand chemistry each play a unique role in determining the outcome of translocation. Specifically, membrane local curvature induced by nanoparticles upon contact is critical for initiating the translocation process. A generalized paradigm is proposed to describe the fundamental mechanisms underlying the bio-nano interface.

Lin et al. investigate interactions between monolayer-protected nanoparticles and model cell membranes, and show four different types of nanoparticle translocation, i.e., outer wrapping, free translocation, inner attach, and embedment. The different translocation types greatly depend on synergism between nanoparticle size, surface charge, and ligand chemistry.

GEMS-Pack: A Graphical User Interface for the Packmol Program

We present GEMS-Pack, a graphical user interface for Packmol. Since Packmol is largely used by the molecular simulation community, this work provides a complement to it, in the form of a user-friendly and efficient interface. A tool for number/volume/density calculation is provided to make needed calculations faster. Also, a visualization utility is included, which lets the users preview how their systems will look like even before running the packing procedure. This application does not modify the original Packmol code; it works in a complementary way, by generating the input script and running it through the system's terminal. This program is part of a development project and is intended to be further extended. Two examples are described in this paper to illustrate GEMS-Pack usage.

Role of membrane curvature on the activation/deactivation of Carnitine Palmitoyltransferase 1A: A coarse grain molecular dynamic study

Carnitine Palmitoyltransferase 1A (CPT 1A) is an enzyme anchored to the outer mitochondrial membrane (OMM), where it regulates the passage of fatty acids into the mitochondria and intervenes in the process of β-oxidation of long-chain fatty acids. Although CPT 1A is inhibited by malonyl-CoA, its activity is also modulated by the curvature of OMM. This modulation depends on the behavior of the N-terminal domain (NTD), which can be adsorbed onto the OMM (nonactive CPT 1A) or interacting with the C-terminal domain (active CPT 1A). Aimed to provide mechanistic insights on the regulatory mechanism of CPT 1A, we studied the influence of the bilayer curvature on the NTD behavior through a series of coarse-grained (CG) molecular dynamics simulations using curved and planar membranes. Comparative analysis suggests that the main determinant for the activation/deactivation of the enzyme is the tilt angle orientation of the transmembrane (TM) domains. Planar membranes induce a wide variation on the tilt angle orientation of TM helices, while curved geometries promote small angles with the membrane normal. Our results identify the first TM domain as an important component of the membrane sensing mechanism.

Computational Modeling of Realistic Cell Membranes

Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead.