Martini 3: a general purpose force field for coarse-grained molecular dynamics

Unbiased MD simulations identify lipid binding sites in lipid transfer proteins

The characterization of lipid binding to lipid transfer proteins (LTPs) is fundamental to understand their molecular mechanism. However, several structures of LTPs, and notably those proposed to act as bridges between membranes, do not provide the precise location of their endogenous lipid ligands. To address this limitation, computational approaches are a powerful alternative methodology, but they are often limited by the high flexibility of lipid substrates. Here, we develop a protocol based on unbiased coarse-grain molecular dynamics simulations in which lipids placed away from the protein can spontaneously bind to LTPs. This approach accurately determines binding pockets in LTPs and provides a working hypothesis for the lipid entry pathway. We apply this approach to characterize lipid binding to bridge LTPs of the Vps13-Atg2 family, for which the lipid localization inside the protein is currently unknown. Overall, our work paves the way to determine binding pockets and entry pathways for several LTPs in an inexpensive, fast, and accurate manner.

Single-molecule imaging and molecular dynamics simulations reveal early activation of the MET receptor in cells

Embedding of cell-surface receptors into a membrane defines their dynamics but also complicates experimental characterization of their signaling complexes. The hepatocyte growth factor receptor MET is a receptor tyrosine kinase involved in cellular processes such as proliferation, migration, and survival. It is also targeted by the pathogen Listeria monocytogenes, whose invasion protein, internalin B (InlB), binds to MET, forming a signaling dimer that triggers pathogen internalization. Here we use an integrative structural biology approach, combining molecular dynamics simulations and single-molecule Förster resonance energy transfer (smFRET) in cells, to investigate the early stages of MET activation. Our simulations show that InlB binding stabilizes MET in a conformation that promotes dimer formation. smFRET reveals that the in situ dimer structure closely resembles one of two previously published crystal structures, though with key differences. This study refines our understanding of MET activation and provides a methodological framework for studying other plasma membrane receptors.

Application of molecular dynamics simulation in the field of food enzymes: improving the thermal-stability and catalytic ability

Enzymes can produce high-quality food with low pollution, high function, high acceptability, and medical aid. However, most enzymes, in their native form, do not meet the industrial requirements. Sequence-based and structure-based methods are the two main strategies used for enzyme modification. Molecular Dynamics (MD) simulation is a sufficiently comprehensive technology, from a molecular perspective, which has been widely used for structure information analysis and enzyme modification. In this review, we summarize the progress and development of MD simulation, particularly for software, force fields, and a standard procedure. Subsequently, we review the application of MD simulation in various food enzymes for thermostability and catalytic improvement was reviewed in depth. Finally, the limitations and prospects of MD simulation in food enzyme modification research are discussed. This review highlights the significance of MD simulation and its prospects in food enzyme modification.

A coarse-grained model for disordered and multi-domain proteins

Many proteins contain more than one folded domain, and such modular multi-domain proteins help expand the functional repertoire of proteins. Because of their larger size and often substantial dynamics, it may be difficult to characterize the conformational ensembles of multi-domain proteins by simulations. Here, we present a coarse-grained model for multi-domain proteins that is both fast and provides an accurate description of the global conformational properties in solution. We show that the accuracy of a one-bead-per-residue coarse-grained model depends on how the interaction sites in the folded domains are represented. Specifically, we find excessive domain-domain interactions if the interaction sites are located at the position of the Cα atoms. We also show that if the interaction sites are located at the center of mass of the residue, we obtain good agreement between simulations and experiments across a wide range of proteins. We then optimize our previously described CALVADOS model using this center-of-mass representation, and validate the resulting model using independent data. Finally, we use our revised model to simulate phase separation of both disordered and multi-domain proteins, and to examine how the stability of folded domains may differ between the dilute and dense phases. Our results provide a starting point for understanding interactions between folded and disordered regions in proteins, and how these regions affect the propensity of proteins to self-associate and undergo phase separation.

Anchorage of bacterial effector at plasma membrane via selective phosphatidic acid binding to modulate host cell signaling

Binding phospholipid is a simple, yet flexible, strategy for anchorage of bacterial effectors at cell membrane to manipulate host signaling responses. Phosphatidylinositol 4-phosphate and phosphatidylinositol 4,5-biphosphate are the only two phospholipid species known to direct bacterial effectors to establish inner leaflet localization at the plasma membrane. Here, selectivity of phosphatidic acid (PA) by bacterial effectors for the plasma membrane anchorage and its molecular entity was identified. C-terminal BID domain of Bartonella T4SS effectors (Beps) directed the plasma membrane localization of Beps in host cells through binding with PA. A hydrophobic segment of the 'HOOK' subdomain from BID is inserted into the bilayer to enhance the interaction of positively charged residues with the lipid headgroups. Mutations of a conserved arginine facilitating the electrostatic interaction, a conserved glycine maintaining the stability of the PA binding groove, and hydrophobic residues determining membrane insertion, prevented the anchorage of Beps at the plasma membrane. Disassociation from plasma membrane to cytosol attenuated the BepC capacity to induce stress fiber formation and cell fragmentation in host cells. The substitution of alanine with aspartic acid at the -1 position preceding the conserved arginine residue hindered BepD anchoring at the plasma membrane, a vital prerequisite for its ability to elicit IL-10 secretion in host macrophages. In conclusion, our findings reveal the PA-binding properties of bacterial effectors to establish plasma membrane localization and will shed light on the intricate mechanisms employed by bacterial effectors within host cells.

Applying Spatiotemporal Modeling of Cell Dynamics to Accelerate Drug Development

Cells act as physical computational programs that utilize input signals to orchestrate molecule-level protein-protein interactions (PPIs), generating and responding to forces, ultimately shaping all of the physiological and pathophysiological behaviors. Genome editing and molecule drugs targeting PPIs hold great promise for the treatments of diseases. Linking genes and molecular drugs with protein-performed cellular behaviors is a key yet challenging issue due to the wide range of spatial and temporal scales involved. Building predictive spatiotemporal modeling systems that can describe the dynamic behaviors of cells intervened by genome editing and molecular drugs at the intersection of biology, chemistry, physics, and computer science will greatly accelerate pharmaceutical advances. Here, we review the mechanical roles of cytoskeletal proteins in orchestrating cellular behaviors alongside significant advancements in biophysical modeling while also addressing the limitations in these models. Then, by integrating generative artificial intelligence (AI) with spatiotemporal multiscale biophysical modeling, we propose a computational pipeline for developing virtual cells, which can simulate and evaluate the therapeutic effects of drugs and genome editing technologies on various cell dynamic behaviors and could have broad biomedical applications. Such virtual cell modeling systems might revolutionize modern biomedical engineering by moving most of the painstaking wet-laboratory effort to computer simulations, substantially saving time and alleviating the financial burden for pharmaceutical industries.

Effect of Surface-Immobilized States of Antimicrobial Peptides on Their Ability to Disrupt Bacterial Cell Membrane Structure

Antimicrobial peptide (AMP) surfaces are widely used to inhibit biofilm formation and bacterial infection. However, endpoint-immobilized AMPs on surfaces are totally different from free-state AMPs due to the constraints of the surface. In this work, the interactions between AMPs and bacterial cell membranes were analyzed through coarse-grained molecular dynamics and all-atom molecular dynamics simulations. This AMP disrupted membrane structure by altering the thickness and curvature of the membrane. Furthermore, the effect of surface-immobilized states of AMPs on their ability to disrupt membrane structure was revealed. The immobilized AMPs in the freeze-N system could bind to the membrane and disrupt the membrane structure through electrostatic forces between positively charged N-terminal amino acid residues and the negatively charged membrane, while the immobilized AMPs in the freeze-C system were repelled. The results will aid in the rational design of new AMP surfaces with enhanced efficacy and stability.

A Nonfouling Electrochemical Biosensor for Protein Analysis in Complex Body Fluids Based on Multifunctional Peptide Conjugated with PEGlyated Phospholipid

Developing antifouling biosensors capable of performing robustly in complex human body fluids is crucial for biomarker diagnosis and health monitoring. Herein, an antifouling and highly sensitive and stable biosensor was constructed through the self-assembly of the designed conjugates composed of a multifunctional peptide (MP) and PEGylated distearoylphosphatidylethanolamine (DSPE-PEG). The self-assembly capability of the DSPE-PEG-MP was demonstrated clearly through coarse-grained molecular dynamics simulation and transmission electron microscopy, and it can be effectively self-assembled onto the electrode surface modified with gold nanoparticles. The MP was designed to be antifouling and contained a peptide sequence that can specifically bind the target protein Annexin A1 (ANXA1), and the D-type amino acid composition of MP can enhance its resistance to enzymatic hydrolysis. The unique design of MP, in conjugation with the self-assembly capability of the PEGylated phospholipid DSPE-PEG, enabled the biosensor to exhibit excellent antifouling capability and stability in various complex human body fluids. The biosensor was capable of sensitively and selectively quantifying ANXA1 and achieved a limit of detection down to 0.12 pg mL-1. More importantly, the biosensor demonstrated satisfactory accuracy for ANXA1 detection in clinical serum samples, as verified by the enzyme linked immunosorbent assay (ELISA) kits. It is expected that various antifouling biosensors suitable for application in complex biological environments can be constructed by utilizing the strategy of designing similar DSPE-PEG-MP conjugates.

Sequence and structural determinants of RNAPII CTD phase-separation and phosphorylation by CDK7

The intrinsically disordered carboxy-terminal domain (CTD) of the largest subunit of RNA Polymerase II (RNAPII) consists of multiple tandem repeats of the consensus heptapeptide Y1-S2-P3-T4-S5-P6-S7. The CTD promotes liquid-liquid phase-separation (LLPS) of RNAPII in vivo. However, understanding the role of the conserved heptad residues in LLPS is hampered by the lack of direct biochemical characterization of the CTD. Here, we generated a systematic array of CTD variants to unravel the sequence-encoded molecular grammar underlying the LLPS of the human CTD. Using in vitro experiments and molecular dynamics simulations, we report that the aromaticity of tyrosine and cis-trans isomerization of prolines govern CTD phase-separation. The cis conformation of prolines and β-turns in the SPXX motif contribute to a more compact CTD ensemble, enhancing interactions among CTD residues. We further demonstrate that prolines and tyrosine in the CTD consensus sequence are required for phosphorylation by Cyclin-dependent kinase 7 (CDK7). Under phase-separation conditions, CDK7 associates with the surface of the CTD droplets, drastically accelerating phosphorylation and promoting the release of hyperphosphorylated CTD from the droplets. Our results highlight the importance of conformationally restricted local structures within spacer regions, separating uniformly spaced tyrosine stickers of the CTD heptads, which are required for CTD phase-separation.

Changing Your Martini Can Still Give You a Hangover

The Martini 3.0 coarse-grained force field, which was parametrized to better capture transferability in top-down coarse-grained models, is analyzed to assess its accuracy in representing thermodynamic and structural properties with respect to the underlying atomistic representation of the system. These results are compared to those obtained following the principles of statistical mechanics that start from the same underlying atomistic system. To this end, the potentials of mean force for lateral association in Martini 3.0 binary lipid bilayers are decomposed into their entropic and enthalpic components and compared to those of corresponding atomistic bilayers that have been projected onto equivalent coarse-grained mappings but evolved under the fully atomistic forces. This is accomplished by applying the reversible work theorem to lateral pair correlation functions between coarse-grained lipid beads taken at a range of different temperatures. The entropy-enthalpy decompositions provide a metric by which the underlying statistical mechanical properties of Martini can be investigated. Overall, Martini 3.0 is found to fail to properly partition entropy and enthalpy for the PMFs compared to the mapped all-atom results, despite changes made to the force field from the Martini 2.0 version. This outcome points to the fact that the development of more accurate top-down coarse-grained models such as Martini will likely necessitate temperature-dependent terms in the corresponding CG force-field; although necessary, this may not be sufficient to improve Martini. In addition to the entropy-enthalpy decompositions, Martini 3.0 produces an incorrect undulation spectrum, in particular at intermediate length scales of biophysical pertinence.

IGF2BP1 phosphorylation in the disordered linkers regulates ribonucleoprotein condensate formation and RNA metabolism

The insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1) is a conserved RNA-binding protein that regulates RNA stability, localization and translation. IGF2BP1 is part of various ribonucleoprotein (RNP) condensates. However, the mechanism that regulates its assembly into condensates remains unknown. By using proteomics, we demonstrate that phosphorylation of IGF2BP1 at S181 in a disordered linker is regulated in a stress-dependent manner. Phosphomimetic mutations in two disordered linkers, S181E and Y396E, modulate RNP condensate formation by IGF2BP1 without impacting its binding affinity for RNA. Intriguingly, the S181E mutant, which lies in linker 1, impairs IGF2BP1 condensate formation in vitro and in cells, whereas a Y396E mutant in the second linker increases condensate size and dynamics. Structural approaches show that the first linker binds RNAs nonspecifically through its RGG/RG motif, an interaction weakened in the S181E mutant. Notably, linker 2 interacts with IGF2BP1's folded domains and these interactions are partially impaired in the Y396E mutant. Importantly, the phosphomimetic mutants impact IGF2BP1's interaction with RNAs and remodel the transcriptome in cells. Our data reveal how phosphorylation modulates low-affinity interaction networks in disordered linkers to regulate RNP condensate formation and RNA metabolism.

A millisecond coarse-grained simulation approach to decipher allosteric cannabinoid binding at the glycine receptor α1

Glycine receptors (GlyR) are regulated by small-molecule binding at several allosteric sites. Cannabinoids like tetrahydrocannabinol (THC) and N-arachidonyl-ethanol-amide (AEA) potentiate the GlyR response but their mechanism of action is not fully established. By combining millisecond coarse-grained (CG) MD simulations powered by Martini 3 with backmapping to all-atom representations, we have characterized the cannabinoid-binding site(s) at the zebrafish GlyR-α1 active state with atomic resolution. Based on hundreds of thousand ligand-binding events, we find that cannabinoids bind to the transmembrane domain of the receptor at both intrasubunit and intersubunit sites. For THC, the intrasubunit binding mode predicted in simulation is in excellent agreement with recent cryo-EM structures, while intersubunit binding recapitulates in full previous mutagenesis experiments. Intriguingly, AEA is predicted to bind at the same intersubunit site despite the strikingly different chemistry. Statistical analyses of the ligand-receptor interactions highlight potentially relevant residues for GlyR potentiation, offering experimentally testable predictions. The predictions for AEA have been validated by electrophysiology recordings of rationally designed mutants. The results highlight the existence of multiple cannabinoid-binding sites for the allosteric regulation of GlyR and put forward an effective strategy for the identification and structural characterization of allosteric binding sites.

Dual regulation of IP3 receptors by IP3 and PIP2 controls the transition from local to global Ca2+ signals

The spatial organization of inositol 1,4,5-trisphosphate (IP3)-evoked Ca2+ signals underlies their versatility. Low stimulus intensities evoke Ca2+ puffs, localized Ca2+ signals arising from a few IP3 receptors (IP3Rs) within a cluster tethered beneath the plasma membrane. More intense stimulation evokes global Ca2+ signals. Ca2+ signals propagate regeneratively as the Ca2+ released stimulates more IP3Rs. How is this potentially explosive mechanism constrained to allow local Ca2+ signaling? We developed methods that allow IP3 produced after G-protein coupled receptor (GPCR) activation to be intercepted and replaced by flash photolysis of a caged analog of IP3. We find that phosphatidylinositol 4,5-bisphosphate (PIP2) primes IP3Rs to respond by partially occupying their IP3-binding sites. As GPCRs stimulate IP3 formation, they also deplete PIP2, relieving the priming stimulus. Loss of PIP2 resets IP3R sensitivity and delays the transition from local to global Ca2+ signals. Dual regulation of IP3Rs by PIP2 and IP3 through GPCRs controls the transition from local to global Ca2+ signals.

Coarse-Graining the Recognition of a Glycolipid by the C-Type Lectin Mincle Receptor

Macrophage inducible Ca2+-dependent lectin (Mincle) receptor recognizes Mycobacterium tuberculosis glycolipids to trigger an immune response. This host membrane receptor is thus a key player in the modulation of the immune response to infection by M. tuberculosis and has emerged as a promising target for the development of new vaccines against tuberculosis. The recent development of the Martini 3 force field for coarse-grained (CG) molecular modeling allows the study of interactions of soluble proteins with small ligands which was not typically modeled well with the previous Martini 2 model. Here, we present a refined approach detailing a protocol for modeling interactions between a glycolipid and its receptor at a CG level using the Martini 3 force field. Using this approach, we studied Mincle and identified critical parameters governing ligand recognition, such as loop flexibility and the regulation of hydrophobic groove formation by calcium ions. In addition, we assessed ligand affinity using free energy perturbation calculations. Our results offer mechanistic insight into the interactions between Mincle and glycolipids, providing a basis for the rational design of molecules targeting this type of membrane receptors.

Coarse-Grained Simulations of Adeno-Associated Virus and Its Receptor Reveal Influences on Membrane Lipid Organization and Curvature

Adeno-associated virus (AAV) is a well-known gene delivery tool with a wide range of applications, including as a vector for gene therapies. However, the molecular mechanism of its cell entry remains unknown. Here, we performed coarse-grained molecular dynamics simulations of the AAV serotype 2 (AAV2) capsid and the universal AAV receptor (AAVR) in a model plasma membrane environment. Our simulations show that binding of the AAV2 capsid to the membrane induces membrane curvature, along with the recruitment and clustering of GM3 lipids around the AAV2 capsid. We also found that the AAVR binds to the AAV2 capsid at the VR-I loops using its PKD2 and PKD3 domains, whose binding poses differs from previous structural studies. These first molecular-level insights into AAV2 membrane interactions suggest a complex process during the initial phase of AAV2 capsid internalization.

Nanomechanical footprint of SARS-CoV-2 variants in complex with a potent nanobody by molecular simulations

Rational design of novel antibody therapeutics against viral infections such as coronavirus relies on surface complementarity and high affinity for their effectiveness. Here, we explore an additional property of protein complexes, the intrinsic mechanical stability, in SARS-CoV-2 variants when complexed with a potent antibody. In this study, we utilized a recent implementation of the GōMartini 3 approach to investigate large conformational changes in protein complexes with a focus on the mechanostability of the receptor-binding domain (RBD) from WT, Alpha, Delta, and XBB.1.5 variants in complex with the H11-H4 nanobody. The analysis revealed moderate differences in mechanical stability among these variants. Also, we identified crucial residues in both the RBD and certain protein segments in the nanobody that contribute to this property. By performing pulling simulations and monitoring the presence of specific native and non-native contacts across the protein complex interface, we provided mechanistic insights into the dissociation process. Force-displacement profiles indicate a tensile force clamp mechanism associated with the type of protein complex. Our computational approach not only highlights the key mechanostable interactions that are necessary to maintain overall stability, but it also paves the way for the rational design of potent antibodies that are mechanostable and effective against emergent SARS-CoV-2 variants.

Alchemical Transformations and Beyond: Recent Advances and Real-World Applications of Free Energy Calculations in Drug Discovery

Computational methods constitute efficient strategies for screening and optimizing potential drug molecules. A critical factor in this process is the binding affinity between candidate molecules and targets, quantified as binding free energy. Among various estimation methods, alchemical transformation methods stand out for their theoretical rigor. Despite challenges in force field accuracy and sampling efficiency, advancements in algorithms, software, and hardware have increased the application of free energy perturbation (FEP) calculations in the pharmaceutical industry. Here, we review the practical applications of FEP in drug discovery projects since 2018, covering both ligand-centric and residue-centric transformations. We show that relative binding free energy calculations have steadily achieved chemical accuracy in real-world applications. In addition, we discuss alternative physics-based simulation methods and the incorporation of deep learning into free energy calculations.

Absorption of Polypropylene in Dipalmitoylphosphatidylcholine Membranes: The Role of Molecular Weight and Initial Configuration of Polymer Chains

We study by molecular dynamics simulations the absorption of polypropylene (PP) chains within a dipalmitoylphosphatidylcholine (DPPC) lipid membrane in aqueous solvent. DPPC represents the most abundant phospholipid in biological membranes, while PP is one of the most common synthetic polymers diffused in the anthropic environment. By following in detail the absorption process, and the corresponding structural modification undergone by the membrane, we show how the initial configuration and the PP molecular weight determine the overall behavior of the system. Specifically, if PP chains initially lie on the DPPC surface, they are fully absorbed; likewise, polymers initially included within the membrane cannot escape from. On the other hand, if polymers are placed sufficiently apart from the membrane, they have time to join together and coalesce into a few nanoparticles. At contact, such nanoparticles may completely dissolve (for low molecular weight) and then be absorbed. For high molecular weight, not all of them dissolve, and therefore the system attains a condition in which some of the chains are absorbed, while others form a residual nanoparticle staying outside (but in contact with) the membrane. Such a state─albeit energetically unfavorable with respect to a condition in which all PP chains are absorbed─remains stable, at the least over a substantial simulation time, extending in our study up to 1.6 μs. The tendency for polymers to spontaneously form aggregates, which then prefer to stay in contact with the membrane, is further corroborated by calculation of the DPPC-nanoparticle potential of mean force.

Evolution of the conformational dynamics of the molecular chaperone Hsp90

Hsp90 is a molecular chaperone of central importance for protein homeostasis in the cytosol of eukaryotic cells, with key functional and structural traits conserved from yeast to man. During evolution, Hsp90 has gained additional functional importance, leading to an increased number of interacting co-chaperones and client proteins. Here, we show that the overall conformational transitions coupled to the ATPase cycle of Hsp90 are conserved from yeast to humans, but cycle timing as well as the dynamics are significantly altered. In contrast to yeast Hsp90, the human Hsp90 is characterized by broad ensembles of conformational states, irrespective of the absence or presence of ATP. The differences in the ATPase rate and conformational transitions between yeast and human Hsp90 are based on two residues in otherwise conserved structural elements that are involved in triggering structural changes in response to ATP binding. The exchange of these two mutations allows swapping of the ATPase rate and of the conformational transitions between human and yeast Hsp90. Our combined results show that Hsp90 evolved to a protein with increased conformational dynamics that populates ensembles of different states with strong preferences for the N-terminally open, client-accepting states.

Structure of tetrameric forms of the serotonin-gated 5-HT3A receptor ion channel

Multimeric membrane proteins are produced in the endoplasmic reticulum and transported to their target membranes which, for ion channels, is typically the plasma membrane. Despite the availability of many fully assembled channel structures, our understanding of assembly intermediates, multimer assembly mechanisms, and potential functions of non-standard assemblies is limited. We demonstrate that the pentameric ligand-gated serotonin 5-HT3A receptor (5-HT3AR) can assemble to tetrameric forms and report the structures of the tetramers in plasma membranes of cell-derived microvesicles and in membrane memetics using cryo-electron microscopy and tomography. The tetrameric structures have near-symmetric transmembrane domains, and asymmetric extracellular domains, and can bind serotonin molecules. Computer simulations, based on our cryo-EM structures, were used to decipher the assembly pathway of pentameric 5-HT3R and suggest a potential functional role for the tetrameric receptors.

Disordered regions in the IRE1α ER lumenal domain mediate its stress-induced clustering

Conserved signaling cascades monitor protein-folding homeostasis to ensure proper cellular function. One of the evolutionary conserved key players is IRE1, which maintains endoplasmic reticulum (ER) homeostasis through the unfolded protein response (UPR). Upon accumulation of misfolded proteins in the ER, IRE1 forms clusters on the ER membrane to initiate UPR signaling. What regulates IRE1 cluster formation is not fully understood. Here, we show that the ER lumenal domain (LD) of human IRE1α forms biomolecular condensates in vitro. IRE1α LD condensates were stabilized both by binding to unfolded polypeptides as well as by tethering to model membranes, suggesting their role in assembling IRE1α into signaling-competent stable clusters. Molecular dynamics simulations indicated that weak multivalent interactions drive IRE1α LD clustering. Mutagenesis experiments identified disordered regions in IRE1α LD to control its clustering in vitro and in cells. Importantly, dysregulated clustering of IRE1α mutants led to defects in IRE1α signaling. Our results revealed that disordered regions in IRE1α LD control its clustering and suggest their role as a common strategy in regulating protein assembly on membranes.

The molecular picture of the local environment in a stable model coacervate

Complex coacervates play essential roles in various biological processes and applications. Although substantial progress has been made in understanding the molecular interactions driving complex coacervation, the mechanisms stabilizing coacervates against coalescence remain experimentally challenging and not fully elucidated. We recently showed that polydiallyldimethylammonium chloride (PDDA) and adenosine triphosphate (ATP) coacervates stabilize upon their transfer to deionized (DI) water. Here, we perform molecular dynamics simulations of PDDA-ATP coacervates in supernatant and DI water, to understand the ion dynamics and structure within stable coacervates. We found that transferring the coacervates to DI water results in an immediate ejection of a significant fraction of small ions (Na+ and Cl-) from the surface of the coacervates to DI water. We also observed a notable reduction in the mobility of these counterions in coacervates when in DI water, both in the cluster-forming and slab simulations, together with a lowered displacement of PDDA and ATP. These results suggest that the initial ejection of the ions from the coacervates in DI water may induce an interfacial skin layer formation, inhibiting further mobility of ions in the skin layer.

Free Energy Analysis of Peptide-Induced Pore Formation in Lipid Membranes by Bridging Atomistic and Coarse-Grained Simulations

Antimicrobial peptides (AMPs) are attractive materials for combating the antimicrobial resistance crisis because they can kill target microbes by directly disrupting cell membranes. Although thousands of AMPs have been discovered, their molecular mechanisms of action are still poorly understood. One broad mechanism for membrane disruption is the formation of membrane-spanning hydrophilic pores which can be stabilized by AMPs. In this study, we use molecular dynamics simulations to investigate the thermodynamics of pore formation in model single-component lipid membranes in the presence of one of three AMPs: aurein 1.2, melittin and magainin 2. To overcome the general challenge of modeling long time scale membrane-related behaviors, including AMP binding, clustering, and pore formation, we develop a generalizable methodology for sampling AMP-induced pore formation. This approach involves the long equilibration of peptides around a pore created with a nucleation collective variable by performing coarse-grained simulations, then backmapping equilibrated AMP-membrane configurations to all-atom resolution. We then perform all-atom simulations to resolve free energy profiles for pore formation while accurately modeling the interplay of lipid-peptide-solvent interactions that dictate pore formation free energies. Using this approach, we quantify free energy barriers for pore formation without direct biases on peptides or whole lipids, allowing us to investigate mechanisms of pore formation for these 3 AMPs that are a consequence of unbiased peptide diffusion and clustering. Further analysis of simulation trajectories then relates variations in pore lining by AMPs, AMP-induced lipid disruptions, and salt bridges between AMPs to the observed pore formation free energies and corresponding mechanisms. This methodology and mechanistic analysis have the potential to generalize beyond the AMPs in this study to improve our understanding of pore formation by AMPs and related antimicrobial materials.

Self-diffusion is temperature independent on active membranes

Molecular transport maintains cellular structures and functions. For example, lipid and protein diffusion sculpts the dynamic shapes and structures on the cell membrane that perform essential cellular functions, such as cell signaling. Temperature variations in thermal equilibrium rapidly change molecular transport properties. The coefficient of lipid self-diffusion increases exponentially with temperature in thermal equilibrium, for example. Hence, maintaining cellular homeostasis through molecular transport is hard in thermal equilibrium in the noisy cellular environment, where temperatures can fluctuate widely due to local heat generation. In this paper, using both molecular and lattice-based modeling of membrane transport, we show that the presence of active transport originating from the cell's cytoskeleton can make the self-diffusion of the molecules on the membrane robust to temperature fluctuations. The resultant temperature-independence of self-diffusion keeps the precision of cellular signaling invariant over a broad range of ambient temperatures, allowing cells to make robust decisions. We have also found that the Kawasaki algorithm, the widely used model of lipid transport on lattices, predicts incorrect temperature dependence of lipid self-diffusion in equilibrium. We propose a new algorithm that correctly captures the equilibrium properties of lipid self-diffusion and reproduces experimental observations.

Plant protein-lipid interfaces studied by molecular dynamics simulations

The delineation of protein-lipid interfaces is essential for understanding the mechanisms of various membrane-associated processes crucial to plant development and growth, including signalling, trafficking, and membrane transport. Due to their highly dynamic nature, the precise characterization of lipid-protein interactions by experimental techniques is challenging. Molecular dynamics simulations provide a powerful computational alternative with a spatial-temporal resolution allowing the atomistic-level description. In this review, we aim to introduce plant scientists to molecular dynamics simulations. We describe different steps of performing molecular dynamics simulations and provide a broad survey of molecular dynamics studies investigating plant protein-lipid interfaces. Our aim is also to illustrate that combining molecular dynamics simulations with artificial intelligence-based protein structure determination opens up unprecedented possibilities for future investigations of dynamic plant protein-lipid interfaces.

A Coarse-Grained SPICA Makeover for Solvated and Bare Sodium and Chloride Ions

Aqueous ionic solutions are pivotal in various scientific domains due to their natural prevalence and vital roles in biological and chemical processes. Molecular dynamics has emerged as an effective methodology for studying the dynamic behavior of these systems. While all-atomistic models have made significant strides in accurately representing and simulating these ions, the challenge persists in achieving precise models for coarse-grained (CG) simulations. Our study introduces two optimized models for sodium and chloride ions within the nonpolarizable surface property fitting coarse-grained force field (SPICA-FF) framework. The two models represent solvated ions, such as the original FF model, and unsolvated or bare ions. The nonbonded Lennard-Jones interactions were reparameterized to faithfully reproduce bulk properties, including density and surface tension, in sodium chloride solutions at varying concentrations. Notably, these optimized models replicate experimental surface tensions at high ionic strengths, a property not well-captured by the ions of the original model in the SPICA-FF. The optimized unsolvated model also proved successful in reproducing experimental osmotic pressure. Additionally, the newly reparameterized ion models capture hydrophobic interactions within sodium chloride solutions and show qualitative agreement when modeling structural changes in phospholipid bilayers, aligning with experimental observations. For aqueous solutions, these optimized models promise a more precise representation of the ion behavior.

Martini 3 OliGo̅mers: A Scalable Approach for Multimers and Fibrils in GROMACS

Martini 3 is a widely used coarse-grained simulation method for large-scale biomolecular simulations. It can be combined with a Go̅ model to realistically describe higher-order protein structures while allowing the folding and unfolding events. However, as of today, this method has largely been used only for individual monomers. In this article, we describe how the Go̅ model can be implemented within the framework of Martini 3 for a multimer system, taking into account both intramolecular and intermolecular interactions in an oligomeric protein system. We demonstrate the method by showing how it can be applied to both structural stability maintenance and assembly/disassembly of protein oligomers, using aquaporin tetramer, insulin dimer, and amyloid-β fibril as examples. We find that addition of intermolecular Go̅ potentials stabilizes the quaternary structure of proteins. The strength of the Go̅ potentials can be tuned so that the internal fluctuations of proteins match the behavior of atomistic simulation models, however, the results also show that the use of too strong intermolecular Go̅ potentials weakens the chemical specificity of oligomerization. The Martini-Go̅ model presented here enables the use of Go̅ potentials in oligomeric molecular systems in a computationally efficient and parallelizable manner, especially in the case of homopolymers, where the number of identical protein monomers is high. This paves the way for coarse-grained simulations of large protein complexes, such as viral protein capsids and prion fibrils, in complex biological environments.

Perpendicular crossing chains enable high mobility in a noncrystalline conjugated polymer

The nature of interchain π-system contacts, and their relationship to hole transport, are elucidated for the high-mobility, noncrystalline conjugated polymer C16-IDTBT by the application of scanning tunneling microscopy, molecular dynamics, and quantum chemical calculations. The microstructure is shown to favor an unusual packing motif in which paired chains cross-over one another at near-perpendicular angles. By linking to mesoscale microstructural features, revealed by coarse-grained molecular dynamics and previous studies, and performing simulations of charge transport, it is demonstrated that the high mobility of C16-IDTBT can be explained by the promotion of a highly interconnected transport network, stemming from the adoption of perpendicular contacts at the nanoscale, in combination with fast intrachain transport.

All-Atom Membrane Builder via Multiscale Simulation

I present an automated and flexible tool designed for constructing bilayer membranes at all-atom (AA) resolution. The builder initiates the construction and equilibration of bilayer membranes at Martini coarse-grained (CG) resolution, followed by resolution enhancement to the atomic level using the accompanying backmapping tool. Notably, this tool enables users to create bilayer membranes with user-defined lipid compositions and protein structures, while also offering the flexibility to accommodate new lipid types. To assess the simplicity and robustness of the tool, I demonstrate the construction of several membranes incorporating protein structures. The tool is freely available at github.com/ksy141/mstool.

Balancing thermodynamic stability, dynamics, and kinetics in phase separation of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are prevalent participants in liquid-liquid phase separation due to their inherent potential for promoting multivalent binding. Understanding the underlying mechanisms of phase separation is challenging, as phase separation is a complex process, involving numerous molecules and various types of interactions. Here, we used a simplified coarse-grained model of IDPs to investigate the thermodynamic stability of the dense phase, conformational properties of IDPs, chain dynamics, and kinetic rates of forming condensates. We focused on the IDP system, in which the oppositely charged IDPs are maximally segregated, inherently possessing a high propensity for phase separation. By varying interaction strengths, salt concentrations, and temperatures, we observed that IDPs in the dense phase exhibited highly conserved conformational characteristics, which are more extended than those in the dilute phase. Although the chain motions and global conformational dynamics of IDPs in the condensates are slow due to the high viscosity, local chain flexibility at the short timescales is largely preserved with respect to that at the free state. Strikingly, we observed a non-monotonic relationship between interaction strengths and kinetic rates for forming condensates. As strong interactions of IDPs result in high stable condensates, our results suggest that the thermodynamics and kinetics of phase separation are decoupled and optimized by the speed-stability balance through underlying molecular interactions. Our findings contribute to the molecular-level understanding of phase separation and offer valuable insights into the developments of engineering strategies for precise regulation of biomolecular condensates.

Martini 3D-OZ: A Theoretical Investigation of Solvation Shell Structures and Solvation Free Energies of Martini Coarse-Grained Proteins

We investigate the properties of aqueous solutions using integral equation theories and molecular dynamics (MD) simulations within the framework of the MARTINI coarse-grained force field. The integral equation theory used in the present work is based on the Ornstein-Zernike equation coupled with the hypernetted chain (HNC) and Kovalenko-Hirata (KH) closures. Overall, the solvation shell structures and solvation thermodynamics in the HNC approximation are shown to be in better agreement with those from the MD simulation than the KH results. Especially, through the analysis of spatial distribution functions of water around a protein, we have demonstrated that the HNC approximation can provide the highly anisotropic structure of the solvation shell of the protein. On the other hand, the KH approximation works well for simple particle solutes, but the results for highly hydrated proteins deviate quite significantly from the MD results. We further explore in detail the reason underlying the deviation caused by the KH approximation. Lastly, a potential application of the integral equation theory with the MARTINI model is outlined.

OLIVES: A Go̅-like Model for Stabilizing Protein Structure via Hydrogen Bonding Native Contacts in the Martini 3 Coarse-Grained Force Field

Coarse-grained molecular dynamics simulations enable the modeling of increasingly complex systems at millisecond timescales. The transferable coarse-grained force field Martini 3 has shown great promise in modeling a wide range of biochemical processes, yet folded proteins in Martini 3 are not stable without the application of external bias potentials, such as elastic networks or Go̅-like models. We herein develop an algorithm, called OLIVES, which identifies native contacts with hydrogen bond capabilities in coarse-grained proteins and use it to implement a novel Go̅-like model for Martini 3. We show that the protein structure instability originates in part from the lack of hydrogen bond energy in the coarse-grained force field representation. By using realistic hydrogen bond energies obtained from literature ab initio calculations, it is demonstrated that protein stability can be recovered by the reintroduction of a coarse-grained hydrogen bond network and that OLIVES removes the need for secondary structure restraints. OLIVES is validated against known protein complexes and at the same time addresses the open question of whether there is a need for protein quaternary structure bias in Martini 3 simulations. It is shown that OLIVES can reduce the number of bias terms, hereby speeding up Martini 3 simulations of proteins by up to ≈30% on a GPU architecture compared to the established Go̅MARTINI Go̅-like model.

Membrane Adsorption Enhances Translocation of Antimicrobial Peptide Buforin 2

Despite ongoing research on antimicrobial peptides (AMPs) and cell-penetrating peptides (CPPs), their precise translocation mechanism remains elusive. This includes Buforin 2 (BF2), a well-known AMP, for which spontaneous translocation across the membrane has been proposed but a high barrier has been calculated. Here, we used computer simulations to investigate the effect of a nonequilibrium situation where the peptides are adsorbed on one side of the lipid bilayer, mimicking experimental conditions. We demonstrated that the asymmetric membrane adsorption of BF2 enhances its translocation across the lipid bilayer by lowering the energy barrier by tens of kJ mol-1. We showed that asymmetric membrane adsorption also reduced the free energy barrier of lipid flip-flop but remained unlikely even at BF2 surface saturation. These results provide insight into the driving forces behind membrane translocation of cell-penetrating peptides in nonequilibrium conditions, mimicking experiments.

Self-assembly of sustainable plant protein protofilaments into a hydrogel for ultra-low friction across length scales

Designing plant protein-based aqueous lubricants can be of great potential to achieve sustainability objectives by capitalising on inherent functional groups without using synthetic chemicals; however, such a concept remains in its infancy. Here, we engineer a class of self-assembled sustainable materials by using plant-based protofilaments and their assembly within a biopolymeric hydrogel giving rise to a distinct patchy architecture. By leveraging physical interactions, this material offers superlubricity with friction coefficients of 0.004-to-0.00007 achieved under moderate-to-high (102-to-103 kPa) contact pressures. Multiscale experimental measurements combined with molecular dynamics simulations reveal an intriguing synergistic mechanism behind such ultra-low friction - where the uncoated areas of the protofilaments glue to the surface by hydrophobic interactions, whilst the hydrogel offers the hydration lubrication. The current approach establishes a robust platform towards unlocking an untapped potential of using plant protein-based building blocks across diverse applications where achieving superlubricity and environmental sustainability are key performance indicators.

BCL-2 and BOK regulate apoptosis by interaction of their C-terminal transmembrane domains

The Bcl-2 family controls apoptosis by direct interactions of pro- and anti-apoptotic proteins. The principle mechanism is binding of the BH3 domain of pro-apoptotic proteins to the hydrophobic groove of anti-apoptotic siblings, which is therapeutically exploited by approved BH3-mimetic anti-cancer drugs. Evidence suggests that also the transmembrane domain (TMD) of Bcl-2 proteins can mediate Bcl-2 interactions. We developed a highly-specific split luciferase assay enabling the analysis of TMD interactions of pore-forming apoptosis effectors BAX, BAK, and BOK with anti-apoptotic Bcl-2 proteins in living cells. We confirm homotypic interaction of the BAX-TMD, but also newly identify interaction of the TMD of anti-apoptotic BCL-2 with the TMD of BOK, a peculiar pro-apoptotic Bcl-2 protein. BOK-TMD and BCL-2-TMD interact at the endoplasmic reticulum. Molecular dynamics simulations confirm dynamic BOK-TMD and BCL-2-TMD dimers and stable heterotetramers. Mutation of BCL-2-TMD at predicted key residues abolishes interaction with BOK-TMD. Also, inhibition of BOK-induced apoptosis by BCL-2 depends specifically on their TMDs. Thus, TMDs of Bcl-2 proteins are a relevant interaction interface for apoptosis regulation and provide a novel potential drug target.

Graph Theoretical Description of Phase Transitions in Complex Multiscale Phases with Supramolecular Assemblies

Phase transitions are typically quantified using order parameters, such as crystal lattice distances and radial distribution functions, which can identify subtle changes in crystalline materials or high-contrast phases with large structural differences. However, the identification of phases with high complexity, multiscale organization and of complex patterns during the structural fluctuations preceding phase transitions, which are essential for understanding the system pathways between phases, is challenging for those traditional analyses. Here, it is shown that for two model systems- thermotropic liquid crystals and a lyotropic water/surfactant mixtures-graph theoretical (GT) descriptors can successfully identify complex phases combining molecular and nanoscale levels of organization that are hard to characterize with traditional methodologies. Furthermore, the GT descriptors also reveal the pathways between the different phases. Specifically, centrality parameters and node-based fractal dimension quantify the system behavior preceding the transitions, capturing fluctuation-induced breakup of aggregates and their long-range cooperative interactions. GT parameterization can be generalized for a wide range of chemical systems and be instrumental for the growth mechanisms of complex nanostructures.

Increased burden of rare risk variants across gene expression networks predisposes to sporadic Parkinson's disease

Alpha-synuclein (αSyn) is an intrinsically disordered protein that accumulates in the brains of patients with Parkinson's disease and forms intraneuronal inclusions called Lewy Bodies. While the mechanism underlying the dysregulation of αSyn in Parkinson's disease is unclear, it is thought that prionoid cell-to-cell propagation of αSyn has an important role. Through a high throughput screen, we recently identified 38 genes whose knock down modulates αSyn propagation. Follow up experiments were undertaken for two of those genes, TAX1BP1 and ADAMTS19, to study the mechanism with which they regulate αSyn homeostasis. We used a recently developed M17D neuroblastoma cell line expressing triple mutant (E35K+E46K+E61K) "3K" αSyn under doxycycline induction. 3K αSyn spontaneously forms inclusions that show ultrastructural similarities to Lewy Bodies. Experiments using that cell line showed that TAX1BP1 and ADAMTS19 regulate how αSyn interacts with lipids and phase separates into inclusions, respectively, adding to the growing body of evidence implicating those processes in Parkinson's disease. Through RNA sequencing, we identified several genes that are differentially expressed after knock-down of TAX1BP1 or ADAMTS19. Burden analysis revealed that those differentially expressed genes (DEGs) carry an increased frequency of rare risk variants in Parkinson's disease patients versus healthy controls, an effect that was independently replicated across two separate cohorts (GP2 and AMP-PD). Weighted gene co-expression network analysis (WGCNA) showed that the DEGs cluster within modules in regions of the brain that develop high degrees of αSyn pathology (basal ganglia, cortex). We propose a novel model for the genetic architecture of sporadic Parkinson's disease: increased burden of risk variants across genetic networks dysregulates pathways underlying αSyn homeostasis, thereby leading to pathology and neurodegeneration.

MDverse, shedding light on the dark matter of molecular dynamics simulations

The rise of open science and the absence of a global dedicated data repository for molecular dynamics (MD) simulations has led to the accumulation of MD files in generalist data repositories, constituting the dark matter of MD - data that is technically accessible, but neither indexed, curated, or easily searchable. Leveraging an original search strategy, we found and indexed about 250,000 files and 2000 datasets from Zenodo, Figshare and Open Science Framework. With a focus on files produced by the Gromacs MD software, we illustrate the potential offered by the mining of publicly available MD data. We identified systems with specific molecular composition and were able to characterize essential parameters of MD simulation such as temperature and simulation length, and could identify model resolution, such as all-atom and coarse-grain. Based on this analysis, we inferred metadata to propose a search engine prototype to explore the MD data. To continue in this direction, we call on the community to pursue the effort of sharing MD data, and to report and standardize metadata to reuse this valuable matter.

Thrombin-derived C-terminal peptides bind and form aggregates with sulfated glycosaminoglycans

Glycosaminoglycans (GAGs) such as heparin and heparan sulfate (HS) play crucial roles in inflammation and wound healing, serving as regulators of growth factors and pro-inflammatory mediators. In this study, we investigated the influence of heparin/HS on thrombin proteolysis and its interaction with the generated 11 kDa thrombin-derived C-terminal peptides (TCPs). Employing various biochemical and biophysical methods, we demonstrated that 11 kDa TCPs aggregate in the presence of GAGs, including heparin, heparan sulfate, and chondroitin sulfate-B. Circular dichroism analysis demonstrated that 11 kDa TCPs, in the presence of GAGs, adopt a β-sheet structure, a finding supported by thioflavin T1 (ThT) fluorescence measurements and visualization of 11 kDa TCP-heparin complexes using transmission electron microscopy (TEM). Furthermore, our investigations revealed a stronger binding affinity between 11 kDa TCPs and GAGs with higher sulfate group contents. Congruently, in silico simulations showed that interactions between 11 kDa TCPs and heparin/HS are predominantly electrostatic in nature. Collectively, our study suggests that 11 kDa TCPs have the capacity to aggregate in the presence of GAGs, shedding light on their potential roles in inflammation and wound healing.

Coarse-Grained Simulations of Columnar Ionic Liquid Crystals: Comparison with Experiments

We simulate a homologous series of guanidinium-based columnar ionic liquid crystals (ILCs) using coarse-grained molecular dynamics (MD) simulations with the Martini force field. We systematically vary the length of alkyl side chains, ILC-n (n = 8, 12, 16), and compare our results with previous experimental findings. Experimentally, ILC-8 exhibits a narrow mesophase window and weak columnar order, while ILC-12 and ILC-16 display a broad mesophase window and high columnar order. The MD simulations show that ILC-8 forms a percolated structure, whereas the longer chain analogues self-assemble into columns, with columnar assembly becoming more prominent as the side chain length increases, in qualitative agreement with the experiments. Furthermore, the intercolumnar distance increases monotonically with increasing side chain length and decreases with increasing temperature. Finally, we find that the diffusion coefficient and ionic conductivity decrease substantially with increasing chain length, consistent with experimental observations. We attribute this decrease in mobility to the formation of hexagonally ordered columns, which restrict transport more than percolated networks.

The surface tension of Martini 3 water mixtures

The Martini model, a coarse-grained forcefield for biomolecular simulations, has experienced a vast increase in popularity in the past decade. Its building-block approach balances computational efficiency with high chemical specificity, enabling the simulation of organic and inorganic molecules. The modeling of coarse-grained beads as Lennard-Jones particles poses challenges for the accurate reproduction of liquid-vapor interfacial properties, which are crucial in various applications, especially in the case of water. The latest version of the forcefield introduces refined interaction parameters for water beads, tackling the well-known artifact of Martini water freezing at room temperature. In addition, multiple sizes of water beads are available for simulating the solvation of small cavities, including the smallest pockets of proteins. This work focuses on studying the interfacial properties of Martini water, including surface tension and surface thickness. Employing the test-area method, we systematically compute the liquid-vapor surface tension across various combinations of water bead sizes and for temperatures from 300 to 350 K. These findings are of interest to the Martini community as they allow users to account for the low interfacial tension of Martini water by properly adjusting observables computed via coarse-grained simulations to allow for accurate matching against all-atom or experimental results. Surface tension data are also interpreted in terms of local enrichment of the various mixture components at the liquid-vapor interface by means of Gibbs' adsorption formalism. Finally, the critical scaling of the Martini surface tension with temperature is reported to be consistent with the critical exponent of the 3D Ising universality class.

Endocannabinoid regulation of inward rectifier potassium (Kir) channels

The inward rectifier potassium channel Kir2.1 (KCNJ2) is an important regulator of resting membrane potential in both excitable and non-excitable cells. The functions of Kir2.1 channels are dependent on their lipid environment, including the availability of PI(4,5)P2, secondary anionic lipids, cholesterol and long-chain fatty acids acyl coenzyme A (LC-CoA). Endocannabinoids are a class of lipids that are naturally expressed in a variety of cells, including cardiac, neuronal, and immune cells. While these lipids are identified as ligands for cannabinoid receptors there is a growing body of evidence that they can directly regulate the function of numerous ion channels independently of CBRs. Here we examine the effects of a panel of endocannabinoids on Kir2.1 function and demonstrate that a subset of endocannabinoids can alter Kir2.1 conductance to varying degrees independently of CBRs. Using computational and Surface plasmon resonance analysis, endocannabinoid regulation of Kir2.1 channels appears to be the result of altered membrane properties, rather than through direct protein-lipid interactions. Furthermore, differences in endocannabinoid effects on Kir4.1 and Kir7.1 channels, indicating that endocannabinoid regulation is not conserved among Kir family members. These findings may have broader implications on the function of cardiac, neuronal and/or immune cells.

Methods for Classical-Mechanical Molecular Simulation in Chemistry: Achievements, Limitations, Perspectives

More than a half century ago it became feasible to simulate, using classical-mechanical equations of motion, the dynamics of molecular systems on a computer. Since then classical-physical molecular simulation has become an integral part of chemical research. It is widely applied in a variety of branches of chemistry and has significantly contributed to the development of chemical knowledge. It offers understanding and interpretation of experimental results, semiquantitative predictions for measurable and nonmeasurable properties of substances, and allows the calculation of properties of molecular systems under conditions that are experimentally inaccessible. Yet, molecular simulation is built on a number of assumptions, approximations, and simplifications which limit its range of applicability and its accuracy. These concern the potential-energy function used, adequate sampling of the vast statistical-mechanical configurational space of a molecular system and the methods used to compute particular properties of chemical systems from statistical-mechanical ensembles. During the past half century various methodological ideas to improve the efficiency and accuracy of classical-physical molecular simulation have been proposed, investigated, evaluated, implemented in general simulation software or were abandoned. The latter because of fundamental flaws or, while being physically sound, computational inefficiency. Some of these methodological ideas are briefly reviewed and the most effective methods are highlighted. Limitations of classical-physical simulation are discussed and perspectives are sketched.

Unraveling mechanisms of protein encapsulation and release in coacervates via molecular dynamics and machine learning

Coacervates play a pivotal role in protein-based drug delivery research, yet their drug encapsulation and release mechanisms remain poorly understood. Here, we utilized the Martini model to investigate bovine serum albumin (BSA) protein encapsulation and release within polylysine/polyglutamate (PLys/PGlu) coacervates. Our findings emphasize the importance of ingredient addition sequence in coacervate formation and encapsulation rates, attributed to preference contact between oppositely charged proteins and poly(amino acid)s. Notably, coacervates composed of β-sheet poly(amino acid)s demonstrate greater BSA encapsulation efficiency due to their reduced entropy and flexibility. Furthermore, we examined the pH responsiveness of coacervates, shedding light on the dissolution process driven by Coulomb forces. By leveraging machine learning algorithms to analyze simulation results, our research advances the understanding of coacervate-based drug delivery systems, with the ultimate goal of optimizing therapeutic outcomes.

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.

Multiscale simulations reveal the driving forces of p53C phase separation accelerated by oncogenic mutations

Liquid-Liquid phase separation (LLPS) of p53 to form liquid condensates has been implicated in cellular functions and dysfunctions. The p53 condensates may serve as amyloid fibril precursors to initiate p53 aggregation, which is associated with oncogenic gain-of-function and various human cancers. M237I and R249S mutations located in p53 core domain (p53C) have been detected respectively in glioblastomas and hepatocellular carcinoma. Interestingly, these p53C mutants can also undergo LLPS and liquid-to-solid phase transition, which are faster than wild type p53C. However, the underlying molecular basis governing the accelerated LLPS and liquid-to-solid transition of p53C remain poorly understood. Herein, we explore the M237I/R249S mutation-induced structural alterations and phase separation behavior of p53C by employing multiscale molecular dynamics simulations. All-atom simulations revealed conformational disruptions in the zinc-binding domain of the M237I mutant and in both loop3 and zinc-binding domain of the R249S mutant. The two mutations enhance hydrophobic exposure of those regions and attenuate intramolecular interactions, which may hasten the LLPS and aggregation of p53C. Martini 3 coarse-grained simulations demonstrated spontaneous phase separation of p53C and accelerated effects of M237I/R249S mutations on the phase separation of p53C. Importantly, we find that the regions with enhanced intermolecular interactions observed in coarse-grained simulations coincide with the disrupted regions with weakened intramolecular interactions observed in all-atom simulations, indicating that M237I/R249S mutation-induced local structural disruptions expedite the LLPS of p53C. This study unveils the molecular mechanisms underlying the two cancer-associated mutation-accelerated LLPS and aggregation of p53C, providing avenues for anticancer therapy by targeting the phase separation process.

GCMe: Efficient Implementation of the Gaussian Core Model with Smeared Electrostatic Interactions for Molecular Dynamics Simulations of Soft Matter Systems

In recent years, molecular dynamics (MD) simulations have emerged as an essential tool for understanding the structure, dynamics, and phase behavior of charged soft matter systems. To explore phenomena across greater length and time scales in MD simulations, molecules are often coarse-grained for better computational performance. However, commonly used force fields represent particles as hard-core interaction centers with point charges, which often overemphasizes the packing effect and short-range electrostatics, especially in systems with bulky deformable organic molecules and systems with strong coarse-graining. This underscores the need for an efficient soft-core model to physically capture the effective interactions between coarse-grained particles. To this end, we implement a soft-core model uniting the Gaussian core model with smeared electrostatic interactions that is phenomenologically equivalent to recent theoretical models. We first parametrize it generically using water as the model solvent. Then, we benchmark its performance in the OpenMM toolkit for different boundary conditions to highlight a computational speedup of up to 34 × compared to commonly used force fields and existing implementations. Finally, we demonstrate its utility by investigating how boundary polarizability affects the adsorption behavior of a polyelectrolyte solution on perfectly conducting and nonmetal boundaries.

Faster but Not Sweeter: A Model of Escherichia coli Re-level Lipopolysaccharide for Martini 3 and a Martini 2 Version with Accelerated Kinetics

Lipopolysaccharide (LPS) is a complex glycolipid molecule that is the main lipidic component of the outer leaflet of the outer membrane of Gram-negative bacteria. It has very limited lateral motion compared to phospholipids, which are more ubiquitous in biological membranes, including in the inner leaflet of the outer membrane of Gram-negative bacteria. The slow-moving nature of LPS can present a hurdle for molecular dynamics simulations, given that the (pragmatically) accessible timescales to simulations are currently limited to microseconds, during which LPS displays some conformational dynamics but hardly any lateral diffusion. Thus, it is not feasible to observe phenomena such as insertion of molecules, including antibiotics/antimicrobials, directly into the outer membrane from the extracellular side nor to observe LPS dissociating from proteins via molecular dynamics using currently available models at the atomistic and more coarse-grained levels of granularity. Here, we present a model of deep rough LPS compatible with the Martini 2 coarse-grained force field with scaled down nonbonded interactions to enable faster diffusion. We show that the faster-diffusing LPS model is able to reproduce the salient biophysical properties of the standard models, but due to its faster lateral motion, molecules are able to penetrate deeper into membranes containing the faster model. We show that the fast ReLPS model is able to reproduce experimentally determined patterns of interaction with outer membrane proteins while also allowing for LPS to associate and dissociate with proteins within microsecond timescales. We also complete the Martini 3 LPS toolkit for Escherichia coli by presenting a (standard) model of deep rough LPS for this force field.

Wild-Type α-Synuclein Structure and Aggregation: A Comprehensive Coarse-Grained and All-Atom Molecular Dynamics Study

α-Synuclein (α-syn) is a 140 amino acid intrinsically disordered protein (IDP) and the primary component of cytotoxic oligomers implicated in the etiology of Parkinson's disease (PD). While IDPs lack a stable three-dimensional structure, they sample a heterogeneous ensemble of conformations that can, in principle, be assessed through molecular dynamics simulations. However, describing the structure and aggregation of large IDPs is challenging due to force field (FF) accuracy and sampling limitations. To cope with the latter, coarse-grained (CG) FFs emerge as a potential alternative at the expense of atomic detail loss. Whereas CG models can accurately describe the structure of the monomer, less is known about aggregation. The latter is key for assessing aggregation pathways and designing aggregation inhibitor drugs. Herein, we investigate the structure and dynamics of α-syn using different resolution CG (Martini3 and Sirah2) and all-atom (Amber99sb and Charmm36m) FFs to gain insight into the differences and resemblances between these models. The dependence of the magnitude of protein-water interactions and the putative need for enhanced sampling (replica exchange) methods in CG simulations are analyzed to distinguish between force field accuracy and sampling limitations. The stability of the CG models of an α-syn fibril was also investigated. Additionally, α-syn aggregation was studied through umbrella sampling for the CG models and CG/all-atom models for an 11-mer peptide (NACore) from an amyloidogenic domain of α-syn. Our results show that despite the α-syn structures of Martini3 and Sirah2 with enhanced protein-water interactions being similar, major differences exist concerning aggregation. The Martini3 fibril is not stable, and the binding free energy of α-syn and NACore is positive, opposite to Sirah2. Sirah2 peptides in a zwitterionic form, in turn, display termini interactions that are too strong, resulting in end-to-end orientation. Sirah2, with enhanced protein-water interactions and neutral termini, provides, however, a peptide aggregation free energy profile similar to that found with all-atom models. Overall, we find that Sirah2 with enhanced protein-water interactions is suitable for studying protein-protein and protein-drug aggregation.

Rescaling protein-protein interactions improves Martini 3 for flexible proteins in solution

Multidomain proteins with flexible linkers and disordered regions play important roles in many cellular processes, but characterizing their conformational ensembles is difficult. We have previously shown that the coarse-grained model, Martini 3, produces too compact ensembles in solution, that may in part be remedied by strengthening protein-water interactions. Here, we show that decreasing the strength of protein-protein interactions leads to improved agreement with experimental data on a wide set of systems. We show that the 'symmetry' between rescaling protein-water and protein-protein interactions breaks down when studying interactions with or within membranes; rescaling protein-protein interactions better preserves the binding specificity of proteins with lipid membranes, whereas rescaling protein-water interactions preserves oligomerization of transmembrane helices. We conclude that decreasing the strength of protein-protein interactions improves the accuracy of Martini 3 for IDPs and multidomain proteins, both in solution and in the presence of a lipid membrane.