Coacervate formation studied by explicit solvent coarse-grain molecular dynamics with the Martini model

Complex coacervates are liquid-liquid phase separated systems, typically containing oppositely charged polyelectrolytes. They are widely studied for their functional properties as well as their potential involvement in cellular compartmentalization as biomolecular condensates. Diffusion and partitioning of solutes into a coacervate phase are important to address because their highly dynamic nature is one of their most important functional characteristics in real-world systems, but are difficult to study experimentally or even theoretically without an explicit representation of every molecule in the system. Here, we present an explicit-solvent, molecular dynamics coarse-grain model of complex coacervates, based on the Martini 3.0 force field. We demonstrate the accuracy of the model by reproducing the salt dependent coacervation of poly-lysine and poly-glutamate systems, and show the potential of the model by simulating the partitioning of ions and small nucleotides between the condensate and surrounding solvent phase. Our model paves the way for simulating coacervates and biomolecular condensates in a wide range of conditions, with near-atomic resolution

Two decades of Martini:Better beads, broader scope

The Martini model, a coarse-grained force field for molecular dynamics simulations, has been around for nearly two decades. Originally developed for lipid-based systems by the groups of Marrink and Tieleman, the Martini model has over the years been extended as a community effort to the current level of a general-purpose force field. Apart from the obvious benefit of a reduction in computational cost, the popularity of the model is largely due to the systematic yet intuitive building-block approach that underlies the model, as well as the open nature of the development and its continuous validation. The easy implementation in the widely used Gromacs software suite has also been instrumental. Since its conception in 2002, the Martini model underwent a gradual refinement of the bead interactions and a widening scope of applications. In this review, we look back at this development, culminating with the release of the Martini 3 version in 2021. The power of the model is illustrated with key examples of recent important findings in biological and material sciences enabled with Martini, as well as examples from areas where coarse-grained resolution is essential, namely high-throughput applications, systems with large complexity, and simulations approaching the scale of whole cells. This article is categorized under: Software > Molecular Modeling Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods Structure and Mechanism > Computational Materials Science Structure and Mechanism > Computational Biochemistry and Biophysics

Pitfalls of the Martini Model

R.A. thanks The Netherlands Organisation for Scientific Research NWO (Graduate Programme Advanced Materials, No. 022.005.006) for financial support. S.T. thanks the European Commission for financial support via a Marie Skłodowska-Curie Actions Individual Fellowship (MicroMod-PSII, grant agreement 748895).The computational and conceptual simplifications realized by coarse-grain (CG) models make them a ubiquitous tool in the current computational modeling landscape. Building block based CG models, such as the Martini model, possess the key advantage of allowing for a broad range of applications without the need to reparametrize the force field each time. However, there are certain inherent limitations to this approach, which we investigate in detail in this work. We first study the consequences of the absence of specific cross Lennard-Jones parameters between different particle sizes. We show that this lack may lead to artificially high free energy barriers in dimerization profiles. We then look at the effect of deviating too far from the standard bonded parameters, both in terms of solute partitioning behavior and solvent properties. Moreover, we show that too weak bonded force constants entail the risk of artificially inducing clustering, which has to be taken into account when designing elastic network models for proteins. These results have implications for the current use of the Martini CG model and provide clear directions for the reparametrization of the Martini model. Moreover, our findings are generally relevant for the parametrization of any other building block based force field.publishersversionpublishe

Modelling structural properties of cyanine dye nanotubes at coarse-grained level

Self-assembly is a ubiquitous process spanning from biomolecular aggregates to nanomaterials. Even though the resulting aggregates can be studied through experimental techniques, the dynamic pathways of the process and the molecular details of the final structures are not necessarily easy to resolve. Consequently, rational design of self-assembling aggregates and their properties remains extremely challenging. At the same time, modelling the self-assembly with computational methods is not trivial, because its spatio-temporal scales are usually beyond the limits of all-atom based simulations. The use of coarse-grained (CG) models can alleviate this limitation, but usually suffers from the lack of optimised parameters for the molecular constituents. In this work, we describe the procedure of parametrizing a CG Martini model for a cyanine dye (C8S3) that self-assembles into hollow double-walled nanotubes. First, we optimised the model based on quantum mechanics calculations and all-atom reference simulations, in combination with available experimental data. Then, we conducted random self-assembly simulations, and the performance of our model was tested on preformed assemblies. Our simulations provide information on the time-dependent local arrangement of this cyanine dye, when aggregates are being formed. Furthermore, we provide guidelines for designing and optimising parameters for similar self-assembling nanomaterials

Martini 3 Coarse-Grained Force Field:Small Molecules

The recent re-parametrization of the Martini coarse-grained force field, Martini 3, improved the accuracy of the model in predicting molecular packing and interactions in molecular dynamics simulations. Here, we describe how small molecules can be accurately parametrized within the Martini 3 framework and present a database of validated small molecule models. We pay particular attention to the description of aliphatic and aromatic ring-like structures, which are ubiquitous in small molecules such as solvents and drugs or in building blocks constituting macromolecules such as proteins and synthetic polymers. In Martini 3, ring-like structures are described by models that use higher resolution coarse-grained particles (small and tiny particles). As such, the present database constitutes one of the cornerstones of the calibration of the new Martini 3 small and tiny particle sizes. The models show excellent partitioning behavior and solvent properties. Miscibility trends between different bulk phases are also captured, completing the set of thermodynamic properties considered during the parametrization. We also show how the new bead sizes allow for a good representation of molecular volume, which translates into better structural properties such as stacking distances. We further present design strategies to build Martini 3 models for small molecules of increased complexity

An alternative conformation of ERβ bound to estradiol reveals H12 in a stable antagonist position

The natural ligand 17β-estradiol (E2) is so far believed to induce a unique agonist-bound active conformation in the ligand binding domain (LBD) of the estrogen receptors (ERs). Both subtypes, ERα and ERβ, are transcriptionally activated in the presence of E2 with ERβ being somewhat less active than ERα under similar conditions. The molecular bases for this intriguing behavior are mainly attributed to subtype differences in the amino-terminal domain of these receptors. However, structural details that confer differences in the molecular response of ER LBDs to E2 still remain elusive. In this study, we present a new crystallographic structure of the ERβ LBD bound to E2 in which H12 assumes an alternative conformation that resembles antagonist ERs structures. Structural observations and molecular dynamics simulations jointly provide evidence that alternative ERβ H12 position could correspond to a stable conformation of the receptor under physiological pH conditions. Our findings shed light on the unexpected role of LBD in the lower functional response of ERβ subtype

Martini 3 Coarse-Grained Force Field for Carbohydrates

The Martini 3 force field is a full re-parametrization of the Martini coarse-grained model for biomolecular simulations. Due to the improved interaction balance it allows for more accurate description of condensed phase systems. In the present work we develop a consistent strategy to parametrize carbohydrate molecules accurately within the framework of Martini 3. In particular, we develop a canonical mapping scheme that decomposes arbitrarily large carbohydrates into a limited number of fragments. Bead types for these fragments have been assigned by matching physicochemical properties of mono- and disaccharides. In addition, guidelines for assigning bonds, angles, and dihedrals are developed. These guidelines enable a more accurate description of carbohydrate conformations than in the Martini 2 force field. We show that models obtained with this approach are able to accurately reproduce osmotic pressures of carbohydrate water solutions. Furthermore, we provide evidence that the model differentiates correctly the solubility of the poly-glucoses dextran (water soluble) and cellulose (water insoluble, but soluble in ionic-liquids). Finally, we demonstrate that the new building blocks can be applied to glycolipids, being able to reproduce membrane properties and to induce binding of peripheral membrane proteins. These test cases demonstrate the validity and transferability of our approach.</p

Computational Modeling of Realistic Cell Membranes

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