LiPyphilic: A Python Toolkit for the Analysis of Lipid Membrane Simulations

Understanding the coarse-grained free energy landscape of phospholipids and their phase separation

The cell membrane exhibits lateral heterogeneity due to the preferential association among the large number of lipid species that constitute the membrane. In particular, the preferential association of cholesterol (CHOL) with saturated lipids into ordered domains has been an area of intense investigation. The large spatiotemporal scales that comprise spontaneous domain formation largely precludes computational investigation via conventional all-atom molecular dynamics. We demonstrate here that molecular coarse-grained (CG) models, obtained from the bottom-up, i.e., via statistical mechanical renormalization of atomistic models, are capable of spontaneous assembly and phase separation for two model raft-like systems, DLiPC/DPPC/CHOL and DOPC/DPPC/CHOL. The resulting bottom-up CG models exhibit spontaneous self-assembly and phase separation and recapitulate the structural correlations of the underlying atomistic models. The accuracy and fast dynamics of these CG models constitute an effective means of bypassing the limited spatiotemporal scales of atomistic simulations. As the first bottom-up CG models of lipid phase separation, the CG models in this work provide an informative analysis for further construction of bottom-up CG models transferable across a range of lipid compositions.

Dynamics and activation of membrane-bound B cell receptor assembly

B-cell receptor (BCR) complexes are expressed on the surface of a B-cell and are critical in antigen recognition and modulating the adaptive immune response. Even though the relevance of antibodies has been known for almost a hundred years, the antigen-dependent activation mechanism of B-cells has remained elusive. Several models have been proposed for BCR activation, including cross-linking, conformation-induced oligomerization, and dissociation activation models. Recently, the first cryo-EM structures of the human B-cell antigen receptor of the IgM and IgG isotypes have been published that validates the asymmetric organization of the BCR complex. Here, we carry out extensive molecular dynamics simulations to probe the conformational changes upon antigen binding and the influence of the membrane lipids. We identify two critical dynamical events that could be associated with antigen-dependent activation of BCR. First, antigen binding causes increased flexibility in regions distal to the antigen binding site. Second, antigen binding alters the rearrangement of IgM transmembrane helices, including the relative interaction of Igα/Igβ that mediates intracellular signaling. Furthermore, these transmembrane rearrangements lead to changes in localized lipid composition. Our work indirectly supports the conformational-change induced models of BCR activation and contributes to the understanding of the antigen-dependent activation mechanism of BCRs.

Effect of ergosterol or cholesterol on the morphology and dynamics of the POPC/sphingomyelin bilayer

Phase segregation and domain formation in cell membranes and model lipid bilayers have become a relevant topic in the last decades due to their role in important cell functions such as signaling and molecule-membrane interactions. To date, the most accepted explanation for the formation of these domains in mammalian cells is that cholesterol-enriched sphingomyelin patches of membrane form because of the preferential interaction between them. However, detailed information on molecular interactions within cholesterol-containing bilayers and their comparison with other sterol-containing bilayers, such as those containing ergosterol, is needed to understand the role these molecules have. Recent experimental findings have shown sterol-dependent differences in the morphology of supported lipid bilayers, but the molecular basis for these differences remains unclear. This work provides a molecular explanation for these differences using atomistic Molecular Dynamics simulations of lipid bilayers composed of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC) and N-palmitoyl-D-erythro-sphingosylphosphorylcholine (PSM) with 20 mol% of cholesterol or ergosterol. Atomic force microscopy was used to validate the simulation. The simulation ran for 11 μs and revealed that both sterols affect the morphology of the membrane. Key findings include: ergosterol induces greater order in PSM domains compared to cholesterol, lipid diffusion constants are lower in ergosterol-containing membranes, sterol flip-flop rates are significantly reduced in ergosterol-containing membranes and ergosterol leads to greater PSM-sterol enrichment. These molecular-level differences provide insight into the experimentally observed variations in domain formation and membrane properties between cholesterol and ergosterol-containing bilayers. Our findings contribute to the understanding of sterol-specific effects on membrane organization and dynamics, with potential implications for cellular processes and drug interactions in different organisms. STATEMENT OF SIGNIFICANCE: This study advances our understanding of how different sterols influence membrane properties through molecular dynamics simulations of three-component lipid membranes. Specifically, we investigate the effects of two major sterols: ergosterol, predominantly found in plants and fungi, and cholesterol, characteristic of mammalian cells. While extensive research has elucidated cholesterol's impact on lipid bilayers, studies on ergosterol's effects are comparatively limited. Our work provides a comprehensive comparison of these sterols, highlighting their similarities and differences. These insights not only enhance our knowledge of cell membrane structure and function, but also contribute to our understanding of selective drug permeability across membranes. This research has potential implications for both fundamental cell biology and pharmaceutical applications.

Computational Insights into Membrane Disruption by Cell-Penetrating Peptides

Cell-penetrating peptides (CPPs) can translocate into cells without inducing cytotoxicity. The internalization process implies several steps at different time scales ranging from microseconds to minutes. We combine adaptive Steered Molecular Dynamics (aSMD) with conventional Molecular Dynamics (cMD) to observe nonequilibrium and equilibrium states to study the early mechanisms of peptide-bilayer interaction leading to CPPs internalization. We define three membrane compositions representing bilayer sections, neutral lipids (i.e., upper leaflet), neutral lipids with cholesterol (i.e., hydrophobic core), and neutral/negatively charged lipids with cholesterol (i.e., lower leaflet) to study the energy barriers and disruption mechanisms of Arg9, MAP, and TP2, representing cationic, amphiphilic, and hydrophobic CPPs, respectively. Cholesterol and negatively charged lipids increase the energetic barriers for the peptide-bilayer crossing. TP2 interacts with the bilayer by hydrophobic insertion, while Arg9 disrupts the bilayer by forming transient or stable pores. MAP has shown both behaviors. Collectively, these findings underscore the significance of innovative computational approaches in studying membrane-disruptive peptides and, more specifically, in harnessing their potential for cell penetration.

Permeability Benchmarking: Guidelines for Comparing in Silico, in Vitro, and in Vivo Measurements

Permeability is a measure of the degree to which cells can transport molecules across biological barriers. Units of permeability are distance per unit time (typically cm/s), where accurate measurements are needed to define drug delivery in homeostasis and to model dysfunction occurring during disease. This perspective offers a set of community-led guidelines to benchmark permeability data across multidisciplinary approaches and different biological contexts. First, we lay out the analytical framework for three methodologies to calculate permeability: in silico assays using either transition-based counting or the inhomogeneous-solubility diffusion approaches, in vitro permeability assays using cells cultured in 2D or 3D geometries, and in vivo assays utilizing in situ brain perfusion or multiple time-point regression analysis. Then, we demonstrate a systematic benchmarking of in silico to both in vitro and in vivo, depicting the ways in which each benchmarking is sensitive to the choices of assay design. Finally, we outline seven recommendations for best practices in permeability benchmarking and underscore the significance of tailored permeability assays in driving advancements in drug delivery research and development. Our exploration encompasses a discussion of "generic" and tissue-specific biological barriers, including the blood-brain barrier (BBB), which is a major hurdle for the delivery of therapeutic agents into the brain. By addressing challenges in reconciling simulated data with experimental assays, we aim to provide insights essential for optimizing accuracy and reliability in permeability modeling.

Examining the Biophysical Properties of the Inner Membrane of Gram-Negative ESKAPE Pathogens

The World Health Organization has identified multidrug-resistant bacteria as a serious global health threat. Gram-negative bacteria are particularly prone to antibiotic resistance, and their high rate of antibiotic resistance has been suggested to be related to the complex structure of their cell membrane. The outer membrane of Gram-negative bacteria contains lipopolysaccharides that protect the bacteria against threats such as antibiotics, while the inner membrane houses 20-30% of the bacterial cellular proteins. Given the cell membrane's critical role in bacterial survival, antibiotics targeting the cell membrane have been proposed to combat bacterial infections. However, a deeper understanding of the biophysical properties of the bacterial cell membrane is crucial to developing effective and specific antibiotics. In this study, Martini coarse-grain molecular dynamics simulations were used to investigate the interplay between membrane composition and biophysical properties of the inner membrane across four pathogenic bacterial species: Klebsiella pneumoniae, Pseudomonas aeruginosa, Enterobacter cloacae, and Escherichia coli. The simulations indicate the impact of species-specific membrane composition on the overall membrane properties. Specifically, the cardiolipin concentration in the inner membrane is a key factor influencing the membrane features. Model membranes with varying concentrations of bacterial lipids (phosphatidylglycerol, phosphatidylethanolamine, and cardiolipin) further support the significant role of cardiolipin in determining the membrane biophysical properties. The bacterial inner membrane models developed in this work pave the way for future simulations of bacterial membrane proteins and for simulations investigating novel strategies aimed at disrupting the bacterial membrane to treat antibiotic-resistant infections.

A Neural-Network-Based Mapping and Optimization Framework for High-Precision Coarse-Grained Simulation

The accuracy and efficiency of a coarse-grained (CG) force field are pivotal for high-precision molecular simulations of large systems with complex molecules. We present an automated mapping and optimization framework for molecular simulation (AMOFMS), which is designed to streamline and improve the force field optimization process. It features a neural-network-based mapping function, DSGPM-TP (deep supervised graph partitioning model with type prediction). This model can accurately and efficiently convert atomistic structures to CG mappings, reducing the need for manual intervention. By integrating bottom-up and top-down methodologies, AMOFMS allows users to freely combine these approaches or use them independently as optimization targets. Moreover, users can select and combine different optimizers to meet their specific mission. With its parallel optimizer, AMOFMS significantly accelerates the optimization process, reducing the time required to achieve optimal results. Successful applications of AMOFMS include parameter optimizations for systems such as POPC and PEO, demonstrating its robustness and effectiveness. Overall, AMOFMS provides a general and flexible framework for the automated development of high-precision CG force fields.

Steroids and steroid-like compounds alter the ion permeability of phospholipid bilayers via distinct interactions with lipids and interfacial water

Steroids are organic compounds found in all forms of biological life. Besides their structural roles in cell membranes, steroids act as signalling molecules in various physiological processes and are used to treat inflammatory conditions. It has been hypothesised that in addition to their well-characterised genomic and non-genomic pathways, steroids exert their biological or pharmacological activities via an indirect, nonreceptor-mediated membrane mechanism caused by steroid-induced changes to the physicochemical properties of cell membranes. While the effect of cholesterol on phospholipid bilayer properties has been extensively studied, much less is known about the effect of other steroids and steroid-like molecules. Here, we combine electrical impedance spectroscopy (EIS) experiments with molecular dynamics (MD) simulations to study the effect of the steroids cortisone, prednisolone and progesterone and the steroid-like compounds enoxolone and carbenoxolone on the ion permeability and structure of phospholipid bilayers composed of the zwitterionic lipid POPC. The EIS data shows that all five compounds increase permeability, while the simulations suggest that this is accompanied by a thinning of the bilayer and reduced lipid order. We show that for steroids, a previously proposed structure-activity relationship that classifies steroids into order-promoting or order-disrupting compounds based on domain formations translates to ion permeability. We confirmed this by additional experiments with cholesterol and 7-ketocholesterol. In contrast, the previously reported relationship between log P and molecular area and a steroid being a promoter does not translate to the steroid-like compounds enoxolone and carbenoxolone. We propose that their membrane-disruption activity can be explained by their hydrogen-bonding capacity that dictates the compound's orientation at the water-lipid interface. Specifically, their membrane-disrupting ability is a result of the steroids to intercalate between lipids and form stable interactions with lipid headgroups and interfacial water, thereby pushing lipids apart and lowering the energy required for ion-induced pores, an effect previously reported for other membrane-altering small molecules.

Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery

G protein-coupled receptors (GPCRs) are the largest human membrane protein family that transduce extracellular signals into cellular responses. They are major pharmacological targets, with approximately 26% of marketed drugs targeting GPCRs, primarily at their orthosteric binding site. Despite their prominence, predicting the pharmacological effects of novel GPCR-targeting drugs remains challenging due to the complex functional dynamics of these receptors. Recent advances in X-ray crystallography, cryo-electron microscopy, spectroscopic techniques and molecular simulations have enhanced our understanding of receptor conformational dynamics and ligand interactions with GPCRs. These developments have revealed novel ligand-binding modes, mechanisms of action and druggable pockets. In this Review, we highlight such aspects for recently discovered small-molecule drugs and drug candidates targeting GPCRs, focusing on three categories: allosteric modulators, biased ligands, and bivalent and bitopic compounds. Although studies so far have largely been retrospective, integrating structural data on ligand-induced receptor functional dynamics into the drug discovery pipeline has the potential to guide the identification of drug candidates with specific abilities to modulate GPCR interactions with intracellular effector proteins such as G proteins and β-arrestins, enabling more tailored selectivity and efficacy profiles.

Atomistic Simulations and Analysis of Peripheral Membrane Proteins with Model Lipid Bilayers

All-atom molecular dynamics (AAMD) is a computational technique that predicts the movement of particles based on the intermolecular forces acting on the system. It enables the study of biological systems at atomic detail, complements observations from experiments, and can help the selection of experimental targets. Here, we describe the applications of MD simulations to study the interaction between peripheral membrane proteins and lipid bilayers. Specifically, we provide step-by-step instructions to set up MD simulations to study the binding and interaction of ALPS, the amphipathic helix of the lipid transport protein Osh4, and Thanatin, an antimicrobial peptide with model membranes. We describe examples of systems built with fully atomistic lipid tails and those truncated with the highly-mobile-membrane-mimetic method to enhance conformational sampling. We also comment on the importance of lipid diversity, molecular resolution, and best practices for constructing, running, and analyzing protein-lipid simulation systems. In this second edition, we include a brief discussion on alternative approaches and software to construct protein-membrane coordinate systems, as well as analysis tools and practices that have become relevant to examining protein-lipid interactions since the first edition of this chapter.

Nanodomains enriched in arachidonic acid promote P2Y12 receptor oligomerization in the platelet plasma membrane

P2Y12 receptors on the platelet plasma membrane are targeted by several antiplatelets drugs. Although oligomerization and functioning of P2Y12 receptors depend on the membrane environment, little is known about their preferred membrane localization and the role of surrounding lipid composition, especially the arachidonic acids (ARA), which are abundant in platelets. Coarse-grained molecular dynamics simulations of platelet plasma membrane based on the lipidomics data were used to investigate the P2Y12 lipid environment and the involvement of ARA in its oligomerization in platelet plasma membranes. The platelet plasma membrane contains two types of lipids nanodomains: ordered, enriched in SM and cholesterol, and disordered, enriched in ARA-containing lipids. P2Y12 receptors prefer to localize in these ARA-rich domains and induce the sorting of the ARA-containing lipids in their vicinity. This ARA-rich environment promotes the oligomerization of P2Y12 receptors and stabilizes the protein-protein interfaces of oligomers. As summary, oligomerization of P2Y12 receptors is promoted in ARA-rich nano-domains of the platelet plasma membrane.

Unveiling Interactions between Self-Assembling Peptides and Neuronal Membranes

The use of self-assembling peptide hydrogels in the treatment of spinal cord and brain injuries, especially when combined with adult neural stem cells, has shown great potential. To advance tissue engineering, it is essential to understand the effect of mechanochemical signaling on cellular differentiation. The elucidation of the molecular interactions at the level of the neuronal membrane still represents a promising area of investigation for many drug delivery and tissue engineering applications. An innovative molecular dynamics framework has been introduced to investigate the effect of SAP fibrils with different charges on neural membrane lipid domain dynamics. Such advance enables the in silico exploration of the biomimetic properties of SAP hydrogels and other polymeric biomaterials for tissue engineering applications.

Dynamics and Activation of Membrane-Bound B Cell Receptor Assembly

B-cell receptor complexes (BCR) are expressed on the surface of a B-cell and are critical in antigen recognition and modulating the adaptive immune response. Even though the relevance of antibodies has been known for almost a hundred years, the antigen-dependent activation mechanism of B-cells has remained elusive. Several models have been proposed for BCR activation, including cross-linking, conformation-induced oligomerization, and dissociation activation models. Recently, the first cryo-EM structures of the human B-cell antigen receptor of the IgM and IgG isotypes were published that validated the asymmetric organization of the BCR complex. Here, we have carried out extensive molecular dynamics simulations to probe the conformational changes upon antigen binding and the influence of the membrane lipids. We identified two critical dynamical events that could be associated with antigen-dependent activation of BCR. First, antigen binding caused increased flexibility in regions distal to the antigen binding site. Second, antigen binding altered the rearrangement of IgM transmembrane helices, including the relative interaction of Igα/Igβ that mediates intracellular signaling. Furthermore, these transmembrane rearrangements led to changes in localized lipid composition.

PLNC8 αβ Potently Inhibits the Flavivirus Kunjin and Modulates Inflammatory and Intracellular Signaling Responses of Alveolar Epithelial Cells

PLNC8 αβ is a cationic antimicrobial peptide that previously has been reported to express both antibacterial and antiviral properties. This study aimed to further elucidate the antiviral effects of PLNC8 αβ and its impact on virus-induced cytotoxicity and inflammatory signaling in human alveolar epithelial cells (A549) infected with the flavivirus Kunjin. Complementary in silico analyses using molecular dynamics (MD) simulation were conducted to investigate the mechanism of action of PLNC8 αβ by studying the interaction of PLNC8 α and β with models of a flavivirus membrane and a eukaryotic plasma membrane, respectively. Our findings demonstrated that PLNC8 αβ significantly reduces both extracellular and intracellular viral loads, as confirmed by plaque reduction assays and RT-PCR. The peptide also mitigated virus-induced cytotoxicity and inflammation. Notably, PLNC8 αβ modulated the virus-induced dysregulation of key signaling and inflammatory genes, such as TLR9, TLR3, NOD2, FOS, JUN, IL6, and CXCL8. MD simulation revealed that PLNC8 αβ exhibits higher binding affinity for a flavivirus membrane model compared to a model of the plasma membrane, likely due to stronger electrostatic interactions with anionic phospholipids. This selective interaction possibly accounts for a potent antiviral activity of PLNC8 αβ combined with a minimal cytotoxicity toward human cells. Overall, PLNC8 αβ shows significant promise as an antiviral agent against flavivirus infections and warrants further exploration for peptide-based antiviral therapies.

Symmetry-adapted Markov state models of closing, opening, and desensitizing in α 7 nicotinic acetylcholine receptors

α7 nicotinic acetylcholine receptors (nAChRs) are homopentameric ligand-gated ion channels with critical roles in the nervous system. Recent studies have resolved and functionally annotated closed, open, and desensitized states of these receptors, providing insight into ion permeation and lipid binding. However, the process by which α7 nAChRs transition between states remains unclear. To understand gating and lipid modulation, we generated two ensembles of molecular dynamics simulations of apo α7 nAChRs, with or without cholesterol. Using symmetry-adapted Markov state modeling, we developed a five-state gating model. Free energies recapitulated functional behavior, with the closed state dominating in absence of agonist. Open-to-nonconducting transition rates corresponded to experimental open durations. Cholesterol relatively stabilized the desensitized state, and reduced open-desensitized barriers. These results establish plausible asymmetric transition pathways between states, define lipid modulation effects on the α7 nAChR conformational cycle, and provide an ensemble of structural models applicable to rational design of lipidic pharmaceuticals.

Polymyxin B1 in the Escherichia coli inner membrane: A complex story of protein and lipopolysaccharide-mediated insertion

The rise in multi-drug resistant Gram-negative bacterial infections has led to an increased need for "last-resort" antibiotics such as polymyxins. However, the emergence of polymyxin-resistant strains threatens to bring about a post-antibiotic era. Thus, there is a need to develop new polymyxin-based antibiotics, but a lack of knowledge of the mechanism of action of polymyxins hinders such efforts. It has recently been suggested that polymyxins induce cell lysis of the Gram-negative bacterial inner membrane (IM) by targeting trace amounts of lipopolysaccharide (LPS) localized there. We use multiscale molecular dynamics (MD), including long-timescale coarse-grained (CG) and all-atom (AA) simulations, to investigate the interactions of polymyxin B1 (PMB1) with bacterial IM models containing phospholipids (PLs), small quantities of LPS, and IM proteins. LPS was observed to (transiently) phase separate from PLs at multiple LPS concentrations, and associate with proteins in the IM. PMB1 spontaneously inserted into the IM and localized at the LPS-PL interface, where it cross-linked lipid headgroups via hydrogen bonds, sampling a wide range of interfacial environments. In the presence of membrane proteins, a small number of PMB1 molecules formed interactions with them, in a manner that was modulated by local LPS molecules. Electroporation-driven translocation of PMB1 via water-filled pores was favored at the protein-PL interface, supporting the 'destabilizing' role proteins may have within the IM. Overall, this in-depth characterization of PMB1 modes of interaction reveals how small amounts of mislocalized LPS may play a role in pre-lytic targeting and provides insights that may facilitate rational improvement of polymyxin-based antibiotics.

Exploring the Properties of Curved Lipid Membranes: Comparative Analysis of Atomistic and Coarse-Grained Force Fields

Curvature emerges as a fundamental membrane characteristic crucial for diverse biological processes, including vesicle formation, cell signaling, and membrane trafficking. Increasingly valuable insights into atomistic details governing curvature-dependent membrane properties are provided by computer simulations. Nevertheless, the underlying force field models are conventionally calibrated and tested in relation to experimentally derived parameters of planar bilayers, thereby leaving uncertainties concerning their consistency in reproducing curved lipid systems. In this study we compare the depiction of buckled phosphatidylcholine (POPC) and POPC-cholesterol membranes by four popular force field models. Aside from agreement with respect to general trends in curvature dependence of a number of parameters, we observe a few qualitative differences. Among the most prominent ones is the difference between atomistic and coarse grained force fields in their representation of relative compressibility of the polar headgroup region and hydrophobic lipid core. Through a number of downstream effects, this discrepancy can influence the way in which curvature modulates the behavior of membrane bound proteins depending on the adopted simulation model.

Insights into the role of glycerophospholipids on the iron export function of SLC40A1 and the molecular mechanisms of ferroportin disease

SLC40A1 is the sole iron export protein reported in mammals. In humans, its dysfunction is responsible for ferroportin disease, an inborn error of iron metabolism transmitted as an autosomal dominant trait and observed in different ethnic groups. As a member of the major facilitator superfamily, SLC40A1 requires a series of conformational changes to enable iron translocation across the plasma membrane. The influence of lipids on protein stability and its conformational changes has been little investigated to date. Here, we combine molecular dynamics simulations of SLC40A1 embedded in membrane bilayers with experimental alanine scanning mutagenesis to analyze the specific role of glycerophospholipids. We identify four basic residues (Lys90, Arg365, Lys366, and Arg371) that are located at the membrane-cytosol interface and consistently interact with 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE) molecules. These residues surround a network of salt bridges and hydrogens bonds that play a critical role in stabilizing SLC40A1 in its basal outward-facing conformation. More deeply embedded in the plasma membrane, we identify Arg179 as a charged amino acid residue also tightly interacting with lipid polar heads. This results in a local deformation of the lipid bilayer. Interestingly, Arg179 is adjacent to Arg178, which forms a functionally important salt-bridge with Asp473 and is a recurrently associated with ferroportin disease when mutated to glutamine. We demonstrate that the two p.Arg178Gln and p.Arg179Thr missense variants have similar functional behaviors. These observations provide insights into the role of phospholipids in the formation/disruption of the SLC40A1 inner gate, and give a better understanding of the diversity of molecular mechanisms of ferroportin disease.

Intrinsically Disordered Membrane Anchors of Rheb, RhoA, and DiRas3 Small GTPases: Molecular Dynamics, Membrane Organization, and Interactions

Protein structure has been well established to play a key role in determining function; however, intrinsically disordered proteins and regions (IDPs and IDRs) defy this paradigm. IDPs and IDRs exist as an ensemble of structures rather than a stable 3D structure yet play essential roles in many cell-signaling processes. Nearly all Ras superfamily GTPases are tethered to membranes by a lipid tail at the end of a flexible IDR. The sequence of the IDR is a key determinant of membrane localization, and interaction between the IDR and the membrane has been shown to affect signaling in RAS proteins through the modulation of dynamic membrane organization. Here, we utilized atomistic molecular dynamics simulations to study the membrane interaction, conformational dynamics, and lipid sorting of three IDRs from small GTPases Rheb, RhoA, and DiRas3 in model membranes representing their physiological target membranes. We found that complementarity between the lipidated IDR sequence and target membrane lipid composition is a determinant of conformational plasticity. We also show that electrostatic interactions between anionic lipids and basic residues on IDRs are correlated with sampling of semistable conformational substates, and lack of these interactions is associated with greater conformational diversity. Finally, we show that small GTPase IDRs with a polybasic domain alter local lipid composition by segregating anionic lipids and, in some cases, excluding other lipids from their immediate vicinity in favor of anionic lipids.

Helical reorganization in the context of membrane protein folding: Insights from simulations with bacteriorhodopsin (BR) fragments

Membrane protein folding is distinct from folding of soluble proteins. Conformational acquisition in major membrane protein subclasses can be delineated into insertion and folding processes. An exception to the "two stage" folding, later developed to "three stage" folding, is observed within the last two helices in bacteriorhodopsin (BR), a system that serves as a model membrane protein. We employ a reductionist approach to understand interplay of molecular factors underlying the apparent defiance. Leveraging available solution NMR structures, we construct, sample in silico, and analyze partially (PIn) and fully inserted (FIn) BR membrane states. The membrane lateral C-terminal helix (CH) in PIn is markedly prone to transient structural distortions over microsecond timescales; a disorder prone region (DPR) is thereby identified. While clear transmembrane propensities are not acquired, the distortions induce alterations in local membrane curvature and area per lipid. Importantly, energetic decompositions reveal that overall, the N-terminal helix (NH) is thermodynamically more stable in the PIn. Higher overall stability of the FIn arises from favorable interactions between the NH and the CH. Our results establish lack of spontaneous transition of the PIn to the FIn, and attributes their partitioning to barriers that exceed those accessible with thermal fluctuations. This work paves the way for further detailed studies aimed at determining the thermo-kinetic roles of the initial five helices, or complementary external factors, in complete helical folding and insertion in BR. We comment that complementing such efforts with the growing field of machine learning assisted energy landscape searches may offer unprecedented insights.

Intrinsically disordered membrane anchors of Rheb, RhoA and DiRas3 small GTPases: Molecular dynamics, membrane organization, and interactions

Protein structure has been well established to play a key role in determining function; however, intrinsically disordered proteins and regions (IDPs and IDRs) defy this paradigm. IDPs and IDRs exist as an ensemble of structures rather than a stable 3D structure yet play essential roles in many cell signaling processes. Nearly all Ras Superfamily GTPases are tethered to membranes by a lipid tail at the end of a flexible IDR. The sequence of these IDRs are key determinants of membrane localization, and interactions between the IDR and the membrane have been shown to affect signaling in RAS proteins through modulation of dynamic membrane organization. Here we utilized atomistic molecular dynamics simulations to study the membrane interactions, conformational dynamics, and lipid sorting of three IDRs from small GTPases Rheb, RhoA and DiRas3 in model membranes representing their physiological target membranes. We found that complementarity between lipidated IDR sequence and target membrane lipid composition is a determinant of conformational plasticity. We also show that electrostatic interactions between anionic lipids and basic residues on IDRs generate semi-stable conformational sub-states, and a lack of these residues leads to greater conformational diversity. Finally, we show that small GTPase IDRs with a polybasic domain alter local lipid composition by segregating anionic membrane lipids, and, in some cases, excluding other lipids from their immediate proximity in favor of anionic lipids.

State-dependent binding of cholesterol and an anionic lipid to the muscle-type Torpedo nicotinic acetylcholine receptor

The ability of the Torpedo nicotinic acetylcholine receptor (nAChR) to undergo agonist-induced conformational transitions requires the presence of cholesterol and/or anionic lipids. Here we use recently solved structures along with multiscale molecular dynamics simulations to examine lipid binding to the nAChR in bilayers that have defined effects on nAChR function. We examine how phosphatidic acid and cholesterol, lipids that support conformational transitions, individually compete for binding with phosphatidylcholine, a lipid that does not. We also examine how the two lipids work synergistically to stabilize an agonist-responsive nAChR. We identify rapidly exchanging lipid binding sites, including both phospholipid sites with a high affinity for phosphatidic acid and promiscuous cholesterol binding sites in the grooves between adjacent transmembrane α-helices. A high affinity cholesterol site is confirmed in the inner leaflet framed by a key tryptophan residue on the MX α-helix. Our data provide insight into the dynamic nature of lipid-nAChR interactions and set the stage for a detailed understanding of the mechanisms by which lipids facilitate nAChR function at the neuromuscular junction.

Building complex membranes with Martini 3

The Martini model is a popular force field for coarse-grained simulations. Membranes have always been at the center of its development, with the latest version, Martini 3, showing great promise in capturing more and more realistic behavior. In this chapter we provide a step-by-step tutorial on how to construct starting configurations, run initial simulations and perform dedicated analysis for membrane-based systems of increasing complexity, including leaflet asymmetry, curvature gradients and embedding of membrane proteins.

Characterization of domain formation in complex membranes

A widely known property of lipid membranes is their tendency to undergo a separation into disordered (Ld) and ordered (Lo) domains. This impacts the local structure of the membrane relevant for the physical (e.g., enhanced electroporation) and biological (e.g., protein sorting) significance of these regions. The increase in computing power, advancements in simulation software, and more detailed information about the composition of biological membranes shifts the study of these domains into the focus of classical molecular dynamics simulations. In this chapter, we present a versatile yet robust analysis pipeline that can be easily implemented and adapted for a wide range of lipid compositions. It employs Gaussian-based Hidden Markov Models to predict the hidden order states of individual lipids by describing their structure through the area per lipid and the average SCC order parameters per acyl chain. Regions of the membrane with a high correlation between ordered lipids are identified by employing the Getis-Ord local spatial autocorrelation statistic on a Voronoi tessellation of the lipids. As an example, the approach is applied to two distinct systems at a coarse-grained resolution, demonstrating either a strong tendency towards phase separation (1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), 1,2-dilinoleoyl-sn-glycero-3-phosphocholine (DIPC), cholesterol) or a weak tendency toward phase separation (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), 1-palmitoyl-2-docosahexaenoyl-sn-glycero-3-phosphocholine (PUPC), cholesterol). Explanations of the steps are complemented by coding examples written in Python, providing both a comprehensive understanding and practical guidance for a seamless integration of the workflow into individual projects.

Functional regulation of aquaporin dynamics by lipid bilayer composition

With the diversity of lipid-protein interactions, any observed membrane protein dynamics or functions directly depend on the lipid bilayer selection. However, the implications of lipid bilayer choice are seldom considered unless characteristic lipid-protein interactions have been previously reported. Using molecular dynamics simulation, we characterize the effects of membrane embedding on plant aquaporin SoPIP2;1, which has no reported high-affinity lipid interactions. The regulatory impacts of a realistic lipid bilayer, and nine different homogeneous bilayers, on varying SoPIP2;1 dynamics are examined. We demonstrate that SoPIP2;1's structure, thermodynamics, kinetics, and water transport are altered as a function of each membrane construct's ensemble properties. Notably, the realistic bilayer provides stabilization of non-functional SoPIP2;1 metastable states. Hydrophobic mismatch and lipid order parameter calculations further explain how lipid ensemble properties manipulate SoPIP2;1 behavior. Our results illustrate the importance of careful bilayer selection when studying membrane proteins. To this end, we advise cautionary measures when performing membrane protein molecular dynamics simulations.

Overlay databank unlocks data-driven analyses of biomolecules for all

Tools based on artificial intelligence (AI) are currently revolutionising many fields, yet their applications are often limited by the lack of suitable training data in programmatically accessible format. Here we propose an effective solution to make data scattered in various locations and formats accessible for data-driven and machine learning applications using the overlay databank format. To demonstrate the practical relevance of such approach, we present the NMRlipids Databank-a community-driven, open-for-all database featuring programmatic access to quality-evaluated atom-resolution molecular dynamics simulations of cellular membranes. Cellular membrane lipid composition is implicated in diseases and controls major biological functions, but membranes are difficult to study experimentally due to their intrinsic disorder and complex phase behaviour. While MD simulations have been useful in understanding membrane systems, they require significant computational resources and often suffer from inaccuracies in model parameters. Here, we demonstrate how programmable interface for flexible implementation of data-driven and machine learning applications, and rapid access to simulation data through a graphical user interface, unlock possibilities beyond current MD simulation and experimental studies to understand cellular membranes. The proposed overlay databank concept can be further applied to other biomolecules, as well as in other fields where similar barriers hinder the AI revolution.

Digestion of lipid micelles leads to increased membrane permeability

Lipid-based drug carriers are an attractive option to solubilise poorly water soluble therapeutics. Previously, we reported that the digestion of a short tail PC lipid (2C6PC) by the PLA2 enzyme has a significant effect on the structure and stability of the micelles it forms. Here, we studied the interactions of micelles of varying composition representing various degrees of digestion with a model ordered (70 mol% DPPC & 30 mol% cholesterol) and disordered (100% DOPC) lipid membrane. Micelles of all compositions disassociated when interacting with the two different membranes. As the percentage of digestion products (C6FA and C6LYSO) in the micelle increased, the disassociation occurred more rapidly. The C6FA inserts preferentially into both membranes. We find that all micelle components increase the area per lipid, increase the disorder and decrease the thickness of the membranes, and the 2C6PC lipid molecules have the most significant impact. Additionally, there is an increase in permeation of water into the membrane that accompanies the insertion of C6FA into the DOPC membranes. We show that the natural digestion of lipid micelles result in molecular species that can enhance the permeability of lipid membranes that in turn result in an enhanced delivery of drugs.

Multimillion Atom Simulations of Di-8-ANEPPS Chromophores Embedded in a Model Plasma Membrane: Toward the Investigation of Realistic Dyed Cell Membranes

A multistep computational approach has been employed to study a multimillion all-atom dyed plasma membrane, with no less than 42 different lipid species spanning the major head groups and a variety of fatty acids, as well as cholesterol, with the objective of investigating its structure and dynamics, as well as its impact on the embedded di-8-ANEPPS dyes. The latter are commonly used as bioimaging probes and serve as local microscopes. So, they provide information on membrane morphology via their second harmonic nonlinear optical (NLO) responses, which have the advantage of being specific to interface regions and sensitive to the chromophore environment. In previous studies, this chromophore has only been studied in simpler membrane models, far from the complexity of real lipid bilayers, while, owing to the ever-increasing computational resources, multimillion lipid bilayers have been studied, giving access to the effects of its heterogeneity. First, using molecular dynamics (MD) simulations, it is found that the combination of lipids produces a more ordered and denser membrane compared to its homogeneous model counterparts, while the local environment of the embedded dyes becomes enriched in phosphatidylcholine. Subsequently, the second harmonic first hyperpolarizability of the probes was calculated at the TDDFT level on selected frames of MD, highlighting the influence of the lipid environment. Due to the complexity of the system, machine learning (ML) tools have been employed to establish relationships between the membrane structural parameters, the orientation of the probes, and their NLO responses. These ML approaches have revealed influential features, including the presence of diacylglycerol lipids close to the dye. On the whole, this work provides a first step toward understanding the cooperation, synergy, and interactions that occur in such complex guest-host environments, which have emerged as new targets for drug design and membrane lipid therapy.

Protein-lipid interactions and protein anchoring modulate the modes of association of the globular domain of the Prion protein and Doppel protein to model membrane patches

The Prion protein is the molecular hallmark of the incurable prion diseases affecting mammals, including humans. The protein-only hypothesis states that the misfolding, accumulation, and deposition of the Prion protein play a critical role in toxicity. The cellular Prion protein (PrPC) anchors to the extracellular leaflet of the plasma membrane and prefers cholesterol- and sphingomyelin-rich membrane domains. Conformational Prion protein conversion into the pathological isoform happens on the cell surface. In vitro and in vivo experiments indicate that Prion protein misfolding, aggregation, and toxicity are sensitive to the lipid composition of plasma membranes and vesicles. A picture of the underlying biophysical driving forces that explain the effect of Prion protein - lipid interactions in physiological conditions is needed to develop a structural model of Prion protein conformational conversion. To this end, we use molecular dynamics simulations that mimic the interactions between the globular domain of PrPC anchored to model membrane patches. In addition, we also simulate the Doppel protein anchored to such membrane patches. The Doppel protein is the closest in the phylogenetic tree to PrPC, localizes in an extracellular milieu similar to that of PrPC, and exhibits a similar topology to PrPC even if the amino acid sequence is only 25% identical. Our simulations show that specific protein-lipid interactions and conformational constraints imposed by GPI anchoring together favor specific binding sites in globular PrPC but not in Doppel. Interestingly, the binding sites we found in PrPC correspond to prion protein loops, which are critical in aggregation and prion disease transmission barrier (β2-α2 loop) and in initial spontaneous misfolding (α2-α3 loop). We also found that the membrane re-arranges locally to accommodate protein residues inserted in the membrane surface as a response to protein binding.

Palmitoylation of the Glucagon-like Peptide-1 Receptor Modulates Cholesterol Interactions at the Receptor-Lipid Microenvironment

The G protein-coupled receptor (GPCR) superfamily of cell surface receptors has been shown to be functionally modulated by post-translational modifications. The glucagon-like peptide receptor-1 (GLP-1R), which is a drug target in diabetes and obesity, undergoes agonist-dependent palmitoyl tail conjugation. The palmitoylation in the C-terminal domain of GLP-1R has been suggested to modulate the receptor-lipid microenvironment. In this work, we have performed coarse-grain molecular dynamics simulations of palmitoylated and nonpalmitoylated GLP-1R to analyze the differential receptor-lipid interactions. Interestingly, the placement and dynamics of the C-terminal domain of GLP-1R are found to be directly dependent on the palmitoyl tail. We observe that both cholesterol and phospholipids interact with the receptor but display differential interactions in the presence and absence of the palmitoyl tail. We characterize important cholesterol-binding sites and validate sites that have been previously reported in experimentally resolved structures of the receptor. We show that the receptor acts like a conduit for cholesterol flip-flop by stabilizing cholesterol in the membrane core. Taken together, our work represents an important step in understanding the molecular effects of lipid modifications in GPCRs.

CGCompiler: Automated Coarse-Grained Molecule Parametrization via Noise-Resistant Mixed-Variable Optimization

Coarse-grained force fields (CG FFs) such as the Martini model entail a predefined, fixed set of Lennard-Jones parameters (building blocks) to model virtually all possible nonbonded interactions between chemically relevant molecules. Owing to its universality and transferability, the building-block coarse-grained approach has gained tremendous popularity over the past decade. The parametrization of molecules can be highly complex and often involves the selection and fine-tuning of a large number of parameters (e.g., bead types and bond lengths) to optimally match multiple relevant targets simultaneously. The parametrization of a molecule within the building-block CG approach is a mixed-variable optimization problem: the nonbonded interactions are discrete variables, whereas the bonded interactions are continuous variables. Here, we pioneer the utility of mixed-variable particle swarm optimization in automatically parametrizing molecules within the Martini 3 coarse-grained force field by matching both structural (e.g., RDFs) as well as thermodynamic data (phase-transition temperatures). For the sake of demonstration, we parametrize the linker of the lipid sphingomyelin. The important advantage of our approach is that both bonded and nonbonded interactions are simultaneously optimized while conserving the search efficiency of vector guided particle swarm optimization (PSO) methods over other metaheuristic search methods such as genetic algorithms. In addition, we explore noise-mitigation strategies in matching the phase-transition temperatures of lipid membranes, where nucleation and concomitant hysteresis introduce a dominant noise term within the objective function. We propose that noise-resistant mixed-variable PSO methods can both improve and automate parametrization of molecules within building-block CG FFs, such as Martini.

LipIDens: simulation assisted interpretation of lipid densities in cryo-EM structures of membrane proteins

Cryo-electron microscopy (cryo-EM) enables the determination of membrane protein structures in native-like environments. Characterising how membrane proteins interact with the surrounding membrane lipid environment is assisted by resolution of lipid-like densities visible in cryo-EM maps. Nevertheless, establishing the molecular identity of putative lipid and/or detergent densities remains challenging. Here we present LipIDens, a pipeline for molecular dynamics (MD) simulation-assisted interpretation of lipid and lipid-like densities in cryo-EM structures. The pipeline integrates the implementation and analysis of multi-scale MD simulations for identification, ranking and refinement of lipid binding poses which superpose onto cryo-EM map densities. Thus, LipIDens enables direct integration of experimental and computational structural approaches to facilitate the interpretation of lipid-like cryo-EM densities and to reveal the molecular identities of protein-lipid interactions within a bilayer environment. We demonstrate this by application of our open-source LipIDens code to ten diverse membrane protein structures which exhibit lipid-like densities.

Effects of lipid saturation on bicelle to vesicle transition of a binary phospholipid mixture: a molecular dynamics simulation study

Controlling the transition from lipid bicelles to vesicles is essential for producing engineered vesicles. We perform coarse-grained molecular dynamics (CGMD) simulations of unsaturated/saturated lipid mixtures to clarify the effects of lipid unsaturation on vesiculation at the molecular scale. The results demonstrate that vesiculation depends on the concentration of unsaturated lipids and the degree of unsaturation. The probability of vesiculation increases linearly with the apparent unsaturated lipid concentration at a low degree of unsaturation. Higher degrees of unsaturation lead to phase segregation within the binary bicelles, reducing the probability of vesiculation. A comparison between CGMD simulations and the conventional theory of vesiculation shows that the theoretical predictions of binary lipid systems must explicitly include phase segregation effects. Furthermore, simulations with biased lipid distributions reveal that vesiculation is facilitated by the preconcentration of unsaturated lipids in the core region of the bicelle but is then temporally limited as the unsaturated lipids move to the bicelle edges. These findings advance theoretical and experimental studies on binary lipid systems and promote the development of tailor-made vesicles.

Phospholipid tail asymmetry allows cellular adaptation to anoxic environments

Membrane biophysical properties are critical to cell fitness and depend on unsaturated phospholipid acyl tails. These can only be produced in aerobic environments since eukaryotic desaturases require molecular oxygen. This raises the question of how cells maintain bilayer properties in anoxic environments. Using advanced microscopy, molecular dynamics simulations, and lipidomics by mass spectrometry we demonstrated the existence of an alternative pathway to regulate membrane fluidity that exploits phospholipid acyl tail length asymmetry, replacing unsaturated species in the membrane lipidome. We show that the fission yeast, Schizosaccharomyces japonicus, which can grow in aerobic and anaerobic conditions, is capable of utilizing this strategy, whereas its sister species, the well-known model organism Schizosaccharomyces pombe, cannot. The incorporation of asymmetric-tailed phospholipids might be a general adaptation to hypoxic environmental niches.

Extension of the iSoLF implicit-solvent coarse-grained model for multicomponent lipid bilayers

iSoLF is a coarse-grained (CG) model for lipid molecules with the implicit-solvent approximation used in molecular dynamics (MD) simulations of biological membranes. Using the original iSoLF (iSoLFv1), MD simulations of lipid bilayers consisting of either POPC or DPPC and these bilayers, including membrane proteins, can be performed. Here, we improve the original model, explicitly treating the electrostatic interactions between different lipid molecules and adding CG particle types. As a result, the available lipid types increase to 30. To parameterize the potential functions of the new model, we performed all-atom MD simulations of each lipid at three different temperatures using the CHARMM36 force field and the modified TIP3P model. Then, we parameterized both the bonded and non-bonded interactions to fit the area per lipid and the membrane thickness of each lipid bilayer by using the multistate Boltzmann Inversion method. The final model reproduces the area per lipid and the membrane thickness of each lipid bilayer at the three temperatures. We also examined the applicability of the new model, iSoLFv2, to simulate the phase behaviors of mixtures of DOPC and DPPC at different concentrations. The simulation results with iSoLFv2 are consistent with those using Dry Martini and Martini 3, although iSoLFv2 requires much fewer computations. iSoLFv2 has been implemented in the GENESIS MD software and is publicly available.

Structural Studies of Monounsaturated and ω-3 Polyunsaturated Free Fatty Acids in Solution with the Combined Use οf NMR and DFT Calculations-Comparison with the Liquid State

Molecular structures, in chloroform and DMSO solution, of the free fatty acids (FFAs) caproleic acid, oleic acid, α-linolenic acid, eicosapentanoic acid (EPA) and docosahexaenoic acid (DHA) are reported with the combined use of NMR and DFT calculations. Variable temperature and concentration chemical shifts of the COOH protons, transient 1D NOE experiments and DFT calculations demonstrate the major contribution of low molecular weight aggregates of dimerized fatty acids through intermolecular hydrogen bond interactions of the carboxylic groups, with parallel and antiparallel interdigitated structures even at the low concentration of 20 mM in CDCl3. For the dimeric DHA, a structural model of an intermolecular hydrogen bond through carboxylic groups and an intermolecular hydrogen bond between the carboxylic group of one molecule and the ω-3 double bond of a second molecule is shown to play a role. In DMSO-d6 solution, NMR and DFT studies show that the carboxylic groups form strong intermolecular hydrogen bond interactions with a single discrete solvation molecule of DMSO. These solvation species form parallel and antiparallel interdigitated structures of low molecular weight, as in chloroform solution. This structural motif, therefore, is an intrinsic property of the FFAs, which is not strongly affected by the length and degree of unsaturation of the chain and the hydrogen bond ability of the solvent.

A dynamic biomimetic model of the membrane-bound CD4-CD3-TCR complex during pMHC disengagement

The coordinated (dis)engagement of the membrane-bound T cell receptor (TCR)-CD3-CD4 complex from the peptide-major histocompatibility complex (pMHC) is fundamental to TCR signal transduction and T cell effector function. As such, an atomic-scale understanding would not only enhance our basic understanding of the adaptive immune response but would also accelerate the rational design of TCRs for immunotherapy. In this study, we explore the impact of the CD4 coreceptor on the TCR-pMHC (dis)engagement by constructing a molecular-level biomimetic model of the CD3-TCR-pMHC and CD4-CD3-TCR-pMHC complexes within a lipid bilayer. After allowing the system complexes to equilibrate (engage), we use steered molecular dynamics to dissociate (disengage) the pMHC. We find that 1) the CD4 confines the pMHC closer to the T cell by 1.8 nm at equilibrium; 2) CD4 confinement shifts the TCR along the MHC binding groove engaging a different set of amino acids and enhancing the TCR-pMHC bond lifetime; 3) the CD4 translocates under load increasing the interaction strength between the CD4-pMHC, CD4-TCR, and CD4-CD3; and 4) upon dissociation, the CD3-TCR complex undergoes structural oscillation and increased energetic fluctuation between the CD3-TCR and CD3-lipids. These atomic-level simulations provide mechanistic insight on how the CD4 coreceptor impacts TCR-pMHC (dis)engagement. More specifically, our results provide further support (enhanced bond lifetime) for a force-dependent kinetic proofreading model and identify an alternate set of amino acids in the TCR that dominate the TCR-pMHC interaction and could thus impact the design of TCRs for immunotherapy.

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.

Functional Regulation of Aquaporin Dynamics by Lipid Bilayer Composition

With the diversity of lipid-protein interactions, any observed membrane protein dynamics or functions directly depend on the lipid bilayer selection. However, the implications of lipid bilayer choice are seldom considered unless characteristic lipid-protein interactions have been previously reported. Using molecular dynamics simulation, we characterize the effects of membrane embedding on plant aquaporin SoPIP2;1, which has no reported high-affinity lipid interactions. The regulatory impacts of a realistic lipid bilayer, and nine different homogeneous bilayers, on varying SoPIP2;1 dynamics were examined. We demonstrate that SoPIP2;1s structure, thermodynamics, kinetics, and water transport are altered as a function of each membrane construct's ensemble properties. Notably, the realistic bilayer provides stabilization of non-functional SoPIP2;1 metastable states. Hydrophobic mismatch and lipid order parameter calculations further explain how lipid ensemble properties manipulate SoPIP2;1 behavior. Our results illustrate the importance of careful bilayer selection when studying membrane proteins. To this end, we advise cautionary measures when performing membrane protein molecular dynamics simulations.

Coarse-grained modeling of polystyrene-modified CNTs and their interactions with lipid bilayers

In the present work, we describe Martini3 coarse-grained models of polystyrene and carboxyl-terminated polystyrene functionalized carbon nanotubes (CNTs) and investigate their interactions with lipid bilayers with and without cholesterol (CHOL) using molecular dynamics simulations. By changing the polystyrene chain length and grafting density at the end ring of the CNTs at two different nanotube concentrations, we observe the translocation of nanoparticles as well as changes in the lipid bilayer properties. Our results show that all developed models passively diffuse into the membranes without causing any damage to the membrane integrity, although high concentrations of CNTs induce structural and elastic changes in lipid bilayers. In the presence of CHOL, increasing CNT concentration results in decreased rates of CHOL transmembrane motions. On the other hand, CNTs are prone to lipid and polystyrene blockage, which affects their equilibrated configurations, and tilting behavior within the membranes. Hence, we demonstrate that polystyrene-functionalized CNTs are promising drug-carrier agents. However, polystyrene chain length and grafting density are important factors to consider to enhance the efficiency of drug delivery.

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.

Atomistic Insights into Organization of RNA-Loaded Lipid Nanoparticles

RNA-based therapies have shown promise in a wide range of applications, from cancer therapy, treatment of inherited diseases to vaccination. Encapsulation of RNA into ionizable lipid (IL) containing lipid nanoparticles (LNPs) has enabled its safe and targeted delivery. We present here the simulations of the self-assembly process of pH-sensitive RNA-carrying LNPs and their internal morphology. At low pH, the simulations confirm a lipid core encapsulating RNA in the hexagonal phase. Our all-atom and coarse-grained simulations show that an RNA molecule inside an LNP is protected from interactions with ions by being enveloped in the charged ILs. At neutral pH, representing the environment after LNP administration into human tissues, LNPs expelled most of the encapsulated RNA and water and formed separate bulk IL-rich and ordered the helper-lipid-rich phase. Helper lipids arranged themselves to be in contact with RNA or water. The presented models provide atomistic understanding of the LNP structure and open a way to investigate them in silico, varying the LNP composition or interacting with other biostructures aiming at increasing the efficiency of RNA-based medicine.

Enhanced antifouling properties of marine antimicrobial peptides by PEGylation

Covalent immobilisation of antimicrobial peptides (AMPs) on underwater surfaces to combat marine biofouling is of great interest as it is an efficient, broad-spectrum and environmentally friendly strategy. Similar to post-translational modifications of natural proteins, artificial modifications of antimicrobial peptides can introduce important impacts on their properties and functions. The present work revealed the enhanced effect of PEGylation on the antifouling properties of marine antimicrobial peptides (LWFYTMWH) through grafting the modified peptides on aluminium surfaces. PEG was coupled to the peptide by solid-phase peptide synthesis, and the PEGylated peptides were bioconjugated to the aluminium surfaces which was pre-treated by aryldiazonium salts to introduce carboxyl groups. The carboxy group has been activated through the reaction with 1-(3-dimethylaminopropyl)-3-ethylcarbodiimide hydrochloride and N-hydroxysuccinimide. The successful modification was confirmed via FT-IR and XPS. Interestingly, the PEGylated peptides modified surfaces could kill 90.0% Escherichia coli (Gram-negative) and 76.1% Bacillus sp. (Gram-positive), and showed better antifouling performance than the original peptides modified surfaces. Furthermore, molecular dynamics simulations showed PEGylation could enhance the ability of peptides to destroy membrane. The PEGylated peptides inserted into the membrane and induced the change in local curvature of membrane, leading to the rupture of membrane. The presence of PEG changed the antimicrobial peptides into more flexible conformations and the high hydrophilicity of PEG hindered the settlement of bacteria. These might be the two main working mechanisms for the increased antifouling efficiency of PEGylated peptides modified surface. This study provided a feasible modification strategy of antimicrobial peptides to enhance their antifouling properties.

The effect of rhamnolipids on fungal membrane models as described by their interactions with phospholipids and sterols: An in silico study

Introduction: Rhamnolipids (RLs) are secondary metabolites naturally produced by bacteria of the genera Pseudomonas and Burkholderia with biosurfactant properties. A specific interest raised from their potential as biocontrol agents for crop culture protection in regard to direct antifungal and elicitor activities. As for other amphiphilic compounds, a direct interaction with membrane lipids has been suggested as the key feature for the perception and subsequent activity of RLs. Methods: Molecular Dynamics (MD) simulations are used in this work to provide an atomistic description of their interactions with different membranous lipids and focusing on their antifungal properties. Results and discussion: Our results suggest the insertion of RLs into the modelled bilayers just below the plane drawn by lipid phosphate groups, a placement that is effective in promoting significant membrane fluidification of the hydrophobic core. This localization is promoted by the formation of ionic bonds between the carboxylate group of RLs and the amino group of the phosphatidylethanolamine (PE) or phosphatidylserine (PS) headgroups. Moreover, RL acyl chains adhere to the ergosterol structure, forming a significantly higher number of van der Waals contact with respect to what is observed for phospholipid acyl chains. All these interactions might be essential for the membranotropic-driven biological actions of RLs.

A brief history of visualizing membrane systems in molecular dynamics simulations

Understanding lipid dynamics and function, from the level of single, isolated molecules to large assemblies, is more than ever an intensive area of research. The interactions of lipids with other molecules, particularly membrane proteins, are now extensively studied. With advances in the development of force fields for molecular dynamics simulations (MD) and increases in computational resources, the creation of realistic and complex membrane systems is now common. In this perspective, we will review four decades of the history of molecular dynamics simulations applied to membranes and lipids through the prism of molecular graphics.

Scalable transcriptomics analysis with Dask: applications in data science and machine learning

BACKGROUND

Gene expression studies are an important tool in biological and biomedical research. The signal carried in expression profiles helps derive signatures for the prediction, diagnosis and prognosis of different diseases. Data science and specifically machine learning have many applications in gene expression analysis. However, as the dimensionality of genomics datasets grows, scalable solutions become necessary.

METHODS

In this paper we review the main steps and bottlenecks in machine learning pipelines, as well as the main concepts behind scalable data science including those of concurrent and parallel programming. We discuss the benefits of the Dask framework and how it can be integrated with the Python scientific environment to perform data analysis in computational biology and bioinformatics.

RESULTS

This review illustrates the role of Dask for boosting data science applications in different case studies. Detailed documentation and code on these procedures is made available at https://github.com/martaccmoreno/gexp-ml-dask .

CONCLUSION

By showing when and how Dask can be used in transcriptomics analysis, this review will serve as an entry point to help genomic data scientists develop more scalable data analysis procedures.

The Effects of Cholesterol Oxidation on Erythrocyte Plasma Membranes: A Monolayer Study

Cholesterol plays a key role in the molecular and mesoscopic organisation of lipid membranes and it is expected that changes in its molecular structure (e.g., through environmental factors such as oxidative stress) may affect adversely membrane properties and function. In this study, we present evidence that oxidation of cholesterol has significant effects on the mechanical properties, molecular and mesoscopic organisation and lipid-sterol interactions in condensed monolayers composed of the main species found in the inner leaflet of the erythrocyte membrane. Using a combination of experimental methods (static area compressibility, surface dilatational rheology, fluorescence microscopy, and surface sensitive X-ray techniques) and atomistic molecular dynamics simulations, we show that oxidation of cholesterol to 7-ketocholesterol leads to stiffening of the monolayer (under both static and dynamic conditions), significant changes in the monolayer microdomain organisation, disruption in the van der Waals, electrostatic and hydrophobic interactions between the sterol and the other lipid species, and the lipid membrane hydration. Surface sensitive X-ray techniques reveal that, whilst the molecular packing mode is not significantly affected by cholesterol oxidation in these condensed phases, there are subtle changes in membrane thickness and a significant decrease in the coherence length in monolayers containing 7-ketocholesterol.

Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape

The surface assessment via grid evaluation (SuAVE) software was developed to account for the effect of curvature in the calculations of structural properties of chemical interfaces regardless of the chemical composition, asymmetry, and level of atom coarseness. It employs differential geometry techniques, enabling the representation of chemical surfaces as fully differentiable. In this article, we present novel developments of SuAVE to treat closed surfaces and complex cavity shapes. These developments expand the repertoire of curvature-dependent analyses already available in the previous version of SuAVE (e.g., area per lipid, density profiles, membrane thickness, deuterium-order parameters, volume per lipid, and surface curvature angle) to include new functionalities applicable to soft matter (e.g., sphericity, average radius, principal moment of inertia, and roundness) and crystalline porous materials (e.g., pore diameter, internal void volume, total area, and the total void volume of the unit cell structure). SuAVE can accurately handle chemical systems with high and low atom density as demonstrated for two distinct chemical systems: the lipid A vesicle and a set of selected metal–organic frameworks. The SuAVE software v2.0 is fully parallel and benefits from a compiler that supports OpenMP. SuAVE is freely available from https://github.com/SuAVE-Software/source and https://www.biomatsite.net/.