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.

Facilitating CG Simulations with MAD: The MArtini Database Server.

The MArtini Database (MAD - https://mad.ibcp.fr) is a web server designed for the sharing of structures and topologies of molecules parametrized with the Martini coarse-grained (CG) force field. MAD can also convert atomistic structures into CG structures and prepare complex systems (including proteins, lipids, etc.) for molecular dynamics (MD) simulations at the CG level. It is dedicated to the generation of input files for Martini 3, the most recent version of this popular CG force field. Specifically, the MAD server currently includes tools to submit or retrieve CG models of a wide range of molecules (lipids, carbohydrates, nanoparticles, etc.), transform atomistic protein structures into CG structures and topologies, with fine control on the process and assemble biomolecules into large systems, and deliver all files necessary to start simulations in the GROMACS MD engine.

The C-terminal Domains of Apoptotic BH3-only Proteins Mediate Their Insertion into Distinct Biological Membranes.

Changes in the equilibrium of pro- and anti-apoptotic members of the B-cell lymphoma-2 (Bcl-2) protein family in the mitochondrial outer membrane (MOM) induce structural changes that commit cells to apoptosis. Bcl-2 homology-3 (BH3)-only proteins participate in this process by either activating pro-apoptotic effectors or inhibiting anti-apoptotic components and by promoting MOM permeabilization. The association of BH3-only proteins with MOMs is necessary for the activation and amplification of death signals; however, the nature of this association remains controversial, as these proteins lack a canonical transmembrane sequence. Here we used an in vitro expression system to study the insertion capacity of hydrophobic C-terminal regions of the BH3-only proteins Bik, Bim, Noxa, Bmf, and Puma into microsomal membranes. An Escherichia coli complementation assay was used to validate the results in a cellular context, and peptide insertions were modeled using molecular dynamics simulations. We also found that some of the C-terminal domains were sufficient to direct green fluorescent protein fusion proteins to specific membranes in human cells, but the domains did not activate apoptosis. Thus, the hydrophobic regions in the C termini of BH3-only members associated in distinct ways with various biological membranes, suggesting that a detailed investigation of the entire process of apoptosis should include studying the membranes as a setting for protein-protein and protein-membrane interactions.

Gold nanoparticles in model biological membranes: A computational perspective.

The electronic, optical, catalytic, and magnetic properties of metal nanoparticles (NPs) make them extremely interesting for biomedical applications. In this rapidly moving field, monolayer-protected gold nanoparticles emerge both as a reference system and as promising candidates for drug and gene delivery, photothermal treatment, and imaging applications. Despite the technological relevance, there is still poor understanding of the molecular processes driving the interactions of metal nanoparticles with cells, and with cell membranes in particular. In this paper we review molecular-level computational studies of the interaction between monolayer-protected gold NPs and model lipid membranes. Our review comprises a brief description of the most relevant experimental results in this field and of the questions they raised, followed by a description of the computational achievements reported so far. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.

Molecular electrometer and binding of cations to phospholipid bilayers.

Despite the vast amount of experimental and theoretical studies on the binding affinity of cations - especially the biologically relevant Na+ and Ca2+ - for phospholipid bilayers, there is no consensus in the literature. Here we show that by interpreting changes in the choline headgroup order parameters according to the 'molecular electrometer' concept [Seelig et al., Biochemistry, 1987, 26, 7535], one can directly compare the ion binding affinities between simulations and experiments. Our findings strongly support the view that in contrast to Ca2+ and other multivalent ions, Na+ and other monovalent ions (except Li+) do not specifically bind to phosphatidylcholine lipid bilayers at sub-molar concentrations. However, the Na+ binding affinity was overestimated by several molecular dynamics simulation models, resulting in artificially positively charged bilayers and exaggerated structural effects in the lipid headgroups. While qualitatively correct headgroup order parameter response was observed with Ca2+ binding in all the tested models, no model had sufficient quantitative accuracy to interpret the Ca2+:lipid stoichiometry or the induced atomistic resolution structural changes. All scientific contributions to this open collaboration work were made publicly, using nmrlipids.blogspot.fi as the main communication platform.

Plasticity and conformational equilibria of influenza fusion peptides in model lipid bilayers.

Membrane fusion is critical to eukaryotic cellular function and crucial to the entry of enveloped viruses such as influenza and human immunodeficiency virus. Influenza viral entry in the host cell is mediated by a 20-23 amino acid long sequence, called the fusion peptide. In the last years, possible structures for the fusion peptide and their implication in the membrane fusion initiation have been proposed; these ranging from an inverted V shaped α-helical structure to an α-helical hairpin, or to a complete α-helix. Here we develop a coarse grained approach to describe effectively the plasticity of the fusion peptide and the explored conformational states. We describe also a trimeric assembly for the fusion peptide and analyse the explored states in a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine model membrane. For the single fusion peptide systems the kink angle observed experimentally for the V shaped structure shows a strong correlation with the orientation of the fusion peptide within the lipid bilayer. The trimeric fusion peptide model also experiences different conformational states and represents a more realistic model for the anchoring mechanism of one influenza haemagglutinin molecule. This article is part of a Special Issue entitled: Viral Membrane Proteins - Channels for Cellular Networking.

Hydrophobic compounds reshape membrane domains.

Cell membranes have a complex lateral organization featuring domains with distinct composition, also known as rafts, which play an essential role in cellular processes such as signal transduction and protein trafficking. In vivo, perturbations of membrane domains (e.g., by drugs or lipophilic compounds) have major effects on the activity of raft-associated proteins and on signaling pathways, but they are difficult to characterize because of the small size of the domains, typically below optical resolution. Model membranes, instead, can show macroscopic phase separation between liquid-ordered and liquid-disordered domains, and they are often used to investigate the driving forces of membrane lateral organization. Studies in model membranes have shown that some lipophilic compounds perturb membrane domains, but it is not clear which chemical and physical properties determine domain perturbation. The mechanisms of domain stabilization and destabilization are also unknown. Here we describe the effect of six simple hydrophobic compounds on the lateral organization of phase-separated model membranes consisting of saturated and unsaturated phospholipids and cholesterol. Using molecular simulations, we identify two groups of molecules with distinct behavior: aliphatic compounds promote lipid mixing by distributing at the interface between liquid-ordered and liquid-disordered domains; aromatic compounds, instead, stabilize phase separation by partitioning into liquid-disordered domains and excluding cholesterol from the disordered domains. We predict that relatively small concentrations of hydrophobic species can have a broad impact on domain stability in model systems, which suggests possible mechanisms of action for hydrophobic compounds in vivo.

Calculating the free energy of transfer of small solutes into a model lipid membrane: Comparison between metadynamics and umbrella sampling.

We compare the performance of two well-established computational algorithms for the calculation of free-energy landscapes of biomolecular systems, umbrella sampling and metadynamics. We look at benchmark systems composed of polyethylene and polypropylene oligomers interacting with lipid (phosphatidylcholine) membranes, aiming at the calculation of the oligomer water-membrane free energy of transfer. We model our test systems at two different levels of description, united-atom and coarse-grained. We provide optimized parameters for the two methods at both resolutions. We devote special attention to the analysis of statistical errors in the two different methods and propose a general procedure for the error estimation in metadynamics simulations. Metadynamics and umbrella sampling yield the same estimates for the water-membrane free energy profile, but metadynamics can be more efficient, providing lower statistical uncertainties within the same simulation time.

Stable polyglutamine dimers can contain ß-hairpins with interdigitated side chains-but not α-helices, ß-nanotubes, ß-pseudohelices, or steric zippers.

A common thread connecting nine fatal neurodegenerative protein aggregation diseases is an abnormally expanded polyglutamine tract found in the respective proteins. Although the structure of this tract in the large mature aggregates is increasingly well described, its structure in the small early aggregates remains largely unknown. As experimental evidence suggests that the most toxic species along the aggregation pathway are the small early ones, developing strategies to alleviate disease pathology calls for understanding the structure of polyglutamine peptides in the early stages of aggregation. Here, we present a criterion, grounded in available experimental data, that allows for using kinetic stability of dimers to assess whether a given polyglutamine conformer can be on the aggregation path. We then demonstrate that this criterion can be assessed using present-day molecular dynamics simulations. We find that although the α-helical conformer of polyglutamine is very stable, dimers of α-helices lack the kinetic stability necessary to support further oligomerization. Dimers of steric zipper, ß-nanotube, and ß-pseudohelix conformers are also too short-lived to initiate aggregation. The ß-hairpin-containing conformers, instead, invariably form very stable dimers when their side chains are interdigitated. Combining these findings with the implications of recent solid-state NMR data on mature fibrils, we propose a possible pathway for the initial stages of polyglutamine aggregation, in which ß-hairpin-containing conformers act as templates for fibril formation.

Lipid membranes as solvents for carbon nanoparticles.

Fullerene is scarcely soluble in most solvents, including alkanes. Yet, it has been shown that C60 dissolves in lipid bilayers, whose interior is chemically identical to alkanes. Here, we use molecular simulations to explain why lipid bilayers are better than alkanes at dissolving fullerene clusters. Fullerene aggregation is driven by entropy, but enthalpic contributions determine the difference between alkanes and bilayers. Surprisingly, confinement and chain alignment in the bilayer do not affect fullerene aggregation, while solvent density and the perturbation of solvent-solvent interactions are key factors.

The molecular structure of a phosphatidylserine bilayer determined by scattering and molecular dynamics simulations.

Phosphatidylserine (PS) lipids play essential roles in biological processes, including enzyme activation and apoptosis. We report on the molecular structure and atomic scale interactions of a fluid bilayer composed of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylserine (POPS). A scattering density profile model, aided by molecular dynamics (MD) simulations, was developed to jointly refine different contrast small-angle neutron and X-ray scattering data, which yielded a lipid area of 62.7 Å(2) at 25 °C. MD simulations with POPS lipid area constrained at different values were also performed using all-atom and aliphatic united-atom models. The optimal simulated bilayer was obtained using a model-free comparison approach. Examination of the simulated bilayer, which agrees best with the experimental scattering data, reveals a preferential interaction between Na(+) ions and the terminal serine and phosphate moieties. Long-range inter-lipid interactions were identified, primarily between the positively charged ammonium, and the negatively charged carboxylic and phosphate oxygens. The area compressibility modulus KA of the POPS bilayer was derived by quantifying lipid area as a function of surface tension from area-constrained MD simulations. It was found that POPS bilayers possess a much larger KA than that of neutral phosphatidylcholine lipid bilayers. We propose that the unique molecular features of POPS bilayers may play an important role in certain physiological functions.

Predicting lipid sorting in curved membranes.

Most biological membranes are curved, and both lipids and proteins play a role in generating curvature. For any given membrane shape and composition, it is not trivial to determine whether lipids are laterally distributed in a homogeneous or inhomogeneous way, and whether the inter-leaflet distribution is symmetric or not. Here we present a simple computational tool that allows to predict the preference of any lipid type for membranes with positive vs. negative curvature, for any given value of curvature. The tool is based on molecular dynamics simulations of tubular membranes with hydrophilic pores. The pores allow spontaneous, barrierless flip-flop of most lipids, while also preventing differences in pressure between the inner and outer water compartments and minimizing membrane asymmetric stresses. Specifically, we provide scripts to build and analyze the simulations. We test the tool by performing simulations on simple binary lipid mixtures, and we show that, as expected, lipids with negative intrinsic curvature distribute to the tubule inner leaflet, the more so when the radius of the tubular membrane is small. Compared to other existing computational methods, relying on membrane buckles and tethers, our method is based on spontaneous inter-leaflet transport of lipids, and therefore allows to explore lipid distribution in asymmetric membranes. The method can easily be adapted to work with any molecular dynamics code and any force field.

Overlay databank unlocks data-driven analyses of biomolecules for all.

Tools based on artificial intelligence (AI) are currently revolutionising many fields, yet their applications are often limited by the lack of suitable training data in programmatically accessible format. Here we propose an effective solution to make data scattered in various locations and formats accessible for data-driven and machine learning applications using the overlay databank format. To demonstrate the practical relevance of such approach, we present the NMRlipids Databank-a community-driven, open-for-all database featuring programmatic access to quality-evaluated atom-resolution molecular dynamics simulations of cellular membranes. Cellular membrane lipid composition is implicated in diseases and controls major biological functions, but membranes are difficult to study experimentally due to their intrinsic disorder and complex phase behaviour. While MD simulations have been useful in understanding membrane systems, they require significant computational resources and often suffer from inaccuracies in model parameters. Here, we demonstrate how programmable interface for flexible implementation of data-driven and machine learning applications, and rapid access to simulation data through a graphical user interface, unlock possibilities beyond current MD simulation and experimental studies to understand cellular membranes. The proposed overlay databank concept can be further applied to other biomolecules, as well as in other fields where similar barriers hinder the AI revolution.

Mechanism for translocation of fluoroquinolones across lipid membranes.

Classical atom-scale molecular dynamics simulations, constrained free energy calculations, and quantum mechanical (QM) calculations are employed to study the diffusive translocation of ciprofloxacin (CPFX) across lipid membranes. CPFX is considered here as a representative of the fluoroquinolone antibiotics class. Neutral and zwitterionic CPFX coexist at physiological pH, with the latter being predominant. Simulations reveal that only the neutral form permeates the bilayer, and it does so through a novel mechanism that involves dissolution of concerted stacks of zwitterionic ciprofloxacins. Subsequent QM analysis of the observed molecular stacking shows the important role of partial charge neutralization in the stacks, highlighting how the zwitterionic form of the drug is neutralized for translocation. The findings propose a translocation mechanism in which zwitterionic CPFX molecules approach the membrane in stacks, but they diffuse through the membrane as neutral CPFX monomers due to intermolecular transfer of protons favored by partial solvation loss. The mechanism is expected to be of importance in the permeation and translocation of a variety of ampholitic drugs with stacking tendencies.

CGCompiler: Automated Coarse-Grained Molecule Parametrization via Noise-Resistant Mixed-Variable Optimization.

Coarse-grained force fields (CG FFs) such as the Martini model entail a predefined, fixed set of Lennard-Jones parameters (building blocks) to model virtually all possible nonbonded interactions between chemically relevant molecules. Owing to its universality and transferability, the building-block coarse-grained approach has gained tremendous popularity over the past decade. The parametrization of molecules can be highly complex and often involves the selection and fine-tuning of a large number of parameters (e.g., bead types and bond lengths) to optimally match multiple relevant targets simultaneously. The parametrization of a molecule within the building-block CG approach is a mixed-variable optimization problem: the nonbonded interactions are discrete variables, whereas the bonded interactions are continuous variables. Here, we pioneer the utility of mixed-variable particle swarm optimization in automatically parametrizing molecules within the Martini 3 coarse-grained force field by matching both structural (e.g., RDFs) as well as thermodynamic data (phase-transition temperatures). For the sake of demonstration, we parametrize the linker of the lipid sphingomyelin. The important advantage of our approach is that both bonded and nonbonded interactions are simultaneously optimized while conserving the search efficiency of vector guided particle swarm optimization (PSO) methods over other metaheuristic search methods such as genetic algorithms. In addition, we explore noise-mitigation strategies in matching the phase-transition temperatures of lipid membranes, where nucleation and concomitant hysteresis introduce a dominant noise term within the objective function. We propose that noise-resistant mixed-variable PSO methods can both improve and automate parametrization of molecules within building-block CG FFs, such as Martini.

Pragmatic Coarse-Graining of Proteins: Models and Applications.

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

Interaction of C70 fullerene with the Kv1.2 potassium channel.

Fullerene C(70) is known to partition into lipid membranes and change their physical properties. Together with gallic acid (GA), C(70) induces cell contraction and cell death. How C(70) and GA-induced perturbations of lipid membranes affect cellular function and membrane protein activity is not understood, though. Meanwhile, fullerene is also known to interfere with the activity of potassium channel proteins, but the mechanisms of protein inhibition are not known. Here we consider the possibility that membrane protein function would be inhibited by C(70) and/or GA through direct contact or through lipid-mediated interactions. To this end, we use microsecond time scale atomistic simulations to explore (a) modifications of membrane properties in the presence of C(70) and/or GA, and (b) the possible conformational changes in Kv1.2, a voltage-gated potassium channel, upon exposure to C(70), or GA, or both. C(70) is found to have an observable effect on structural and elastic properties of protein-free membranes, while the effects of GA on the membrane are less evident. Fullerene­GA interaction is strong and affects significantly the partitioning of C(70) in the membrane, stabilizing C(70) in the aqueous phase. When Kv1.2 is exposed to the solutes, only small conformational changes are observed on the microsecond time scale ­ comparable to the fluctuations observed in the absence of any solute. Blocking of the channel entrance is not observed, as fullerene binds mainly to hydrophobic residues, both in the water-exposed loops and in the transmembrane helices. The tilt angle of transmembrane helices in the voltage-sensing domain appears to be affected by direct contact with fullerene, but a generic effect due to the small increase in membrane thickness might also play a role. A small rotation of the S3 and S4 helices in the voltage-sensing domain is noticed when C(70) is embedded in the membrane. The interpretation of the observed conformational changes is not straightforward due to the associated time scales, which are difficult to sample with state-of-the-art computing resources. We cannot exclude that both membrane-mediated interactions and specific protein­solute interactions affect the conformation of the protein.

Interaction of Phthalates with Lipid Bilayer Membranes.

Phthalates are esters of phthalic acid, widely used as additives in the manufacture of plastics. They are not covalently linked to polymer chains and can easily leach out, disperse in the environment, and get into contact with living organisms. Several short chain phthalates are classified as endocrine disruptors or hormonal active agents, and have also been reported to promote various kinds of cancer. However, the biological effects of longer chain analogues are less well known. Moreover, little is known on the permeation of phthalates and their metabolites through biological membranes and on their effects on the physical properties of membranes. Here we explore the interaction of a group of phthalates and their main metabolites with model biological membranes. We focus on three industrially relevant phthalates, with acyl chains of different sizes, and their monoester metabolites. We use molecular dynamics simulations to predict the distribution in model membranes, as well as permeabilities and effects on the structural, dynamic, and elastic properties of the membranes. We find that alterations of membrane properties are significant and only weakly affected by the size of acyl chains, suggesting that modifications of molecular size may not be sufficient to reduce the impact of this class of molecules on the environment and health.

Polyply; a python suite for facilitating simulations of macromolecules and nanomaterials.

Molecular dynamics simulations play an increasingly important role in the rational design of (nano)-materials and in the study of biomacromolecules. However, generating input files and realistic starting coordinates for these simulations is a major bottleneck, especially for high throughput protocols and for complex multi-component systems. To eliminate this bottleneck, we present the polyply software suite that provides 1) a multi-scale graph matching algorithm designed to generate parameters quickly and for arbitrarily complex polymeric topologies, and 2) a generic multi-scale random walk protocol capable of setting up complex systems efficiently and independent of the target force-field or model resolution. We benchmark quality and performance of the approach by creating realistic coordinates for polymer melt simulations, single-stranded as well as circular single-stranded DNA. We further demonstrate the power of our approach by setting up a microphase-separated block copolymer system, and by generating a liquid-liquid phase separated system inside a lipid vesicle.

Polystyrene perturbs the structure, dynamics, and mechanical properties of DPPC membranes: An experimental and computational study.

Synthetic plastic oligomers can interact with the cells of living organisms by different ways. They can be intentionally administered to the human body as part of nanosized biomedical devices. They can be inhaled by exposed workers, during the production of multicomponent, polymer-based nanocomposites. They can leak out of food packaging. Most importantly, they can result from the degradation of plastic waste, and enter the food chain. A physicochemical characterization of the effects of synthetic polymers on the structure and dynamics of cell components is still lacking. Here, we combine a wide spectrum of experimental techniques (calorimetry, x-ray, and neutron scattering) with atomistic Molecular Dynamics simulations to study the interactions between short chains of polystyrene (25 monomers) and model lipid membranes (DPPC, in both gel and fluid phase). We find that doping doses of polystyrene oligomers alter the thermal properties of DPPC, stabilizing the fluid lipid phase. They perturb the membrane structure and dynamics, in a concentration-dependent fashion. Eventually, they modify the mechanical properties of DPPC, reducing its bending modulus in the fluid phase. Our results call for a systematic, interdisciplinary assessment of the mechanisms of interaction of synthetic, everyday use polymers with cell membranes.