There and back again: bridging meso- and nano-scales to understand lipid vesicle patterning.

We describe a complete methodology to bridge the scales between nanoscale molecular dynamics and (micrometer) mesoscale Monte Carlo simulations in lipid membranes and vesicles undergoing phase separation, in which curving molecular species are furthermore embedded. To go from the molecular to the mesoscale, we notably appeal to physical renormalization arguments enabling us to rigorously infer the mesoscale interaction parameters from its molecular counterpart. We also explain how to deal with the physical timescales at stake at the mesoscale. Simulating the as-obtained mesoscale system enables us to equilibrate the long wavelengths of the vesicles of interest, up to the vesicle size. Conversely, we then backmap from the meso- to the nano-scale, which enables us to equilibrate in turn the short wavelengths down to the molecular length-scales. By applying our approach to the specific situation of patterning a vesicle membrane, we show that macroscopic membranes can thus be equilibrated at all length-scales in achievable computational time offering an original strategy to address the fundamental challenge of timescale in simulations of large bio-membrane systems.

Modeling membranes in situ.

Molecular dynamics simulations of cellular membranes have come a long way-from simple model lipid bilayers to multicomponent systems capturing the crowded and complex nature of real cell membranes. In this opinionated minireview, we discuss the current challenge to simulate the dynamics of membranes in their native environment, in situ, with the prospect of reaching the level of whole cells and cell organelles using an integrative modeling framework.

Capturing chemical reactions inside biomolecular condensates with reactive Martini simulations.

Biomolecular condensates are phase separated systems that play an important role in the spatio-temporal organisation of cells. Their distinct physico-chemical nature offers a unique environment for chemical reactions to occur. The compartmentalisation of chemical reactions is also believed to be central to the development of early life. To demonstrate how molecular dynamics may be used to capture chemical reactions in condensates, here we perform reactive molecular dynamics simulations using the coarse-grained Martini forcefield. We focus on the formation of rings of benzene-1,3-dithiol inside a synthetic peptide-based condensate, and find that the ring size distribution shifts to larger macrocycles compared to when the reaction takes place in an aqueous environment. Moreover, reaction rates are noticeably increased when the peptides simultaneously undergo phase separation, hinting that condensates may act as chaperones in recruiting molecules to reaction hubs.

Shocker─A Molecular Dynamics Protocol and Tool for Accelerating and Analyzing the Effects of Osmotic Shocks.

The process of osmosis, a fundamental phenomenon in life, drives water through a semipermeable membrane in response to a solute concentration gradient across this membrane. In vitro, osmotic shocks are often used to drive shape changes in lipid vesicles, for instance, to study fission events in the context of artificial cells. While experimental techniques provide a macroscopic picture of large-scale membrane remodeling processes, molecular dynamics (MD) simulations are a powerful tool to study membrane deformations at the molecular level. However, simulating an osmotic shock is a time-consuming process due to slow water diffusion across the membrane, making it practically impossible to examine its effects in classic MD simulations. In this article, we present Shocker, a Python-based MD tool for simulating the effects of an osmotic shock by selecting and relocating water particles across a membrane over the course of several pumping cycles. Although this method is primarily aimed at efficiently simulating volume changes in vesicles, it can also handle membrane tubes and double bilayer systems. Additionally, Shocker is force field-independent and compatible with both coarse-grained and all-atom systems. We demonstrate that our tool is applicable to simulate both hypertonic and hypotonic osmotic shocks for a range of vesicular and bilamellar setups, including complex multicomponent systems containing membrane proteins or crowded internal solutions.

Probing the stability and interdomain interactions in the ABC transporter OpuA using single-molecule optical tweezers.

Transmembrane transporter proteins are essential for maintaining cellular homeostasis and, as such, are key drug targets. Many transmembrane transporter proteins are known to undergo large structural rearrangements during their functional cycles. Despite the wealth of detailed structural and functional data available for these systems, our understanding of their dynamics and, consequently, how they function is generally limited. We introduce an innovative approach that enables us to directly measure the dynamics and stability of interdomain interactions of transmembrane proteins using optical tweezers. Focusing on the osmoregulatory ATP-binding cassette transporter OpuA from Lactococcus lactis, we examine the mechanical properties and potential interactions of its substrate-binding domains. Our measurements are performed in lipid nanodiscs, providing a native-mimicking environment for the transmembrane protein. The technique provides high spatial and temporal resolution and allows us to study the functionally relevant motions and interdomain interactions of individual transmembrane transporter proteins in real time in a lipid bilayer.

Vesicle protrusion induced by antimicrobial peptides suggests common carpet mechanism for short antimicrobial peptides.

Short-cationic alpha-helical antimicrobial peptides (SCHAMPs) are promising candidates to combat the growing global threat of antimicrobial resistance. They are short-sequenced, selective against bacteria, and have rapid action by destroying membranes. A full understanding of their mechanism of action will provide key information to design more potent and selective SCHAMPs. Molecular Dynamics (MD) simulations are invaluable tools that provide detailed insights into the peptide-membrane interaction at the atomic- and meso-scale level. We use atomistic and coarse-grained MD to look into the exact steps that four promising SCHAMPs-BP100, Decoralin, Neurokinin-1, and Temporin L-take when they interact with membranes. Following experimental set-ups, we explored the effects of SCHAMPs on anionic membranes and vesicles at multiple peptide concentrations. Our results showed all four peptides shared similar binding steps, initially binding to the membrane through electrostatic interactions and then flipping on their axes, dehydrating, and inserting their hydrophobic moieties into the membrane core. At higher concentrations, fully alpha-helical peptides induced membrane budding and protrusions. Our results suggest the carpet mode of action is fit for the description of SCHAMPs lysis activity and discuss the importance of large hydrophobic residues in SCHAMPs design and activity.

Exploring the Ligand Binding and Conformational Dynamics of the Substrate-Binding Domain 1 of the ABC Transporter GlnPQ.

The adenosine triphosphate (ATP)-binding cassette (ABC) importer GlnPQ from Lactococcus lactis has two sequential covalently linked substrate-binding domains (SBDs), which capture the substrates and deliver them to the translocon. The two SBDs differ in their ligand specificities, binding affinities and the distance to the transmembrane domain; interestingly, both SBDs can bind their ligands simultaneously without affecting each other. In this work, we studied the binding of ligands to both SBDs using X-ray crystallography and molecular dynamics simulations. We report three high-resolution structures of SBD1, namely, the wild-type SBD1 with bound asparagine or arginine, and E184D SBD1 with glutamine bound. Molecular dynamics (MD) simulations provide a detailed insight into the dynamics associated with open-closed transitions of the SBDs.

Building complex membranes with Martini 3.

The Martini model is a popular force field for coarse-grained simulations. Membranes have always been at the center of its development, with the latest version, Martini 3, showing great promise in capturing more and more realistic behavior. In this chapter we provide a step-by-step tutorial on how to construct starting configurations, run initial simulations and perform dedicated analysis for membrane-based systems of increasing complexity, including leaflet asymmetry, curvature gradients and embedding of membrane proteins.

Structural basis of the obligatory exchange mode of human neutral amino acid transporter ASCT2.

ASCT2 is an obligate exchanger of neutral amino acids, contributing to cellular amino acid homeostasis. ASCT2 belongs to the same family (SLC1) as Excitatory Amino Acid Transporters (EAATs) that concentrate glutamate in the cytosol. The mechanism that makes ASCT2 an exchanger rather than a concentrator remains enigmatic. Here, we employ cryo-electron microscopy and molecular dynamics simulations to elucidate the structural basis of the exchange mechanism of ASCT2. We establish that ASCT2 binds three Na+ ions per transported substrate and visits a state that likely acts as checkpoint in preventing Na+ ion leakage, both features shared with EAATs. However, in contrast to EAATs, ASCT2 retains one Na+ ion even under Na+-depleted conditions. We demonstrate that ASCT2 cannot undergo the structural transition in TM7 that is essential for the concentrative transport cycle of EAATs. This structural rigidity and the high-affinity Na+ binding site effectively confine ASCT2 to an exchange mode.

Bartender: Martini 3 Bonded Terms via Quantum Mechanics-Based Molecular Dynamics.

Coarse-grained (CG) molecular dynamics (MD) simulations have grown in applicability over the years. The recently released version of the Martini CG force field (Martini 3) has been successfully applied to simulate many processes, including protein-ligand binding. However, the current ligand parametrization scheme is manual and requires an a priori reference all-atom (AA) simulation for benchmarking. For systems with suboptimal AA parameters, which are often unknown, this translates into a CG model that does not reproduce the true dynamical behavior of the underlying molecule. Here, we present Bartender, a quantum mechanics (QM)/MD-based parametrization tool written in Go. Bartender harnesses the power of QM simulations and produces reasonable bonded terms for Martini 3 CG models of small molecules in an efficient and user-friendly manner. For small, ring-like molecules, Bartender generates models whose properties are indistinguishable from the human-made models. For more complex, drug-like ligands, it is able to fit functional forms beyond simple harmonic dihedrals and thus better captures their dynamical behavior. Bartender has the power to both increase the efficiency and the accuracy of Martini 3-based high-throughput applications by producing numerically stable and physically realistic CG models.