Martini 3 Coarse-Grained Force Field for Cholesterol.

Cholesterol plays a crucial role in biomembranes by regulating various properties, such as fluidity, rigidity, permeability, and organization of lipid bilayers. The latest version of the Martini model, Martini 3, offers significant improvements in interaction balance, molecular packing, and inclusion of new bead types and sizes. However, the release of the new model resulted in the need to reparameterize many core molecules, including cholesterol. Here, we describe the development and validation of a Martini 3 cholesterol model, addressing issues related to its bonded setup, shape, volume, and hydrophobicity. The proposed model mitigates some limitations of its Martini 2 predecessor while maintaining or improving the overall behavior.

Free energy along drug-protein binding pathways interactively sampled in virtual reality.

We describe a two-step approach for combining interactive molecular dynamics in virtual reality (iMD-VR) with free energy (FE) calculation to explore the dynamics of biological processes at the molecular level. We refer to this combined approach as iMD-VR-FE. Stage one involves using a state-of-the-art 'human-in-the-loop' iMD-VR framework to generate a diverse range of protein-ligand unbinding pathways, benefitting from the sophistication of human spatial and chemical intuition. Stage two involves using the iMD-VR-sampled pathways as initial guesses for defining a path-based reaction coordinate from which we can obtain a corresponding free energy profile using FE methods. To investigate the performance of the method, we apply iMD-VR-FE to investigate the unbinding of a benzamidine ligand from a trypsin protein. The binding free energy calculated using iMD-VR-FE is similar for each pathway, indicating internal consistency. Moreover, the resulting free energy profiles can distinguish energetic differences between pathways corresponding to various protein-ligand conformations (e.g., helping to identify pathways that are more favourable) and enable identification of metastable states along the pathways. The two-step iMD-VR-FE approach offers an intuitive way for researchers to test hypotheses for candidate pathways in biomolecular systems, quickly obtaining both qualitative and quantitative insight.

The emerging potential of interactive virtual reality in drug discovery.

INTRODUCTION: The potential of virtual reality (VR) to contribute to drug design and development has been recognized for many years. A recent advance is to use VR not only to visualize and interact with molecules, but also to interact with molecular dynamics simulations 'on the fly' (interactive molecular dynamics in VR, IMD-VR), which is useful for flexible docking and examining binding processes and conformational changes. AREAS COVERED: The authors use the term 'interactive VR' to refer to software where interactivity is an inherent part of the user VR experience e.g. in making structural modifications or interacting with a physically rigorous molecular dynamics (MD) simulation, as opposed to using VR controllers to rotate and translate the molecule for enhanced visualization. Here, they describe these methods and their application to problems relevant to drug discovery, highlighting the possibilities that they offer in this arena. EXPERT OPINION: The ease of viewing and manipulating molecular structures and dynamics, using accessible VR hardware, and the ability to modify structures on the fly (e.g. adding or deleting atoms) - and for groups of researchers to work together in the same virtual environment - makes modern interactive VR a valuable tool to add to the armory of drug design and development methods.

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.

Interactive Molecular Dynamics in Virtual Reality Is an Effective Tool for Flexible Substrate and Inhibitor Docking to the SARS-CoV-2 Main Protease.

The main protease (Mpro) of the SARS-CoV-2 virus is one focus of drug development efforts for COVID-19. Here, we show that interactive molecular dynamics in virtual reality (iMD-VR) is a useful and effective tool for creating Mpro complexes. We make these tools and models freely available. iMD-VR provides an immersive environment in which users can interact with MD simulations and so build protein complexes in a physically rigorous and flexible way. Recently, we have demonstrated that iMD-VR is an effective method for interactive, flexible docking of small molecule drugs into their protein targets (Deeks et al. PLoS One 2020, 15, e0228461). Here, we apply this approach to both an Mpro inhibitor and an oligopeptide substrate, using experimentally determined crystal structures. For the oligopeptide, we test against a crystallographic structure of the original SARS Mpro. Docking with iMD-VR gives models in agreement with experimentally observed (crystal) structures. The docked structures are also tested in MD simulations and found to be stable. Different protocols for iMD-VR docking are explored, e.g., with and without restraints on protein backbone, and we provide recommendations for its use. We find that it is important for the user to focus on forming binding interactions, such as hydrogen bonds, and not to rely on using simple metrics (such as RMSD), in order to create realistic, stable complexes. We also test the use of apo (uncomplexed) crystal structures for docking and find that they can give good results. This is because of the flexibility and dynamic response allowed by the physically rigorous, atomically detailed simulation approach of iMD-VR. We make our models (and interactive simulations) freely available. The software framework that we use, Narupa, is open source, and uses commodity VR hardware, so these tools are readily accessible to the wider research community working on Mpro (and other COVID-19 targets). These should be widely useful in drug development, in education applications, e.g., on viral enzyme structure and function, and in scientific communication more generally.

Piezo1 Forms Specific, Functionally Important Interactions with Phosphoinositides and Cholesterol.

Touch, hearing, and blood pressure regulation require mechanically gated ion channels that convert mechanical stimuli into electrical currents. One such channel is Piezo1, which plays a key role in the transduction of mechanical stimuli in humans and is implicated in diseases, such as xerocytosis and lymphatic dysplasia. There is building evidence that suggests Piezo1 can be regulated by the membrane environment, with the activity of the channel determined by the local concentration of lipids, such as cholesterol and phosphoinositides. To better understand the interaction of Piezo1 with its environment, we conduct simulations of the protein in a complex mammalian bilayer containing more than 60 different lipid types together with electrophysiology and mutagenesis experiments. We find that the protein alters its local membrane composition, enriching specific lipids and forming essential binding sites for phosphoinositides and cholesterol that are functionally relevant and often related to Piezo1-mediated pathologies. We also identify a number of key structural connections between the propeller and pore domains located close to lipid-binding sites.

Titratable Martini model for constant pH simulations.

In this work, we deliver a proof of concept for a fast method that introduces pH effects into classical coarse-grained (CG) molecular dynamics simulations. Our approach is based upon the latest version of the popular Martini CG model to which explicit proton mimicking particles are added. We verify our approach against experimental data involving several different molecules and different environmental conditions. In particular, we compute titration curves, pH dependent free energies of transfer, and lipid bilayer membrane affinities as a function of pH. Using oleic acid as an example compound, we further illustrate that our method can be used to study passive translocation in lipid bilayers via protonation. Finally, our model reproduces qualitatively the expansion of the macromolecule dendrimer poly(propylene imine) as well as the associated pKa shift of its different generations. This example demonstrates that our model is able to pick up collective interactions between titratable sites in large molecules comprising many titratable functional groups.

Coupling Coarse-Grained to Fine-Grained Models via Hamiltonian Replica Exchange.

The energy landscape of biomolecular systems contains many local minima that are separated by high energy barriers. Sampling this landscape in molecular dynamics simulations is a challenging task and often requires the use of enhanced sampling techniques. Here, we increase the sampling efficiency by coupling the fine-grained (FG) GROMOS force field to the coarse-grained (CG) Martini force field via the Hamiltonian replica exchange method (HREM). We tested the efficiency of this procedure using a lutein/octane system. In traditional simulations, cis-trans transitions of lutein are barely observed due to the high energy barrier separating these states. However, many of these transitions are sampled with our HREM scheme. The proposed method offers new possibilities for enhanced sampling of biomolecular conformations, making use of CG models without compromising the accuracy of the FG model.

Dual Resolution Membrane Simulations Using Virtual Sites.

All-atomistic (AA) and coarse-grain (CG) simulations have been successfully applied to investigate a broad range of biomolecular processes. However, the accessible time and length scales of AA simulation are limited and the specific molecular details of CG simulation are simplified. Here, we propose a virtual site (VS) based hybrid scheme that can concurrently couple AA and CG resolutions in a single membrane simulation, mitigating the shortcomings of either representation. With some adjustments to make the AA and CG force fields compatible, we demonstrate that lipid bilayer properties are well kept in our hybrid approach. Our VS hybrid method was also applied to simulate a small lipid vesicle, with the inner leaflet and interior solvent represented in AA, and the outer leaflet together with exterior solvent at the CG level. Our multiscale method opens the way to investigate biomembrane properties at increased computational efficiency, in particular applications involving large solvent filled regions.

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.

Capturing Choline-Aromatics Cation-π Interactions in the MARTINI Force Field.

Cation-π interactions play an important role in biomolecular recognition, including interactions between membrane phosphatidylcholine lipids and aromatic amino acids of peripheral proteins. While molecular mechanics coarse grain (CG) force fields are particularly well suited to simulate membrane proteins in general, they are not parameterized to explicitly reproduce cation-π interactions. We here propose a modification of the polarizable MARTINI coarse grain (CG) model enabling it to model membrane binding events of peripheral proteins whose aromatic amino acid interactions with choline headgroups are crucial for their membrane binding. For this purpose, we first collected and curated a dataset of eight peripheral proteins from different families. We find that the MARTINI CG model expectedly underestimates aromatics-choline interactions and is unable to reproduce membrane binding of the peripheral proteins in our dataset. Adjustments of the relevant interactions in the polarizable MARTINI force field yield significant improvements in the observed binding events. The orientation of each membrane-bound protein is comparable to reference data from all-atom simulations and experimental binding data. We also use negative controls to ensure that choline-aromatics interactions are not overestimated. We finally check that membrane properties, transmembrane proteins, and membrane translocation potential of mean force (PMF) of aromatic amino acid side-chain analogues are not affected by the new parameter set. This new version "MARTINI 2.3P" is a significant improvement over its predecessors and is suitable for modeling membrane proteins including peripheral membrane binding of peptides and proteins.

Sex and Ontogenetic Variation in the Crest of Numida meleagris: Implications for Crested Vertebrates.

Crested vertebrates are known from a wide variety of modern and fossil taxa, however, the actual formation and function of the crest is still debatable. Among modern birds, the globally distributed guinea fowl (Numida meleagris) is characterized by having a cranial bony crest (overlain by keratin), but surprisingly little is known about its development. Here, we studied the crest of 202 wild guinea fowl from the same population, using anatomical measurements as well as 2D-morphometry. Our results show that juveniles have smaller skulls than adults and have smaller, simpler crests that are visible even in very young individuals. Among adults, female skulls are smaller than males, and they have smaller, simpler shaped crests, which permit a discrimination between the sexes of 93% when the keratin is preserved with the bony crest, and of 89% when only the bony crest is available. By extrapolation, these results confirm that the crest can be used as an ontogenetic character, as well as for sex discrimination in the fossil record. Our results also show that the overlying keratin does not always mimic the underlying bony crest, which should be considered when reconstructing extinct crested vertebrates. Anat Rec, 303:1018-1034, 2020. © 2019 American Association for Anatomy.

Gangliosides Destabilize Lipid Phase Separation in Multicomponent Membranes.

Gangliosides (GMs) form an important class of lipids found in the outer leaflet of the plasma membrane. Typically, they colocalize with cholesterol and sphingomyelin in ordered membrane domains. However, detailed understanding of the lateral organization of GM-rich membranes is still lacking. To gain molecular insight, we performed molecular dynamics simulations of GMs in model membranes composed of coexisting liquid-ordered and liquid-disordered domains. We found that GMs indeed have a preference to partition into the ordered domains. At higher concentrations (>10 mol %), we observed a destabilizing effect of GMs on the phase coexistence. Further simulations with modified GMs show that the structure of the GM headgroup affects the phase separation, whereas the nature of the tail determines the preferential location. Together, our findings provide a molecular basis to understand the lateral organization of GM-rich membranes.

Sharing Data from Molecular Simulations.

Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations has become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 ( https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/ ). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way toward more open, interoperable, and reproducible outputs coming from research studies using MD simulations.

Alcohol Interactions with Lipid Bilayers.

We investigate the structural changes to lipid membrane that ensue from the addition of aliphatic alcohols with various alkyl tail lengths. Small angle neutron diffraction from flat lipid bilayers that are hydrated through water vapor has been employed to eliminate possible artefacts of the membrane curvature and the alcohol's membrane-water partitioning. We have observed clear changes to membrane structure in both transversal and lateral directions. Most importantly, our results suggest the alteration of the membrane-water interface. The water encroachment has shifted in the way that alcohol loaded bilayers absorbed more water molecules when compared to the neat lipid bilayers. The experimental results have been corroborated by molecular dynamics simulations to reveal further details. Namely, the order parameter profiles have been fruitful in correlating the mechanical model of structural changes to the effect of anesthesia.

PBxplore: a tool to analyze local protein structure and deformability with Protein Blocks.

This paper describes the development and application of a suite of tools, called PBxplore, to analyze the dynamics and deformability of protein structures using Protein Blocks (PBs). Proteins are highly dynamic macromolecules, and a classical way to analyze their inherent flexibility is to perform molecular dynamics simulations. The advantage of using small structural prototypes such as PBs is to give a good approximation of the local structure of the protein backbone. More importantly, by reducing the conformational complexity of protein structures, PBs allow analysis of local protein deformability which cannot be done with other methods and had been used efficiently in different applications. PBxplore is able to process large amounts of data such as those produced by molecular dynamics simulations. It produces frequencies, entropy and information logo outputs as text and graphics. PBxplore is available at https://github.com/pierrepo/PBxplore and is released under the open-source MIT license.

Protein flexibility in the light of structural alphabets.

Protein structures are valuable tools to understand protein function. Nonetheless, proteins are often considered as rigid macromolecules while their structures exhibit specific flexibility, which is essential to complete their functions. Analyses of protein structures and dynamics are often performed with a simplified three-state description, i.e., the classical secondary structures. More precise and complete description of protein backbone conformation can be obtained using libraries of small protein fragments that are able to approximate every part of protein structures. These libraries, called structural alphabets (SAs), have been widely used in structure analysis field, from definition of ligand binding sites to superimposition of protein structures. SAs are also well suited to analyze the dynamics of protein structures. Here, we review innovative approaches that investigate protein flexibility based on SAs description. Coupled to various sources of experimental data (e.g., B-factor) and computational methodology (e.g., Molecular Dynamic simulation), SAs turn out to be powerful tools to analyze protein dynamics, e.g., to examine allosteric mechanisms in large set of structures in complexes, to identify order/disorder transition. SAs were also shown to be quite efficient to predict protein flexibility from amino-acid sequence. Finally, in this review, we exemplify the interest of SAs for studying flexibility with different cases of proteins implicated in pathologies and diseases.

C60 fullerene promotes lung monolayer collapse.

Airborne nanometre-sized pollutants are responsible for various respiratory diseases. Such pollutants can reach the gas-exchange surface in the alveoli, which is lined with a monolayer of lung surfactant. The relationship between physiological effects of pollutants and molecular-level interactions is largely unknown. Here, we determine the effects of carbon nanoparticles on the properties of a model of lung monolayer using molecular simulations. We simulate phase-separated lipid monolayers in the presence of a model pollutant nanoparticle, C60 fullerene. In the absence of nanoparticles, the monolayers collapse only at very low surface tensions (around 0 mN m(-1)). In the presence of nanoparticles, instead, monolayer collapse is observed at significantly higher surface tensions (up to ca 10 mN m(-1)). Collapse at higher tensions is related to lower mechanical rigidity of the monolayer. It is possible that similar mechanisms operate on lung surfactant in vivo, which suggests that health effects of airborne carbon nanoparticles may be mediated by alterations of the mechanical properties of lung surfactant.

Coarse-grained force fields for molecular simulations.

Molecular dynamics (MD) simulations at the atomic scale are a powerful tool to study the structure and dynamics of model biological systems. However, because of their high computational cost, the time and length scales of atomistic simulations are limited. Biologically important processes, such as protein folding, ion channel gating, signal transduction, and membrane remodeling, are difficult to investigate using atomistic simulations. Coarse-graining reduces the computational cost of calculations by reducing the number of degrees of freedom in the model, allowing simulations of larger systems for longer times. In the first part of this chapter we review briefly some of the coarse-grained models available for proteins, focusing on the specific scope of each model. Then we describe in more detail the MARTINI coarse-grained force field, and we illustrate how to set up and run a simulation of a membrane protein using the Gromacs software package. We explain step-by-step the preparation of the protein and the membrane, the insertion of the protein in the membrane, the equilibration of the system, the simulation itself, and the analysis of the trajectory.

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.