Unbreaking Assemblies in Molecular Simulations with Periodic Boundaries.

In molecular simulations, periodic boundary conditions are typically used to avoid surface effects occurring at the boundaries of the simulation box. A consequence of this is that molecules and assemblies may appear split over the boundaries. Broken molecular assemblies make it difficult to interpret, analyze, and visualize molecular simulation data. We present a general and fast algorithm that repairs molecular assemblies that are broken due to periodic boundary conditions. The open source method presented here, MDVWhole, works for all translation-only crystallographic periodic boundary conditions. The method consumes little memory and can fix the visualization of the assembly of millions of particles in a few seconds. Thus, it is suitable for processing both single simulation frames and long trajectories with millions of points.

Molecular architecture and dynamics of SARS-CoV-2 envelope by integrative modeling.

Despite tremendous efforts, the exact structure of SARS-CoV-2 and related betacoronaviruses remains elusive. SARS-CoV-2 envelope is a key structural component of the virion that encapsulates viral RNA. It is composed of three structural proteins, spike, membrane (M), and envelope, which interact with each other and with the lipids acquired from the host membranes. Here, we developed and applied an integrative multi-scale computational approach to model the envelope structure of SARS-CoV-2 with near atomistic detail, focusing on studying the dynamic nature and molecular interactions of its most abundant, but largely understudied, M protein. The molecular dynamics simulations allowed us to test the envelope stability under different configurations and revealed that the M dimers agglomerated into large, filament-like, macromolecular assemblies with distinct molecular patterns. These results are in good agreement with current experimental data, demonstrating a generic and versatile approach to model the structure of a virus de novo.

Sequential Voxel-Based Leaflet Segmentation of Complex Lipid Morphologies.

As molecular dynamics simulations increase in complexity, new analysis tools are necessary to facilitate interpreting the results. Lipids, for instance, are known to form many complicated morphologies, because of their amphipathic nature, becoming more intricate as the particle count increases. A few lipids might form a micelle, where aggregation of tens of thousands could lead to vesicle formation. Millions of lipids comprise a cell and its organelle membranes, and are involved in processes such as neurotransmission and transfection. To study such phenomena, it is useful to have analysis tools that understand what is meant by emerging entities such as micelles and vesicles. Studying such systems at the particle level only becomes extremely tedious, counterintuitive, and computationally expensive. To address this issue, we developed a method to track all the individual lipid leaflets, allowing for easy and quick detection of topological changes at the mesoscale. By using a voxel-based approach and focusing on locality, we forego costly geometrical operations without losing important details and chronologically identify the lipid segments using the Jaccard index. Thus, we achieve a consistent sequential segmentation on a wide variety of (lipid) systems, including monolayers, bilayers, vesicles, inverted hexagonal phases, up to the membranes of a full mitochondrion. It also discriminates between adhesion and fusion of leaflets. We show that our method produces consistent results without the need for prefitting parameters, and segmentation of millions of particles can be achieved on a desktop machine.

Competing Roles of Ca2+ and Nonmuscle Myosin IIA on the Dynamics of the Metastasis-Associated Protein S100A4.

The calcium-binding protein S100A4 plays an important role in a wide range of biological processes such as cell motility, invasion, angiogenesis, survival, differentiation, contractility, and tumor metastasis and interacts with a range of partners. To understand the functional roles and interplay of S100A4 binding partners such as Ca2+ and nonmuscle myosin IIA (NMIIA), we used molecular dynamics simulations to investigate apo S100A4 and four holo S100A4 structures: S100A4 bound to Ca2+, S100A4 bound to NMIIA, S100A4 bound to Ca2+ and NMIIA, and a mutated S100A4 bound to Ca2+ and NMIIA. Our results show that two competing factors, namely, Ca2+-induced activation and NMIIA-induced inhibition, modulate the dynamics of S100A4 in a competitive manner. Moreover, Ca2+ binding results in enhanced dynamics, regulating the interactions of S100A4 with NMIIA, while NMIIA induces asymmetric dynamics between the chains of S100A4. The results also show that in the absence of Ca2+ the S100A4-NMIIA interaction is weak compared to that of between S100A4 bound to Ca2+ and NMIIA, which may offer a quick response to dropping calcium levels. In addition, certain mutations are shown to play a marked role on the dynamics of S100A4. The results described here contribute to understanding the interactions of S100A4 with NMIIA and the functional roles of Ca2+, NMIIA, and certain mutations on the dynamics of S100A4. The results of this study could be interesting for the development of inhibitors that exploit the shift of balance between the competing roles of Ca2+ and NMIIA.

Retinyl esters form lipid droplets independently of triacylglycerol and seipin.

Lipid droplets store neutral lipids, primarily triacylglycerol and steryl esters. Seipin plays a role in lipid droplet biogenesis and is thought to determine the site of lipid droplet biogenesis and the size of newly formed lipid droplets. Here we show a seipin-independent pathway of lipid droplet biogenesis. In silico and in vitro experiments reveal that retinyl esters have the intrinsic propensity to sequester and nucleate in lipid bilayers. Production of retinyl esters in mammalian and yeast cells that do not normally produce retinyl esters causes the formation of lipid droplets, even in a yeast strain that produces only retinyl esters and no other neutral lipids. Seipin does not determine the size or biogenesis site of lipid droplets composed of only retinyl esters or steryl esters. These findings indicate that the role of seipin in lipid droplet biogenesis depends on the type of neutral lipid stored in forming droplets.

General Protocol for Constructing Molecular Models of Nanodiscs.

Nanodisc technology is increasingly being applied for structural and biophysical studies of membrane proteins. In this work, we present a general protocol for constructing molecular models of nanodiscs for molecular dynamics simulations. The protocol is written in python and based on geometric equations, making it fast and easy to modify, enabling automation and customization of nanodiscs in silico. The novelty being the ability to construct any membrane scaffold protein (MSP) variant fast and easy given only an input sequence. We validated and tested the protocol by simulating seven different nanodiscs of various sizes and with different membrane scaffold proteins, both circularized and noncircularized. The structural and biophysical properties were analyzed and shown to be in good agreement with previously reported experimental data and simulation studies.

Asymmetric CorA Gating Mechanism as Observed by Molecular Dynamics Simulations.

The CorA family of proteins plays a housekeeping role in the homeostasis of divalent metal ions in many bacteria and archaea as well as in mitochondria of eukaryotes, rendering it an important target to study the mechanisms of divalent transport and regulation across different life domains. Despite numerous studies, the mechanistic details of the channel gating and the transport of the metal ions are still not entirely understood. Here, we use all-atom and coarse-grained molecular dynamics simulations combined with in vitro experiments to investigate the influence of divalent cations on the function of CorA. Simulations reveal pronounced asymmetric movements of monomers that enable the rotation of the α7 helix and the cytoplasmic subdomain with the subsequent formation of new interactions and the opening of the channel. These computational results are functionally validated using site-directed mutagenesis of the intracellular cytoplasmic domain residues and biochemical assays. The obtained results infer a complex network of interactions altering the structure of CorA to allow gating. Furthermore, we attempt to reconcile the existing gating hypotheses for CorA to conclude the mechanism of transport of divalent cations via these proteins.

Martini 3: a general purpose force field for coarse-grained molecular dynamics.

The coarse-grained Martini force field is widely used in biomolecular simulations. Here we present the refined model, Martini 3 ( http://cgmartini.nl ), with an improved interaction balance, new bead types and expanded ability to include specific interactions representing, for example, hydrogen bonding and electronic polarizability. The updated model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.

Structural characterization of supramolecular hollow nanotubes with atomistic simulations and SAXS.

Self-assembled nanostructures arise when building blocks spontaneously organize into ordered aggregates that exhibit different properties compared to the disorganized monomers. Here, we study an amphiphilic cyanine dye (C8S3) that is known to self-assemble into double-walled, hollow, nanotubes with interesting optical properties. The molecular packing of the dyes inside the nanotubes, however, remains elusive. To reveal the structural features of the C8S3 nanotubes, we performed atomistic Molecular Dynamics simulations of preformed bilayers and nanotubes. We find that different packing arrangements lead to stable structures, in which the tails of the C8S3 molecules are interdigitated. Our results are verified by SAXS experiments. Together our data provide a detailed structural characterization of the C8S3 nanotubes. Furthermore, our approach was able to resolve the ambiguity inherent from cryo-TEM measurements in calculating the wall thickness of similar systems. The insights obtained are expected to be generally useful for understanding and designing other supramolecular assemblies.

Lipid-dependent conformational landscape of the ErbB2 growth factor receptor dimers.

Altered lipid metabolism has been linked to cancer development and progression. Several roles have been attributed to the increased saturation and length of lipid acyl tails observed in tumors, but its effect on signaling receptors is still emerging. In this work, we have analyzed the lipid dependence of the ErbB2 growth factor receptor dimerization that plays an important role in the pathogenesis of breast cancer. We have performed coarse-grain ensemble molecular dynamics simulations to comprehensively sample the ErbB2 monomer-dimer association. Our results indicate a dynamic dimer state with a complex conformational landscape that is modulated with increasing lipid tail length. We resolve the native N-terminal "active" and C-terminal "inactive" conformations in all membrane compositions. However, the relative population of the N-terminal and C-terminal conformers is dependent on length of the saturated lipid tails. In short-tail membranes, additional non-specific dimers are observed which are reduced or absent in long-tailed bilayers. Our results indicate that the relative population as well as the structure of the dimer state is modulated by membrane composition. We have correlated these differences to local perturbations of the membrane around the receptor. Our work is an important step in characterizing ErbB dimers in healthy and diseased states and emphasize the importance of sampling lipid dynamics in understanding receptor association.

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.

Charge-dependent interactions of monomeric and filamentous actin with lipid bilayers.

The cytoskeletal protein actin polymerizes into filaments that are essential for the mechanical stability of mammalian cells. In vitro experiments showed that direct interactions between actin filaments and lipid bilayers are possible and that the net charge of the bilayer as well as the presence of divalent ions in the buffer play an important role. In vivo, colocalization of actin filaments and divalent ions are suppressed, and cells rely on linker proteins to connect the plasma membrane to the actin network. Little is known, however, about why this is the case and what microscopic interactions are important. A deeper understanding is highly beneficial, first, to obtain understanding in the biological design of cells and, second, as a possible basis for the building of artificial cortices for the stabilization of synthetic cells. Here, we report the results of coarse-grained molecular dynamics simulations of monomeric and filamentous actin in the vicinity of differently charged lipid bilayers. We observe that charges on the lipid head groups strongly determine the ability of actin to adsorb to the bilayer. The inclusion of divalent ions leads to a reversal of the binding affinity. Our in silico results are validated experimentally by reconstitution assays with actin on lipid bilayer membranes and provide a molecular-level understanding of the actin-membrane interaction.

LION/web: a web-based ontology enrichment tool for lipidomic data analysis.

BACKGROUND: A major challenge for lipidomic analyses is the handling of the large amounts of data and the translation of results to interpret the involvement of lipids in biological systems. RESULTS: We built a new lipid ontology (LION) that associates >50,000 lipid species to biophysical, chemical, and cell biological features. By making use of enrichment algorithms, we used LION to develop a web-based interface (LION/web, www.lipidontology.com) that allows identification of lipid-associated terms in lipidomes. LION/web was validated by analyzing a lipidomic dataset derived from well-characterized sub-cellular fractions of RAW 264.7 macrophages. Comparison of isolated plasma membranes with the microsomal fraction showed a significant enrichment of relevant LION-terms including "plasma membrane", "headgroup with negative charge", "glycerophosphoserines", "above average bilayer thickness", and "below average lateral diffusion". A second validation was performed by analyzing the membrane fluidity of Chinese hamster ovary cells incubated with arachidonic acid. An increase in membrane fluidity was observed both experimentally by using pyrene decanoic acid and by using LION/web, showing significant enrichment of terms associated with high membrane fluidity ("above average", "very high", and "high lateral diffusion" and "below average transition temperature"). CONCLUSIONS: The results demonstrate the functionality of LION/web, which is freely accessible in a platform-independent way.

Statistical efficiency of methods for computing free energy of hydration.

The hydration free energy (HFE) is a critical property for predicting and understanding chemical and biological processes in aqueous solution. There are a number of computational methods to derive HFE, generally classified into the equilibrium or non-equilibrium methods, based on the type of calculations used. In the present study, we compute the hydration free energies of 34 small, neutral, organic molecules with experimental HFE between +2 and -16 kcal/mol. The one-sided non-equilibrium methods Jarzynski Forward (JF) and Backward (JB), the two-sided non-equilibrium methods Jarzynski mean based on the average of JF and JB, Crooks Gaussian Intersection (CGI), and the Bennett Acceptance Ratio (BAR) are compared to the estimates from the two-sided equilibrium method Multistate Bennett Acceptance Ratio (MBAR), which is considered as the reference method for HFE calculations, and experimental data from the literature. Our results show that the estimated hydration free energies from all the methods are consistent with MBAR results, and all methods provide a mean absolute error of ∼0.8 kcal/mol and root mean square error of ∼1 kcal for the 34 organic molecules studied. In addition, the results show that one-sided methods JF and JB result in systematic deviations that cannot be corrected entirely. The statistical efficiency ε of the different methods can be expressed as the one over the simulation time times the average variance in the HFE. From such an analysis, we conclude that ε(MBAR) > ε(BAR) ≈ ε(CGI) > ε(JX), where JX is any of the Jarzynski methods. In other words, the non-equilibrium methods tested here for the prediction of HFE have lower computational efficiency than the MBAR method.

Lipid-Protein Interactions Are Unique Fingerprints for Membrane Proteins.

Cell membranes contain hundreds of different proteins and lipids in an asymmetric arrangement. Our current understanding of the detailed organization of cell membranes remains rather elusive, because of the challenge to study fluctuating nanoscale assemblies of lipids and proteins with the required spatiotemporal resolution. Here, we use molecular dynamics simulations to characterize the lipid environment of 10 different membrane proteins. To provide a realistic lipid environment, the proteins are embedded in a model plasma membrane, where more than 60 lipid species are represented, asymmetrically distributed between the leaflets. The simulations detail how each protein modulates its local lipid environment in a unique way, through enrichment or depletion of specific lipid components, resulting in thickness and curvature gradients. Our results provide a molecular glimpse of the complexity of lipid-protein interactions, with potentially far-reaching implications for our understanding of the overall organization of real cell membranes.

Dopamine transporter oligomerization involves the scaffold domain, but spares the bundle domain.

The human dopamine transporter (hDAT) is located on presynaptic neurons, where it plays an essential role in limiting dopaminergic signaling by temporarily curtailing high neurotransmitter concentration through rapid re-uptake. Transport by hDAT is energized by transmembrane ionic gradients. Dysfunction of this transporter leads to disease states, such as Parkinson's disease, bipolar disorder or depression. It has been shown that hDAT and other members of the monoamine transporter family exist in oligomeric forms at the plasma membrane. Several residues are known to be involved in oligomerization, but interaction interfaces, oligomer orientation and the quarternary arrangement in the plasma membrane remain poorly understood. Here we examine oligomeric forms of hDAT using a direct approach, by following dimerization of two randomly-oriented hDAT transporters in 512 independent simulations, each being 2 µs in length. We employed the DAFT (docking assay for transmembrane components) approach, which is an unbiased molecular dynamics simulation method to identify oligomers, their conformations and populations. The overall ensemble of a total of >1 ms simulation time revealed a limited number of symmetric and asymmetric dimers. The identified dimer interfaces include all residues known to be involved in dimerization. Importantly, we find that the surface of the bundle domain is largely excluded from engaging in dimeric interfaces. Such an interaction would typically lead to inhibition by stabilization of one conformation, while substrate transport relies on a large scale rotation between the inward-facing and the outward-facing state.

eTOX ALLIES: an automated pipeLine for linear interaction energy-based simulations.

BACKGROUND: Computational methods to predict binding affinities of small ligands toward relevant biological (off-)targets are helpful in prioritizing the screening and synthesis of new drug candidates, thereby speeding up the drug discovery process. However, use of ligand-based approaches can lead to erroneous predictions when structural and dynamic features of the target substantially affect ligand binding. Free energy methods for affinity computation can include steric and electrostatic protein-ligand interactions, solvent effects, and thermal fluctuations, but often they are computationally demanding and require a high level of supervision. As a result their application is typically limited to the screening of small sets of compounds by experts in molecular modeling. RESULTS: We have developed eTOX ALLIES, an open source framework that allows the automated prediction of ligand-binding free energies requiring the ligand structure as only input. eTOX ALLIES is based on the linear interaction energy approach, an efficient end-point free energy method derived from Free Energy Perturbation theory. Upon submission of a ligand or dataset of compounds, the tool performs the multiple steps required for binding free-energy prediction (docking, ligand topology creation, molecular dynamics simulations, data analysis), making use of external open source software where necessary. Moreover, functionalities are also available to enable and assist the creation and calibration of new models. In addition, a web graphical user interface has been developed to allow use of free-energy based models to users that are not an expert in molecular modeling. CONCLUSIONS: Because of the user-friendliness, efficiency and free-software licensing, eTOX ALLIES represents a novel extension of the toolbox for computational chemists, pharmaceutical scientists and toxicologists, who are interested in fast affinity predictions of small molecules toward biological (off-)targets for which protein flexibility, solvent and binding site interactions directly affect the strength of ligand-protein binding.

Dynamic Cholesterol-Conditioned Dimerization of the G Protein Coupled Chemokine Receptor Type 4.

G protein coupled receptors (GPCRs) allow for the transmission of signals across biological membranes. For a number of GPCRs, this signaling was shown to be coupled to prior dimerization of the receptor. The chemokine receptor type 4 (CXCR4) was reported before to form dimers and their functionality was shown to depend on membrane cholesterol. Here, we address the dimerization pattern of CXCR4 in pure phospholipid bilayers and in cholesterol-rich membranes. Using ensembles of molecular dynamics simulations, we show that CXCR4 dimerizes promiscuously in phospholipid membranes. Addition of cholesterol dramatically affects the dimerization pattern: cholesterol binding largely abolishes the preferred dimer motif observed for pure phospholipid bilayers formed mainly by transmembrane helices 1 and 7 (TM1/TM5-7) at the dimer interface. In turn, the symmetric TM3,4/TM3,4 interface is enabled first by intercalating cholesterol molecules. These data provide a molecular basis for the modulation of GPCR activity by its lipid environment.

A MoS2-Based Capacitive Displacement Sensor for DNA Sequencing.

We propose an aqueous functionalized molybdenum disulfide nanoribbon suspended over a solid electrode as a capacitive displacement sensor aimed at determining the DNA sequence. The detectable sequencing events arise from the combination of Watson-Crick base-pairing, one of nature's most basic lock-and-key binding mechanisms, with the ability of appropriately sized atomically thin membranes to flex substantially in response to subnanonewton forces. We employ carefully designed numerical simulations and theoretical estimates to demonstrate excellent (79% to 86%) raw target detection accuracy at ∼70 million bases per second and electrical measurability of the detected events. In addition, we demonstrate reliable detection of repeated DNA motifs. Finally, we argue that the use of a nanoscale opening (nanopore) is not requisite for the operation of the proposed sensor and present a simplified sensor geometry without the nanopore as part of the sensing element. Our results, therefore, potentially suggest a realistic, inherently base-specific, high-throughput electronic DNA sequencing device as a cost-effective de novo alternative to the existing methods.

Nucleobase-functionalized graphene nanoribbons for accurate high-speed DNA sequencing.

We propose a water-immersed nucleobase-functionalized suspended graphene nanoribbon as an intrinsically selective device for nucleotide detection. The proposed sensing method combines Watson-Crick selective base pairing with graphene's capacity for converting anisotropic lattice strain to changes in an electrical current at the nanoscale. Using detailed atomistic molecular dynamics (MD) simulations, we study sensor operation at ambient conditions. We combine simulated data with theoretical arguments to estimate the levels of measurable electrical signal variation in response to strains and determine that the proposed sensing mechanism shows significant promise for realistic DNA sensing devices without the need for advanced data processing, or highly restrictive operational conditions.