Purification, Reconstitution, and Functional Analysis of Connexin Hemichannels.

Connexins are the proteins that form the gap junction channels that are essential for cell-to-cell communication. These channels are formed by head-to-head docking of hemichannels (each from one of two adjacent cells). Free "undocked" hemichannels at the plasma membrane are mostly closed, although they are still important under physiological conditions. However, abnormal and sustained increase in hemichannel activity due to connexin mutations or acquired conditions can produce or contribute to cell damage. For example, mutations of Cx26, a connexin isoform, can increase hemichannel activity and cause deafness. Studies using purified isolated systems under well-controlled conditions are essential for a full understanding of molecular mechanisms of hemichannel function under normal conditions and in disease, and here, we present methodology for the expression, purification, and functional analysis of hemichannels formed by Cx26.

Molecular robotic agents that survey molecular landscapes for information retrieval.

DNA-based artificial motors have allowed the recapitulation of biological functions and the creation of new features. Here, we present a molecular robotic system that surveys molecular environments and reports spatial information in an autonomous and repeated manner. A group of molecular agents, termed 'crawlers', roam around and copy information from DNA-labeled targets, generating records that reflect their trajectories. Based on a mechanism that allows random crawling, we show that our system is capable of counting the number of subunits in example molecular complexes. Our system can also detect multivalent proximities by generating concatenated records from multiple local interactions. We demonstrate this capability by distinguishing colocalization patterns of three proteins inside fixed cells under different conditions. These mechanisms for examining molecular landscapes may serve as a basis towards creating large-scale detailed molecular interaction maps inside the cell with nanoscale resolution.

Modulation of Phospholipase A2 Membrane Activity by Anti-inflammatory Drugs.

The phospholipase A2 (PLA2) superfamily consists of lipolytic enzymes that hydrolyze specific cell membrane phospholipids and have long been considered a central hub of biosynthetic pathways, where their lipid metabolites exert a variety of physiological roles. A misregulated PLA2 activity is associated with mainly inflammatory-derived pathologies and thus has shown relevant therapeutic potential. Many natural and synthetic anti-inflammatory drugs (AIDs) have been proposed as direct modulators of PLA2 activity. However, despite the specific chemical properties that these drugs share in common, little is known about the indirect modulation able to finely tune membrane structural changes at the precise lipid-binding site. Here, we use a novel experimental strategy based on differential scanning calorimetry to systematically study the structural properties of lipid membrane systems during PLA2 cleavage and under the influence of several AIDs. For a better understanding of the AIDs-membrane interaction, we present a comprehensive and comparative set of molecular dynamics (MD) simulations. Our thermodynamic results clearly demonstrate that PLA2 cleavage is hindered by those AIDs that significantly reduce the lipid membrane cooperativity, while the rest of the AIDs oppositely tend to catalyze PLA2 activity to different extents. On the other hand, our MD simulations support experimental results by providing atomistic details on the binding, insertion, and dynamics of each AID on a pure lipid system; the drug efficacy to impact membrane cooperativity is related to the lipid order perturbation. This work suggests a membrane-based mechanism of action for diverse AIDs against PLA2 activity and provides relevant clues that must be considered in its modulation.

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments.

Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.

Simulation of gap junction formation reveals critical role of Cys disulfide redox state in connexin hemichannel docking.

Video Abstract.

Electric field-mediated adhesive dynamics of cells inside bio-functionalised microchannels offers important cues for active control of cell-substrate adhesion.

Adhesive dynamics of cells plays a critical role in determining different biophysical processes orchestrating health and disease in living systems. While the rolling of cells on functionalised substrates having similarity with biophysical pathways appears to be extensively discussed in the literature, the effect of an external stimulus in the form of an electric field on the same remains underemphasized. Here, we bring out the interplay of fluid shear and electric field on the rolling dynamics of adhesive cells in biofunctionalised micro-confinements. Our experimental results portray that an electric field, even restricted to low strengths within the physiologically relevant regimes, can significantly influence the cell adhesion dynamics. We quantify the electric field-mediated adhesive dynamics of the cells in terms of two key parameters, namely, the voltage-altered rolling velocity and the frequency of adhesion. The effect of the directionality of the electric field with respect to the flow direction is also analysed by studying cellular migration with electrical effects acting both along and against the flow. Our experiment, on one hand, demonstrates the importance of collagen functionalisation in the adhesive dynamics of cells through micro channels, while on the other hand, it reveals how the presence of an axial electric field can lead to significant alteration in the kinetic rate of bond breakage, thereby modifying the degree of cell-substrate adhesion and quantifying in terms of the adhesion frequency of the cells. Proceeding further forward, we offer a simple theoretical explanation towards deriving the kinetics of cellular bonding in the presence of an electric field, which corroborates favourably with our experimental outcome. These findings are likely to offer fundamental insights into the possibilities of local control of cellular adhesion via electric field mediated interactions, bearing critical implications in a wide variety of medical conditions ranging from wound healing to cancer metastasis.

CryoEM structures of the human CLC-2 voltage-gated chloride channel reveal a ball-and-chain gating mechanism.

CLC-2 is a voltage-gated chloride channel that contributes to electrical excitability and ion homeostasis in many different tissues. Among the nine mammalian CLC homologs, CLC-2 is uniquely activated by hyperpolarization, rather than depolarization, of the plasma membrane. The molecular basis for the divergence in polarity of voltage gating among closely related homologs has been a long-standing mystery, in part because few CLC channel structures are available. Here, we report cryoEM structures of human CLC-2 at 2.46 - 2.76 Å, in the presence and absence of the selective inhibitor AK-42. AK-42 binds within the extracellular entryway of the Cl--permeation pathway, occupying a pocket previously proposed through computational docking studies. In the apo structure, we observed two distinct conformations involving rotation of one of the cytoplasmic C-terminal domains (CTDs). In the absence of CTD rotation, an intracellular N-terminal 15-residue hairpin peptide nestles against the TM domain to physically occlude the Cl--permeation pathway. This peptide is highly conserved among species variants of CLC-2 but is not present in other CLC homologs. Previous studies suggested that the N-terminal domain of CLC-2 influences channel properties via a "ball-and-chain" gating mechanism, but conflicting data cast doubt on such a mechanism, and thus the structure of the N-terminal domain and its interaction with the channel has been uncertain. Through electrophysiological studies of an N-terminal deletion mutant lacking the 15-residue hairpin peptide, we support a model in which the N-terminal hairpin of CLC-2 stabilizes a closed state of the channel by blocking the cytoplasmic Cl--permeation pathway.

Energy conservation by collective movement in schooling fish.

Many animals moving through fluids exhibit highly coordinated group movement that is thought to reduce the cost of locomotion. However, direct energetic measurements demonstrating the energy-saving benefits of fluid-mediated collective movements remain elusive. By characterizing both aerobic and anaerobic metabolic energy contributions in schools of giant danio (Devario aequipinnatus), we discovered that fish schools have a concave upward shaped metabolism-speed curve, with a minimum metabolic cost at ~1 body length s-1. We demonstrate that fish schools reduce total energy expenditure (TEE) per tail beat by up to 56% compared to solitary fish. When reaching their maximum sustained swimming speed, fish swimming in schools had a 44% higher maximum aerobic performance and used 65% less non-aerobic energy compared to solitary individuals, which lowered the TEE and total cost of transport by up to 53%, near the lowest recorded for any aquatic organism. Fish in schools also recovered from exercise 43% faster than solitary fish. The non-aerobic energetic savings that occur when fish in schools actively swim at high speed can considerably improve both peak and repeated performance which is likely to be beneficial for evading predators. These energetic savings may underlie the prevalence of coordinated group locomotion in fishes.

Schools of fish, flocks of birds flying in a V-formation and other collective movements of animals are common and mesmerizing behaviours. Moving as a group can have many benefits including helping the animals to find food and reproduce and protecting them from predators. Collective movements may also help animals to save energy as they travel by altering the flow of air or water around individuals. Computational models based on the flow of water suggest several possible mechanisms for how fish swimming in schools may use less energy compared to fish swimming on their own. However, few studies have directly measured how much energy fish schools actually use while they swim compared to a solitary individual. Zhang and Lauder used a device called a respirometer to directly measure the energy used by small tropical fish, known as giant danio, swimming in schools and on their own in an aquatic treadmill. The experiments found that the fish swimming in schools used 53% less energy compared with fish swimming on their own, and that fish in schools recovered from a period of high-speed swimming 43% quicker than solitary fish. By adjusting the flow of the water in the tanks, the team were able to study the fish schools swimming at different speeds. This revealed that the fish used more energy when they hovered slowly, or swam fast, than when they swam at a more moderate speed. Previous studies have found that many fish tend to swim at a moderate speed of around one body length per second while they travel long distances. Zhang and Lauder found that the giant danio used the least energy when they swam at this 'migratory' speed. These findings show that swimming in schools can help fish save energy compared with swimming alone. Along with furthering our understanding of how collective movement benefits fish and other animals, this work may help engineers to design robots that can team up with other robots to move more efficiently through the water.

Segregation of co-cultured multicellular systems: review and modeling consideration.

Cell segregation caused by collective cell migration (CCM) is crucial for morphogenesis, functional development of tissue parts, and is an important aspect in other diseases such as cancer and its metastasis process. Efficiency of the cell segregation depends on the interplay between: (1) biochemical processes such as cell signaling and gene expression and (2) physical interactions between cells. Despite extensive research devoted to study the segregation of various co-cultured systems, we still do not understand the role of physical interactions in cell segregation. Cumulative effects of these physical interactions appear in the form of physical parameters such as: (1) tissue surface tension, (2) viscoelasticity caused by CCM, and (3) solid stress accumulated in multicellular systems. These parameters primarily depend on the interplay between the state of cell-cell adhesion contacts and cell contractility. The role of these physical parameters on the segregation efficiency is discussed on model systems such as co-cultured breast cell spheroids consisting of two subpopulations that are in contact. This review study aims to: (1) summarize biological aspects related to cell segregation, mechanical properties of cell collectives, effects along the biointerface between cell subpopulations and (2) describe from a biophysical/mathematical perspective the same biological aspects summarized before. So that overall it can illustrate the complexity of the biological systems that translate into very complex biophysical/mathematical equations. Moreover, by presenting in parallel these two seemingly different parts (biology vs. equations), this review aims to emphasize the need for experiments to estimate the variety of parameters entering the resulting complex biophysical/mathematical models.

Insights into Activation Dynamics and Functional Sites of Inwardly Rectifying Potassium Channel Kir3.2 by an Elastic Network Model Combined with Perturbation Methods.

The inwardly rectifying potassium channel Kir3.2, a member of the inward rectifier potassium (Kir) channel family, exerts important biological functions through transporting potassium ions outside of the cell, during which a large-scale synergistic movement occurs among its different domains. Currently, it is not fully understood how the binding of the ligand to the Kir3.2 channel leads to the structural changes and which key residues are responsible for the channel gating and allosteric dynamics. Here, we construct the Gaussian network model (GNM) of the Kir3.2 channel with the secondary structure and covalent interaction information considered (sscGNM), which shows a better performance in reproducing the channel's flexibility compared with the traditional GNM. In addition, the sscANM-based perturbation method is used to simulate the channel's conformational transition caused by the activator PIP2's binding. By applying certain forces to the PIP2 binding pocket, the coarse-grained calculations generate the similar conformational changes to the experimental observation, suggesting that the topology structure as well as PIP2 binding are crucial to the allosteric activation of the Kir3.2 channel. We also utilize the sscGNM-based thermodynamic cycle method developed by us to identify the key residues whose mutations significantly alter the channel's binding free energy with PIP2. We identify not only the residues important for the specific binding but also the ones critical for the allosteric transition coupled with PIP2 binding. This study is helpful for understanding the working mechanism of Kir3.2 channels and can provide important information for related drug design.

cAMP binding to closed pacemaker ion channels is cooperative.

The cooperative action of the subunits in oligomeric receptors enables fine-tuning of receptor activation, as demonstrated for the regulation of voltage-activated HCN pacemaker ion channels by relating cAMP binding to channel activation in ensemble signals. HCN channels generate electric rhythmicity in specialized brain neurons and cardiomyocytes. There is conflicting evidence on whether binding cooperativity does exist independent of channel activation or not, as recently reported for detergent-solubilized receptors positioned in zero-mode waveguides. Here, we show positive cooperativity in ligand binding to closed HCN2 channels in native cell membranes by following the binding of individual fluorescence-labeled cAMP molecules. Kinetic modeling reveals that the affinity of the still empty binding sites rises with increased degree of occupation and that the transition of the channel to a flip state is promoted accordingly. We conclude that ligand binding to the subunits in closed HCN2 channels not pre-activated by voltage is already cooperative. Hence, cooperativity is not causally linked to channel activation by voltage. Our analysis also shows that single-molecule binding measurements at equilibrium can quantify cooperativity in ligand binding to receptors in native membranes.

Implicit model to capture electrostatic features of membrane environment.

Membrane protein structure prediction and design are challenging due to the complexity of capturing the interactions in the lipid layer, such as those arising from electrostatics. Accurately capturing electrostatic energies in the low-dielectric membrane often requires expensive Poisson-Boltzmann calculations that are not scalable for membrane protein structure prediction and design. In this work, we have developed a fast-to-compute implicit energy function that considers the realistic characteristics of different lipid bilayers, making design calculations tractable. This method captures the impact of the lipid head group using a mean-field-based approach and uses a depth-dependent dielectric constant to characterize the membrane environment. This energy function Franklin2023 (F23) is built upon Franklin2019 (F19), which is based on experimentally derived hydrophobicity scales in the membrane bilayer. We evaluated the performance of F23 on five different tests probing (1) protein orientation in the bilayer, (2) stability, and (3) sequence recovery. Relative to F19, F23 has improved the calculation of the tilt angle of membrane proteins for 90% of WALP peptides, 15% of TM-peptides, and 25% of the adsorbed peptides. The performances for stability and design tests were equivalent for F19 and F23. The speed and calibration of the implicit model will help F23 access biophysical phenomena at long time and length scales and accelerate the membrane protein design pipeline.

An individual-based model to explore the impact of psychological stress on immune infiltration into tumour spheroids.

In recentin vitroexperiments on co-culture between breast tumour spheroids and activated immune cells, it was observed that the introduction of the stress hormone cortisol resulted in a decreased immune cell infiltration into the spheroids. Moreover, the presence of cortisol deregulated the normal levels of the pro- and anti-inflammatory cytokines IFN-γand IL-10. We present an individual-based model to explore the interaction dynamics between tumour and immune cells under psychological stress conditions. With our model, we explore the processes underlying the emergence of different levels of immune infiltration, with particular focus on the biological mechanisms regulated by IFN-γand IL-10. The set-up of numerical simulations is defined to mimic the scenarios considered in the experimental study. Similarly to the experimental quantitative analysis, we compute a score that quantifies the level of immune cell infiltration into the tumour. The results of numerical simulations indicate that the motility of immune cells, their capability to infiltrate through tumour cells, their growth rate and the interplay between these cell parameters can affect the level of immune cell infiltration in different ways. Ultimately, numerical simulations of this model support a deeper understanding of the impact of biological stress-induced mechanisms on immune infiltration.

Energy, water, and protein folding: A molecular dynamics-based quantitative inventory of molecular interactions and forces that make proteins stable.

Protein folding energetics can be determined experimentally on a case-by-case basis but it is not understood in sufficient detail to provide deep control in protein design. The fundamentals of protein stability have been outlined by calorimetry, protein engineering, and biophysical modeling, but these approaches still face great difficulty in elucidating the specific contributions of the intervening molecules and physical interactions. Recently, we have shown that the enthalpy and heat capacity changes associated to the protein folding reaction can be calculated within experimental error using molecular dynamics simulations of native protein structures and their corresponding unfolded ensembles. Analyzing in depth molecular dynamics simulations of four model proteins (CI2, barnase, SNase, and apoflavodoxin), we dissect here the energy contributions to ΔH (a key component of protein stability) made by the molecular players (polypeptide and solvent molecules) and physical interactions (electrostatic, van der Waals, and bonded) involved. Although the proteins analyzed differ in length, isoelectric point and fold class, their folding energetics is governed by the same quantitative pattern. Relative to the unfolded ensemble, the native conformations are enthalpically stabilized by comparable contributions from protein-protein and solvent-solvent interactions, and almost equally destabilized by interactions between protein and solvent molecules. The native protein surface seems to interact better with water than the unfolded one, but this is outweighed by the unfolded surface being larger. From the perspective of physical interactions, the native conformations are stabilized by van de Waals and Coulomb interactions and destabilized by conformational strain arising from bonded interactions. Also common to the four proteins, the sign of the heat capacity change is set by interactions between protein and solvent molecules or, from the alternative perspective, by Coulomb interactions.

Combined Effects of Pressure and Ionic Strength on Protein-Protein Interactions: An Empirical Approach.

Proteins are exposed to hydrostatic pressure (HP) in a variety of ecosystems as well as in processing steps such as freeze-thaw, cell disruption, sterilization, and homogenization, yet pressure effects on protein-protein interactions (PPIs) remain underexplored. With the goal of contributing toward the expanded use of HP as a fundamental control parameter in protein research, processing, and engineering, small-angle X-ray scattering was used to examine the effects of HP and ionic strength on ovalbumin, a model protein. Based on an extensive data set, we develop an empirical method for scaling PPIs to a master curve by combining HP and osmotic effects. We define an effective pressure parameter that has been shown to successfully apply to other model protein data available in the literature, with deviations evident for proteins that do not follow the apparent Hofmeister series. The limitations of the empirical scaling are discussed in the context of the hypothesized underlying mechanisms.

A label-free approach for measuring interactions of proteins with lipid membranes.

In this issue of Cell Reports Methods, Sadi et al. present a nuclear magnetic resonance approach for quantitative assessment of protein interactions with lipid membranes. It is sensitive, applicable to diverse membrane systems, covers a broad range of KDs, and does not require large amounts of material.

A general model for the motion of multivalent cargo interacting with substrates.

Multivalent interactions are common in biology at many different length scales, and can result in the directional motion of multivalent cargo along substrates. Here, a general analytical model has been developed that can describe the directional motion of multivalent cargo as a response to position dependence in the binding and unbinding rates exhibited by their interaction sites. Cargo exhibit both an effective velocity, which acts in the direction of increasing cargo-substrate binding rate and decreasing cargo-substrate unbinding rate, and an effective diffusivity. This model can reproduce previously published experimental findings using only the binding and unbinding rate distributions of cargo interaction sites, and without any further parameter fitting. Extension of the cargo binding model to two dimensions reveals an effective velocity with the same properties as that derived for the one-dimensional case.

Simulation-guided engineering of split GFPs with efficient ß-strand photodissociation.

Green fluorescent proteins (GFPs) are ubiquitous for protein tagging and live-cell imaging. Split-GFPs are widely used to study protein-protein interactions by fusing proteins of interest to split GFP fragments that create a fluorophore upon typically irreversible complementation. Thus, controlled dissociation of the fragments is desirable. Although we have found that split strands can be photodissociated, the quantum efficiency of light-induced photodissociation of split GFPs is low. Traditional protein engineering approaches to increase efficiency, including extensive mutagenesis and screening, have proved difficult to implement. To reduce the search space, key states in the dissociation process are modeled by combining classical and enhanced sampling molecular dynamics with QM/MM calculations, enabling the rational design and engineering of split GFPs with up to 20-fold faster photodissociation rates using non-intuitive amino acid changes. This demonstrates the feasibility of modeling complex molecular processes using state-of-the-art computational methods, and the potential of integrating computational methods to increase the success rate in protein engineering projects.

The ice-binding site of antifreeze protein irreversibly binds to cell surface for its hypothermic protective function.

Antifreeze proteins (AFPs) are multifunctional polypeptides that adsorb onto ice crystals to inhibit their growth and onto cells to protect them from nonfreezing hypothermic damage. However, the mechanism by which AFP exerts its hypothermic cell protective (HCP) function remains uncertain. Here, we assessed the HCP function of three types of fish-derived AFPs (type I, II, and III AFPs) against human T-lymphoblastic lymphoma by measuring the survival rate (%) of the cells after preservation at 4 °C for 24 h. All AFPs improved the survival rate in a concentration-dependent manner, although the HCP efficiency was inferior for type III AFP compared to other AFPs. In addition, after point mutations were introduced into the ice-binding site (IBS) of a type III AFP, HCP activity was dramatically increased, suggesting that the IBS of AFP is involved in cell adsorption. Significantly, high HCP activity was observed for a mutant that exhibited poorer antifreeze activity, indicating that AFP exerts HCP- and ice-binding functions through a different mechanism. We next incubated the cells in an AFP-containing solution, replaced it with pure EC solution, and then preserved the cells, showing that no significant reduction in the cell survival rate occurred for type I and II AFPs even after replacement. Thus, these AFPs irreversibly bind to the cells at 4 °C, and only tightly adsorbed AFP molecules contribute towards the cell-protection function.