Martini 3 Coarse-Grained Model for Second-Generation Unidirectional Molecular Motors and Switches

Determining the Role of Electrostatics in the Making and Breaking of the Caprin1-ATP Nanocondensate

We employ a multiscale computational approach to investigate the condensation process of the C-terminal low-complexity region of the Caprin1 protein as a function of increasing ATP concentration for three states: the initial mixed state, nanocondensate formation, and dissolution of the droplet as it reenters the mixed state. We show that upon condensation, ATP assembles via pi-pi interactions, resulting in the formation of a large cluster of stacked ATP molecules stabilized by sodium counterions. The surface of the ATP assembly interacts with the arginine-rich regions of the Caprin1 protein, particularly with its N-terminus, to promote the complete phase-separated droplet on a length scale of tens of nanometers. In order to understand droplet stability, we analyzed the near-surface electrostatic potential (NS-ESP) of Caprin1 and estimated the zeta potential of the Caprin1-ATP assemblies. We predict a positive NS-ESP at the Caprin1 surface for low ATP concentrations that defines the early mixed state, in excellent agreement with the NS-ESP obtained from NMR experiments using paramagnetic resonance enhancement. By contrast, the NS-ESP of Caprin1 at the surface of the nanocondensate at moderate levels of ATP is highly negative compared to that at the mixed state, and estimates of a large zeta potential outside the highly dense region of charge further explain the remarkable stability of this phase-separated droplet assembly. As ATP concentrations rise further, the strong electrostatic forces needed for nanocondensate stability are replaced by weaker Caprin1-ATP interactions that drive the re-entry into the mixed state that exhibits a much lower zeta potential.

MartiniGlass: a Tool for Enabling Visualization of Coarse-Grained Martini Topologies

As molecular modeling gains ever more prominence in understanding cellular processes, high quality visualization of models and dynamics has never been more important. Naturally, much molecular visualization software is written to enable the visualization of atomic level details in structures. While necessary, this means that visualization of increasingly popular coarse-grained (CG) models remains a challenge. Here, we present a Python package, MartiniGlass, that facilitates the visualization of systems simulated with the widely used CG Martini force field using the popular visualization package VMD. MartiniGlass rapidly processes molecular topologies and accounts for important topological features at CG resolution, such as secondary structure restraints, preparing them for easy visualization of simulated trajectories.

XPB: an Extendable Polymer Builder for High-Throughput and High-Quality Generation of Complex Polymer Structures

The efficient generation of complex initial structures for polymers remains a critical challenge in the field of molecular simulation. This necessitates the development of high-quality and highly efficient modeling algorithms. Inspired by fundamental polymerization reactions, we propose a general algorithm for an efficient de novo polymer model building, resulting in the development of the eXtendable Polymer Builder (XPB) package. We show that XPB is well-suited for constructing a wide range of polymer models, including linear, dendritic, and cross-linked structures. It offers a precise control over polymer morphology through adjustable, physically meaningful parameters such as residue types, connection preferences, and cross-linking distances. As a showcase, XPB can construct well-defined dendrimers up to the 10th generation and hyperbranched polymers with tens of thousands of residues within mere minutes, while effectively minimizing structural overlaps. This versatility facilitates the construction of more complex polymer architectures than before, providing a general and robust framework for the high-throughput and high-quality generation of diverse polymer structures.

Coarse-Graining the Recognition of a Glycolipid by the C-Type Lectin Mincle Receptor

Macrophage inducible Ca2+-dependent lectin (Mincle) receptor recognizes Mycobacterium tuberculosis glycolipids to trigger an immune response. This host membrane receptor is thus a key player in the modulation of the immune response to infection by M. tuberculosis and has emerged as a promising target for the development of new vaccines against tuberculosis. The recent development of the Martini 3 force field for coarse-grained (CG) molecular modeling allows the study of interactions of soluble proteins with small ligands which was not typically modeled well with the previous Martini 2 model. Here, we present a refined approach detailing a protocol for modeling interactions between a glycolipid and its receptor at a CG level using the Martini 3 force field. Using this approach, we studied Mincle and identified critical parameters governing ligand recognition, such as loop flexibility and the regulation of hydrophobic groove formation by calcium ions. In addition, we assessed ligand affinity using free energy perturbation calculations. Our results offer mechanistic insight into the interactions between Mincle and glycolipids, providing a basis for the rational design of molecules targeting this type of membrane receptors.

Martini 3 OliGo̅mers: A Scalable Approach for Multimers and Fibrils in GROMACS

Martini 3 is a widely used coarse-grained simulation method for large-scale biomolecular simulations. It can be combined with a Go̅ model to realistically describe higher-order protein structures while allowing the folding and unfolding events. However, as of today, this method has largely been used only for individual monomers. In this article, we describe how the Go̅ model can be implemented within the framework of Martini 3 for a multimer system, taking into account both intramolecular and intermolecular interactions in an oligomeric protein system. We demonstrate the method by showing how it can be applied to both structural stability maintenance and assembly/disassembly of protein oligomers, using aquaporin tetramer, insulin dimer, and amyloid-β fibril as examples. We find that addition of intermolecular Go̅ potentials stabilizes the quaternary structure of proteins. The strength of the Go̅ potentials can be tuned so that the internal fluctuations of proteins match the behavior of atomistic simulation models, however, the results also show that the use of too strong intermolecular Go̅ potentials weakens the chemical specificity of oligomerization. The Martini-Go̅ model presented here enables the use of Go̅ potentials in oligomeric molecular systems in a computationally efficient and parallelizable manner, especially in the case of homopolymers, where the number of identical protein monomers is high. This paves the way for coarse-grained simulations of large protein complexes, such as viral protein capsids and prion fibrils, in complex biological environments.

Switching Go̅-Martini for Investigating Protein Conformational Transitions and Associated Protein-Lipid Interactions

Proteins are dynamic biomolecules that can transform between different conformational states when exerting physiological functions, which is difficult to simulate using all-atom methods. Coarse-grained (CG) Go̅-like models are widely used to investigate large-scale conformational transitions, which usually adopt implicit solvent models and therefore cannot explicitly capture the interaction between proteins and surrounding molecules, such as water and lipid molecules. Here, we present a new method, named Switching Go̅-Martini, to simulate large-scale protein conformational transitions between different states, based on the switching Go̅ method and the CG Martini 3 force field. The method is straightforward and efficient, as demonstrated by the benchmarking applications for multiple protein systems, including glutamine binding protein (GlnBP), adenylate kinase (AdK), and β2-adrenergic receptor (β2AR). Moreover, by employing the Switching Go̅-Martini method, we can not only unveil the conformational transition from the E2Pi-PL state to E1 state of the type 4 P-type ATPase (P4-ATPase) flippase ATP8A1-CDC50 but also provide insights into the intricate details of lipid transport.