Biology subjects

Marrink, S.-J.

Publications and source records attributed to Marrink, S.-J..

At least 19 recordsLinked to original sources

bioRxiv2026

MEMBRANE PORES ACT AS SELF-RESEALING LIPID SCRAMBLASES

Biological membranes continuously experience leaflet lipid imbalances during growth, lipid synthesis, and vesicle fusion. To alleviate such imbalances and prevent these asymmetries from compromising membrane integrity, cells rely on lipid scramblases - fast and non-specific lipid channel proteins. Here we show that lipid number asymmetry alone is sufficient to drive spontaneous formation of transient hydrophilic pores that function as self-resealing lipid scramblases. Using giant unilamellar vesicles, living cells, and coarse-grained molecular dynamics simulations, we demonstrate that fusion-induced excess lipids in one leaflet lowers membrane edge tension, generating size-selective pores whose size and lifetime scale with the magnitude of asymmetry. Below a critical threshold, these pores reseal spontaneously; above it, membranes collapse. Strikingly, pore opening enables rapid, non-selective lipid translocation between leaflets, dissipating the asymmetry that nucleates the pore and thereby promoting their own closure. Cholesterol buffers moderate imbalances through spontaneous flip flop before pore formation, whereas pore-mediated lipid scrambling relieves the remaining asymmetry and restores cholesterols initial distribution. Our findings identify transient lipid pores as an intrinsic, protein-independent mechanism that couples membrane destabilization to self-repair, providing a universal physical principle for membrane homeostasis during growth, remodelling, and early cellular evolution.

biophysics↗

bioRxiv2026

The Martini 3 Metabolome

Metabolites are ubiquitous in all living cells and are essential mediators of biochemical processes, serving either as substrates or as cofactors to enable the reactions. Capturing this diversity in computational workflows is important for allowing realistic simulations of the cytoplasm. Coarse-grained molecular dynamics enables the simulation of large scale systems up to the level of whole-cells, but is limited by the availability of refined parameters for all possible components in the system. In this work, we describe the parameterization of 186 common metabolites found in bacteria and eukaryotes within the framework of the Martini 3 force field. To showcase the behavior of Martini metabolites in a biological setting, we report simulations of protein-ligand binding and membrane permeation. The establishment of a Martini metabolome enables high-throughput simulations of metabolites interacting with other biomolecules, and opens the way for simulations of realistic cellular environments.

biophysics↗

bioRxiv2026

Ligand Binding Free Energy Landscapes at the Tubulin Colchicine Site from Coarse-Grained Metadynamics

Accessing deeply buried binding sites remains a major challenge in structure-based drug discovery, where accurate description of both protein dynamics and ligand binding pathways is required. Funnel metadynamics enables simulation of complete binding processes but is computationally demanding at the all-atom resolution. By adopting the Martini 3 force field, coarse-grained funnel metadynamics (CG-FMD) substantially reduces computational requirements while retaining enhanced sampling capabilities. In this work, we assess the capability of CG-FMD to model ligand recognition at the deeply buried colchicinoids site of the tubulin {beta}-heterodimer, a multisite protein of strategic importance. We investigated the binding of colchicine, podophyllotoxin and combretastatin-A4, recovering free energy profiles with improved statistical convergence compared to AA-FMD and comparable to experimental references. In particular CG-FMD binding free energies present mean absolute errors between 3 and 10 kJ mol-1. These results propose CG-FMD as an efficient, physics-based framework for probing ligand binding to challenging sites.

biophysics↗

bioRxiv2026

Community Web Portal for Open Collaboration in the Martini Force Field Initiative

AO_SCPLOWBSTRACTC_SCPLOWThe Martini coarse-grained force field is widely used for biomolecular simulations by a large and rapidly expanding community worldwide. Over time, the development of Martini parameters, tools, and documentation has become increasingly dispersed across numerous research groups, leading to fragmentation and making it challenging for users and developers to keep track of the latest models, software, and best practices. Consequently, the development of Martini as a genuinely community-driven process has grown into a bottleneck. In response, the Martini Force Field Initiative (MFFI) has been established as an open-science effort to coordinate and support the collaborative development of all Martini resources. Here, we introduce the MFFI web portal, a platform designed around five core pillars: (i) avoiding reliance on a single group or local server; (ii) minimizing long-term maintenance overhead; (iii) reducing technical barriers for contributions; (iv) providing a unified home for parameters, tools, tutorials, example workflows, and research outputs; and (v) enabling timely dissemination of updates to the community. To achieve this, we use Quarto to generate a static website authored in Markdown, lowering the technical barrier to making contributions, and serverless architectures on Amazon Web Services for scalable, event-triggered backend operations. The source code is hosted in a public GitHub repository under an MIT license, with automated deployment via GitHub Actions and a contribution model based on pull requests for quality control. This design creates a sustainable, low-maintenance, and collaborative infrastructure that consolidates Martini resources and supports transparency. More broadly, our design exemplifies a transferable pattern for building open, community-oriented platforms for molecular modeling and computational science.

biophysics↗

bioRxiv2026

Extending the MAD Toolbox: New Polymer Builder and Enhanced Martini Database

The MArtini Database (MAD) web server (https://mad.ens-lyon.fr/) has been updated with new tools, models, and capabilities to support a broader range of molecular systems for the Martini coarse-grained (CG) force field. The most notable addition is the MAD:Polymer Builder, enabling the automated construction of CG polymer models with varying architectures and complexities. The server now incorporates the latest developments in Martini 3, providing enhanced control within the MAD:Molecule Builder over the conversion of all-atom structures into CG representations, including the implementation of G[o]Martini 3 for protein complexes and water-protein interaction biases. The MAD:Polymer Builder and MAD:Molecule Builder are both adapted to work with intrinsically disordered proteins and domains. Substantial progress has been made in expanding the MAD:Database, making a growing library of Martini-ready compounds readily accessible across the entire MAD ecosystem. These advances position MAD as a comprehensive and evolving platform for the preparation of diverse systems in CG molecular simulations.

bioinformatics↗

bioRxiv2025

An optimized contact map for GoMartini 3 enabling conformational changes in protein assemblies

Advances in structural biology, particularly cryo-electron microscopy, have enabled high-resolution characterization of complex biomolecular assemblies. These developments emphasize the need for computational approaches capable of describing biologically relevant conformational changes over extended timescales. G[o]Martini 3 is a coarse-grained approach that demonstrates computational efficiency and versatility across several systems, from protein-binding membranes and soluble proteins to intrinsically disordered proteins, while preserving key physicochemical features. In this work, we introduce an optimized approach that integrates dynamic contact information from AA-MD simulations to refine the contact map in G[o]Martini simulations. Specifically, we define high-frequency contacts (HFC), which reduce the number of original G[o] contacts set by {approx}20-30%, thereby improving the representation of conformational states beyond the original approach. Benchmarking different contact-selection criteria revealed that including intra- and interchain HFC captures structural flexibility and domain dynamics. The method was tested on three small soluble proteins and on the SARS-CoV-2 spike protein. Overall, the optimized contact map improves sampling efficiency and expands the accessible conformational landscape relative to the original G[o]Martini 3 implementation. The full framework is available as an open-source resource for large-scale simulations of biomolecular assemblies.

biophysics↗

bioRxiv2025

Butyrate blocks specific histone acetylation by preventing recruitment of p300 to acetylated histones

Butyrate, a short-chain fatty acid (SCFA) produced by microbial fermentation of dietary fiber, exerts beneficial metabolic and immunomodulatory functions through hyperactivation of the histone acetylase (HAT) p300 and inhibition of histone deacetylases (HDAC). These effects are widely believed to result in the acetylation of distinct histones that regulate specific genes, including at transcription starting sites (TSS) and enhancers. However, we show that this is not the case, as butyrate dose-dependently increases the acetylation of histones throughout the entire genome. Molecular dynamics simulations suggest that the RING-loop prevents the recruitment of p300 to acetylated histones through its bromodomain, and thereby cannot maintain the acetylation of specific histones through positive feedback. This was confirmed by showing that only catalytically inactive p300 stably binds to acetylated histones. Thus, the epigenetic regulation of specific genes by butyrate is limited, but butyrate instead increases histone acetylation globally resulting in opening of the entire chromatin structure.

molecular biology↗

bioRxiv2025

A Comparative Nanomechanical Study of Antibody and Nanobody Binding to SARS-CoV-2 Variants

The receptor-binding domain of the SARS-CoV-2 spike protein is the principal target of neutralizing antibodies (Abs) and nanobodies (Nbs). Although their thermodynamic binding properties have been extensively characterized, their stability under mechanical force remains less understood. Here, we perform a comparative nanomechanical analysis of three Abs (PDI-231, S2X259, and R1-32) and three Nbs (R14, C1, and n3113.1) bound to the RBD from the WT strain and the Omicron BA.4 and JN.1 variants. Using coarse-grained steered molecular dynamics within the G[o]Martini 3 framework, we identified distinct force-response behaviors shaped by epitope topology, binding architecture, and variant-specific mutations. Ab/RBD dissociation was characterized by asymmetric rupture events, variant-dependent unfolding of RBD segments, and occasional deformation of antibody constant domains. Analysis of single-chain systems revealed that the heavy chain acts as the main load-bearing element, while the light chain sustains a consistent but weaker mechanical response. For the two-chain Ab system, the cooperative action of both chains enhances stability, enabling complexes to withstand rupture forces in the range of 500 pN. By contrast, Nb/RBD complexes dissociated primarily through rigid-body mechanisms, transmitting force more directly to the RBD interface with minimal structural disruption. Together, these results demonstrate that mechanical resilience emerges from immune complex topology and inter-chain cooperation, providing complementary insights beyond affinity into the design of therapeutics resilient to viral evolution.

biophysics↗

bioRxiv2025

Phase separation of protein kinase A regulatory subunits is driven by similar inter- and intra-molecular interactions involving the inhibitory segment

Phase separation of biological macromolecules has emerged as a widespread mechanism for cellular organization, governing the spatiotemporal regulation of biochemical processes including signaling pathways. The regulatory subunit of the cAMP-dependent protein kinase A (PKA) RI phase separates following cAMP-induced kinase activation, thereby restricting and enhancing PKA activity in space and time. The N-terminal dimerization/docking (D/D) domain and the linker region of RI have been identified as necessary and sufficient for phase separation, but their interactions at atomic resolution have remained elusive. We report here a structural investigation of the minimal phase-separating region of RI by nuclear magnetic resonance spectroscopy (NMR) and molecular dynamics (MD) simulations. The intrinsically disordered regions of RI cause broadening of NMR signals throughout the protein indicative of widespread dynamic interactions. Mutation of arginine residues in the RI inhibitory sequence leads to a reduction in signal broadening accompanied by loss of phase separation. Independently, binding of RI to an A-kinase anchoring protein (AKAP) leads to spectral changes that are indicative of a loss of interactions between the D/D domain and the linker region, suggestive of a competition between intramolecular interactions and partner binding. Corroborating the experimental observations, multiscale MD simulations detect pervasive interactions of the folded D/D domain of RI with the intrinsically disordered linker, and the intermolecular interactions in the condensate mirror those found internally in RI dimers. Our results support the view that for PKA RI, homotypic phase separation is underpinned by intermolecular interactions that are similar to intramolecular interactions.

biophysics↗

bioRxiv2025

Condition-dependent, amorphous protein agglomerates control cytoplasmic rheology

Molecular crowding in the bacterial cytoplasm restricts the diffusion of large molecules, impacting cellular processes. However, how nutrient availability influences cytoplasmic rheology is not well understood. With single-particle tracking in Escherichia coli, we observed a threefold variation in the diffusion of a 40-nm particle across exponential growth conditions. Previously suggested determinants of rheology did not account for this variation; instead, we found a strong anticorrelation between the diffusion coefficient and the abundance of amino acid metabolism proteins, persisting upon genetic perturbations and showing that lower diffusion is associated with increased viscoelasticity. Photoactivated light microscopy revealed that some amino acid metabolism proteins form clusters. Electron microscopy showed that these proteins could form amorphous agglomerates at physiological concentrations in vitro, likely driven by their low intrinsic disorder, high compactness and hydropathy score. These findings show that protein agglomerates regulate cytoplasmic rheology in a condition-dependent manner, suggesting an underappreciated level of cytoplasmic organization. HighlightsO_LIDiffusion of 40-nm particles varies threefold across growth conditions in E. coli C_LIO_LICytoplasmic diffusion inversely correlates with COG-E protein abundance COG-E proteins form agglomerates that increase cytoplasmic viscoelasticity C_LIO_LIProtein compactness and hydrophobicity predict condition-dependent crowding effects C_LI

biophysics↗

bioRxiv2025

TS2CG as a membrane builder

Molecular dynamics (MD) simulations excel at capturing biological processes at the molecular scale but rely on a well-defined initial structure. As MD simulations now extend to whole-cell-level modeling, new tools are needed to efficiently build initial structures. Here, we introduce TS2CG version 2, designed to construct coarse-grained membrane structures with any desired shape and lateral organization. This version enables precise placement of lipids and proteins based on curvature preference, facilitating the creation of large, near-equilibrium membranes. Additional features include controlled pore generation and the placement of specific lipids at membrane edges for stabilization. Moreover, a Python interface allows users to extend functionality while maintaining the high performance of the C++ core. To demonstrate its capabilities, we showcase challenging simulations, including a Mobius strip membrane, a vesicle with lipid domain as continental plates (Martini globe), and entire mitochondrial membranes exhibiting lipid heterogeneity due to curvature, along with a comprehensive set of tutorials.

biophysics↗

bioRxiv2025

Martini 3 protein models - a practical introduction to different structure bias models and their comparison

Biophysical characterization of protein structure and dynamics is essential in many scientific fields, including molecular biology, drug discovery, and enzyme design. Molecular dynamics (MD) simulations have become an increasingly important tool for studying these properties. This chapter provides a hands-on introduction to protein modeling with the Martini 3 coarse-grained (CG) force field. We outline its two-layer framework, where the first layer defines molecular topology and interactions, while the second layer applies structural bias to maintain secondary, tertiary, and quaternary structures. Three structure bias approaches - Elastic Network (EN), G[o]Martini, and OLIVES - are discussed, highlighting their advantages and trade-offs. Using a protein kinase as a case study, we demonstrate the step-by-step setup of Martini 3 protein models for simulations with the program package GROMACS, including system preparation, fine-tuning, and validation against atomistic reference simulations. Additionally, we explore the combination of an intrinsically disordered region (IDR) with a structured protein domain. By the end of this chapter, readers will have the necessary expertise to apply Martini 3-based protein modeling to a wide range of research applications.

biophysics↗

bioRxiv2024

An integrative modelling approach to the mitochondrial cristae

Mitochondria are implicated in many cellular functions such as energy production and apoptosis but also disease pathogenesis. To effectively perform these roles, the mitochondrial inner membrane has invaginations known as cristae that dramatically increase the surface area. This works to provide more space for membrane proteins that are essential to the roles of mitochondria. While separate components of this have been studied computationally, it remains a challenge to combine elements into an overall model. Here we present a workflow to create a comprehensive model of a crista junction from a human mitochondrion. Our coarse-grained representation of a crista shows how various experimentally determined features of organelles can be combined with molecular modelling to give insights into the interactions and dynamics of complicated biological systems. This work is presented as an initial living model for this system, intended to be built upon and improved as our understanding, methodology and resources develop.

biochemistry↗

bioRxiv2024

Benchmarking coarse-grained simulation methods for investigation of transport tunnels in enzymes

Enzymes are pivotal to numerous biological processes, often featuring buried active sites linked to the surrounding solvent through intricate and dynamic tunnels. These tunnels are vital for facilitating substrate access, enabling product release, and regulating solvent exchange, which collectively influence enzymatic function and efficiency. Consequently, knowledge of tunnels is key for a holistic understanding of the effect of mutations as well as predicting drug residence times. Unfortunately, most transport tunnels are transient, i.e., equipped by molecular gates, rendering their opening a rare event that is often notoriously hard to study with conventional molecular dynamics simulations. To overcome the sampling limitation of such simulations, this study investigated the efficacy of three different coarse-grained (CG) molecular dynamics simulation methods for inferring enzyme tunnel structure and dynamics. Here, we covered the Martini and SIRAH models with different restraint protocols providing stability to CG proteins while to some extent biasing the sampling towards a reference structure. By contrasting CG results with all-atom simulations, we benchmarked the ability of CG methods to replicate ensemble characteristics of complex tunnel networks in haloalkane dehalogenase LinB and two of its mutants with engineered tunnel networks. The assessed tunnel parameters are essential for prioritizing functionally relevant tunnels and delineating the effect of mutations on transport tunnels. Our findings reveal that while CG methods significantly enhance the efficiency of tunnel analyses, some of them, like Martini with Elastic network restraints, were limited in recapitulating all-atom tunnel dynamics due to the structural bias applied. In contrast, the Martini G[o] model even captured the intricate details of mutation perturbing tunnel dynamics. All studied CG methods performed well in capturing the geometry of tunnel ensembles in line with all-atom simulations. Additionally, the wider applicability of CG methods was verified by analyzing tunnel networks of nine enzymes from different combinations of structural and functional classes, demonstrating their potential to uncover new tunnel phenomena and validate their utility in broader biological and functional contexts. This comprehensive evaluation underscores the strengths and constraints of CG simulations in capturing enzyme tunnels and benefiting from their computational speed for studying huge datasets of enzymes. These insights are valuable for enzyme engineering, drug design, and understanding enzyme function while benefitting from the efficiency of coarse-grained models.

bioinformatics↗

bioRxiv2024

Hexokinase-I directly binds to a charged membrane-buried glutamate of mitochondrial VDAC1 and VDAC2

Binding of hexokinase HKI to mitochondrial voltage-dependent anion channels (VDACs) has far-reaching physiological implications. However, the structural basis of this interaction is unclear. Combining computer simulations with experiments in cells, we here show that complex assembly relies on intimate contacts between the N-terminal -helix of HKI and a charged membrane-buried glutamate on the outer wall of VDAC1 and VDAC2. Protonation of this residue blocks complex formation in silico while acidification of the cytosol causes a reversable release of HKI from mitochondria. Membrane insertion of HKI occurs adjacent to the bilayer-facing glutamate where a pair of polar channel residues mediates a marked thinning of the cytoplasmic leaflet. Disrupting the membrane thinning capacity of VDAC1 dramatically impairs its ability to bind HKI in silico and in cells. Our data reveal key topological and mechanistic insights into HKI-VDAC complex assembly that may benefit the development of therapeutics to counter pathogenic imbalances in this process.

biochemistry↗

bioRxiv2024

Hybrid lipid-block copolymer membranes enable stable reconstitution of a wide range of nanopores and robust sampling of serum

Biological nanopores are powerful tools for detecting biomolecules at the single-molecule level, making them appealing as sensors for biological samples. However, the lipid membranes in which nanopores reside can be unstable in the presence of biological fluids. Here, membranes formed with the amphiphilic polymers PMOXA-PDMS-PMOXA and PBD-PEO are tested as potential alternatives for nanopore sensing. We demonstrate that polymer membranes can possess increased stability towards applied potentials and high concentrations of human serum, but that the stable insertion of a wide range of biological nanopores is most often compromised. Alternatively, hybrid polymer-lipid membranes comprising a 1:1 w/w mixture of PBD11PEO8 and DPhPC showed high electrical and biochemical stability while creating a suitable environment for all tested nanopores. Analytes such as proteins, DNA and sugars were efficiently sampled, indicating that in hybrid membranes nanopores showed native-like properties. Molecular dynamics simulations revealed that lipids form [~]12 nm domains interspersed by a polymer matrix. Nanopores partitioned into these lipid nanodomains and sequestered lipids possibly offering the same binding strength as in a native bilayer. This work shows that single-molecule analysis with nanopores in [PBD11PEO8 + DPhPC] membranes is feasible and present stable recordings in the presence of human serum. These results pave the way towards novel nanopore-based biosensors.

biophysics↗

bioRxiv2023

Curvature-induced lipid sorting beyond the critical packing parameter

Over the last few decades, the spatial organization of biomembranes has received a lot of attention. With the fluid mosaic model, Singer and Nicolson proposed that biomembranes behave as two-dimensional fluids, allowing proteins and lipids to diffuse freely and thus react to external stimuli. Biological functionality and membrane organization are intricately linked to each other, however, how these organizations emerge is yet to be established. Here we use coarse-grained molecular dynamics simulations to explore the relationship between membrane shape and lateral organization at the nanoscale for a broad range of lipid mixtures. Our results illustrate that membrane curvature and lateral organization are intimately linked at the nanoscale and the relationship is much more complicated compared to the traditional views, in particular the lipid shape concept. Furthermore, we show that large membrane curvature can disrupt phase separation, line tension, and interleaflet coupling leading to non-intuitive lipid sorting. Our findings highlight how curvature-driven sorting can alter the phase behavior of lipid mixtures, which could be crucial for cellular functionality.

biophysics↗

bioRxiv2023

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 semi-permeable 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 the slow water diffusion across the membrane, making it practically impossible to examine its effects in classic MD simulations. In this paper, 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 of vesicles it can handle membrane tubes and double bilayer systems as well. 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 multi-component systems containing membrane proteins or crowded internal solutions.

biophysics↗