Membrane lipid composition varies significantly across organisms, cell types, and organelles. Mammalian membranes predominantly contain lipids like phosphatidylcholine or sphingomyelin, whereas bacterial membranes are rich in phosphatidylglycerol, phosphatidylethanolamine, and cardiolipin. This diversity in lipid composition presents an opportunity to design peptides that target specific cell types. Particularly, peptides designed to preferentially bind bacterial membranes can have applications to treat bacterial infections while avoiding toxicity. Here, we present a method to identify a broad range of peptide sequences with preferential binding to bacterial membrane models. Using molecular dynamics simulations, we calculated the free energy of insertion for natural amino acid side chains into simplified bacterial and mammalian membranes and implemented a genetic algorithm to identify alpha helical peptide sequences that preferentially adsorb to bacterial membranes. The main limitation of the model is the assumption of helical secondary structure.

Flaviviruses are globally distributed human pathogens. However, the mechanisms underlying flavivirus assembly and maturation remain poorly understood. Here, we show that many particles of tick-borne encephalitis virus (TBEV) are asymmetric and lack subsets of surface heterodimers. Immature particles of TBEV contain incomplete spikes, providing evidence that their coats assemble directly from heterodimers of premembrane (prM) and envelope (E) proteins. Exposure of TBEV particles to acidic pH in the Golgi complex promotes maturation. The spikes and herringbone regions in TBEV maturation intermediates are oriented randomly rather than conforming to a common icosahedral symmetry. Consequently, the mature herringbone lattice forms around a randomly oriented nucleation center, expanding by addition of membrane-envelope heterodimers as the spikes disassemble and prMs are cleaved. The observed incompleteness of the protein coats explains, as an alternative to particle breathing, how flaviviruses can be neutralized by antibodies that bind to regions of E proteins normally inaccessible in the spiky or herringbone structures.

Antibiotic resistance is a global health threat, driving the need for new molecules that kill bacteria via nontraditional mechanisms. Here, we present a computational de novo design strategy for α-helical peptides that self-assemble into large, stable and membrane-spanning nanopores with antimicrobial activity, including in vivo efficacy against drug-resistant pathogens. Molecular dynamics simulations guided the selection of sequences for transmembrane barrel-stave pore formation, which were validated by microscopy, electrophysiology and fluorescence assays. Using computational and experimental analyses, including negative design controls, we developed general design guidelines and 52 modular sequence templates with tunable antimicrobial, pore-forming properties. Mechanistic studies confirmed bacterial cytoplasmic membrane disruption via designed nanopore formation. A tuned lead peptide selectively killed drug-resistant ESKAPEE bacteria, including Acinetobacter baumannii, without harming human cells, and showed anti-infective efficacy in preclinical mouse infection models. The framework presented here enables the design of synthetic peptide nanopores for precision antimicrobials, anticancer agents, molecular sensors and delivery systems.

All-atom molecular dynamics simulations are powerful tools for studying cell membranes and their interactions with proteins and other molecules. However, these processes occur on time scales determined by the diffusion rate of phospholipids, which are challenging to achieve in all-atom models. Here, we present a new all-atom model that accelerates lipid diffusion by splitting phospholipid molecules into head and tail groups. The bilayer structure is maintained by using external lateral potentials, which compensate for the lipid split. This split model enhances lateral lipid diffusion more than ten times, allowing faster and cheaper equilibration of large systems with different phospholipid types. The current model has been tested on membranes containing PSM, POPC, POPS, POPE, POPA, and cholesterol. We have also evaluated the interaction of the split model membranes with the Disheveled DEP domain and amphiphilic helix motif of the transcriptional repressor Opi1 as representative of peripheral proteins as well as the dimeric fragment of the epidermal growth factor receptor transmembrane domain and the Human A2A Adenosine of G protein-coupled receptors as representative of transmembrane proteins. The split model can predict the interaction sites of proteins and their preferred phospholipid type. Thus, the model could be used to identify lipid binding sites and equilibrate large membranes at an affordable computational cost.

The elongation rates of RNA polymerase II (RNAPII) require precise control to prevent transcriptional stress, which can impede co-transcriptional pre-mRNA processing and contribute to many age- or disease-associated molecular changes (e.g., loss of proteostasis). Additionally mesoscale organization of transcription is thought to control the transcriptional rates and multiple factors have been reported to form biomolecular condensates and integrate RNAPII through the interaction with the C-terminal domain (CTD) of the largest subunit, RPB1. However, the structural organization of these condensates remains uncharacterized due to their small size and inherently dynamic nature. Here, we investigated the molecular mechanisms by which a general transcription factor - RECQ5 - associates with hyperphosphorylated RNAPII elongation complex (P-RNAPII EC) and controls translocation of RNAPII along genes. We combined biochemical reconstitution, electron cryomicroscopy, cryotomography, and coarse-grained simulations. We report two mechanisms by which RECQ5 modulates RNAPII transcription. At the atomic level, we demonstrate that RECQ5 uses the brake helix as a doorstop to control RNAPII translocation along DNA, attenuating transcription. At the mesoscale level, RECQ5 forms a condensate scaffold matrix, integrating P-RNAPII EC through a network of site-specific interactions, reinforcing the structural integrity of the condensate. Our integrative, multi-scale study provides insights into the structural basis of transcription attenuation and into the molecular architecture and biogenesis of a model RNAPII condensate. ### Competing Interest Statement The authors have declared no competing interest.

Polymyxins, critical last-resort antibiotics, impact the distribution of membrane-bound divalent cations in the outer membrane of Gram-negative bacteria. We employed atomistic molecular dynamics simulations to model the effect of displacing these ions. Two polymyxin-sensitive and two polymyxin-resistant models of the outer membrane of Salmonella enterica were investigated. First, we found that the removal of all calcium ions induces global stress on the model membranes, leading to substantial membrane restructuring. Next, we used enhanced sampling methods to explore the effects of localized stress by displacing membrane-bound ions. Our findings indicate that creating defects in the membrane-bound ion network facilitates polymyxin permeation. Additionally, our study of polymyxin-resistant mutations revealed that divalent ions in resistant model membranes are less likely to be displaced, potentially contributing to the increased resistance associated with these mutations. Lastly, we compared results from all-atom molecular dynamics simulations with coarse-grained simulations, demonstrating that the choice of force field significantly influences the behavior of membrane-bound ions under stress.

The degree of unsaturation in lipids, which refers to the number of double bonds in their acyl chains, influences properties such as fluidity and lipid packing. However, it is not well understood how the unsaturation affects the ability of peptides to sense membrane curvature. In our study, we compared membranes with varying levels of unsaturation: monounsaturated POPC; bis-unsaturated DOPC; and polyunsaturated PAPC. We investigated how these membranes interact with peptides of varying hydrophobicity. Using coarse-grained molecular dynamics simulations, we found that increasing unsaturation leads to deeper peptide insertion into the lipid bilayer, which correlates with a shift in curvature preference toward more negative values. We demonstrate that specific peptides preferentially localize on the positively curved regions in saturated membranes but shift preference to negatively curved regions in unsaturated membranes, thereby functioning as sensors of membrane unsaturation. In addition, polyunsaturated lipids facilitate the reorientation of peptides from a membrane-adsorbed state to a transmembrane state. These findings may play a role in biological processes such as vesicle formation, membrane fusion, and protein sorting and highlight the adaptability of peptides to different lipid compositions in membranes.

Biomolecular condensates underpin the spatial and temporal organization of cellular biochemistry in the cell. Their architectures often arises from complex, multicomponent mixtures whose behavior is governed by weak, multivalent interactions, frequently mediated by intrinsically disordered regions (IDRs) of proteins. However, current approaches lack generalizable metrics to determine whether IDRs will mix or segregate within condensates. Here, we show that our domain decomposition method can both accurately determine concentrations in the dense/dilute phases, and provide a continuous metric for characterizing IDR mixing in molecular dynamics simulations. Applying this methodology to 1,963 binary mixtures, we find that mixing at equimolar ratios is rare. Most condensate-forming pairs favoring one dominant scaffold and minority client molecules. We found that hydrophobic IDRs mix promiscuously with most sequences, while the mixing of charged sequences is sensitive to the charge and complementarity of the partner. When applied to experimental protein interaction networks, our simulations successfully distinguish IDR-mediated partitioning from those requiring additional factors such as RNA or site specific binding. Our results provide a foundation for determining condensate composition in complex cellular environments and for designing synthetic IDRs that can infiltrate or modulate biomolecular condensates. ### Competing Interest Statement The authors have declared no competing interest.

HaloTag technology represents a versatile tool for studying proteins. Fluorescent HaloTag ligands employed in sequential labeling led to the discovery of distinct protein variants for histones, cohesins, and MCM complexes. However, an efficient biochemical approach to separate these distinct protein variants to study their biological functions is missing. Principally, being a gap in technology, the HaloTag toolbox lacks affinity ligands displaying good cell permeability and efficient affinity capture. Here, we describe the design, synthesis, and validation of a new cell-permeable biotin-HaloTag ligand, which allows rapid labeling of Halo-tagged proteins in live cells and their efficient separation using streptavidin pull-down. We provide a proof-of-concept application of how to use the herein-developed affinity ligand in sequential labeling to biochemically separate protein variants and study their biological properties. This approach enables to address fundamental questions concerning essential cellular processes, including genome duplication and chromatin maintenance.

Lipid order parameters are an important metric for quantifying the molecular structure of biological membranes. They can be derived from both molecular simulations and experimental measurements, enabling robust comparisons between the two. Although methods for calculating lipid order parameters from molecular dynamics simulations of membrane systems at various resolutions are well established, a comprehensive and user-friendly package for these calculations is lacking, which has even led some researchers to use tools that are known to perform the calculations incorrectly. To address this, we have developed gorder, an analysis tool capable of calculating lipid order parameters in atomistic, united-atom, and coarse-grained systems, compatible with any force field, and applicable to both planar and curved membrane geometries. gorder is designed to be fast and versatile, providing a unified solution for lipid order calculations. The tool is freely available from https://crates.io/crates/gorder and https://github.com/Ladme/gorder under the MIT License.

Understanding the molecular mechanisms of pore formation is crucial for elucidating fundamental biological processes and developing therapeutic strategies, such as the design of drug delivery systems and antimicrobial agents. Although experimental methods can provide valuable information, they often lack the temporal and spatial resolution necessary to fully capture the dynamic stages of pore formation. In this study, we present two novel collective variables (CVs) designed to characterize membrane pore behavior, particularly its energetics, through molecular dynamics (MD) simulations. The first CV─termed Full-Path─effectively tracks both the nucleation and expansion phases of pore formation. The second CV─called Rapid─is tailored to accurately assess pore expansion in the limit of large pores, providing quick and reliable method for evaluating membrane line tension under various conditions. Our results clearly demonstrate that the line tension predictions from both our CVs are in excellent agreement. Moreover, these predictions align qualitatively with available experimental data. Specifically, they reflect higher line tension of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) membranes containing 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-l-serine (POPS) lipids compared to pure POPC, the decrease in line tension of POPC vesicles as the 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPG) content increases, and higher line tension when ionic concentration is increased. Notably, these experimental trends are accurately captured only by the all-atom CHARMM36 and prosECCo75 force fields. In contrast, the all-atom Slipids force field, along with the coarse-grained Martini 2.2, Martini 2.2 polarizable, and Martini 3 models, show varying degrees of agreement with experiments. Our developed CVs can be adapted to various MD simulation engines for studying pore formation, with potential implications in membrane biophysics. They are also applicable to simulations involving external agents, offering an efficient alternative to existing methodologies.

The diffusion of macromolecules, nanoparticles, viruses, and bacteria is essential for targeting hosts or cellular destinations. While these entities can bind to receptors and ligands on host surfaces, the impact of multiple binding sites-referred to as multivalency-on diffusion along strands or surfaces is poorly understood. Through numerical simulations, we have discovered a significant acceleration in diffusion for particles with increasing valency, while maintaining the same overall affinity to the host surface. This acceleration arises from the redistribution of the binding affinity of the particle across multiple binding ligands. As a result, particles that are immobilized when monovalent can achieve near-unrestricted diffusion upon becoming multivalent. Additionally, we demonstrate that the diffusion of multivalent particles with a rigid ligand distribution can be modulated by patterned host receptors. These findings provide insights into the complex diffusion mechanisms of multivalent particles and biological entities, and offer new strategies for designing advanced nanoparticle systems with tailored diffusion properties, thereby enhancing their effectiveness in applications such as drug delivery and diagnostics.

Phospholipid membranes serve as essential barriers in biological systems, and protein-mediated lipid flip-flop is a crucial process for lipid homeostasis in membranes, which is vital for various cellular functions. These phenomena can be studied using the Martini coarse-grained force field, a valuable tool for membrane simulations that balances computational efficiency with chemical accuracy while capturing key membrane properties. However, the accuracy of the newer Martini 3 force field in describing energetics of phospholipid flip-flop remains unknown. Here, we show dramatic differences in the free energy barriers of lipid flip-flop when simulated with Martini 3, Martini 2.2, and CHARMM36m force fields. Using umbrella sampling simulations of six phospholipids (POPC, DPPA, POPE, POPG, POPS, and DPTAP) in the POPC membrane, we demonstrate that Martini 3 predicts significantly lower flip-flop barriers compared to all-atom simulations and the older Martini 2.2 version, with particularly severe underestimation for the positively charged lipid (DPTAP). For DPTAP, we identified that altered Lennard-Jones parameters between choline and alkyl tail beads likely contribute to this discrepancy, as evidenced by our systematic parameter testing. These findings highlight limitations in the current Martini 3 parametrization that should be considered when studying processes involving molecular transport across membranes and suggest potential refinements to improve the model's accuracy for such phenomena. To complete the picture, we also discuss the energetics of flip-flops of phospholipids with various lipid tail lengths (DLPC, DMPC, DPPC, DSPC) and lipid tail saturation (DOPC).