ADAM10 is a crucial membrane-bound metalloprotease that regulates cellular physiology by cleaving and releasing membrane-anchored proteins, including adhesion molecules and growth factor precursors, t...

Deep eutectic solvents (DESs) are often promoted as a more environmentally friendly alternative for ionic liquids and other ionic solvents. Like ionic liquids, DESs can be designed for specific tasks ...

Lipid membranes are central to cellular life. Complementing experiments, computational modeling has been essential in unraveling complex lipid-biomolecule interactions, crucial in both academia and industry. The Martini model, a coarse-grained force field for efficient molecular dynamics simulations, is widely used to study membrane phenomena but has faced limitations, particularly in capturing realistic lipid phase behavior. Here, we present refined Martini 3 lipid models with a mapping scheme that distinguishes lipid tails that differ by just two carbon atoms, enhancing the structural resolution and thermodynamic accuracy of model membrane systems including ternary mixtures. The expanded Martini lipid library includes thousands of models, enabling simulations of complex and biologically relevant systems. These advancements establish Martini as a robust platform for lipid-based simulations across diverse fields.

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.

The existence of the phenomenon of enhanced enzyme diffusion (EED) has been a topic of debate in recent literature. One proposed mechanism to explain the origin of EED is oligomeric enzyme dissociation. We used mass photometry (MP), a label-free single-molecule technique, to investigate the dependence of the oligomeric states of several enzymes on their ligands. The studied enzymes of interest are catalase, aldolase, alkaline phosphatase, and vanillyl-alcohol oxidase (VAO). We compared the ratios of oligomeric states in the presence and absence of the substrate as well as different substrate and inhibitor concentrations. Catalase and aldolase were found to dissociate into smaller oligomers in the presence of their substrates, independently of inhibition, while for alkaline phosphatase and VAO, different behaviors were observed. Thus, we have identified a possible mechanism which explains the previously observed diffusion enhancement in vitro. This enhancement may occur due to the dissociation of oligomers through ligand binding.