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.

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.

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.

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.

Substrate-bound and substrate-free outward-facing structures of a multidrug ABC exporter.

Multidrug ABC transporters translocate drugs across membranes by a mechanism for which the molecular features of drug release are so far unknown. Here, we resolved three ATP-Mg2+-bound outward-facing conformations of the Bacillus subtilis (homodimeric) BmrA by x-ray crystallography and single-particle cryo-electron microscopy (EM) in detergent solution, one of them with rhodamine 6G (R6G), a substrate exported by BmrA when overexpressed in B. subtilis. Two R6G molecules bind to the drug-binding cavity at the level of the outer leaflet, between transmembrane (TM) helices 1-2 of one monomer and TM5'-6' of the other. They induce a rearrangement of TM1-2, highlighting a local flexibility that we confirmed by hydrogen/deuterium exchange and molecular dynamics simulations. In the absence of R6G, simulations show a fast postrelease occlusion of the cavity driven by hydrophobicity, while when present, R6G can move within the cavity, maintaining it open.

Towards design of drugs and delivery systems with the Martini coarse-grained model.

Coarse-grained (CG) modelling with the Martini force field has come of age. By combining a variety of bead types and sizes with a new mapping approach, the newest version of the model is able to accurately simulate large biomolecular complexes at millisecond timescales. In this perspective, we discuss possible applications of the Martini 3 model in drug discovery and development pipelines and highlight areas for future development. Owing to its high simulation efficiency and extended chemical space, Martini 3 has great potential in the area of drug design and delivery. However, several aspects of the model should be improved before Martini 3 CG simulations can be routinely employed in academic and industrial settings. These include the development of automatic parameterisation protocols for a variety of molecule types, the improvement of backmapping procedures, the description of protein flexibility and the development of methodologies enabling efficient sampling. We illustrate our view with examples on key areas where Martini could give important contributions such as drugs targeting membrane proteins, cryptic pockets and protein-protein interactions and the development of soft drug delivery systems.

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.

Perspectives on High-Throughput Ligand/Protein Docking With Martini MD Simulations.

Molecular docking is central to rational drug design. Current docking techniques suffer, however, from limitations in protein flexibility and solvation models and by the use of simplified scoring functions. All-atom molecular dynamics simulations, on the other hand, feature a realistic representation of protein flexibility and solvent, but require knowledge of the binding site. Recently we showed that coarse-grained molecular dynamics simulations, based on the most recent version of the Martini force field, can be used to predict protein/ligand binding sites and pathways, without requiring any a priori information, and offer a level of accuracy approaching all-atom simulations. Given the excellent computational efficiency of Martini, this opens the way to high-throughput drug screening based on dynamic docking pipelines. In this opinion article, we sketch the roadmap to achieve this goal.

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.

Effect of quercetin on lipid membrane rigidity: assessment by atomic force microscopy and molecular dynamics simulations.

Quercetin (3,3',4',5,7-pentahydroxyl-flavone) is a natural flavonoid with many valuable biological effects, but its solubility in water is low, posing major limitations in applications. Quercetin encapsulation in liposomes increases its bioavailability; the drug effect on liposome elastic properties is required for formulation development. Here, we quantify the effect of quercetin molecules on the rigidity of lipoid E80 liposomes using atomic force microscopy (AFM) and molecular dynamics (MD) simulations. AFM images show no effect of quercetin molecules on liposomes morphology and structure. However, AFM force curves suggest that quercetin softens lipid membranes; the Young modulus measured for liposomes encapsulating quercetin is smaller than that determined for blank liposomes. We then used MD simulations to interpret the effect of quercetin on membrane rigidity in terms of molecular interactions. The decrease in membrane rigidity was confirmed by the simulations, which also revealed that quercetin affects structural and dynamic properties: membrane thickness is decreased, acyl chains disorder is increased, and diffusion coefficients of lipid molecules are also increased. Such changes appear to be related to the preferential localization of quercetin within the membrane, near the interface between the hydrophobic core and polar head groups of the lipids.

Elastic moduli of lipid membranes: Reproducibility of AFM measures.

Membrane elastic properties play a major role in membrane remodeling events, such as vesicle fusion and fission. They are also crucial in drug delivery by liposomes. Different experimental techniques are available to measure elastic properties. Among them, atomic force microscopy (AFM) presents the unique advantage of being directly applicable to nano-sized liposomes. Unfortunately, different AFM measures reported in the literature show little agreement among each other and are difficult to compare with measures of bending modulus obtained by other experimental techniques or by molecular simulations. In this work we determine the bending rigidity of Egg PC liposomes in terms of Young modulus via AFM measurements, using two different tip shapes and different cantilever force constants. We interpret the measures using the Hertz and Shell models, and observe a clear dependency of the Young modulus values on the tip properties and on the interpretative theory. The effect of the AFM tip shape is less important than the effect of the cantilever force constant, and the mathematical model has a major effect on the interpretation of the data. The Shell theory provides the closest agreement between AFM data and other experimental data for the membrane bending modulus. Finally, we compare the results to calculations of bending modulus from molecular dynamics simulations of membrane buckles. Simulations provide values of bending modulus consistent with literature data, but the agreement with AFM experiments is reasonable only for some specific experimental conditions.

Understanding the Functional Properties of Lipid Heterogeneity in Pulmonary Surfactant Monolayers at the Atomistic Level.

Pulmonary surfactant is a complex mixture of lipids and proteins lining the interior of the alveoli, and constitutes the first barrier to both oxygen and pathogens as they progress toward blood circulation. Despite decades of study, the behavior of the pulmonary surfactant at the molecular scale is poorly understood, which hinders the development of effective surfactant replacement therapies, useful in the treatment of several lung-related diseases. In this work, we combined all-atom molecular dynamics simulations, Langmuir trough measurements, and AFM imaging to study synthetic four-component lipid monolayers designed to model protein-free pulmonary surfactant. We characterized the structural and dynamic properties of the monolayers with a special focus on lateral heterogeneity. Remarkably, simulations reproduce almost quantitatively the experimental data on pressure-area isotherms and the presence of lateral heterogeneities highlighted by AFM. Quite surprisingly, the pressure-area isotherms do not show a plateau region, despite the presence of liquid-condensed nanometer-sized domains at surface pressures larger than 20 mN/m. In the simulations, the liquid-condensed domains were small and transient, but they did not coalesce to yield a separate phase. They were only slightly enriched in DPPC and cholesterol, and their chemical composition remained very similar to the overall composition of the monolayer membrane. Instead, they differed from liquid-expanded regions in terms of membrane thickness (in agreement with AFM data), diffusion rates, as well as acyl chain packing and orientation. We hypothesize that such lateral heterogeneities are crucial for lung surfactant function, as they allow both efficient packing, to achieve low surface tension, and sufficient fluidity, critical for rapid adsorption to the air-liquid interface during the breathing cycle.

Triacylglycerols sequester monotopic membrane proteins to lipid droplets.

Triacylglycerols (TG) are synthesized at the endoplasmic reticulum (ER) bilayer and packaged into organelles called lipid droplets (LDs). LDs are covered by a single phospholipid monolayer contiguous with the ER bilayer. This connection is used by several monotopic integral membrane proteins, with hydrophobic membrane association domains (HDs), to diffuse between the organelles. However, how proteins partition between ER and LDs is not understood. Here, we employed synthetic model systems and found that HD-containing proteins strongly prefer monolayers and returning to the bilayer is unfavorable. This preference for monolayers is due to a higher affinity of HDs for TG over membrane phospholipids. Protein distribution is regulated by PC/PE ratio via alterations in monolayer packing and HD-TG interaction. Thus, HD-containing proteins appear to non-specifically accumulate to the LD surface. In cells, protein editing mechanisms at the ER membrane would be necessary to prevent unspecific relocation of HD-containing proteins to LDs.

On Calculating the Bending Modulus of Lipid Bilayer Membranes from Buckling Simulations.

The bending modulus is an important physical constant characterizing lipid membranes. Different methods have been devised for calculating the bending modulus from simulations, and one of them, named the buckling method, is nowadays widely used due to its simplicity and numerical stability. However, questions remain on the reproducibility, finite size effects, and interpretation of results on lipid mixtures. Here we explore the dependence of simulation results on the system size and the strain. We find that the dimensions of the box have a negligible impact on the results when the system size is beyond a certain threshold. We then calculate the bending rigidity for of a series of common single-component lipid bilayers (PC, PS, PE, PG, and SM), as well as a number of binary and ternary lipid mixtures. We find that bending moduli of lipid mixtures can be predicted from the weighted average of the moduli of the individual components, as long as the mixture is homogeneous. For phase-separated mixtures, the apparent elastic modulus is closer to the value of the softer component. Predictions of the bending modulus based on the area compressibility modulus are found to be generally unreliable.

Size-dependent aggregation of hydrophobic nanoparticles in lipid membranes.

The aggregation of nanoparticles affects their reactivity, transport across biological membranes, uptake into cells, toxicity, and fate in the environment. In the case of membrane-embedded, hydrophobic nanoparticles the relationship between size and aggregation pattern is not well understood. Here, we explore this relationship for the case of spherically symmetrical nanoparticles using the MARTINI coarse-grained force field. We find that the free energy of dimerization depends strongly on nanoparticle size: the smallest molecules (mimicking C60 fullerene) aggregate only weakly, the largest ones form large three-dimensional aggregates causing major deformations in the host membrane, and the intermediate-sized particles show a tendency to form linear aggregates. Suppressing membrane undulations reduces very significantly aggregation, and substantially abolishes linear aggregation, suggesting a relationship between membrane curvature and aggregation geometry. At low concentration, when placed on membranes of variable curvature, the intermediate size nanoparticles move rapidly to high curvature regions - suggesting that they can sense membrane curvature. At high concentration, the same nanoparticles induce massive membrane deformations, without affecting the mechanical stability of the membrane - suggesting that they can generate membrane curvature.

Prevention of postoperative surgical wound complications in ankle and distal tibia fractures: results of Incisional Negative Pressure Wound Therapy.

BACKGROUND AND AIM OF THE WORK: complications in surgical wound healing represent the main postoperative complication in ankle and distal tibia fractures. Whereas the use of Incisional Negative Pressure Wound Therapy (INPWT) is recognized to have a role in wound complications prevention in prosthetic surgery, literature about its use in trauma surgery is scarce. The aim of this study was to compare the effectiveness of INWPT with a conventional dressing in order to prevent surgical wound complications in ankle and distal tibia fractures. METHODS: The study population included patients over 65 years as well as patients under 65 years considered at risk for wound complications (smokers, obese, affected by diabetes), who underwent ORIF for bi/tri-malleolar ankle fractures or distal tibia (pilon) fractures. After surgery, patients were randomized to receive a conventional dressing or INPWT. Complications in surgical wound healing were classified in major (requiring surgical intervention) and minor complications. RESULTS: 65 patients were included in the study. The rate of minor and major complications between the two groups was not significantly different, although a positive trend towards a lower minor complications rate was noted in the INPWT group (12.6% vs 34.7%). No complications or complaints were reported for the INPWT device. CONCLUSIONS: INPWT proved to be safe, well-tolerated and showed promising results in preventing surgical wound complications in ankle and distal tibia fractures.