Characterization of Lipid-Protein Interactions and Lipid-Mediated Modulation of Membrane Protein Function through Molecular Simulation

Analysis of protein-protein and protein-membrane interactions by isotope-edited infrared spectroscopy

The objective of this work is to highlight the power of isotope-edited Fourier transform infrared (FTIR) spectroscopy in resolving important problems encountered in biochemistry, biophysics, and biomedical research, focusing on protein-protein and protein membrane interactions that play key roles in practically all life processes. An overview of the effects of isotope substitutions in (bio)molecules on spectral frequencies and intensities is given. Data are presented demonstrating how isotope-labeled proteins and/or lipids can be used to elucidate enzymatic mechanisms, the mode of membrane binding of peripheral proteins, regulation of membrane protein function, protein aggregation, and local and global structural changes in proteins during functional transitions. The use of polarized attenuated total reflection FTIR spectroscopy to identify the spatial orientation and the secondary structure of a membrane-bound interfacial enzyme and the mode of lipid hydrolysis is described. Methods of production of site-directed, segmental, and domain-specific labeling of proteins by the synthetic, semisynthetic, and recombinant strategies, including advanced protein engineering technologies such as nonsense suppression and frameshift quadruplet codons are overviewed.

Impact of aging on the GABAB receptor-mediated connectome

GABA B receptors (GABABRs) are heterodimeric seven-transmembrane receptors that interact with a range of proteins and form large protein complexes on cholesterol-rich membrane microdomains. As the brain ages, membrane cholesterol levels exhibit alterations, although it remains unclear how these changes impact protein-protein interactions and downstream signaling. Herein, we studied the structural bases for the interaction between GABABR and the KCC2 transporter, including their protein expression and distribution, and we compared data between young and aged rat cerebella. Also, we analyzed lipid profiles for both groups, and we used molecular dynamics simulations on three plasma membrane systems with different cholesterol concentrations, to further explore the GABABR-transporter interaction. Based on our results, we report that a significant decrease in GABAB2 subunit expression occurs in the aged rat cerebella. After performing a comparative co-immunoprecipitation analysis, we confirm that GABABR and KCC2 form a protein complex in adult and aged rat cerebella, although their interaction levels are reduced substantially as the cerebellum ages. On the other hand, our lipid analyses reveal a significant increase in cholesterol and sphingomyelin levels of the aged cerebella. Finally, we used the Martini coarse-grained model to conduct molecular dynamics simulations, from which we observed that membrane cholesterol concentrations can dictate whether the GABABR tail domains physically establish G protein-independent contacts with a transporter, and the timing when those associations eventually occur. Taken together, our findings illustrate how age-related alterations in membrane cholesterol levels affect protein-protein interactions, and how they could play a crucial role in regulating GABABR's interactome-mediated signaling.

Significance Statement

This study elucidates age-related changes in cerebellar GABAB receptors (GABABRs), KCC2, and plasma membrane lipids, shedding light on mechanisms underlying neurological decline. Molecular dynamics simulations reveal how membrane lipids influence protein-protein interactions, offering insights into age-related neurodegeneration. The findings underscore the broader impact of cerebellar aging on motor functions, cognition, and emotional processing in the elderly. By elucidating plasma membrane regulation and GABAergic dynamics, this research lays the groundwork for understanding aging-related neurological disorders and inspires further investigation into therapeutic interventions.

Studies of Protein Binding to Biomimetic Membranes Using a Group of Uniform Materials Based on Organic Salts Derived From 8-Anilino-1-naphthalenesulfonic Acid

Tuning the 8-anilino-1-naphthalenesulfonic acid (ANS) structure usually requires harsh conditions and long reaction times, which can result in low yields. Herein, ANS was modified to form an ANS group of uniform materials based on organic salts (GUMBOS), prepared with simple metathesis reactions and distinct cations, namely tetrabutylammonium (N4444), tetrahexylammonium (N6666), and tetrabutylphosphonium (P4444). These ANS-based GUMBOS were investigated as fluorescent probes for membrane binding studies with four proteins having distinct physicochemical properties. Liposomes of 1,2-dimyristoyl-sn-glycero-3-phosphocholine were employed as membrane models as a result of their ability to mimic the structure and chemical composition of cell membranes. Changes in fluorescence intensity were used to monitor protein binding to liposomes, and adsorption data were fitted to a Freundlich-like isotherm. It was determined that [N4444][ANS] and [P4444][ANS] GUMBOS have enhanced optical properties and lipophilicity as compared to parent ANS. As a result, these two GUMBOS were selected for subsequent protein-membrane binding studies. Both [N4444][ANS] and [P4444][ANS] GUMBOS and parent ANS independently reached membrane saturation within the same concentration range. Furthermore, distinct fluorescence responses were observed upon the addition of proteins to each probe, which demonstrates the impact of properties such as lipophilicity on the binding process. The relative maintenance of binding cooperativity and maximum fluorescence intensity suggests that proteins compete with ANS-based probes for the same membrane binding sites. Finally, this GUMBOS-based approach is simple, rapid, and involves relatively small amounts of reagents, making it attractive for high-throughput purposes. These results presented herein can also provide relevant information for designing GUMBOS with ameliorated properties.

Atomistic characterization of β2-glycoprotein I domain V interaction with anionic membranes

BACKGROUND

Interaction of β2-glycoprotein I (β2GPI) with anionic membranes is crucial in antiphospholipid syndrome (APS), implicating the role of its membrane-binding domain, domain V (DV). The mechanism of DV binding to anionic lipids is not fully understood.

OBJECTIVES

This study aimed to elucidate the molecular details of β2GPI DV binding to anionic membranes.

METHODS

We utilized molecular dynamics simulations to investigate the structural basis of anionic lipid recognition by DV. To corroborate the membrane-binding mode identified in the highly mobile membrane mimetic simulations, we conducted additional simulations using a full membrane model.

RESULTS

The study identified critical regions in DV, namely the lysine-rich loop and the hydrophobic loop, which are essential for membrane association via electrostatic and hydrophobic interactions, respectively. A novel lysine pair contributing to membrane binding was also discovered, providing new insights into β2GPI's membrane interaction. Simulations revealed 2 distinct binding modes of DV to the membrane, with mode 1 characterized by the insertion of the hydrophobic loop into the lipid bilayer, suggesting a dominant mechanism for membrane association. This interaction is pivotal for the pathogenesis of APS, as it facilitates the recognition of β2GPI by antiphospholipid antibodies.

CONCLUSION

The study advances our understanding of the molecular interactions between β2GPI's DV and anionic membranes, which are crucial for APS pathogenesis. It highlights the importance of specific regions in DV for membrane binding and reveals a predominant binding mode. These findings have significant implications for APS diagnostics and therapeutics, offering a deeper insight into the molecular basis of the syndrome.

Topological Learning Approach to Characterizing Biological Membranes

Biological membranes play key roles in cellular compartmentalization, structure, and its signaling pathways. At varying temperatures, individual membrane lipids sample from different configurations, a process that frequently leads to higher-order phase behavior and phenomena. Here, we present a persistent homology (PH)-based method for quantifying the structural features of individual and bulk lipids, providing local and contextual information on lipid tail organization. Our method leverages the mathematical machinery of algebraic topology and machine learning to infer temperature-dependent structural information on lipids from static coordinates. To train our model, we generated multiple molecular dynamics trajectories of dipalmitoyl-phosphatidylcholine membranes at varying temperatures. A fingerprint was then constructed for each set of lipid coordinates by PH filtration, in which interaction spheres were grown around the lipid atoms while tracking their intersections. The sphere filtration formed a simplicial complex that captures enduring key topological features of the configuration landscape using homology, yielding persistence data. Following fingerprint extraction for physiologically relevant temperatures, the persistence data were used to train an attention-based neural network for assignment of effective temperature values to selected membrane regions. Our persistence homology-based method captures the local structural effects, via effective temperature, of lipids adjacent to other membrane constituents, e.g., sterols and proteins. This topological learning approach can predict lipid effective temperatures from static coordinates across multiple spatial resolutions. The tool, called MembTDA, can be accessed at https://github.com/hyunp2/Memb-TDA.

Securing LYTAC with Logic-Identification System for Cancer Cell-Selective Membrane Protein Degradation

Lysosome-targeting chimera (LYTAC) links proteins of interest (POIs) with lysosome-targeting receptors (LTRs) to achieve membrane protein degradation, which is becoming a promising therapeutic modality. However, cancer cell-selective membrane protein degradation remains a big challenge considering expressions of POIs in both cancer cells and normal cells, as well as broad tissue distribution of LTRs. Here a logic-identification system is designed, termed Logic-TAC, based on cell membrane-guided DNA calculations to secure LYTAC selectively for cancer cells. Logic-TAC is designed as a duplex DNA structure, with both POI and LTR recognition regions sealed to avoid systematic toxicity during administration. MCF-7 and MCF-10A are chosen as sample cancer cell and normal cell respectively. As input 1 for logic-identification, membrane proteins EpCAM, which is highly expressed by MCF-7 but barely by MCF-10A, reacts with Logic-TAC to expose POI recognition region. As input 2 for logic-identification, Logic-TAC binds to POI, membrane protein MUC1, to expose LTR recognition region. As output, MUC1 is connected to LTR and degraded via lysosome pathway selectively for cancer cell MCF-7 with little side effect on normal cell MCF-10A. The logic-identification system also demonstrated satisfactory in vivo therapeutic results, indicating its promising potential in precise targeted therapy.

Improved Highly Mobile Membrane Mimetic Model for Investigating Protein-Cholesterol Interactions

Cholesterol (CHL) plays an integral role in modulating the function and activity of various mammalian membrane proteins. Due to the slow dynamics of lipids, conventional computational studies of protein-CHL interactions rely on either long-time scale atomistic simulations or coarse-grained approximations to sample the process. A highly mobile membrane mimetic (HMMM) has been developed to enhance lipid diffusion and thus used to facilitate the investigation of lipid interactions with peripheral membrane proteins and, with customized in silico solvents to replace phospholipid tails, with integral membrane proteins. Here, we report an updated HMMM model that is able to include CHL, a nonphospholipid component of the membrane, henceforth called HMMM-CHL. To this end, we had to optimize the effect of the customized solvents on CHL behavior in the membrane. Furthermore, the new solvent is compatible with simulations using force-based switching protocols. In the HMMM-CHL, both improved CHL dynamics and accelerated lipid diffusion are integrated. To test the updated model, we have applied it to the characterization of protein-CHL interactions in two membrane protein systems, the human β2-adrenergic receptor (β2AR) and the mitochondrial voltage-dependent anion channel 1 (VDAC-1). Our HMMM-CHL simulations successfully identified CHL binding sites and captured detailed CHL interactions in excellent consistency with experimental data as well as other simulation results, indicating the utility of the improved model in applications where an enhanced sampling of protein-CHL interactions is desired.

Three-Dimensional Interaction Homology: Deconstructing Residue-Residue and Residue-Lipid Interactions in Membrane Proteins

A method is described to deconstruct the network of hydropathic interactions within and between a protein's sidechain and its environment into residue-based three-dimensional maps. These maps encode favorable and unfavorable hydrophobic and polar interactions, in terms of spatial positions for optimal interactions, relative interaction strength, as well as character. In addition, these maps are backbone angle-dependent. After map calculation and clustering, a finite number of unique residue sidechain interaction maps exist for each backbone conformation, with the number related to the residue's size and interaction complexity. Structures for soluble proteins (~749,000 residues) and membrane proteins (~387,000 residues) were analyzed, with the latter group being subdivided into three subsets related to the residue's position in the membrane protein: soluble domain, core-facing transmembrane domain, and lipid-facing transmembrane domain. This work suggests that maps representing residue types and their backbone conformation can be reassembled to optimize the medium-to-high resolution details of a protein structure. In particular, the information encoded in maps constructed from the lipid-facing transmembrane residues appears to paint a clear picture of the protein-lipid interactions that are difficult to obtain experimentally.

Gel-assisted mass spectrometry imaging enables sub-micrometer spatial lipidomics

A technique capable of label-free detection, mass spectrometry imaging (MSI) is a powerful tool for spatial investigation of native biomolecules in intact specimens. However, MSI has often been precluded from single-cell applications due to the spatial resolution limit set forth by the physical and instrumental constraints of the method. By taking advantage of the reversible interaction between the analytes and a superabsorbent hydrogel, we have developed a sample preparation and imaging workflow named Gel-Assisted Mass Spectrometry Imaging (GAMSI) to overcome the spatial resolution limits of modern mass spectrometers. With GAMSI, we show that the spatial resolution of MALDI-MSI can be enhanced ~3-6-fold to the sub-micrometer level without changing the existing mass spectrometry hardware or analysis pipeline. This approach will vastly enhance the accessibility of MSI-based spatial analysis at the cellular scale.

Epoxiconazole altered hepatic metabolism in adult zebrafish based on transcriptomic analysis

Epoxiconazole (EPX) is a triazole fungicide, which has been widely used in pest control of cereal crops. However, its extensive use has led to concerning levels of residue in water bodies, posing substantial risks to aquatic life. In this study, we characterized the toxicological effects of EPX on 6-month-old male and female zebrafish at 70 and 700 μg/L, respectively. The results revealed that EPX exposure markedly increased both body length and weight in zebrafish of both sexes, consequently elevating their condition factor. Besides, EPX exposure resulted in notable alterations in hepatic histopathology. These changes included loosened hepatocyte structure, ballooning degeneration, nucleolysis, and disappearance of cell line, with male zebrafish exhibiting more severe damage. High concentration of EPX also significantly increased hepatic lipid accumulation in male zebrafish, as well as increased hepatic triglyceride (TG) levels. Correspondingly, there was a notable alteration in the transcription of genes including cyp51, hmgcr, and PPAR-γ, which associated with cholesterol and lipid metabolism. Interestingly, with the hepatic transcriptomic analysis, high concentration of EPX produced 195 upregulated and 107 downregulated differential expression genes. Both KEGG and GO analyses identified significant enrichment of these genes in lipid and amino acid metabolism pathways. Notably, some key genes involved in the steroid synthesis pathway were marked upregulated. In addition, molecular docking study confirmed that EPX could bind CYP51 protein well (△G = -7.7 kcal/mol). Taken together, these findings demonstrated the multiple toxic effects of EPX on adult zebrafish.

Subtractive Proteomics and Reverse-Vaccinology Approaches for Novel Drug Target Identification and Chimeric Vaccine Development against Bartonella henselae Strain Houston-1

Bartonella henselae is a Gram-negative bacterium causing a variety of clinical symptoms, ranging from cat-scratch disease to severe systemic infections, and it is primarily transmitted by infected fleas. Its status as an emerging zoonotic pathogen and its capacity to persist within host erythrocytes and endothelial cells emphasize its clinical significance. Despite progress in understanding its pathogenesis, limited knowledge exists about the virulence factors and regulatory mechanisms specific to the B. henselae strain Houston-1. Exploring these aspects is crucial for targeted therapeutic strategies against this versatile pathogen. Using reverse-vaccinology-based subtractive proteomics, this research aimed to identify the most antigenic proteins for formulating a multi-epitope vaccine against the B. henselae strain Houston-1. One crucial virulent and antigenic protein, the PAS domain-containing sensor histidine kinase protein, was identified. Subsequently, the identification of B-cell and T-cell epitopes for the specified protein was carried out and the evaluated epitopes were checked for their antigenicity, allergenicity, solubility, MHC binding capability, and toxicity. The filtered epitopes were merged using linkers and an adjuvant to create a multi-epitope vaccine construct. The structure was then refined, with 92.3% of amino acids falling within the allowed regions. Docking of the human receptor (TLR4) with the vaccine construct was performed and demonstrated a binding energy of -1047.2 Kcal/mol with more interactions. Molecular dynamic simulations confirmed the stability of this docked complex, emphasizing the conformation and interactions between the molecules. Further experimental validation is necessary to evaluate its effectiveness against B. henselae.

Lipid-dependent conformational dynamics of bacterial ATP-binding cassette transporter Sav1866

Sav1866, a bacterial ATP-binding cassette (ABC) exporter, plays a crucial role in cellular processes by facilitating the efflux of a diverse range of substrates, including drugs, chemotherapeutic agents, peptides, and lipids. This efflux activity significantly impacts the effectiveness of various therapies against bacterial infections. In our recent investigation, we focused on understanding the conformational dynamics of Sav1866 within different lipid environments. Specifically, we explored its behavior in environments composed of DMPC and POPE lipids, which exhibit crucial distinctions not only in their headgroup polarity but also in the length and saturation of their hydrophobic tails. Our extensive set of equilibrium microsecond-level all-atom molecular dynamics (MD) simulations revealed significant distinctions in transporter behavior influenced by these lipid compositions. We observed a rapid transition to an occluded-inward-facing (IF-occ) conformation in POPE environments, contrasting with a channel-like behavior in DMPC environments, deviating from the expected alternating access mechanism (AAM). These findings underscore the significant impact of lipid compositions on ABC transporter function, offering new perspectives on membrane transport mechanisms.

Comprehensive Characterization of LAT1 Cholesterol-Binding Sites

The human L-type amino acid transporter 1 (LAT1; SLC7A5), is an amino acid exchanger protein, primarily found in the blood-brain barrier, placenta, and testis, where it plays a key role in amino acid homeostasis. Cholesterol is an essential lipid that has been highlighted to play a role in regulating the activity of membrane transporters, such as LAT1, yet little is known about the molecular mechanisms driving this phenomenon. Here we perform a comprehensive computational analysis to investigate cholesterol's role in LAT1 structure and function, focusing on four cholesterol-binding sites (CHOL1-4) identified in a recent LAT1-apo inward-open conformation cryo-EM structure. Through a series of independent molecular dynamics (MD) simulations, molecular docking, MM/GBSA free energy calculations, and other analysis tools, we explored the interactions between LAT1 and cholesterol. Our findings suggest that CHOL3 forms the most stable and favorable interactions with LAT1. Principal component analysis (PCA) and center of mass (COM) distance assessments show that CHOL3 binding stabilizes the inward-open state of LAT1 by preserving the spatial arrangement of the hash and bundle domains. Additionally, we propose an alternative cholesterol-binding site for originally assigned CHOL1. Overall, this study improves the understanding of cholesterol's modulatory effect on LAT1 and proposes candidate sites for the discovery of future allosteric ligands with rational design.

Dynamic framework for large-scale modeling of membranes and peripheral proteins

In this chapter, we present a novel computational framework to study the dynamic behavior of extensive membrane systems, potentially in interaction with peripheral proteins, as an alternative to conventional simulation methods. The framework effectively describes the complex dynamics in protein-membrane systems in a mesoscopic particle-based setup. Furthermore, leveraging the hydrodynamic coupling between the membrane and its surrounding solvent, the coarse-grained model grounds its dynamics in macroscopic kinetic properties such as viscosity and diffusion coefficients, marrying the advantages of continuum- and particle-based approaches. We introduce the theoretical background and the parameter-space optimization method in a step-by-step fashion, present the hydrodynamic coupling method in detail, and demonstrate the application of the model at each stage through illuminating examples. We believe this modeling framework to hold great potential for simulating membrane and protein systems at biological spatiotemporal scales, and offer substantial flexibility for further development and parametrization.

Capture of endogenous lipids in peptidiscs and effect on protein stability and activity

Compared to protein-protein and protein-nucleic acid interactions, our knowledge of protein-lipid interactions remains limited. This is primarily due to the inherent insolubility of membrane proteins (MPs) in aqueous solution. The traditional use of detergents to overcome the solubility barrier destabilizes MPs and strips away certain lipids that are increasingly recognized as crucial for protein function. Recently, membrane mimetics have been developed to circumvent the limitations. In this study, using the peptidisc, we find that MPs in different lipid states can be isolated based on protein purification and reconstitution methods, leading to observable effects on MP activity and stability. Peptidisc also enables re-incorporating specific lipids to fine-tune the protein microenvironment and assess the impact on downstream protein associations. This study offers a first look at the illusive protein-lipid interaction specificity, laying the path for a systematic evaluation of lipid identity and contributions to membrane protein function.

Electron videography of a lipid-protein tango

Biological phenomena, from enzymatic catalysis to synaptic transmission, originate in the structural transformations of biomolecules and biomolecular assemblies in liquid water. However, directly imaging these nanoscopic dynamics without probes or labels has been a fundamental methodological challenge. Here, we developed an approach for "electron videography"-combining liquid phase electron microscopy with molecular modeling-with which we filmed the nanoscale structural fluctuations of individual, suspended, and unlabeled membrane protein nanodiscs in liquid. Systematic comparisons with biochemical data and simulation indicate the graphene encapsulation involved can afford sufficiently reduced effects of the illuminating electron beam for these observations to yield quantitative fingerprints of nanoscale lipid-protein interactions. Our results suggest that lipid-protein interactions delineate dynamically modified membrane domains across unexpectedly long ranges. Moreover, they contribute to the molecular mechanics of the nanodisc as a whole in a manner specific to the protein within. Overall, this work illustrates an experimental approach to film, quantify, and understand biomolecular dynamics at the nanometer scale.

Fabrication of High-Negatively Charged Bicelle-Mediated Supported Lipid Bilayer

Supported lipid bilayers (SLBs), two-dimensional lipid films formed on a solid-supporting substrate, serve as models for biomembranes and exhibit remarkable potential in chemistry, biology, and medicine. However, preparing SLBs with highly negatively charged contents on the negatively charged surface by overcoming electrostatic repulsion remains a challenge. Here, a creative bicelle-mediated and divalent cation-free SLB preparation method with the assistance of phosphate-buffered saline (PBS) solution was proposed, which can form the SLBs containing 50% DOPS or 30% CL on the silica surface monitored by a quartz crystal microbalance with dissipation (QCM-D). Results of molecular dynamics (MD) simulation indicate that electrostatic repulsion can be overcome by the increased number of hydrogen bonds caused by the adsorption of dihydrogen phosphate ions onto the headgroups of lipids. In addition, the negatively charged SLB formation was identified to be a three-step kinetic process, which differs from a two-step mechanism in the case of amphoteric SLB. The extra kinetic step can be attributed to the reduction in the number of intermolecular hydrogen bonds and the ordering of water molecules in the hydration layer. This investigation resolves the challenge of fabricating SLB over negatively charged surfaces and offers a fresh perspective on the SLB assembly methodology.

Configurational Sampling of All-Atom Solvated Membranes Using Hybrid Nonequilibrium Molecular Dynamics Monte Carlo Simulations

All-atom simulations are a powerful approach to study the structure and dynamics of biological membranes. However, sampling the atomic configurations of inhomogeneous membranes can be challenging due to the slow lateral diffusion of the various constituents. To address this issue, a hybrid nonequilibrium molecular dynamics Monte Carlo (neMD/MC) simulation method is proposed in which randomly chosen lipid molecules are swapped to generate configurations that are subsequently accepted or rejected according to a Metropolis criterion based on the alchemical work for the attempted swap calculated via a short trajectory. A dual-topology framework constraining the common atoms of the exchanging molecules yields a good acceptance probability using switching trajectories as short as 10 ps. The performance of the hybrid neMD/MC algorithm and its ability to sample the distribution of lipids near a transmembrane helix carrying a net charge are illustrated for a binary mixture of charged and zwitterionic 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.

Atomistic Characterization of Beta-2-Glycoprotein I Domain V Interaction with Anionic Membranes

Background

Interaction of beta-2-glycoprotein I ( β 2 GPI) with anionic membranes is crucial in antiphospholipid syndrome (APS), implicating the role of it's membrane bind-ing domain, Domain V (DV). The mechanism of DV binding to anionic lipids is not fully understood.

Objectives

This study aims to elucidate the mechanism by which DV of β 2 GPI binds to anionic membranes.

Methods

We utilized molecular dynamics (MD) simulations to investigate the struc-tural basis of anionic lipid recognition by DV. To corroborate the membrane-binding mode identified in the HMMM simulations, we conducted additional simulations using a full mem-brane model.

Results

The study identified critical regions in DV, namely the lysine-rich loop and the hydrophobic loop, essential for membrane association via electrostatic and hydrophobic interactions, respectively. A novel lysine pair contributing to membrane binding was also discovered, providing new insights into β 2 GPI's membrane interaction. Simulations revealed two distinct binding modes of DV to the membrane, with mode 1 characterized by the insertion of the hydrophobic loop into the lipid bilayer, suggesting a dominant mechanism for membrane association. This interaction is pivotal for the pathogenesis of APS, as it facilitates the recognition of β 2 GPI by antiphospholipid antibodies.

Conclusion

The study advances our understanding of the molecular interactions be-tween β 2 GPI's DV and anionic membranes, crucial for APS pathogenesis. It highlights the importance of specific regions in DV for membrane binding and reveals a predominant bind-ing mode. These findings have significant implications for APS diagnostics and therapeutics, offering a deeper insight into the molecular basis of the syndrome.

Rendering protein structures inside cells at the atomic level with Unreal Engine

While the recent development of cryogenic electron tomography (CryoET) makes it possible to identify various macromolecules inside cells and determine their structure at near-atomic resolution, it remains challenging to visualize the complex cellular environment at the atomic level. One of the main hurdles in cell visualization is to render the millions of molecules in real time computationally. Here, using a video game engine, we demonstrate the capability of rendering massive biological macromolecules at the atomic level within their native environment. To facilitate the visualization, we also provide tools that help the interactive navigation inside the cells, as well as software that converts protein structures identified using CryoET to a scene that can be explored with the game engine.

Natural Products-Based Inhaled Formulations for Treating Pulmonary Diseases

Given the unique physiological and pathological characteristics of the lung, the direct, inhalable route is more conducive to pulmonary drug delivery and disease control than traditional systemic drug delivery, significantly circumventing drug loss, off-target effects, systemic and organ toxicity, etc., and is widely regarded as the preferred regimen for pulmonary drug delivery. However, very few lung diseases are currently treated with the preferred inhaled formulations, such as asthma, chronic obstructive pulmonary disease and pulmonary hypertension. And there is a lack of appropriate inhaled formulations for other critical lung diseases, such as lung cancer and pulmonary fibrosis, due to the fact that the physicochemical properties of the drugs and their pharmacokinetic profiles do not match the physiology of the lung, and conventional inhalation devices are unable to deliver them to the specific parts of the lung. Phytochemicals of natural origin, due to their wide availability and clear safety profile, hold great promise for the preparation of inhalable formulations to improve the current dilemma in the treatment of lung diseases. In particular, the preparation of inhalable formulations based on nano- and microparticulate carriers for drug delivery to deep lung tissues, which overcome the shortcomings of conventional inhalation therapies while targeting the drug activity directly to a specific part of the lung, may be the best approach to change the current dilemma of lung disease treatment. In this review, we discuss recent advances in nano- and micron-carrier-based inhalation formulations for the delivery of natural products for the treatment of pulmonary diseases, which may represent an opportunity for practical clinical translation of natural products.

Studying Conformational Properties of Transmembrane Domain of KCNE3 in a Lipid Bilayer Membrane Using Molecular Dynamics Simulations

KCNE3 is a single-pass integral membrane protein that regulates numerous voltage-gated potassium channel functions such as KCNQ1. Previous solution NMR studies suggested a moderate degree of curved α-helical structure in the transmembrane domain (TMD) of KCNE3 in lyso-myristoylphosphatidylcholine (LMPC) micelles and isotropic bicelles with the residues T71, S74 and G78 situated along the concave face of the curved helix. During the interaction of KCNE3 and KCNQ1, KCNE3 pushes its transmembrane domain against KCNQ1 to lock the voltage sensor in its depolarized conformation. A cryo-EM study of KCNE3 complexed with KCNQ1 in nanodiscs suggested a deviation of the KCNE3 structure from its independent structure in isotropic bicelles. Despite the biological significance of KCNE3 TMD, the conformational properties of KCNE3 are poorly understood. Here, all atom molecular dynamics (MD) simulations were utilized to investigate the conformational dynamics of the transmembrane domain of KCNE3 in a lipid bilayer containing a mixture of POPC and POPG lipids (3:1). Further, the effect of the interaction impairing mutations (V72A, I76A and F68A) on the conformational properties of the KCNE3 TMD in lipid bilayers was investigated. Our MD simulation results suggest that the KCNE3 TMD adopts a nearly linear α helical structural conformation in POPC-POPG lipid bilayers. Additionally, the results showed no significant change in the nearly linear α-helical conformation of KCNE3 TMD in the presence of interaction impairing mutations within the sampled time frame. The KCNE3 TMD is more stable with lower flexibility in comparison to the N-terminal and C-terminal of KCNE3 in lipid bilayers. The overall conformational flexibility of KCNE3 also varies in the presence of the interaction-impairing mutations. The MD simulation data further suggest that the membrane bilayer width is similar for wild-type KCNE3 and KCNE3 containing mutations. The Z-distance measurement data revealed that the TMD residue site A69 is close to the lipid bilayer center, and residue sites S57 and S82 are close to the surfaces of the lipid bilayer membrane for wild-type KCNE3 and KCNE3 containing interaction-impairing mutations. These results agree with earlier KCNE3 biophysical studies. The results of these MD simulations will provide complementary data to the experimental outcomes of KCNE3 to help understand its conformational dynamic properties in a more native lipid bilayer environment.

Anillin-related Mid1 as an adaptive and multimodal contractile ring anchoring protein: A simulation study

Cytokinesis of animal and fungi cells depends crucially on the anillin scaffold proteins. Fission yeast anillin-related Mid1 anchors cytokinetic ring precursor nodes to the membrane. However, it is unclear if both of its Pleckstrin Homology (PH) and C2 C-terminal domains bind to the membrane as monomers or dimers, and if one domain plays a dominant role. We studied Mid1 membrane binding with all-atom molecular dynamics near a membrane with yeast-like lipid composition. In simulations with the full C terminal region started away from the membrane, Mid1 binds through the disordered L3 loop of C2 in a vertical orientation, with the PH away from the membrane. However, a configuration with both C2 and PH initially bound to the membrane remains associated with the membrane. Simulations of C2-PH dimers show extensive asymmetric membrane contacts. These multiple modes of binding may reflect Mid1's multiple interactions with membranes, node proteins, and ability to sustain mechanical forces.

Tunable Multivalent Aptamer-Based DNA Nanostructures To Regulate Multiheteroreceptor-Mediated Tumor Recognition

Precise mapping and regulation of cell surface receptors hold immense significance in disease treatment, such as cancer, infection, and neurodisorders, but also face enormous challenges. In this study, we designed a series of adjustable multivalent aptamer-based DNA nanostructures to precisely control their interaction with receptors in tumor cells. By profiling surface receptors on 12 cell lines using 10 different aptamers, we generated a heatmap that accurately distinguished between various tumor types based on multiple markers. We then incorporated these aptamers onto DNA origami structures to regulate receptor recognition, with patch-like structures demonstrating a tendency to be trapped on the cell surface and with tube-like structures showing a preference for internalization. Through precise control of aptamer species, valence, and geometric patterns, we found that multiheteroreceptor-mediated recognition not only favored the specific binding of nanostructures to tumor cells but also greatly enhanced intracellular uptake by promoting clathrin-dependent endocytosis. Specifically, we achieved over 5-fold uptake in different tumor cells versus normal cells using tube-like structures modified with different diheteroaptamer pairs, facilitating targeted drug delivery. Moreover, patch-like structures with triheteroaptamers guided specific interactions between macrophages and tumor cells, leading to effective immune clearance. This programmable multivalent system allows for the precise regulation of cell recognition using multiple parameters, demonstrating great potential for personalized tumor treatment.

Estimating the Cholesterol Affinity of Integral Membrane Proteins from Experimental Data

The cholesterol affinities of many integral plasma membrane proteins have been estimated by molecular computation. However, these values lack experimental confirmation. We therefore developed a simple mathematical model to extract sterol affinity constants and stoichiometries from published isotherms for the dependence of the activity of such proteins on the membrane cholesterol concentration. The binding curves for these proteins are sigmoidal, with strongly lagged thresholds attributable to competition for the cholesterol by bilayer phospholipids. The model provided isotherms that matched the experimental data using published values for the sterol association constants and stoichiometries of the phospholipids. Three oligomeric transporters were found to bind cholesterol without cooperativity, with dimensionless association constants of 35 for Kir3.4* and 100 for both Kir2 and a GAT transporter. (The corresponding ΔG° values were -8.8, -11.4, and -11.4 kJ/mol, respectively). These association constants are significantly lower than those for the phospholipids, which range from ∼100 to 6000. The BK channel, the nicotinic acetylcholine receptor, and the M192I mutant of Kir3.4* appear to bind multiple cholesterol molecules cooperatively (n = 2 or 4), with subunit affinities of 563, 950, and 700, respectively. The model predicts that the three less avid transporters are approximately half-saturated in their native plasma membranes; hence, they are sensitive to variations in cholesterol in vivo. The more avid proteins would be nearly saturated in vivo. The method can be applied to any integral protein or other ligands in any bilayer for which there are reasonable estimates of the sterol affinities and stoichiometries of the phospholipids.

Lipid and cholesterols modulate the dynamics of SARS-CoV-2 viral ion channel ORF3a and its pathogenic variants

SARS-CoV-2 accessory protein, ORF3a is a putative ion channel which immensely contributes to viral pathogenicity by modulating host immune responses and virus-host interactions. Relatively high expression of ORF3a in diseased individuals and implication with inflammasome activation, apoptosis and autophagy inhibition, ratifies as an effective target for developing vaccines and therapeutics. Herein, we present the elusive dynamics of ORF3a-dimeric state using all-atoms molecular dynamics (MD) simulations at μ-seconds scale in a heterogeneous lipid-mimetic system in multiple replicates. Additionally, we also explore the effect of non-synonymous pathogenic mutations on ORF3a ion channel activity and viral pathogenicity in different SARS-CoV-2 variants using various structure-based protein stability (ΔΔG) tools and computational saturation mutagenesis. Our study ascertains the role of phosphatidylcholines and cholesterol in modulating the structure of ORF3a, which perturbs the size and flexibility of the polar cavity that allows permeation of large cations. Discrete trend in ion channel pore radius and area per lipid arises the premise that presence of lipids might also affect the overall conformation of ORF3a. MD structural-ensembles, in some replicates rationalize the crucial role of TM2 in maintaining the native structure of ORF3a. We also infer that loss of structural stability primarily grounds for pathogenicity in more than half of the pathogenic variants of ORF3a. Overall, the effect of mutation on alteration of ion permeability of ORF3a, proposed in this study brings mechanistic insights into variant consequences on viral membrane proteins of SARS-CoV-2, which can be utilized for the development of novel therapeutics to treat COVID-19 and other coronavirus diseases.

Exploring the role of microbial proteins in controlling environmental pollutants based on molecular simulation

Molecular simulation has been widely used to study microbial proteins' structural composition and dynamic properties, such as volatility, flexibility, and stability at the microscopic scale. Herein, this review describes the key elements of molecular docking and molecular dynamics (MD) simulations in molecular simulation; reviews the techniques combined with molecular simulation, such as crystallography, spectroscopy, molecular biology, and machine learning, to validate simulation results and bridge information gaps in the structure, microenvironmental changes, expression mechanisms, and intensity quantification; illustrates the application of molecular simulation, in characterizing the molecular mechanisms of interaction of microbial proteins with four different types of contaminants, namely heavy metals (HMs), pesticides, dyes and emerging contaminants (ECs). Finally, the review outlines the important role of molecular simulations in the study of microbial proteins for controlling environmental contamination and provides ideas for the application of molecular simulation in screening microbial proteins and incorporating targeted mutagenesis to obtain more effective contaminant control proteins.

Atomistic Insights into the Effect of Functional Groups on the Adsorption of Water by Activated Carbon for Heat Energy Storage

Adsorption heat storage holds great promise for solar energy applications. The development of new adsorbent materials is currently the research focus in this area. The present work designs several activated carbon models with different functional groups, including -OH, -NH2, -COOH, and -SO3H, and explores the influence of functional groups' categories and numbers on the water adsorption capacity of the activated carbon using the GCMC method. The adsorption mechanism between functional groups and water molecules is analyzed using density functional theory. The results show that the functional groups could significantly improve the water adsorption capacity of activated carbon due to the hydrogen bond between functional groups and water molecules. In the scope of this paper, under low pressure, the activated carbon with -SO3H exhibits the best adsorption capacity, followed by the activated carbon with -COOH. Under low and medium pressure, increasing the number of -SO3H functional groups could increase the water adsorption capacity; however, when the pressure is high, increasing the functional group numbers might decrease the water adsorption capacity. As the temperature increases, the water adsorption capacity of activated carbons decreases, and the activated carbon with -SO3H is proven to have excellent application prospects in heat energy storage.

Improved Protein Model in SPICA Force Field

The previous version of the SPICA coarse-grained (CG) force field (FF) protein model focused primarily on membrane proteins and successfully reproduced the dimerization free energies of several transmembrane helices and the stable structures of various membrane protein assemblies. However, that model had limited accuracy when applied to other proteins, such as intrinsically disordered proteins (IDPs) and peripheral proteins, because the dimensions of the IDPs in an aqueous solution were too compact, and protein binding on the lipid membrane surface was overstabilized. To improve the accuracy of the SPICA FF model for the simulation of such systems, in this study, we introduce protein secondary structure-dependent nonbonded interaction parameters to the backbone segments and reoptimize almost all nonbonded parameters for amino acids. The improved FF proposed here successfully reproduces the radii of gyration of various IDPs, the binding sensitivity of several peripheral membrane proteins, and the dimerization free energies of several transmembrane helices. The new model also shows improved agreement with experiments on the free energy of peptide association in water. In addition, an extensive library of nonbonded interactions between proteins and lipids, including various glycerophospholipids, sphingolipids, and cholesterol, allows the study of specific interactions between lipids and peripheral and transmembrane proteins. Hence, the new SPICA FF (version 2) proposed herein is applicable with high accuracy for simulating a wide range of protein systems.

Topological Learning Approach to Characterizing Biological Membranes

Biological membranes play key roles in cellular compartmentalization, structure, and its signaling pathways. At varying temperatures, individual membrane lipids sample from different configurations, a process that frequently leads to higher-order phase behavior and phenomena. Here we present a persistent homology-based method for quantifying the structural features of individual and bulk lipids, providing local and contextual information on lipid tail organization. Our method leverages the mathematical machinery of algebraic topology and machine learning to infer temperature-dependent structural information of lipids from static coordinates. To train our model, we generated multiple molecular dynamics trajectories of DPPC membranes at varying temperatures. A fingerprint was then constructed for each set of lipid coordinates by a persistent homology filtration, in which interactions spheres were grown around the lipid atoms while tracking their intersections. The sphere filtration formed a simplicial complex that captures enduring key topological features of the configuration landscape, using homology, yielding persistence data. Following fingerprint extraction for physiologically relevant temperatures, the persistence data were used to train an attention-based neural network for assignment of effective temperature values to selected membrane regions. Our persistence homology-based method captures the local structural effects, via effective temperature, of lipids adjacent to other membrane constituents, e.g. sterols and proteins. This topological learning approach can predict lipid effective temperatures from static coordinates across multiple spatial resolutions. The tool, called MembTDA, can be accessed at https://github.com/hyunp2/Memb-TDA.

Myr-Arf1 conformational flexibility at the membrane surface sheds light on the interactions with ArfGAP ASAP1

ADP-ribosylation factor 1 (Arf1) interacts with multiple cellular partners and membranes to regulate intracellular traffic, organelle structure and actin dynamics. Defining the dynamic conformational landscape of Arf1 in its active form, when bound to the membrane, is of high functional relevance and key to understanding how Arf1 can alter diverse cellular processes. Through concerted application of nuclear magnetic resonance (NMR), neutron reflectometry (NR) and molecular dynamics (MD) simulations, we show that, while Arf1 is anchored to the membrane through its N-terminal myristoylated amphipathic helix, the G domain explores a large conformational space, existing in a dynamic equilibrium between membrane-associated and membrane-distal conformations. These configurational dynamics expose different interfaces for interaction with effectors. Interaction with the Pleckstrin homology domain of ASAP1, an Arf-GTPase activating protein (ArfGAP), restricts motions of the G domain to lock it in what seems to be a conformation exposing functionally relevant regions.

Top-Down Machine Learning of Coarse-Grained Protein Force Fields

Developing accurate and efficient coarse-grained representations of proteins is crucial for understanding their folding, function, and interactions over extended time scales. Our methodology involves simulating proteins with molecular dynamics and utilizing the resulting trajectories to train a neural network potential through differentiable trajectory reweighting. Remarkably, this method requires only the native conformation of proteins, eliminating the need for labeled data derived from extensive simulations or memory-intensive end-to-end differentiable simulations. Once trained, the model can be employed to run parallel molecular dynamics simulations and sample folding events for proteins both within and beyond the training distribution, showcasing its extrapolation capabilities. By applying Markov state models, native-like conformations of the simulated proteins can be predicted from the coarse-grained simulations. Owing to its theoretical transferability and ability to use solely experimental static structures as training data, we anticipate that this approach will prove advantageous for developing new protein force fields and further advancing the study of protein dynamics, folding, and interactions.

How Does pH Affect the Adsorption of Human Serum Protein in the Presence of Hydrophobic and Hydrophilic Nanoparticles at Air-Water and Lipid-Water Interfaces?

This study investigates interaction between hydrophilic (11-mercaptoundecanoic acid (MUA)) and hydrophobic (1-undecanethiol (UDT)) gold nanoparticles (GNPs) with human serum albumin (HSA) protein on air-water and lipid-water interfaces at pH 3 and 7. Vibrational sum frequency generation (VSFG) spectroscopy is used to analyze changes in the intensity of interfacial water molecules and the C-H group of the protein. At the air-water interface, the hydrophobic interaction between the HSA protein and hydrophobic GNPs at pH 3 leads to their accumulation at the interface, resulting in an increased C-H intensity of the protein with a slight decrease in water intensity. Whereas, at pH 7, where the negative charge of the protein results in the reduced surface activity of the HSA compared to pH 3, the interaction between alkyl chain of the hydrophobic GNPs and alkyl group of the protein results in the adsorption of the protein-capped GNPs at the interface. This leads to an increased intensity of the C-H group of protein and water molecules. However, negatively charged hydrophilic GNPs do not induce significant changes in the interfacial water structure or the C-H group of the protein due to the electrostatic force of repulsion with the negatively charged HSA at pH 7. In contrast, at the lipid-water interface, both hydrophobic and hydrophilic GNPs interact with HSA protein, causing disordering of interfacial water molecules at pH 3 and ordering at pH 7. Interestingly, similar behavior of the protein with both types of GNPs results in comparable ordering/disordering at the interface depending on the pH of solution. Furthermore, the VSFG results obtained with the deuterated lipid suggest that changes in ordering and disorder occur due to increased protein adsorption in the presence of GNPs, causing alterations in the membrane structure. These findings give a better understanding of the mechanisms that govern protein-nanoparticle interaction and their consequential effects on the structure, function, and behavior of molecules at the biological membrane interface, which is crucial for developing safe and effective nanoparticle-based therapeutics.

Selective expression of light-harvesting complexes alters phospholipid composition in the intracytoplasmic membrane and core complex of purple phototrophic bacteria

Phospholipid-protein interactions play important roles in regulating the function and morphology of photosynthetic membranes in purple phototrophic bacteria. Here, we characterize the phospholipid composition of intracytoplasmic membrane (ICM) from Rhodobacter (Rba.) sphaeroides that has been genetically altered to selectively express light-harvesting (LH) complexes. In the mutant strain (DP2) that lacks a peripheral light-harvesting (LH2) complex, the phospholipid composition was significantly different from that of the wild-type strain; strain DP2 showed a marked decrease in phosphatidylglycerol (PG) and large increases in cardiolipin (CL) and phosphatidylcholine (PC) indicating preferential interactions between the complexes and specific phospholipids. Substitution of the core light-harvesting (LH1) complex of Rba. sphaeroides strain DP2 with that from the purple sulfur bacterium Thermochromatium tepidum further altered the phospholipid composition, with substantial increases in PG and PE and decreases in CL and PC, indicating that the phospholipids incorporated into the ICM depend on the nature of the LH1 complex expressed. Purified LH1-reaction center core complexes (LH1-RC) from the selectively expressing strains also contained different phospholipid compositions than did core complexes from their corresponding wild-type strains, suggesting different patterns of phospholipid association between the selectively expressed LH1-RC complexes and those purified from native strains. Effects of carotenoids on the phospholipid composition were also investigated using carotenoid-suppressed cells and carotenoid-deficient species. The findings are discussed in relation to ICM morphology and specific LH complex-phospholipid interactions.

Martini 3 Coarse-Grained Force Field for Cholesterol

Cholesterol plays a crucial role in biomembranes by regulating various properties, such as fluidity, rigidity, permeability, and organization of lipid bilayers. The latest version of the Martini model, Martini 3, offers significant improvements in interaction balance, molecular packing, and inclusion of new bead types and sizes. However, the release of the new model resulted in the need to reparameterize many core molecules, including cholesterol. Here, we describe the development and validation of a Martini 3 cholesterol model, addressing issues related to its bonded setup, shape, volume, and hydrophobicity. The proposed model mitigates some limitations of its Martini 2 predecessor while maintaining or improving the overall behavior.

Lactadherin's Multistate Binding Predicts Stable Membrane-Bound Conformations of Factors V and VIII's C Domains

Protein binding to negatively charged lipids is essential for maintaining numerous vital cellular processes where its dysfunction can lead to various diseases. One such protein that plays a crucial role in this process is lactadherin, which competes with coagulation factors for membrane binding sites to regulate blood clotting. Despite identifying key binding regions of these proteins through structural and biochemical studies, models incorporating membrane dynamics are still lacking. In this study, we report on the multimodal binding of lactadherin and use it to gain insight into the binding mechanisms of its C domain homologs, factor V and factor VIII. Molecular dynamics simulations enhanced with the highly mobile mimetic model enabled the determination of lactadherin's multimodal binding on membranes that revealed critical interacting residues consistent with prior NMR and mutagenesis data. The binding occurred primarily via two dynamic structural ensembles: an inserted state and an unreported, highly conserved side-lying state driven by a cationic patch. We utilized these findings to analyze the membrane binding domains of coagulation factors V and VIII and identified their preferred membrane-bound conformations. Specifically, factor V's C domains maintained an inserted state, while factor VIII preferred a tilted, side-lying state that permitted antibody binding. Insight into lactadherin's atomistically resolved membrane interactions from a multistate perspective can guide new therapeutic opportunities in treating diseases related to blood coagulation.

The Important Role of Transporter Structures in Drug Disposition, Efficacy, and Toxicity

The ATP-binding cassette (ABC) and solute carrier (SLC) transporters are critical determinants of drug disposition, clinical efficacy, and toxicity as they specifically mediate the influx and efflux of various substrates and drugs. ABC transporters can modulate the pharmacokinetics of many drugs via mediating the translocation of drugs across biologic membranes. SLC transporters are important drug targets involved in the uptake of a broad range of compounds across the membrane. However, high-resolution experimental structures have been reported for a very limited number of transporters, which limits the study of their physiologic functions. In this review, we collected structural information on ABC and SLC transporters and described the application of computational methods in structure prediction. Taking P-glycoprotein (ABCB1) and serotonin transporter (SLC6A4) as examples, we assessed the pivotal role of structure in transport mechanisms, details of ligand-receptor interactions, drug selectivity, the molecular mechanisms of drug-drug interactions, and differences caused by genetic polymorphisms. The data collected contributes toward safer and more effective pharmacological treatments. SIGNIFICANCE STATEMENT: The experimental structure of ATP-binding cassette and solute carrier transporters was collected, and the application of computational methods in structure prediction was described. P-glycoprotein and serotonin transporter were used as examples to reveal the pivotal role of structure in transport mechanisms, drug selectivity, the molecular mechanisms of drug-drug interactions, and differences caused by genetic polymorphisms.

Glycosphingolipids within membrane contact sites influence their function as signaling hubs in neurodegenerative diseases

Intracellular organelles carry out many of their functions by engaging in extensive interorganellar communication through specialized membrane contact sites (MCSs) formed where two organelles tether to each other or to the plasma membrane (PM) without fusing. In recent years, these ubiquitous membrane structures have emerged as central signaling hubs that control a multitude of cellular pathways, ranging from lipid metabolism/transport to the exchange of metabolites and ions (i.e., Ca2+ ), and general organellar biogenesis. The functional crosstalk between juxtaposed membranes at MCSs relies on a defined composite of proteins and lipids that populate these microdomains in a dynamic fashion. This is particularly important in the nervous system, where alterations in the composition of MCSs have been shown to affect their functions and have been implicated in the pathogenesis of neurodegenerative diseases. In this review, we focus on the MCSs that are formed by the tethering of the endoplasmic reticulum (ER) to the mitochondria, the ER to the endo-lysosomes and the mitochondria to the lysosomes. We highlight how glycosphingolipids that are aberrantly processed/degraded and accumulate ectopically in intracellular membranes and the PM change the topology of MCSs, disrupting signaling pathways that lead to neuronal demise and neurodegeneration. In particular, we focus on neurodegenerative lysosomal storage diseases linked to altered glycosphingolipid catabolism.

Advances in ultrahigh-throughput screening technologies for protein evolution

Inspired by natural evolution, directed evolution randomly mutates the gene of interest through artificial evolution conditions with variants being screened for the required properties. Directed evolution is vital to the enhancement of protein properties and comprises the construction of libraries with considerable diversity as well as screening methods with sufficient efficiency as key steps. Owing to the various characteristics of proteins, specific methods are urgently needed for library screening, which is one of the main limiting factors in accelerating evolution. This review initially organizes the principles of ultrahigh-throughput screening from the perspective of protein properties. It then provides a comprehensive introduction to the latest progress and future trends in ultrahigh-throughput screening technologies for directed evolution.

Flexible Modulation of Cellular Activities with Cationic Photosensitizers: Insights of Alkyl Chain Length on Reactive Oxygen Species Antimicrobial Mechanisms

Cationic photosensitizers have good binding ability with negatively charged bacteria and fungi, exhibiting broad applications potential in antimicrobial photodynamic therapy (aPDT). However, cationic photosensitizers often display unsatisfactory transkingdom selectivity between mammalian cells and pathogens, especially for eukaryotic fungi. It is unclear which biomolecular sites are more efficient for photodynamic damage, owing to the lack of systematic research with the same photosensitizer system. Herein, a series of cationic aggregation-induced emission (AIE) derivatives (CABs) (using berberine (BBR) as the photosensitizers core) with different length alkyl chains are successfully designed and synthesized for flexible modulation of cellular activities. The BBR core can efficiently produce reactive oxygen species (ROS) and achieve high-performance aPDT . Through the precise regulation of alkyl chain length, different bindings, localizations, and photodynamic killing effects of CABs are achieved and investigated systematically among bacteria, fungi, and mammalian cells. It is found that intracellular active substances, not membranes, are more efficient damage sites of aPDT. Moderate length alkyl chains enable CABs to effectively kill Gram-negative bacteria and fungi with light, while still maintaining excellent mammalian cell and blood compatibility. This study is expected to provide systematic theoretical and strategic research guidance for the construction of high-performance cationic photosensitizers with good transkingdom selectivity.

Targeting SLC transporters: small molecules as modulators and therapeutic opportunities

Solute carrier (SLCs) transporters mediate the transport of a broad range of solutes across biological membranes. Dysregulation of SLCs has been associated with various pathologies, including metabolic and neurological disorders, as well as cancer and rare diseases. SLCs are therefore emerging as key targets for therapeutic intervention with several recently approved drugs targeting these proteins. Unlocking this large and complex group of proteins is essential to identifying unknown SLC targets and developing next-generation SLC therapeutics. Recent progress in experimental and computational techniques has significantly advanced SLC research, including drug discovery. Here, we review emerging topics in therapeutic discovery of SLCs, focusing on state-of-the-art approaches in structural, chemical, and computational biology, and discuss current challenges in transporter drug discovery.

Phase-Separated Giant Liposomes for Stable Elevation of α-Hemolysin Concentration in Lipid Membranes

Staphylococcus aureus α-hemolysin (αHL) is one of the most popular proteins in nanopore experiments within lipid membranes. Higher concentrations of αHL within the lipid membrane are desirable to enhance the mass transport capacity through nanopores. However, the reconstitution of αHL at high concentrations is associated with the problem of membrane lytic disruption. In this study, we present a method that effectively increases αHL concentration while maintaining membrane stability. This method is achieved by using phase-separated giant liposomes, where coexisting liquid-disordered (Ld) and liquid-ordered phases (Lo) are enriched in unsaturated lipids and saturated lipids with cholesterol (Chol), respectively. Fluorescence observation of αHL in liposomes revealed that the presence of Chol facilitates αHL insertion into the membrane. Despite the preferential localization of αHL in the Ld phase rather than the Lo phase, the coexistence of both Lo and Ld phases prevents membrane disruption in the presence of concentrated αHL. We have explained this stabilization mechanism considering the lower membrane tension exhibited by phase-separated liposomes compared to homogeneous liposomes. Under hypertonic conditions, we have successfully increased the local concentration of αHL by invagination of the lipid-only region in the Ld phase, leaving αHL behind. This method exhibits potential for the reconstitution of various nanochannels and membrane proteins that prefer the Ld phase over the Lo phase, thus enabling the production of giant liposomes at high concentrations and the replication of the membrane-crowding condition observed in cells.

Ionizable Amino Lipids Distribution and Effects on DSPC/Cholesterol Membranes: Implications for Lipid Nanoparticle Structure

Lipid nanoparticles (LNPs) containing ionizable aminolipids are among the leading platforms for the successful delivery of nucleic-acid-based therapeutics, including messenger RNA (mRNA). The two recently FDA-approved COVID-19 vaccines developed by Moderna and Pfizer/BioNTech belong to this category. Ionizable aminolipids, cholesterol, and DSPC lipids are among the key components of such formulations, crucially modulating physicochemical properties of these formulations and, consequently, the potency of these therapeutics. Despite the importance of these components, the distribution of these molecules in LNPs containing mRNA is not clear. In this study, we used all-atom molecular dynamics (MD) simulations to investigate the distribution and effects of the Lipid-5 (apparent pKa of the lipid nanoparticle = 6.56), a rationally designed and previously reported ionizable aminolipid by Moderna, on lipid bilayers [Mol. Ther. 2018, 26, 1509-1519]. The simulations were conducted with half of the aminolipids charged and half neutral approximately to the expected ionization in the microenvironment of the LNP surface. In all five simulated systems in this work, the cholesterol content was kept constant, whereas the DSPC and Lipid-5 concentrations were changed systematically. We found that at higher concentrations of the ionizable aminolipids, the neutral aminolipids form a disordered aggregate in the membrane interior that preferentially includes cholesterol. The rules underlying the lipid redistribution could be used to rationally choose lipids to optimize the LNP function.

More simple, efficient and accurate food research promoted by intermolecular interaction approaches: A review

The investigation of intermolecular interactions has become increasingly important in many studies, mainly by combining different analytical approaches to reveal the molecular mechanisms behind specific experimental phenomena. From spectroscopic analysis to sophisticated molecular simulation techniques like molecular docking, molecular dynamics (MD) simulation, and quantum chemical calculations (QCC), the mechanisms of intermolecular interactions are gradually being characterized more clearly and accurately, leading to revolutionary advances. This article aims to review the progression in the main techniques involving intermolecular interactions in food research and the corresponding experimental results. Finally, we discuss the significant impact that cutting-edge molecular simulation technologies may have on the future of conducting deeper exploration. Applications of molecular simulation technology may revolutionize the food research, making it possible to design new future foods with precise nutrition and desired properties.

Self-Association of ACE-2 with Different RBD Amounts: A Dynamic Simulation Perspective on SARS-CoV-2 Infection

Transmissibility of SARS-CoV-2 initially relies on its trimeric Spike-RBDs to tether the ACE-2 on host cells, and enhanced self-association of ACE-2 engaged with Spike facilitates the viral infection. Two primary packing modes of Spike-ACE2 heteroproteins exist potentially due to discrepant amounts of RBDs loading on ACE-2, but the resultant self-association difference is inherently unclear. We used extensive coarse-grained dynamic simulations to characterize the self-association efficiency, the conformation relevance, and the molecular mechanism of ACE-2 with different RBD amounts. It was revealed that the ACE-2 hanging two/full RBDs (Mode-A) rapidly dimerized into the heteroprotein complex in a compact "linear" conformation, while the bare ACE-2 showed weakened self-association and a protein complex. The RBD-tethered ectodomains of ACE-2 presented a more upright conformation relative to the membrane, and the intermolecular ectodomains were predominantly packed by the neck domains, which was obligated to the rapid protein self-association in a compact pattern. Noted is the fact that the ACE-2 tethered by a single RBD (Mode-B) retained considerable self-association efficiency and clustering capability, which unravels the interrelation of ACE-2 colocalization and protein cross-linkage. The molecular perspectives in this study expound the self-association potency of ACE-2 with different RBD amounts and the viral activity implications, which can greatly enhance our comprehension of SARS-CoV-2 infection details.

Molecular Dynamics Simulations of High-Concentration Li[TFSA] Sulfone Solution: Effect of Easy Conformation Change of Sulfolane on Fast Diffusion of Li Ion

The parameters of the polarizable force field used for molecular dynamics simulations of Li diffusion in high-concentration lithium bis(trifluoromethanesulfonyl)amide (Li[TFSA]) sulfone (sulfolane, dimethylsulfone, ethylmethylsulfone, and ethyl-i-propylsulfone) solutions were refined. The densities of the solutions obtained by molecular dynamics simulations reproduced well the experimental values. The calculated concentration, temperature, and solvent dependencies of self-diffusion coefficients of ions and solvents in the mixtures well reproduce the experimentally observed dependencies. Ab initio calculations show that the intermolecular interactions between Li ions and four sulfones are not largely different. Conformational analyses show that sulfolane can change the conformation more easily owing to lower barrier height for pseudorotation compared to the rotational barrier heights of diethylsulfone and ethylmethylsulfone. Molecular dynamics simulations indicate that the easy conformation change of solvent affects the rotational relaxation of the solvent and the diffusion of Li ion in the mixture. The easy conformation change of sulfolane is one of the causes of faster diffusion of Li ion in the mixture of Li[TFSA] and sulfolane compared to the mixtures of smaller dimethylsulfone and ethylmethylsulfone.

Molecular Dynamics Simulations of Ion Transport through Protein Nanochannels in Peritoneal Dialysis

In recent decades, the development of dialysis techniques has greatly improved the survival rate of renal failure patients, and peritoneal dialysis is gradually showing dominance over hemodialysis. This method relies on the abundant membrane proteins in the peritoneum, avoiding the use of artificial semipermeable membranes, and the ion fluid transport is partly controlled by the protein nanochannels. Hence, this study investigated ion transport in these nanochannels by using molecular dynamics (MD) simulations and an MD Monte Carlo (MDMC) algorithm for a generalized protein nanochannel model and a saline fluid environment. The spatial distribution of ions was determined via MD simulations, and it agreed with that modeled via the MDMC method; the effects of simulation duration and external electronic fields were also explored to validate the MDMC algorithm. The specific atomic sequence within a nanochannel was visualized, which was the rare transport state during the ion transport process. The residence time was assessed through both methods to represent the involved dynamic process, and its values showed the temporal sequential order of different components in the nanochannel as follows: H₂O > Na⁺ > Cl^-. The accurate prediction using the MDMC method of the spatial and temporal properties proves its suitability to handle ion transport problems in protein nanochannels.

Exploring the Role of Anionic Lipid Nanodomains in the Membrane Disruption and Protein Folding of Human Islet Amyloid Polypeptide Oligomers on Lipid Membrane Surfaces Using Multiscale Molecular Dynamics Simulations

The aggregation of human Islet Amyloid Polypeptide (hIAPP) on cell membranes is linked to amyloid diseases. However, the physio-chemical mechanisms of how these hIAPP aggregates trigger membrane damage are unclear. Using coarse-grained and all-atom molecular dynamics simulations, we investigated the role of lipid nanodomains in the presence or absence of anionic lipids, phosphatidylserine (PS), and a ganglioside (GM1), in the membrane disruption and protein folding behaviors of hIAPP aggregates on phase-separated raft membranes. Our raft membranes contain liquid-ordered (Lo), liquid-disordered (Ld), mixed Lo/Ld (Lod), PS-cluster, and GM1-cluster nanosized domains. We observed that hIAPP aggregates bound to the Lod domain in the absence of anionic lipids, but also to the GM1-cluster- and PS-cluster-containing domains, with stronger affinity in the presence of anionic lipids. We discovered that L16 and I26 are the lipid anchoring residues of hIAPP binding to the Lod and PS-cluster domains. Finally, significant lipid acyl chain order disruption in the annular lipid shells surrounding the membrane-bound hIAPP aggregates and protein folding, particularly beta-sheet formation, in larger protein aggregates were evident. We propose that the interactions of hIAPP and both non-anionic and anionic lipid nanodomains represent key molecular events of membrane damage associated with the pathogenesis of amyloid diseases.

Unravelling the mechanisms of drugs partitioning phenomena in micellar systems via NMR spectroscopy

Despite extensive use of micelles in materials and colloidal science, their supramolecular organization as well as host-guest interactions within these dynamic assemblies are poorly understood. Small guest molecules in the presence of micelles undergo constant exchange between a micellar aggregate and the surrounding solution, posing a considerable challenge for their molecular level characterisation. In this work we reveal the interaction maps between small guest molecules and surfactants forming micelles via novel applications of NMR techniques supported with state-of-the-art analytical methods used in colloidal science. Model micelles composed of structurally distinct surfactants (block non-ionic polymer Pluronic® F-127, non-ionic surfactant Tween 20 or Tween 80, and ionic surfactant sodium lauryl sulphate, SLS) were selected and loaded with model small molecules of biological relevance (i.e. the drugs fluconazole, FLU or indomethacin, IMC) known to have different partition coefficients. Molecular level organization of FLU or IMC within hydrophilic and hydrophobic domains of micellar aggregates was established using the combination of NMR methods (1D ¹H NMR, 1D ¹⁹F NMR, 2D ¹H-¹H NOESY and 2D ¹H-¹⁹F HOESY, and the multifrequency-STD NMR) and corroborated with molecular dynamics (MD) simulations. This is the first application of multifrequency-STD NMR to colloidal systems, enabling us to elucidate intricately detailed patterns of drug/micelle interactions in a single NMR experiment within minutes. Importantly, our results indicate that flexible surfactants, such as block copolymers and polysorbates, form micellar aggregates with a surface composed of both hydrophilic and hydrophobic domains and do not follow the classical core-shell model of the micelle. We propose that the magnitude of changes in ¹H chemical shifts corroborated with interaction maps obtained from DEEP-STD NMR and 2D NMR experiments can be used as an indicator of the strength of the guest-surfactant interactions. This NMR toolbox can be adopted for the analysis of broad range of colloidal host-guest systems from soft materials to biological systems.