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.

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.

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.

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.

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.

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.

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.

Identification of inhibitors targeting the energy-coupling factor (ECF) transporters.

The energy-coupling factor (ECF) transporters are a family of transmembrane proteins involved in the uptake of vitamins in a wide range of bacteria. Inhibition of the activity of these proteins could reduce the viability of pathogens that depend on vitamin uptake. The central role of vitamin transport in the metabolism of bacteria and absence from humans make the ECF transporters an attractive target for inhibition with selective chemical probes. Here, we report on the identification of a promising class of inhibitors of the ECF transporters. We used coarse-grained molecular dynamics simulations on Lactobacillus delbrueckii ECF-FolT2 and ECF-PanT to profile the binding mode and mechanism of inhibition of this novel chemotype. The results corroborate the postulated mechanism of transport and pave the way for further drug-discovery efforts.

CRAFTing Delivery of Membrane Proteins into Protocells using Nanodiscs.

For the successful generative engineering of functional artificial cells, a convenient and controllable means of delivering membrane proteins into membrane lipid bilayers is necessary. Here we report a delivery system that achieves this by employing membrane protein-carrying nanodiscs and the calcium-dependent fusion of phosphatidylserine lipid membranes. We show that lipid nanodiscs can fuse a transported lipid bilayer with the lipid bilayers of small unilamellar vesicles (SUVs) or giant unilamellar vesicles (GUVs) while avoiding recipient vesicles aggregation. This is triggered by a simple, transient increase in calcium concentration, which results in efficient and rapid fusion in a one-pot reaction. Furthermore, nanodiscs can be loaded with membrane proteins that can be delivered into target SUV or GUV membranes in a detergent-independent fashion while retaining their functionality. Nanodiscs have a proven ability to carry a wide range of membrane proteins, control their oligomeric state, and are highly adaptable. Given this, our approach may be the basis for the development of useful tools that will allow bespoke delivery of membrane proteins to protocells, equipping them with the cell-like ability to exchange material across outer/subcellular membranes.

Watching Molecular Nanotubes Self-Assemble in Real Time.

Molecular self-assembly is a fundamental process in nature that can be used to develop novel functional materials for medical and engineering applications. However, their complex mechanisms make the short-lived stages of self-assembly processes extremely hard to reveal. In this article, we track the self-assembly process of a benchmark system, double-walled molecular nanotubes, whose structure is similar to that found in biological and synthetic systems. We selectively dissolved the outer wall of the double-walled system and used the inner wall as a template for the self-reassembly of the outer wall. The reassembly kinetics were followed in real time using a combination of microfluidics, spectroscopy, cryogenic transmission electron microscopy, molecular dynamics simulations, and exciton modeling. We found that the outer wall self-assembles through a transient disordered patchwork structure: first, several patches of different orientations are formed, and only on a longer time scale will the patches interact with each other and assume their final preferred global orientation. The understanding of patch formation and patch reorientation marks a crucial step toward steering self-assembly processes and subsequent material engineering.

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.

Pragmatic Coarse-Graining of Proteins: Models and Applications.

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

Multiscale simulations reveal TDP-43 molecular-level interactions driving condensation.

The RNA-binding protein TDP-43 is associated with mRNA processing and transport from the nucleus to the cytoplasm. TDP-43 localizes in the nucleus as well as accumulating in cytoplasmic condensates such as stress granules. Aggregation and formation of amyloid-like fibrils of cytoplasmic TDP-43 are hallmarks of numerous neurodegenerative diseases, most strikingly present in >90% of amyotrophic lateral sclerosis (ALS) patients. If excessive accumulation of cytoplasmic TDP-43 causes, or is caused by, neurodegeneration is presently not known. In this work, we use molecular dynamics simulations at multiple resolutions to explore TDP-43 self- and cross-interaction dynamics. A full-length molecular model of TDP-43, all 414 amino acids, was constructed from select structures of the protein functional domains (N-terminal domain, and two RNA recognition motifs, RRM1 and RRM2) and modeling of disordered connecting loops and the low complexity glycine-rich C-terminus domain. All-atom CHARMM36m simulations of single TDP-43 proteins served as guides to construct a coarse-grained Martini 3 model of TDP-43. The Martini model and a coarser implicit solvent C⍺ model, optimized for disordered proteins, were subsequently used to probe TDP-43 interactions; self-interactions from single-chain full-length TDP-43 simulations, cross-interactions from simulations with two proteins and simulations with assemblies of dozens to hundreds of proteins. Our findings illustrate the utility of different modeling scales for accessing TDP-43 molecular-level interactions and suggest that TDP-43 has numerous interaction preferences or patterns, exhibiting an overall strong, but dynamic, association and driving the formation of biomolecular condensates.

Membrane manipulation by free fatty acids improves microbial plant polyphenol synthesis.

Microbial synthesis of nutraceutically and pharmaceutically interesting plant polyphenols represents a more environmentally friendly alternative to chemical synthesis or plant extraction. However, most polyphenols are cytotoxic for microorganisms as they are believed to negatively affect cell integrity and transport processes. To increase the production performance of engineered cell factories, strategies have to be developed to mitigate these detrimental effects. Here, we examine the accumulation of the stilbenoid resveratrol in the cell membrane and cell wall during its production using Corynebacterium glutamicum and uncover the membrane rigidifying effect of this stilbenoid experimentally and with molecular dynamics simulations. A screen of free fatty acid supplements identifies palmitelaidic acid and linoleic acid as suitable additives to attenuate resveratrol's cytotoxic effects resulting in a three-fold higher product titer. This cost-effective approach to counteract membrane-damaging effects of product accumulation is transferable to the microbial production of other polyphenols and may represent an engineering target for other membrane-active bioproducts.

Dynamics of chromosome organization in a minimal bacterial cell.

Computational models of cells cannot be considered complete unless they include the most fundamental process of life, the replication and inheritance of genetic material. By creating a computational framework to model systems of replicating bacterial chromosomes as polymers at 10 bp resolution with Brownian dynamics, we investigate changes in chromosome organization during replication and extend the applicability of an existing whole-cell model (WCM) for a genetically minimal bacterium, JCVI-syn3A, to the entire cell-cycle. To achieve cell-scale chromosome structures that are realistic, we model the chromosome as a self-avoiding homopolymer with bending and torsional stiffnesses that capture the essential mechanical properties of dsDNA in Syn3A. In addition, the conformations of the circular DNA must avoid overlapping with ribosomes identitied in cryo-electron tomograms. While Syn3A lacks the complex regulatory systems known to orchestrate chromosome segregation in other bacteria, its minimized genome retains essential loop-extruding structural maintenance of chromosomes (SMC) protein complexes (SMC-scpAB) and topoisomerases. Through implementing the effects of these proteins in our simulations of replicating chromosomes, we find that they alone are sufficient for simultaneous chromosome segregation across all generations within nested theta structures. This supports previous studies suggesting loop-extrusion serves as a near-universal mechanism for chromosome organization within bacterial and eukaryotic cells. Furthermore, we analyze ribosome diffusion under the influence of the chromosome and calculate in silico chromosome contact maps that capture inter-daughter interactions. Finally, we present a methodology to map the polymer model of the chromosome to a Martini coarse-grained representation to prepare molecular dynamics models of entire Syn3A cells, which serves as an ultimate means of validation for cell states predicted by the WCM.

Seeing the Invisibles: Detection of Peptide Enantiomers, Diastereomers, and Isobaric Ring Formation in Lanthipeptides Using Nanopores.

Mass spectrometry (MS) is widely used in proteomic analysis but cannot differentiate between molecules with the same mass-to-charge ratio. Nanopore technology might provide an alternative method for the rapid and cost-effective analysis and sequencing of proteins. In this study, we demonstrate that nanopore currents can distinguish between diastereomeric and enantiomeric differences in l- and d-peptides, not observed by conventional MS analysis, down to individual d-amino acids in small opioid peptides. Molecular dynamics simulations suggest that similar to chiral chromatography the resolution likely arises from multiple chiral interactions during peptide transport across the nanopore. Additionally, we used nanopore recordings to rapidly assess 4- and 11-amino acid ring formation in lanthipeptides, a process used in the synthesis of pharmaceutical peptides. The cyclization step requires distinguishing between constitutional isomers, which have identical MS signals and typically involve numerous tedious experiments to confirm. Hence, nanopore technology offers new possibilities for the rapid and cost-effective analysis of peptides, including those that cannot be easily differentiated by mass spectrometry.

Computational prediction of ω-transaminase selectivity by deep learning analysis of molecular dynamics trajectories.

We previously presented a computational protocol to predict the enzymatic (enantio)selectivity of an ω-transaminase towards a set of ligands (Ramírez-Palacios et al. (2021) Journal of Chemical Information and Modeling 61(11), 5569-5580) by counting the number of binding poses present in molecular dynamics (MD) simulations that met a defined set of geometric criteria. The geometric criteria consisted of a hand-crafted set of distances, angles and dihedrals deemed to be important for the enzymatic reaction to take place. In this work, the MD trajectories are reanalysed using a deep-learning approach to predict the enantiopreference of the enzyme without the need for hand-crafted criteria. We show that a convolutional neural network is capable of classifying the trajectories as belonging to the 'reactive' or 'non-reactive' enantiomer (binary classification) with a good accuracy (>0.90). The new method reduces the computational cost of the methodology, because it does not necessitate the sampling approach from the previous work. We also show that analysing how neural networks reach specific decisions can aid hand-crafted approaches (e.g. definition of near-attack conformations, or binding poses).

Molecular insights into the effects of focused ultrasound mechanotherapy on lipid bilayers: Unlocking the keys to design effective treatments.

Administration of focused ultrasounds (US) represents an attractive complement to classical therapies for a wide range of maladies, from cancer to neurological pathologies, as they are non-invasive, easily targeted, their dosage is easy to control, and they involve low risks. Different mechanisms have been proposed for their activity but the direct effect of their interaction with cell membranes is not well understood at the molecular level. This is in part due to the difficulty of designing experiments able to probe the required spatio-temporal resolutions. Here we use Molecular Dynamics (MD) simulations at two resolution levels and machine learning (ML) classification tools to shed light on the effects that focused US mechanotherapy methods have over a range of lipid bilayers. Our results indicate that the dynamic-structural response of the membrane models to the mechanical perturbations caused by the sound waves strongly depends on the lipid composition. The analyses performed on the MD trajectories contribute to a better understanding of the behavior of lipid membranes, and to open up a path for the rational design of new therapies for the long list of diseases characterized by specific lipid profiles of pathological membrane cells.

Lateral membrane organization as target of an antimicrobial peptidomimetic compound.

Antimicrobial resistance is one of the leading concerns in medical care. Here we study the mechanism of action of an antimicrobial cationic tripeptide, AMC-109, by combining high speed-atomic force microscopy, molecular dynamics, fluorescence assays, and lipidomic analysis. We show that AMC-109 activity on negatively charged membranes derived from Staphylococcus aureus consists of two crucial steps. First, AMC-109 self-assembles into stable aggregates consisting of a hydrophobic core and a cationic surface, with specificity for negatively charged membranes. Second, upon incorporation into the membrane, individual peptides insert into the outer monolayer, affecting lateral membrane organization and dissolving membrane nanodomains, without forming pores. We propose that membrane domain dissolution triggered by AMC-109 may affect crucial functions such as protein sorting and cell wall synthesis. Our results indicate that the AMC-109 mode of action resembles that of the disinfectant benzalkonium chloride (BAK), but with enhanced selectivity for bacterial membranes.