Capturing Choline-Aromatics Cation-π Interactions in the MARTINI Force Field

Influence of branched ligand architectures on nanoparticle interactions with lipid bilayers

Gold nanoparticles functionalized with organic cationic ligands have shown promise as biomedical agents, but their interactions with cellular membranes are not yet well-understood and design rules for ligands that promote desired cellular interactions are lacking. Past experimental studies have demonstrated that ligand lipophilicity, quantified by the ligand end group partition coefficient, can be used as a descriptor for predicting nano-bio interactions, but such a descriptor is incapable accounting for ligand architecture, such as chain branching. To probe the effects of ligand end group architecture on ligand-lipid interactions, we perform molecular dynamics simulations to investigate how ligand alkyl chain branching modulates the thermodynamics and mechanisms of nanoparticle adsorption to lipid membranes. We designed four pairs of 2 nm diameter gold nanoparticles where each pair had ligand end groups with similar lipophilicity but varying alkyl chain architecture (e.g., one long alkyl chain vs. two short chains) to isolate branching effects from lipophilicity. Free energy calculations and mechanistic insight revealed that alkyl end group branching can decrease free energy barriers for adsorption by disrupting ligand monolayer packing, increasing end group protrusions that lead to favorable ligand intercalation with minimal membrane disruption. Furthermore, increased end group branching promotes adsorption by increasing the exposure of nonpolar surface area to water, which results in a greater reduction of free energy upon exposure to the nonpolar core of the lipid bilayer. These results show that ligand chain architecture can modulate nano-bio interactions, limiting the exclusive use of lipophilicity as a descriptor to predict cellular uptake of surface-functionalized nanoparticles.

Recalibration of MARTINI-3 Parameters for Improved Interactions between Peripheral Proteins and Lipid Bilayers

The MARTINI force field is one of the most used coarse-grained models for biomolecular simulations. Many limitations of the model including the protein-protein overaggregation have been improved in its latest version, MARTINI-3. In this study, we investigate the efficacy of the MARTINI-3 parameters for capturing the interactions of peripheral proteins with model plasma membranes. Particularly, we consider two classes of proteins, namely, annexin and epsin, which are known to generate negative and positive membrane curvatures, respectively. We find that current MARTINI-3 parameters are not able to correctly describe the protein-membrane interface and the protein-induced membrane curvatures for any of these proteins. The problem arises due to the lack of proper hydrophobic interactions between the protein residues and lipid tails. Making systematic adjustments, we show that a combination of reduction in the protein-water interactions and enhancement of protein-lipid hydrophobic interactions is essential for accurate prediction of the interfacial structure including the protein-induced membrane curvature. Next, we apply our model to a couple of other peripheral proteins, namely, Snf7, a core component of the ESCRT-III complex, and the PH domain of evectin-2. We find that our model captures the protein-membrane interfacial structure much more accurately than the MARTINI-3 model for all of the peripheral proteins considered in this study. However, the strategy described in this study may not be suitable for oligomeric transmembrane proteins where protein-protein hydrophobic interactions should be increased instead of protein-lipid hydrophobic interactions.

Mechanically Adaptive Metal-Coordinated Electrogel Membranes

Achieving specific mechanical properties of hydrogels, especially when used as thin films, can be crucial in diverse applications, including tissue engineering and bioelectronics. Here, a novel electrochemical approach for fabricating uniform and robust hydrogel films based on carboxymethyl cellulose cross-linked by Fe3+ ions (Fe-CMC), exhibiting tunable, dynamic properties is introduced. High modulation of the mechanical properties of the film is achieved by applying multiple electrochemical pulses of oxidative voltage during hydrogel deposition. Our study shows also a remarkable effect of the ionic strength on the properties of the electrodeposited hydrogel films. We found that switching from a salt solution to water enhanced the stiffness of the hydrogels, thereby regulating the permeability of the films. These results are supported by molecular dynamics (MD) simulations, showing that an increase in the ionic strength induces a weakening of the Fe-CMC interactions, ultimately affecting the network strength. Finally, the robustness of these electrodeposited hydrogel films enables their delamination from the electrode without any damage, thereby expanding their potential applications as freestanding smart membranes. By providing fundamental insights into the dynamics of metal-coordinated bonds and their response at the macroscopic scale, we have demonstrated the versatility of electrochemical gelation for the fabrication of robust hydrogel films with tunable mechanical properties, which could serve as smart platforms for a variety of biomedical applications.

Chain-Length Dependence of Peptide-Lipid Bilayer Interaction Strength and Binding Kinetics: A Combined Theoretical and Experimental Approach

Physical interactions between polypeptide chains and lipid membranes underlie critical cellular processes. Yet, despite fundamental importance, key mechanistic aspects of these interactions remain elusive. Bulk experiments have revealed a linear relationship between free energy and peptide chain length in a model system, but does this linearity extend to the interaction strength and to the kinetics of lipid binding? To address these questions, we utilized a combination of coarse-grained molecular dynamics (CG MD) simulations, analytical modeling, and atomic force microscopy (AFM)-based single molecule force spectroscopy. Following previous bulk experiments, we focused on interactions between short hydrophobic peptides (WLn, n = 1, ..., 5) with 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC) bilayers, a simple system that probes peptide primary structure effects. Potentials of mean force extracted from CG MD recapitulated the linearity of free energy with the chain length. Simulation results were quantitatively connected to bulk biochemical experiments via a single scaling factor of order unity, corroborating the methodology. Additionally, CG MD revealed an increase in the distance to the transition state, a result that weakens the dependence of the dissociation force on the peptide chain length. AFM experiments elucidated rupture force distributions and, through modeling, intrinsic dissociation rates. Taken together, the analysis indicates a rupture force plateau in the WLn-POPC system, suggesting that the final rupture event involves the last 2 or 3 residues. In contrast, the linear dependence on chain length was preserved in the intrinsic dissociation rate. This study advances the understanding of peptide-lipid interactions and provides potentially useful insights for the design of peptides with tailored membrane-interacting properties.

Long-Chain Lipids Facilitate Insertion of Large Nanoparticles into Membranes of Small Unilamellar Vesicles

Insertion of hydrophobic nanoparticles into phospholipid bilayers is limited to small particles that can incorporate into a hydrophobic membrane core between two lipid leaflets. Incorporation of nanoparticles above this size limit requires the development of challenging surface engineering methodologies. In principle, increasing the long-chain lipid component in the lipid mixture should facilitate incorporation of larger nanoparticles. Here, we explore the effect of incorporating very long phospholipids (C24:1) into small unilamellar vesicles on the membrane insertion efficiency of hydrophobic nanoparticles that are 5-11 nm in diameter. To this end, we improve an existing vesicle preparation protocol and utilized cryogenic electron microscopy imaging to examine the mode of interaction and evaluate the insertion efficiency of membrane-inserted nanoparticles. We also perform classical coarse-grained molecular dynamics simulations to identify changes in lipid membrane structural properties that may increase insertion efficiency. Our results indicate that long-chain lipids increase the insertion efficiency by preferentially accumulating near membrane-inserted nanoparticles to reduce the thermodynamically unfavorable disruption of the membrane.

Effect of GM1 concentration change on plasma membrane: molecular dynamics simulation and analysis

Ganglioside GM1 is a class of glycolipids predominantly located in the nervous system. Comprising a ceramide anchor and an oligosaccharide chain containing sialic acid, GM1 plays a pivotal role in various cellular processes, including signal transduction, cell adhesion, and membrane organization. Moreover, GM1 has been implicated in the pathogenesis of several neurological disorders, such as Parkinson's disease, Alzheimer's disease, and stroke. In this study, by creating a neural cell model membrane simulation system and employing rigorous molecular models, we utilize a coarse-grained molecular dynamics approach to explore the structural and dynamic characteristics of multi-component neuronal plasma membranes at varying GM1 ganglioside concentrations. The simulation results reveal that as GM1 concentration increases, a greater number of hydrogen bonds form between GM1 molecules, resulting in the formation of larger clusters, which leads to reduced membrane fluidity, increased lipid ordering, decreased membrane thickness and surface area and higher levels of GM1 dissociation. Through a meticulous analysis, while considering GM1's structural attributes, we offer valuable insights into the structural and dynamic traits of the cell membrane. This study provides a robust methodology for exploring membrane characteristics and enhances our comprehension of GM1 molecules, serving as a resource for both experimental and computational researchers in this field.

Ligand Lipophilicity Determines Molecular Mechanisms of Nanoparticle Adsorption to Lipid Bilayers

The interactions of ligand-functionalized nanoparticles with the cell membrane affect cellular uptake, cytotoxicity, and related behaviors, but relating these interactions to ligand properties remains challenging. In this work, we perform coarse-grained molecular dynamics simulations to study how the adsorption of ligand-functionalized cationic gold nanoparticles (NPs) to a single-component lipid bilayer (as a model cell membrane) is influenced by ligand end group lipophilicity. A set of 2 nm diameter NPs, each coated with a monolayer of organic ligands that differ only in their end groups, was simulated to mimic NPs recently studied experimentally. Metadynamics calculations were performed to determine key features of the free energy landscape for adsorption as a function of the distance of the NP from the bilayer and the number of NP-lipid contacts. These simulations revealed that NP adsorption is thermodynamically favorable for all NPs due to the extraction of lipids from the bilayer and into the NP monolayer. To resolve ligand-dependent differences in adsorption behavior, string method calculations were performed to compute minimum free energy pathways for adsorption. These calculations revealed a surprising nonmonotonic dependence of the free energy barrier for adsorption on ligand end group lipophilicity. Large free energy barriers are predicted for the least lipophilic end groups because favorable NP-lipid contacts are initiated only through the unfavorable protrusion of lipid tail groups out of the bilayer. The smallest free energy barriers are predicted for end groups of intermediate lipophilicity which promote NP-lipid contacts by intercalating within the bilayer. Unexpectedly, large free energy barriers are also predicted for the most lipophilic end groups which remain sequestered within the ligand monolayer rather than intercalating within the bilayer. These trends are broadly in agreement with past experimental measurements and reveal how subtle variations in ligand lipophilicity dictate adsorption mechanisms and associated kinetics by influencing the interplay of lipid-ligand interactions.

Molecular Dynamics Simulations in Protein-Protein Docking

Concerted interactions between all the cell components form the basis of biological processes. Protein-protein interactions (PPIs) constitute a tremendous part of this interaction network. Deeper insight into PPIs can help us better understand numerous diseases and lead to the development of new diagnostic and therapeutic strategies. PPI interfaces, until recently, were considered undruggable. However, it is now believed that the interfaces contain "hot spots," which could be targeted by small molecules. Such a strategy would require high-quality structural data of PPIs, which are difficult to obtain experimentally. Therefore, in silico modeling can complement or be an alternative to in vitro approaches. There are several computational methods for analyzing the structural data of the binding partners and modeling of the protein-protein dimer/oligomer structure. The major problem with in silico structure prediction of protein assemblies is obtaining sufficient sampling of protein dynamics. One of the methods that can take protein flexibility and the effects of the environment into account is Molecular Dynamics (MD). While sampling of the whole protein-protein association process with plain MD would be computationally expensive, there are several strategies to harness the method to PPI studies while maintaining reasonable use of resources. This chapter reviews known applications of MD in the PPI investigation workflows.

Pragmatic Coarse-Graining of Proteins: Models and Applications

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

An implementation of the Martini coarse-grained force field in OpenMM

We describe a complete implementation of Martini 2 and Martini 3 in the OpenMM molecular dynamics software package. Martini is a widely used coarse-grained force field with applications in biomolecular simulation, materials, and broader areas of chemistry. It is implemented as a force field but makes extensive use of facilities unique to the GROMACS software, including virtual sites and bonded terms that are not commonly used in standard atomistic force fields. OpenMM is a flexible molecular dynamics package widely used for methods development and is competitive in speed on GPUs with other commonly used packages. OpenMM has facilities to easily implement new force field terms, external forces and fields, and other nonstandard features, which we use to implement all force field terms used in Martini 2 and Martini 3. This allows Martini simulations, starting with GROMACS topology files that are processed by custom scripts, with all the added flexibility of OpenMM. We provide a GitHub repository with test cases, compare accuracy and performance between GROMACS and OpenMM, and discuss the limitations of our implementation in terms of direct comparison with GROMACS. We describe a use case that implements the Modeling Employing Limited Data method to apply experimental constraints in a Martini simulation to efficiently determine the structure of a protein complex. We also discuss issues and a potential solution with the Martini 2 topology for cholesterol.

The prolactin receptor scaffolds Janus kinase 2 via co-structure formation with phosphoinositide-4,5-bisphosphate

Class 1 cytokine receptors transmit signals through the membrane by a single transmembrane helix to an intrinsically disordered cytoplasmic domain that lacks kinase activity. While specific binding to phosphoinositides has been reported for the prolactin receptor (PRLR), the role of lipids in PRLR signaling is unclear. Using an integrative approach combining nuclear magnetic resonance spectroscopy, cellular signaling experiments, computational modeling, and simulation, we demonstrate co-structure formation of the disordered intracellular domain of the human PRLR, the membrane constituent phosphoinositide-4,5-bisphosphate (PI(4,5)P2) and the FERM-SH2 domain of the Janus kinase 2 (JAK2). We find that the complex leads to accumulation of PI(4,5)P2 at the transmembrane helix interface and that the mutation of residues identified to interact specifically with PI(4,5)P2 negatively affects PRLR-mediated activation of signal transducer and activator of transcription 5 (STAT5). Facilitated by co-structure formation, the membrane-proximal disordered region arranges into an extended structure. We suggest that the co-structure formed between PRLR, JAK2, and PI(4,5)P2 locks the juxtamembrane disordered domain of the PRLR in an extended structure, enabling signal relay from the extracellular to the intracellular domain upon ligand binding. We find that the co-structure exists in different states which we speculate could be relevant for turning signaling on and off. Similar co-structures may be relevant for other non-receptor tyrosine kinases and their receptors.

Ceramide-1-phosphate transfer protein enhances lipid transport by disrupting hydrophobic lipid-membrane contacts

Cellular distributions of the sphingolipid ceramide-1-phosphate (C1P) impact essential biological processes. C1P levels are spatiotemporally regulated by ceramide-1-phosphate transfer protein (CPTP), which efficiently shuttles C1P between organelle membranes. Yet, how CPTP rapidly extracts and inserts C1P into a membrane remains unknown. Here, we devise a multiscale simulation approach to elucidate biophysical details of CPTP-mediated C1P transport. We find that CPTP binds a membrane poised to extract and insert C1P and that membrane binding promotes conformational changes in CPTP that facilitate C1P uptake and release. By significantly disrupting a lipid's local hydrophobic environment in the membrane, CPTP lowers the activation free energy barrier for passive C1P desorption and enhances C1P extraction from the membrane. Upon uptake of C1P, further conformational changes may aid membrane unbinding in a manner reminiscent of the electrostatic switching mechanism used by other lipid transfer proteins. Insertion of C1P into an acceptor membrane, eased by a decrease in membrane order by CPTP, restarts the transfer cycle. Most notably, we provide molecular evidence for CPTP's ability to catalyze C1P extraction by breaking hydrophobic C1P-membrane contacts with compensatory hydrophobic lipid-protein contacts. Our work, thus, provides biophysical insights into how CPTP efficiently traffics C1P between membranes to maintain sphingolipid homeostasis and, additionally, presents a simulation method aptly suited for uncovering the catalytic mechanisms of other lipid transfer proteins.

Martini 3 Coarse-Grained Force Field for Carbohydrates

The Martini 3 force field is a full reparametrization of the Martini coarse-grained model for biomolecular simulations. Due to the improved interaction balance, it allows for a more accurate description of condensed phase systems. In the present work, we develop a consistent strategy to parametrize carbohydrate molecules accurately within the framework of Martini 3. In particular, we develop a canonical mapping scheme which decomposes arbitrarily large carbohydrates into a limited number of fragments. Bead types for these fragments have been assigned by matching physicochemical properties of mono- and disaccharides. In addition, guidelines for assigning bonds, angles, and dihedrals were developed. These guidelines enable a more accurate description of carbohydrate conformations than in the Martini 2 force field. We show that models obtained with this approach are able to accurately reproduce osmotic pressures of carbohydrate water solutions. Furthermore, we provide evidence that the model differentiates correctly the solubility of the polyglucoses dextran (water-soluble) and cellulose (water insoluble but soluble in ionic liquids). Finally, we demonstrate that the new building blocks can be applied to glycolipids. We show they are able to reproduce membrane properties and induce binding of peripheral membrane proteins. These test cases demonstrate the validity and transferability of our approach.

Membrane binding of pore-forming γ-hemolysin components studied at different lipid compositions

Methicillin-resistant Staphylococcus aureus is among those pathogens currently posing the highest threat to public health. Its host immune evasion strategy is mediated by pore-forming toxins (PFTs), among which the bi-component γ-hemolysin is one of the most common. The complexity of the porogenesis mechanism by γ-hemolysin poses difficulties in the development of antivirulence therapies targeting PFTs from S. aureus, and sparse and apparently contrasting experimental data have been produced. Here, through a large set of molecular dynamics simulations at different levels of resolution, we investigate the first step of pore formation, and in particular the effect of membrane composition on the ability of γ-hemolysin components, LukF and Hlg2, to steadily adhere to the lipid bilayer in the absence of proteinaceous receptors. Our simulations are in agreement with experimental data of γ-hemolysin pore formation on model membranes, which are here explained on the basis of the bilayer properties. Our computational investigation suggests a possible rationale to explain experimental data on phospholipid binding to the LukF component, and to hypothesise a mechanism by which, on purely lipidic bilayers, the stable anchoring of LukF to the cell surface facilitates Hlg2 binding, through the exposure of its N-terminal region. We expect that further insights on the mechanism of transition between soluble and membrane bound-forms and on the role played by the lipid molecules will contribute to the design of antivirulence agents with enhanced efficacy against methicillin-resistant S. aureus infections.

Phospholipid Monolayer/Graphene Interfaces: Curvature Effect on Lipid Morphology and Dynamics

Phospholipids are an important class of lipids that are widely used as model platforms for the study of biological processes and interactions. These lipids can form stable interfaces with solid substrates, such as graphene, and these interfaces have potential applications in biosensing and targeted drug delivery. In this paper, we perform molecular dynamics simulations of graphene-supported lipid monolayers to characterize the lipid properties of such interfaces. We observed substantial differences between the supported monolayer and free-standing bilayer in terms of the lipid properties, such as the tail order parameters, density profiles, diffusion rates, and so on. Furthermore, we studied these interfaces on sinusoidally deformed graphene substrates to understand the effect of curvature on the supported lipids. Here, we observed that the nature of the substrate curvature, that is, concave or convex, can locally affect the lipid/substrate adhesion strength and induce structural and dynamic changes in the adsorbed lipid monolayer. Together, these results help characterize the properties of lipid/graphene interfaces and provide insights into the substrate curvature effect on these interfaces, which can enable the tuning of lipid properties for various sensor devices and drug delivery applications.

Key aspects of the past 30 years of protein design

Proteins are the workhorse of life. They are the building infrastructure of living systems; they are the most efficient molecular machines known, and their enzymatic activity is still unmatched in versatility by any artificial system. Perhaps proteins' most remarkable feature is their modularity. The large amount of information required to specify each protein's function is analogically encoded with an alphabet of just ∼20 letters. The protein folding problem is how to encode all such information in a sequence of 20 letters. In this review, we go through the last 30 years of research to summarize the state of the art and highlight some applications related to fundamental problems of protein evolution.

Small ionic radii limit time step in Martini 3 molecular dynamics simulations

Among other improvements, the Martini~3 coarse-grained force field provides a more accurate description of the solvation of protein pockets and channels through the consistent use of various bead types and sizes. Here, we show that the representation of Na+ and Cl- ions as ``tiny' (TQ5) beads limits the accessible time step to 25~fs. By contrast, with Martini~2, time steps of 30-40~fs were possible for lipid bilayer systems without proteins. This limitation is relevant for systems that require long equilibration times. We derive a quantitative kinetic model of time-integration instabilities in molecular dynamics as a function of time step, ion concentration and mass, system size, and simulation time. We demonstrate that ion-water interactions are the main source of instability at physiological conditions, followed closely by ion-ion interactions. We show that increasing the ionic masses makes it possible to use time steps up to 40~fs with minimal impact on static equilibrium properties and on dynamical quantities such as lipid and ion diffusion coefficients. Increasing the size of the bead representing the ions (and thus changing their hydration) also permits longer time steps. For a soluble protein, we find that increasing the mass of tiny beads also on the protein permits simulations with 30-fs time step. The use of larger time steps in Martini~3 results in a more efficient exploration of configuration space. The kinetic model of MD simulation crashes can be used to determine the maximum allowed time step upfront for an efficient use of resources and whenever sampling efficiency is critical.

Molecular Mechanism of CD44 Homodimerization Modulated by Palmitoylation and Membrane Environments

The homodimerization of CD44 plays a key role in an intercellular-to-extracellular signal transduction and tumor progression. Acylated modification and specific membrane environments have been reported to mediate translocation and oligomerization of CD44, however, the underlying molecular mechanism remains elusive. In this study, extensive molecular dynamics simulations are performed to characterize the dimerization of palmitoylated CD44 variants in different bilayer environments. CD44 forms homodimer depending on the cysteines on the juxta-membrane domains, and the dimerization efficiency and packing configurations are defected by their palmitoylated modifications. In the phase-segregated (raft included) membrane, homodimerization of the palmitoylated CD44 is hardly observed, whereas PIP2 addition compensates to realize dimerization. However, the structure of CD44 homodimer formed in the phase-segregated bilayer turns susceptive and PIP2 addition allows for an extensive conformation of the cytoplasmic domain, a proposal prerequisite to access the cytoskeleton linker proteins. The results unravel a delicate competitive relationship between PIP2, lipid raft and palmitoylation in mediating protein homodimerization, which helps to clarify the dynamic dimer conformations and involved cellular signaling of the CD44 likewise proteins.

Specific interactions of peripheral membrane proteins with lipids: what can molecular simulations show us?

Peripheral membrane proteins (PMPs) can reversibly and specifically bind to biological membranes to carry out functions such as cell signalling, enzymatic activity, or membrane remodelling. Structures of these proteins and of their lipid-binding domains are typically solved in a soluble form, sometimes with a lipid or lipid headgroup at the binding site. To provide a detailed molecular view of PMP interactions with the membrane, computational methods such as molecular dynamics (MD) simulations can be applied. Here, we outline recent attempts to characterise these binding interactions, focusing on both intracellular proteins, such as phosphatidylinositol phosphate (PIP)-binding domains, and extracellular proteins such as glycolipid-binding bacterial exotoxins. We compare methods used to identify and analyse lipid-binding sites from simulation data and highlight recent work characterising the energetics of these interactions using free energy calculations. We describe how improvements in methodologies and computing power will help MD simulations to continue to contribute to this field in the future.

The Bak core dimer focuses triacylglycerides in the membrane

Apoptosis, the intrinsic programmed cell death process, is mediated by the Bcl-2 family members Bak and Bax. Activation via formation of symmetric core dimers and oligomerization on the mitochondrial outer membrane (MOM) leads to permeabilization and cell death. Although this process is linked to the MOM, the role of the membrane in facilitating such pores is poorly understood. We recently described Bak core domain dimers, revealing lipid binding sites and an initial role of lipids in oligomerization. Here we describe simulations that identified localized clustering and interaction of triacylglycerides (TAGs) with a minimized Bak dimer construct. Coalescence of TAGs occurred beneath this Bak dimer, mitigating dimer-induced local membrane thinning and curvature in representative coarse-grain MOM and model membrane systems. Furthermore, the effects observed as a result of coarse-grain TAG cluster formation was concentration dependent, scaling from low physiological MOM concentrations to those found in other organelles. We find that increasing the TAG concentration in liposomes mimicking the MOM decreased the ability of activated Bak to permeabilize these liposomes. These results suggest that the presence of TAGs within a Bak-lipid membrane preserves membrane integrity and is associated with reduced membrane stress, suggesting a possible role of TAGs in Bak-mediated apoptosis.

Improved Parameterization of Phosphatidylinositide Lipid Headgroups for the Martini 3 Coarse-Grain Force Field

Phosphoinositides are a family of membrane phospholipids that play crucial roles in membrane regulatory events. As such, these lipids are often a key part of molecular dynamics simulation studies of biological membranes, in particular of those employing coarse-grain models because of the potential long times and sizes of the involved membrane processes. Version 3 of the widely used Martini coarse-grain force field has been recently published, greatly refining many aspects of biomolecular interactions. In order to properly use it for lipid membrane simulations with phosphoinositides, we put forth the Martini 3-specific parameterization of inositol, phosphatidylinositol, and seven physiologically relevant phosphorylated derivatives of phosphatidylinositol. Compared to parameterizations for earlier Martini versions, focus was put on a more accurate reproduction of the behavior seen in both atomistic simulations and experimental studies, including the signaling-relevant phosphoinositide interaction with divalent cations. The models that we develop improve upon the conformational dynamics of phosphoinositides in the Martini force field and provide stable topologies at typical Martini time steps. They are able to reproduce experimentally known protein-binding poses as well as phosphoinositide aggregation tendencies. The latter was tested both in the presence and absence of calcium and included correct behavior of PI(4,5)P₂ calcium-induced clusters, which can be of relevance for regulation.

Computational Approaches to Investigate and Design Lipid-binding Domains for Membrane Biosensing

Association of proteins with cellular membranes is critical for signaling and membrane trafficking processes. Many peripheral lipid-binding domains have been identified in the last few decades and have been investigated for their specific lipid-sensing properties using traditional in vivo and in vitro studies. However, several knowledge gaps remain owing to intrinsic limitations of these methodologies. Thus, novel approaches are necessary to further our understanding in lipid-protein biology. This review briefly discusses lipid-binding domains that act as specific lipid biosensors and provides a broad perspective on the computational approaches such as molecular dynamics (MD) simulations and machine learning (ML)-based techniques that can be used to study protein-membrane interactions. We also highlight the need for de novo design of proteins that elicit specific lipid-binding properties.

Regulation of a pentameric ligand-gated ion channel by a semiconserved cationic lipid-binding site

Pentameric ligand-gated ion channels (pLGICs) are crucial mediators of electrochemical signal transduction in various organisms from bacteria to humans. Lipids play an important role in regulating pLGIC function, yet the structural bases for specific pLGIC-lipid interactions remain poorly understood. The bacterial channel ELIC recapitulates several properties of eukaryotic pLGICs, including activation by the neurotransmitter GABA and binding and modulation by lipids, offering a simplified model system for structure-function relationship studies. In this study, functional effects of noncanonical amino acid substitution of a potential lipid-interacting residue (W206) at the top of the M1-helix, combined with detergent interactions observed in recent X-ray structures, are consistent with this region being the location of a lipid-binding site on the outward face of the ELIC transmembrane domain. Coarse-grained and atomistic molecular dynamics simulations revealed preferential binding of lipids containing a positive charge, particularly involving interactions with residue W206, consistent with cation-π binding. Polar contacts from other regions of the protein, particularly M3 residue Q264, further support lipid binding via headgroup ester linkages. Aromatic residues were identified at analogous sites in a handful of eukaryotic family members, including the human GABAA receptor ε subunit, suggesting conservation of relevant interactions in other evolutionary branches. Further mutagenesis experiments indicated that mutations at this site in ε-containing GABAA receptors can change the apparent affinity of the agonist response to GABA, suggesting a potential role of this site in channel gating. In conclusion, this work details type-specific lipid interactions, which adds to our growing understanding of how lipids modulate pLGICs.

A Data-Driven Dimensionality Reduction Approach to Compare and Classify Lipid Force Fields

Molecular dynamics simulations of all-atom and coarse-grained lipid bilayer models are increasingly used to obtain useful insights for understanding the structural dynamics of these assemblies. In this context, one crucial point concerns the comparison of the performance and accuracy of classical force fields (FFs), which sometimes remains elusive. To date, the assessments performed on different classical potentials are mostly based on the comparison with experimental observables, which typically regard average properties. However, local differences of the structure and dynamics, which are poorly captured by average measurements, can make a difference, but these are nontrivial to catch. Here, we propose an agnostic way to compare different FFs at different resolutions (atomistic, united-atom, and coarse-grained), by means of a high-dimensional similarity metrics built on the framework of Smooth Overlap of Atomic Position (SOAP). We compare and classify a set of 13 FFs, modeling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayers. Our SOAP kernel-based metrics allows us to compare, discriminate, and correlate different FFs at different model resolutions in an unbiased, high-dimensional way. This also captures differences between FFs in modeling nonaverage events (originating from local transitions), for example, the liquid-to-gel phase transition in dipalmitoylphosphatidylcholine (DPPC) bilayers, for which our metrics allows us to identify nucleation centers for the phase transition, highlighting some intrinsic resolution limitations in implicit versus explicit solvent FFs.

Controlling Peptide Function by Directed Assembly Formation: Mechanistic Insights Using Multiscale Modeling on an Antimicrobial Peptide-Drug-Membrane System

Owing to their potential applicability against multidrug-resistant bacteria, antimicrobial peptides (AMPs) or host defense peptides (HDPs) gain increased attention. Besides diverse immunomodulatory roles, their classical mechanism of action mostly involves membrane disruption of microbes. Notably, their unbalanced overexpression has also been associated with host cell cytotoxicity in various diseases. Relatedly, AMPs can be subject to aggregate formation, either via self-assembly or together with other compounds, which has demonstrated a modulation effect on their biological functions, thus highly relevant both for drug targeting projects and understanding their in vivo actions. However, the molecular aspects of the related assembly formation are not understood. Here, we focused in detail on an experimentally studied AMP-drug system, i.e., CM15-suramin, and performed all-atom and coarse-grain (CG) simulations. Results obtained for all systems were in close line with experimental observations and indicate that the CM15-suramin aggregation is an energetically favorable and dynamic process. In the presence of bilayers, the peptide-drug assembly formation was highly dependent on lipid composition, and peptide aggregates themselves were also capable of binding to the membranes. Interestingly, longer CG simulations with zwitterionic membranes indicated an intermediate state in the presence of both AMP-drug assemblies and monomeric peptides located on the membrane surface. In sharp contrast, larger AMP-drug aggregates could not be detected with a negatively charged membrane, rather the AMPs penetrated its surface in a monomeric form, in line with previous in vitro observations. Considering experimental and theoretical results, it is promoted that in biological systems, cationic AMPs may often form associates with anionic compounds in a reversible manner, resulting in lower bioactivity. This is only mildly affected by zwitterionic membranes; however, membranes with a negative charge strongly alter the energetic preference of AMP assemblies, resulting in the dissolution of the complexes into the membrane. The phenomenon observed here at a molecular level can be followed in several experimental systems studied recently, where peptides interact with food colors, drug molecules, or endogenous compounds, which strongly indicates that reversible associate formation is a general phenomenon for these complexes. These results are hoped to be exploited in novel therapeutic strategies aiming to use peptides as drug targets and control AMP bioactivity by directed assembly formation.

Evaluating the Efficiency of the Martini Force Field to Study Protein Dimerization in Aqueous and Membrane Environments

Protein-protein complex assembly is one of the major drivers of biological response. Understanding the mechanisms of protein oligomerization/dimerization would allow one to elucidate how these complexes participate in biological activities and could ultimately lead to new approaches in designing novel therapeutic agents. However, determining the exact association pathways and structures of such complexes remains a challenge. Here, we use parallel tempering metadynamics simulations in the well-tempered ensemble to evaluate the performance of Martini 2.2P and Martini open-beta 3 (Martini 3) force fields in reproducing the structure and energetics of the dimerization process of membrane proteins and proteins in an aqueous solution in reasonable accuracy and throughput. We find that Martini 2.2P systematically overestimates the free energy of association by estimating large barriers in distinct areas, which likely leads to overaggregation when multiple monomers are present. In comparison, the less viscous Martini 3 results in a systematic underestimation of the free energy of association for proteins in solution, while it performs well in describing the association of membrane proteins. In all cases, the near-native dimer complexes are identified as minima in the free energy surface albeit not always as the lowest minima. In the case of Martini 3, we find that the spurious supramolecular protein aggregation present in Martini 2.2P multimer simulations is alleviated and thus this force field may be more suitable for the study of protein oligomerization. We propose that the use of enhanced sampling simulations with a refined coarse-grained force field and appropriately defined collective variables is a robust approach for studying the protein dimerization process, although one should be cautious of the ranking of energy minima.

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

The coarse-grained Martini force field is widely used in biomolecular simulations. Here we present the refined model, Martini 3 ( http://cgmartini.nl ), with an improved interaction balance, new bead types and expanded ability to include specific interactions representing, for example, hydrogen bonding and electronic polarizability. The updated model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.

Perspectives on High-Throughput Ligand/Protein Docking With Martini MD Simulations

Molecular docking is central to rational drug design. Current docking techniques suffer, however, from limitations in protein flexibility and solvation models and by the use of simplified scoring functions. All-atom molecular dynamics simulations, on the other hand, feature a realistic representation of protein flexibility and solvent, but require knowledge of the binding site. Recently we showed that coarse-grained molecular dynamics simulations, based on the most recent version of the Martini force field, can be used to predict protein/ligand binding sites and pathways, without requiring any a priori information, and offer a level of accuracy approaching all-atom simulations. Given the excellent computational efficiency of Martini, this opens the way to high-throughput drug screening based on dynamic docking pipelines. In this opinion article, we sketch the roadmap to achieve this goal.

Estimating the accuracy of the MARTINI model towards the investigation of peripheral protein–membrane interactions

In this article, we investigate the ability of the MARTINI CG force field, specifically the 3 open-beta version, to reproduce known experimental observations regarding the membrane binding behavior of 12 peripheral membrane proteins and peptides.

In Silico Prediction of the Binding, Folding, Insertion, and Overall Stability of Membrane-Active Peptides

Membrane-active peptides (MAPs) are short-length peptides used for potential biomedical applications in diagnostic imaging of tissues, targeted drug delivery, gene delivery, and antimicrobials and antibiotics. The broad appeal of MAPs is that they are infinitely variable, relatively low cost, and biocompatible. However, experimentally characterizing the specific properties of a MAP or its many variants is a low-resolution and potentially time-consuming endeavor; molecular dynamics (MD) simulations have emerged as an invaluable tool in identifying the biophysical interactions that are fundamental to the function of MAPs. In this chapter, a step-by-step approach to discreetly model the binding, folding, and insertion of a membrane-active peptide to a model lipid bilayer using MD simulations is described. Detailed discussion is devoted to the critical aspects of running these types of simulations: prior knowledge of the system, understanding the strengths and weaknesses of molecular mechanics force fields, proper construction and equilibration of the system, realistically estimating both experimental and computational timescales, and leveraging analysis to make direct comparisons to experimental results as often as possible.

Effect of alcohol on the phase separation in model membranes

The discovery of coexisting liquid-ordered and liquid-disordered phases in multicomponent lipid bilayers has received widespread attention due to its potential relevance for biological systems. One of the many open questions is how the presence of additional components affects the nature of the coexisting phases. Of particular interest is the addition of alcohols because their anesthetic properties may arise from modulating bilayer behavior. We use coarse-grained Molecular Dynamics simulations to gain insight into the partitioning preferences of linear n-alcohols into ordered and disordered bilayers alongside their effects on local membrane structure. We find that alcohols cause only small changes to membrane composition alongside a lack of significant effects on membrane thickness and lipid tail order. Cholesterol and n-alcohol trans-bilayer motion is measured and found to be near or within the range of previous atomistic results. The cholesterol flip-flop rates increase with both n-alcohol length and concentration for octanol, dodecanol, and hexadecanol, indicating a decrease in lipid order. Umbrella sampling simulations of removing cholesterol from tertiary membranes find no significant difference with or without n-alcohols at various concentrations. Simulations of a phase-separated bilayer show that octanol preferentially partitions into the liquid-disordered phase in a ratio of approximately 3:1 over the liquid-ordered phase. Furthermore, partition coefficients of alcohol in single-phase membranes show a preference for longer alcohols (dodecanol and hexadecanol) to partition preferentially into the liquid-ordered phase, while decreasing the length of the alcohol reverses this trend. Our work tests experimental results while also investigating the ability for coarse-grained MARTINI simulations to capture minute differences in model membrane spatial arrangements on the nanoscale level.