Dynamic cluster formation determines viscosity and diffusion in dense protein solutions

Fusion Dynamics and Size-Dependence of Droplet Microstructure in ssDNA-Mediated Protein Phase Separation

Biomolecular condensation involving proteins and nucleic acids has been recognized to play crucial roles in genome organization and transcriptional regulation. However, the biophysical mechanisms underlying the droplet fusion dynamics and microstructure evolution during the early stage of liquid-liquid phase separation (LLPS) remain elusive. In this work, we study the phase separation of linker histone H1, which is among the most abundant chromatin proteins, in the presence of single-stranded DNA (ssDNA) capable of forming a G-quadruplex by using molecular simulations and experimental characterization. We found that droplet fusion is a rather stochastic and kinetically controlled process. Productive fusion events are triggered by the formation of ssDNA-mediated electrostatic bridges within the droplet contacting zone. The droplet microstructure is size-dependent and evolves driven by maximizing the number of electrostatic contacts. We also showed that the folding of ssDNA to the G-quadruplex promotes LLPS by increasing the multivalency and strength of protein-DNA interactions. These findings provide deep mechanistic insights into the growth dynamics of biomolecular droplets and highlight the key role of kinetic control during the early stage of ssDNA-protein condensation.

Membrane remodeling via ubiquitin-mediated pathways

The dynamic process of membrane shaping and remodeling plays a vital role in cellular functions, with proteins and cellular membranes interacting intricately to adapt to various cellular needs and environmental cues. Ubiquitination-a posttranslational modification-was shown to be essential in regulating membrane structure and shape. It influences virtually all pathways relying on cellular membranes, such as endocytosis and autophagy by directing protein degradation, sorting, and oligomerization. Ubiquitin is mostly known as a protein modifier; however, it was reported that ubiquitin and ubiquitin-like proteins can associate directly with lipids, affecting membrane curvature and dynamics. In this review, we summarize some of the current knowledge on ubiquitin-mediated membrane remodeling in the context of endocytosis, autophagy, and ER-phagy.

Diffusion of proteins in crowded solutions studied by docking-based modeling

The diffusion of proteins is significantly affected by macromolecular crowding. Molecular simulations accounting for protein interactions at atomic resolution are useful for characterizing the diffusion patterns in crowded environments. We present a comprehensive analysis of protein diffusion under different crowding conditions based on our recent docking-based approach simulating an intracellular crowded environment by sampling the intermolecular energy landscape using the Markov Chain Monte Carlo protocol. The procedure was extensively benchmarked, and the results are in very good agreement with the available experimental and theoretical data. The translational and rotational diffusion rates were determined for different types of proteins under crowding conditions in a broad range of concentrations. A protein system representing most abundant protein types in the E. coli cytoplasm was simulated, as well as large systems of other proteins of varying sizes in heterogeneous and self-crowding solutions. Dynamics of individual proteins was analyzed as a function of concentration and different diffusion rates in homogeneous and heterogeneous crowding. Smaller proteins diffused faster in heterogeneous crowding of larger molecules, compared to their diffusion in the self-crowded solution. Larger proteins displayed the opposite behavior, diffusing faster in the self-crowded solution. The results show the predictive power of our structure-based simulation approach for long timescales of cell-size systems at atomic resolution.

Portable Microfluidic Viscometer for Formulation Development and in Situ Quality Control of Protein and Antibody Solutions

Viscosity of protein solutions is a critical product quality attribute for protein therapeutics such as monoclonal antibodies. Here we introduce a portable single-use analytical chip-based viscometer for determining the viscosity of protein solutions using low sample volumes of 10 μL. Through the combined use of a microfluidic viscometer, a smartphone camera for image capture, and an automated data processing algorithm for the calculation of the viscosity of fluids, we enable measurement of viscosity of multiple samples in parallel. We first validate the viscometer using glycerol-water mixtures and subsequently demonstrate the ability to perform rapid characterization of viscosity in four different monoclonal antibody formulations in a broad concentration (1 to 320 mg/mL) and viscosity (1 to 600 cP) range, showing excellent agreement with values obtained by a conventional cone-plate rheometer. Not only does the platform offer benefits of viscosity measurements using minimal sample volumes, but enables higher throughput compared to gold-standard methodologies owing to multiplexing of the measurement and single-use characteristics of the viscometer, thus showing great promise in developability studies. Additionally, as our platform has the capability of performing viscosity measurements at the point of sample collection, it offers the opportunity to employ viscosity measurement as an in situ quality control of therapeutic proteins and antibodies.

O-glycans Expand Lubricin and Attenuate Its Viscosity and Shear Thinning

Lubricin, an intrinsically disordered glycoprotein, plays a pivotal role in facilitating smooth movement and ensuring the enduring functionality of synovial joints. The central domain of this protein serves as a source of this excellent lubrication and is characterized by its highly glycosylated, negatively charged, and disordered structure. However, the influence of O-glycans on the viscosity of lubricin remains unclear. In this study, we employ molecular dynamics simulations in the absence and presence of shear, along with continuum simulations, to elucidate the intricate interplay between O-glycans and lubricin and the impact of O-glycans on lubricin's conformational properties and viscosity. We found the presence of O-glycans to induce a more extended conformation in fragments of the disordered region of lubricin. These O-glycans contribute to a reduction in solution viscosity but at the same time weaken shear thinning at high shear rates, compared to nonglycosylated systems with the same density. This effect is attributed to the steric and electrostatic repulsion between the fragments, which prevents their conglomeration and structuring. Our computational study yields a mechanistic mechanism underlying previous experimental observations of lubricin and paves the way to a more rational understanding of its function in the synovial fluid.

Modeling reveals the strength of weak interactions in stacked-ring assembly

Cells employ many large macromolecular machines for the execution and regulation of processes that are vital for cell and organismal viability. Interestingly, cells cannot synthesize these machines as functioning units. Instead, cells synthesize the molecular parts that must then assemble into the functional complex. Many important machines, including chaperones such as GroEL and proteases such as the proteasome, comprise protein rings that are stacked on top of one another. While there is some experimental data regarding how stacked-ring complexes such as the proteasome self-assemble, a comprehensive understanding of the dynamics of stacked-ring assembly is currently lacking. Here, we developed a mathematical model of stacked-trimer assembly and performed an analysis of the assembly of the stacked homomeric trimer, which is the simplest stacked-ring architecture. We found that stacked rings are particularly susceptible to a form of kinetic trapping that we term "deadlock," in which the system gets stuck in a state where there are many large intermediates that are not the fully assembled structure but that cannot productively react. When interaction affinities are uniformly strong, deadlock severely limits assembly yield. We thus predicted that stacked rings would avoid situations where all interfaces in the structure have high affinity. Analysis of available crystal structures indicated that indeed the majority-if not all-of stacked trimers do not contain uniformly strong interactions. Finally, to better understand the origins of deadlock, we developed a formal pathway analysis and showed that, when all the binding affinities are strong, many of the possible pathways are utilized. In contrast, optimal assembly strategies utilize only a small number of pathways. Our work suggests that deadlock is a critical factor influencing the evolution of macromolecular machines and provides general principles for understanding the self-assembly efficiency of existing machines.

Stability of Protein Pharmaceuticals: Recent Advances

There have been significant advances in the formulation and stabilization of proteins in the liquid state over the past years since our previous review. Our mechanistic understanding of protein-excipient interactions has increased, allowing one to develop formulations in a more rational fashion. The field has moved towards more complex and challenging formulations, such as high concentration formulations to allow for subcutaneous administration and co-formulation. While much of the published work has focused on mAbs, the principles appear to apply to any therapeutic protein, although mAbs clearly have some distinctive features. In this review, we first discuss chemical degradation reactions. This is followed by a section on physical instability issues. Then, more specific topics are addressed: instability induced by interactions with interfaces, predictive methods for physical stability and interplay between chemical and physical instability. The final parts are devoted to discussions how all the above impacts (co-)formulation strategies, in particular for high protein concentration solutions.'

Fatty acid binding to the human transport proteins FABP3, FABP4, and FABP5 from a Ligand's perspective

Fatty acid binding proteins (FABPs) are a family of amphiphilic transport proteins with high diversity in terms of their amino acid sequences and binding preferences. Beyond their main biological role as cytosolic fatty acid transporters, many aspects regarding their binding mechanism and functional specializations in human cells remain unclear. In this work, the binding properties and thermodynamics of FABP3, FABP4, and FABP5 were analyzed under various physical conditions. For this purpose, the FABPs were loaded with fatty acids bearing fluorescence or spin probes as model ligands, comparing their binding affinities via microscale thermophoresis (MST) and continuous-wave electron paramagnetic resonance (CW EPR) spectroscopy. The CW EPR spectra of non-covalently bound 5- and 16-DOXYL stearic acid (5/16-DSA) deliver in-depth information about the dynamics and chemical environments of ligands inside the binding pockets of the FABPs. EPR spectral simulations allow the construction of binding curves, revealing two different binding states ('intermediately' and 'strongly' bound). The proportion of bound 5/16-DSA depends strongly on the FABP concentration and the temperature but with remarkable differences between the three isoforms. Additionally, the more dynamic state ('intermediately bound') seems to dominate at body temperature with thermodynamic preference. The ligand binding studies were supplemented by aggregation studies via dynamic light scattering and bioinformatic analyses. Beyond the remarkably fine-tuned binding properties exhibited by each FABP, which were discernible with our EPR-centered approach, the results of this work attest to the power of simple spectroscopic experiments to provide new insights into the ligand binding mechanisms of proteins in general on a molecular level.

Combining Scattering Experiments and Colloid Theory to Characterize Charge Effects in Concentrated Antibody Solutions

Charges and their contribution to protein-protein interactions are essential for the key structural and dynamic properties of monoclonal antibody (mAb) solutions. In fact, they influence the apparent molecular weight, the static structure factor, the collective diffusion coefficient, or the relative viscosity, and their concentration dependence. Further, charges play an important role in the colloidal stability of mAbs. There exist standard experimental tools to characterize mAb net charges, such as the measurement of the electrophoretic mobility, the second virial coefficient, or the diffusion interaction parameter. However, the resulting values are difficult to directly relate to the actual overall net charge of the antibody and to theoretical predictions based on its known molecular structure. Here, we report the results of a systematic investigation of the solution properties of a charged IgG1 mAb as a function of concentration and ionic strength using a combination of electrophoretic measurements, static and dynamic light scattering, small-angle X-ray scattering, and tracer particle-based microrheology. We analyze and interpret the experimental results using established colloid theory and coarse-grained computer simulations. We discuss the potential and limits of colloidal models for the description of the interaction effects of charged mAbs, in particular pointing out the importance of incorporating shape and charge anisotropy when attempting to predict structural and dynamic solution properties at high concentrations.

Entropy Tug-of-War Determines Solvent Effects in the Liquid-Liquid Phase Separation of a Globular Protein

Liquid-liquid phase separation (LLPS) plays a key role in the compartmentalization of cells via the formation of biomolecular condensates. Here, we combined atomistic molecular dynamics (MD) simulations and terahertz (THz) spectroscopy to determine the solvent entropy contribution to the formation of condensates of the human eye lens protein γD-Crystallin. The MD simulations reveal an entropy tug-of-war between water molecules that are released from the protein droplets and those that are retained within the condensates, two categories of water molecules that were also assigned spectroscopically. A recently developed THz-calorimetry method enables quantitative comparison of the experimental and computational entropy changes of the released water molecules. The strong correlation mutually validates the two approaches and opens the way to a detailed atomic-level understanding of the different driving forces underlying the LLPS.

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.

SPANA: Spatial decomposition analysis for cellular-scale molecular dynamics simulations

The rapid increase in computational power with the latest supercomputers has enabled atomistic molecular dynamics (MDs) simulations of biomolecules in biological membrane, cytoplasm, and other cellular environments. These environments often contain a million or more atoms to be simulated simultaneously. Therefore, their trajectory analyses involve heavy computations that can become a bottleneck in the computational studies. Spatial decomposition analysis (SPANA) is a set of analysis tools in the Generalized-Ensemble Simulation System (GENESIS) software package that can carry out MD trajectory analyses of large-scale biological simulations using multiple CPU cores in parallel. SPANA applies the spatial decomposition of a large biological system to distribute structural and dynamical analyses into individual CPU cores, which reduces the computational time and the memory size, significantly. SPANA opens new possibilities for detailed atomistic analyses of biomacromolecules as well as solvent water molecules, ions, and metabolites in MD simulation trajectories of very large biological systems containing more than millions of atoms in cellular environments.

Electrostatically Mediated Attractive Self-Interactions and Reversible Self-Association of Fc-Fusion Proteins

Attractive self-interactions and reversible self-association are implicated in many problematic solution behaviors for therapeutic proteins, such as irreversible aggregation, elevated viscosity, phase separation, and opalescence. Protein self-interactions and reversible oligomerization of two Fc-fusion proteins (monovalent and bivalent) and the corresponding fusion partner protein were characterized experimentally with static and dynamic light scattering as a function of pH (5 and 6.5) and ionic strength (10 mM to at least 300 mM). The fusion partner protein and monovalent Fc-fusion each displayed net attractive electrostatic self-interactions at pH 6.5 and net repulsive electrostatic self-interactions at pH 5. Solutions of the bivalent Fc-fusion contained higher molecular weight species that prevented quantification of typical interaction parameters (B22 and kD). All three of the proteins displayed reversible self-association at pH 6.5, where oligomers dissociated with increased ionic strength. Coarse-grained molecular simulations were used to model the self-interactions measured experimentally, assess net self-interactions for the bivalent Fc-fusion, and probe the specific electrostatic interactions between charged amino acids that were involved in attractive electrostatic self-interactions. Mayer-weighted pairwise electrostatic energies from the simulations suggested that attractive electrostatic self-interactions at pH 6.5 for the two Fc-fusion proteins were due to cross-domain interactions between the fusion partner domain(s) and the Fc domain.

The effects of biological crowders on fibrillization, structure, diffusion, and conformational dynamics of α-synuclein

α-synuclein is an intrinsically disordered protein (IDP) whose aggregation in presynaptic neuronal cells is a pathological hallmark of Lewy body formation and Parkinson's disease. This aggregation process is likely affected by the crowded macromolecular cellular environment. In this study, α-synuclein was studied in the presence of both a synthetic crowder, Ficoll70, and a biological crowder composed of lysed cells that better mimics the biocomplexity of the cellular environment. 15 N-1 H HSQC NMR results show similar α-synuclein chemical shifts in non-crowded and all crowded conditions implying that it remains similarly unstructured in all conditions. Nevertheless, both HSQC NMR and fluorescence measurements indicate that, only in the cell lysate, α-synuclein forms aggregates over a timescale of 48 h. 15 N-edited diffusion measurements indicate that all crowders slow down the α-synuclein's diffusivity. Interestingly, at high concentrations, α-synuclein diffuses faster in cell lysate than in Ficoll70, possibly due to additional soft (e.g., electrostatic or hydrophobic) interactions. 15 N-edited relaxation measurements show that some residues are more mobile in cell lysate than in Ficoll70; the rates that are most different are predominantly in hydrophobic residues. We thus examined cell lysates with reduced hydrophobicity and found slower dynamics (higher relaxation rates) in several α-synuclein residues. Taken together, these experiments suggest that while cell lysate does not substantially affect α-synuclein structure (HSQC spectra), it does affect chain dynamics and translational diffusion, and strongly affects aggregation over a timescale of days, in a manner that is different from either no crowder or an artificial crowder: soft hydrophobic interactions are implicated.

Computational Procedure for Predicting Excipient Effects on Protein-Protein Affinities

Protein-protein interactions lie at the center of many biological processes and are a challenge in formulating biological drugs, such as antibodies. A key to mitigating protein association is to use small-molecule additives, i.e., excipients that can weaken protein-protein interactions. Here, we develop a computationally efficient model for predicting the viscosity-reducing effect of different excipient molecules by combining atomic-resolution MD simulations, binding polynomials, and a thermodynamic perturbation theory. In a proof of principle, this method successfully ranks the order of four types of excipients known to reduce the viscosity of solutions of a particular monoclonal antibody. This approach appears useful for predicting the effects of excipients on protein association and phase separation, as well as the effects of buffers on protein solutions.

Decoding the Role of the Global Proteome Dynamics for Cellular Thermal Stability

Molecular mechanisms underlying the thermal response of cells remain elusive. On the basis of the recent result that the short-time diffusive dynamics of the Escherichia coli proteome is an excellent indicator of temperature-dependent bacterial metabolism and death, we used neutron scattering (NS) spectroscopy and molecular dynamics (MD) simulations to investigate the sub-nanosecond proteome mobility in psychro-, meso-, and hyperthermophilic bacteria over a wide temperature range. The magnitude of thermal fluctuations, measured by atomic mean square displacements, is similar among all studied bacteria at their respective thermal cell death. Global roto-translational motions turn out to be the main factor distinguishing the bacterial dynamical properties. We ascribe this behavior to the difference in the average proteome net charge, which becomes less negative for increasing bacterial thermal stability. We propose that the chemical-physical properties of the cytoplasm and the global dynamics of the resulting proteome are fine-tuned by evolution to uphold optimal thermal stability conditions.

Poly(glutamic acid)-Based Viscosity Reducers for Concentrated Formulations of a Monoclonal IgG Antibody

Above a concentration threshold, the viscosity of solutions of proteins increases abruptly, which hampers the injectability of therapeutic formulations. Concentrations above 200 g/L are an ideal goal for subcutaneous application of antibodies. Molecular additives, such as amino acids (e.g., arginine) help decrease the viscosity, but they are used at concentrations as high as about 200 mmol/L. We addressed the question of whether poly(amino acids) could be more efficient than small molecular additives. We observed marked fluidification of a model therapeutic monoclonal antibody (mAb) solution by poly(d,l-glutamic acid) and poly(l-glutamic acid) derivatives added at concentrations of <6.5 g/L (i.e., a mAb/polymer chain molar ratio between 4:1 and 1:1 mol/mol). The bare poly(glutamate) parent chains were compared with polyethylene glycol-grafted chains as PEGylation is a common way to enhance stability. Viscosity could be decreased to ∼20 mPa s as compared to values of ∼100 mPa s in the absence of polymers at 200 g/L mAb. Formation of complexes between the mAb and the polyglutamates was characterized by capillary electrophoresis analysis in dilute solutions (1 g/L mAb) and by observation of phase separation at higher concentrations, suggesting tight association at about 2:1 mol/mol mAb/polymer. Altogether, these results show that polyglutamate derivatives hold an untapped potential as an excipient for fluidification of concentrated protein solutions.

Gallic acid-functionalized soy protein-based multiple cross-linked hydrogel: Mechanism analysis, physicochemical properties, and digestive characteristics

Herein, carbodiimide hydrochloride/N-hydroxysuccinimide was used to mediate the grafting of gallic acid (GA) (0.005, 0.0015, and 0.025 wt%) with soybean protein isolate (SPI) in the preparation of SPI-GA conjugates and hydrogels. The modified materials were primarily joined via the CN bonds and exhibited excellent antioxidant properties. In addition, spectral analysis revealed that the grafting of GA increased the flexibility of the SPI structure. The SPI-GA hydrogel is fabricated through covalent/non-covalent cross-linking mechanisms, including Schiff base, Michael addition, and hydrogen bonding. Furthermore, the microstructure, rheological properties, thermal stability, and textural properties of the hydrogel were affected by the amount of GA grafted. The SPI-GA hydrogel exhibited the best performance when the amount of GA graft was 0.015 wt%. Furthermore, the tightly cross-linked structure of SPI-GA prevented premature degradation of the protein by pepsin. In conclusion, these capabilities provide numerous possibilities for the development of multifunctional and active substance delivery carriers.

What determines sub-diffusive behavior in crowded protein solutions?

The aqueous environment inside cells is densely packed. A typical cell has a macromolecular concentration in the range 90-450 g/L, with 5%-40% of its volume being occupied by macromolecules, resulting in what is known as macromolecular crowding. The space available for the free diffusion of metabolites and other macromolecules is thus greatly reduced, leading to so-called excluded volume effects. The slow diffusion of macromolecules under crowded conditions has been explained using transient complex formation. However, sub-diffusion noted in earlier works is not well characterized, particularly the role played by transient complex formation and excluded volume effects. We have used Brownian dynamics simulations to characterize the diffusion of chymotrypsin inhibitor 2 in protein solutions of bovine serum albumin and lysozyme at concentrations ranging from 50 to 300 g/L. The predicted changes in diffusion coefficient as a function of crowder concentration are consistent with NMR experiments. The sub-diffusive behavior observed in the sub-microsecond timescale can be explained in terms of a so-called cage effect, arising from rattling motion in a local molecular cage as a consequence of excluded volume effects. By selectively manipulating the nature of interactions between protein molecules, we determined that excluded volume effects induce sub-diffusive dynamics at sub-microsecond timescales. These findings may help to explain the diffusion-mediated effects of protein crowding on cellular processes.

Autoinhibition in the Signal Transducer CIN85 Modulates B Cell Activation

Signal transduction by the ligated B cell antigen receptor (BCR) depends on the preorganization of its intracellular components, such as the effector proteins SLP65 and CIN85 within phase-separated condensates. These liquid-like condensates are based on the interaction between three Src homology 3 (SH3) domains and the corresponding proline-rich recognition motifs (PRM) in CIN85 and SLP65, respectively. However, detailed information on the protein conformation and how it impacts the capability of SLP65/CIN85 condensates to orchestrate BCR signal transduction is still lacking. This study identifies a hitherto unknown intramolecular SH3:PRM interaction between the C-terminal SH3 domain (SH3C) of CIN85 and an adjacent PRM. We used high-resolution nuclear magnetic resonance (NMR) experiments to study the flexible linker region containing the PRM and determined the extent of the interaction in multidomain constructs of the protein. Moreover, we observed that the phosphorylation of a serine residue located in the immediate vicinity of the PRM regulates this intramolecular interaction. This allows for a dynamic modulation of CIN85's valency toward SLP65. B cell culture experiments further revealed that the PRM/SH3C interaction is crucial for maintaining the physiological level of SLP65/CIN85 condensate formation, activation-induced membrane recruitment of CIN85, and subsequent mobilization of Ca2+. Our findings therefore suggest that the intramolecular interaction with the adjacent disordered linker is effective in modulating CIN85's valency both in vitro and in vivo. This therefore constitutes a powerful way for the modulation of SLP65/CIN85 condensate formation and subsequent B cell signaling processes within the cell.

Instant Protection Spray for Anti-Infection and Accelerated Healing of Empyrosis

Distinct from common injuries, deep burns often require a chronic recovery cycle for healing and long-term antibiotic treatment to prevent infection. The rise of drug-resistant bacteria has caused antibiotics to no longer be perfect, and continuous drug use can easily lead to repeated infection and even death. Inspired by wild animals that chew plants to prevent wound infection, probiotic extracts with a structure similar to the tailspike of phage are obtained from Lactobacillus casei and combined with different flavones to design a series of nonantibiotic bactericides. These novel antibacterial agents are combined with a rapid gelation spray with a novel cross-angle layout to form an instant protection spray (IPS) and provide a physical and anti-infectious barrier for burns within 30 s. This IPS is able to sterilize 100.00% and 96.14% of multidrug-resistant Staphylococcus aureus (MRSA) in vitro and in vivo, respectively. In addition, it is found to effectively reduce inflammation in MRSA-infected burns in rats and to promote tissue healing.

Nonspecificity fingerprints for clinical-stage antibodies in solution

Monoclonal antibodies (mAbs) have successfully been developed for the treatment of a wide range of diseases. The clinical success of mAbs does not solely rely on optimal potency and safety but also require good biophysical properties to ensure a high developability potential. In particular, nonspecific interactions are a key developability parameter to monitor during discovery and development. Despite an increased focus on the detection of nonspecific interactions, their underlying physicochemical origins remain poorly understood. Here, we employ solution-based microfluidic technologies to characterize a set of clinical-stage mAbs and their interactions with commonly used nonspecificity ligands to generate nonspecificity fingerprints, providing quantitative data on the underlying physical chemistry. Furthermore, the solution-based analysis enables us to measure binding affinities directly, and we evaluate the contribution of avidity in nonspecific binding by mAbs. We find that avidity can increase the apparent affinity by two orders of magnitude. Notably, we find that a subset of these highly developed mAbs show nonspecific electrostatic interactions, even at physiological pH and ionic strength, and that they can form microscale particles with charge-complementary polymers. The group of mAb constructs flagged here for nonspecificity are among the worst performers in independent reports of surface and column-based screens. The solution measurements improve on the state-of-the-art by providing a stand-alone result for individual mAbs without the need to benchmark against cohort data. Based on our findings, we propose a quantitative solution-based nonspecificity score, which can be integrated in the development workflow for biological therapeutics and more widely in protein engineering.

A computational procedure for predicting excipient effects on protein-protein affinities

Protein-protein interactions lie at the center of much biology and are a challenge in formulating biological drugs such as antibodies. A key to mitigating protein association is to use small molecule additives, i.e. excipients that can weaken protein-protein interactions. Here, we develop a computationally efficient model for predicting the viscosity-reducing effect of different excipient molecules by combining atomic-resolution MD simulations, binding polynomials and a thermodynamic perturbation theory. In a proof of principle, this method successfully rank orders four types of excipients known to reduce the viscosity of solutions of a particular monoclonal antibody. This approach appears useful for predicting effects of excipients on protein association and phase separation, as well as the effects of buffers on protein solutions.

A dual-lock-controlled mitochondria-targeted ratiometric fluorescence probe for simultaneous detection of atherosclerosis-related HClO and viscosity

Precise detection of inflammatory microenvironment-related viscosity and hypochlorous acid (HClO) contributes to illuminating the pathogenesis and further diagnosing of atherosclerosis (AS). Herein, a dual-lock-controlled mitochondria-targeted fluorescence probe (NS) for simultaneous imaging of HClO and viscosity in AS-related foam cells is presented. NS performs linear increase in green-fluorescence along with increased viscosity (excited at 425 nm), permitting "off-on" fluorescence imaging of viscosity. Meanwhile, upon HClO activation, NS exhibits red-shifted and enhanced fluorescence in orange, thus leading to ratiometric fluorescence quantification of HClO (excited at 465 nm). Such dual-lock-controlled effect makes NS realize simultaneous imaging of viscosity and HClO with high sensitivity and selectivity via "off-on" and ratiometric fluorescence readouts, respectively. Besides, endowed with mitochondria-targeting capacity, NS achieves in situ imaging of mitochondria viscosity and HClO in living RAW264.7 cells. Importantly, for the first time, NS realizes simultaneous imaging of mitochondria viscosity and HClO in macrophage-derived foam cells, revealing the close association between HClO level and viscosity change in mitochondria during foaming translation of macrophages in atherogenesis. This work not only provides a novel strategy and tool to image organelle-located viscosity and HClO in living systems, but also holds great potential in early diagnosis of AS.

In-Cell Dynamics: The Next Focus of All-Atom Simulations

The cell is a crowded space where large biomolecules and metabolites are in continuous motion. Great strides have been made in in vitro studies of protein dynamics, folding, and protein-protein interactions, and much new data are emerging of how they differ in the cell. In this Perspective, we highlight the current progress in atomistic modeling of in-cell environments, both bacteria and mammals, with emphasis on classical all-atom molecular dynamics simulations. These simulations have been recently used to capture and characterize functional and non-functional protein-protein interactions, protein folding dynamics of small proteins with varied topologies, and dynamics of metabolites. We further discuss the challenges and efforts for updating modern force fields critical to the progress of cellular environment simulations. We also briefly summarize developments in relevant state-of-the-art experimental techniques. As computational and experimental methodologies continue to progress and produce more directly comparable data, we are poised to capture the complex atomistic picture of the cell.

Viscosity Prediction of High-Concentration Antibody Solutions with Atomistic Simulations

The computational prediction of the viscosity of dense protein solutions is highly desirable, for example, in the early development phase of high-concentration biopharmaceutical formulations where the material needed for experimental determination is typically limited. Here, we use large-scale atomistic molecular dynamics (MD) simulations with explicit solvation to de novo predict the dynamic viscosities of solutions of a monoclonal IgG1 antibody (mAb) from the pressure fluctuations using a Green-Kubo approach. The viscosities at simulated mAb concentrations of 200 and 250 mg/mL are compared to the experimental values, which we measured with rotational rheometry. The computational viscosity of 24 mPa·s at the mAb concentration of 250 mg/mL matches the experimental value of 23 mPa·s obtained at a concentration of 213 mg/mL, indicating slightly different effective concentrations (or activities) in the MD simulations and in the experiments. This difference is assigned to a slight underestimation of the effective mAb-mAb interactions in the simulations, leading to a too loose dynamic mAb network that governs the viscosity. Taken together, this study demonstrates the feasibility of all-atom MD simulations for predicting the properties of dense mAb solutions and provides detailed microscopic insights into the underlying molecular interactions. At the same time, it also shows that there is room for further improvements and highlights challenges, such as the massive sampling required for computing collective properties of dense biomolecular solutions in the high-viscosity regime with reasonable statistical precision.

Biophysical Determinants for the Viscosity of Concentrated Monoclonal Antibody Solutions

Monoclonal antibodies (mAbs) are particularly relevant for therapeutics due to their high specificity and versatility, and mAb-based drugs are hence used to treat numerous diseases. The increased patient compliance of self-administration motivates the formulation of products for subcutaneous (SC) administration. The associated challenge is to formulate highly concentrated antibody solutions to achieve a significant therapeutic effect, while limiting their viscosity and preserving their physicochemical stability. Protein-protein interactions (PPIs) are in fact the root cause of several potential problems concerning the stability, manufacturability, and delivery of a drug product. The understanding of macroscopic viscosity requires an in-depth knowledge on protein diffusion, PPIs, and self-association/aggregation. Here, we study the self-diffusion of different mAbs of the IgG1 subtype in aqueous solution as a function of the concentration and temperature by quasi-elastic neutron scattering (QENS). QENS allows us to probe the short-time self-diffusion of the molecules and therefore to determine the hydrodynamic mAb cluster size and to gain information on the internal mAb dynamics. Small-angle neutron scattering (SANS) is jointly employed to probe structural details and to understand the nature and intensity of PPIs. Complementary information is provided by molecular dynamics (MD) simulations and viscometry, thus obtaining a comprehensive picture of mAb diffusion.

Single-molecule tracking to determine the abundances and stoichiometries of freely-diffusing protein complexes in living cells: Past applications and future prospects

Most biological processes in living cells rely on interactions between proteins. Live-cell compatible approaches that can quantify to what extent a given protein participates in homo- and hetero-oligomeric complexes of different size and subunit composition are therefore critical to advance our understanding of how cellular physiology is governed by these molecular interactions. Biomolecular complex formation changes the diffusion coefficient of constituent proteins, and these changes can be measured using fluorescence microscopy-based approaches, such as single-molecule tracking, fluorescence correlation spectroscopy, and fluorescence recovery after photobleaching. In this review, we focus on the use of single-molecule tracking to identify, resolve, and quantify the presence of freely-diffusing proteins and protein complexes in living cells. We compare and contrast different data analysis methods that are currently employed in the field and discuss experimental designs that can aid the interpretation of the obtained results. Comparisons of diffusion rates for different proteins and protein complexes in intracellular aqueous environments reported in the recent literature reveal a clear and systematic deviation from the Stokes-Einstein diffusion theory. While a complete and quantitative theoretical explanation of why such deviations manifest is missing, the available data suggest the possibility of weighing freely-diffusing proteins and protein complexes in living cells by measuring their diffusion coefficients. Mapping individual diffusive states to protein complexes of defined molecular weight, subunit stoichiometry, and structure promises to provide key new insights into how protein-protein interactions regulate protein conformational, translational, and rotational dynamics, and ultimately protein function.

Diffusive intracellular interactions: On the role of protein net charge and functional adaptation

A striking feature of nucleic acids and lipid membranes is that they all carry net negative charge and so is true for the majority of intracellular proteins. It is suggested that the role of this negative charge is to assure a basal intermolecular repulsion that keeps the cytosolic content suitably 'fluid' for function. We focus in this review on the experimental, theoretical and genetic findings which serve to underpin this idea and the new questions they raise. Unlike the situation in test tubes, any functional protein-protein interaction in the cytosol is subject to competition from the densely crowded background, i.e. surrounding stickiness. At the nonspecific limit of this stickiness is the 'random' protein-protein association, maintaining profuse populations of transient and constantly interconverting complexes at physiological protein concentrations. The phenomenon is readily quantified in studies of the protein rotational diffusion, showing that the more net negatively charged a protein is the less it is retarded by clustering. It is further evident that this dynamic protein-protein interplay is under evolutionary control and finely tuned across organisms to maintain optimal physicochemical conditions for the cellular processes. The emerging picture is then that specific cellular function relies on close competition between numerous weak and strong interactions, and where all parts of the protein surfaces are involved. The outstanding challenge is now to decipher the very basics of this many-body system: how the detailed patterns of charged, polar and hydrophobic side chains not only control protein-protein interactions at close- and long-range but also the collective properties of the cellular interior as a whole.

Protein compactness and interaction valency define the architecture of a biomolecular condensate across scales

Non-membrane-bound biomolecular condensates have been proposed to represent an important mode of subcellular organization in diverse biological settings. However, the fundamental principles governing the spatial organization and dynamics of condensates at the atomistic level remain unclear. The Saccharomyces cerevisiae Lge1 protein is required for histone H2B ubiquitination and its N-terminal intrinsically disordered fragment (Lge11-80) undergoes robust phase separation. This study connects single- and multi-chain all-atom molecular dynamics simulations of Lge11-80 with the in vitro behavior of Lge11-80 condensates. Analysis of modeled protein-protein interactions elucidates the key determinants of Lge11-80 condensate formation and links configurational entropy, valency, and compactness of proteins inside the condensates. A newly derived analytical formalism, related to colloid fractal cluster formation, describes condensate architecture across length scales as a function of protein valency and compactness. In particular, the formalism provides an atomistically resolved model of Lge11-80 condensates on the scale of hundreds of nanometers starting from individual protein conformers captured in simulations. The simulation-derived fractal dimensions of condensates of Lge11-80 and its mutants agree with their in vitro morphologies. The presented framework enables a multiscale description of biomolecular condensates and embeds their study in a wider context of colloid self-organization.

Subclass Effects on Self-Association and Viscosity of Monoclonal Antibodies at High Concentrations

The effects of a subclass of monoclonal antibodies (mAbs) on protein-protein interactions, formation of reversible oligomers (clusters), and viscosity (η) are not well understood at high concentrations. Herein, we quantify a short-range anisotropic attraction between the complementarity-determining region (CDR) and CH3 domains (K_CDR-CH3) for vedolizumab IgG1, IgG2, or IgG4 subclasses by fitting small-angle X-ray scattering (SAXS) structure factor S_eff(q) data with an extensive library of 12-bead coarse-grained (CG) molecular dynamics simulations. The K_CDR-CH3 bead attraction strength was isolated from the strength of long-range electrostatic repulsion for the full mAb, which was determined from the theoretical net charge and a scaling parameter ψ to account for solvent accessibility and ion pairing. At low ionic strength (IS), the strongest short-range attraction (K_CDR-CH3) and consequently the largest clusters and highest η were observed with IgG1, the subclass with the most positively charged CH3 domain. Furthermore, the trend in K_CDR-CH3 with the subclass followed the electrostatic interaction energy between the CDR and CH3 regions calculated with the BioLuminate software using the 3D mAb structure and molecular interaction potentials. Whereas the equilibrium cluster size distributions and fractal dimensions were determined from fits of SAXS with the MD simulations, the degree of cluster rigidity under flow was estimated from the experimental η with a phenomenological model. For the systems with the largest clusters, especially IgG1, the inefficient packing of mAbs in the clusters played the largest role in increasing η, whereas for other systems, the relative contribution from stress produced by the clusters was more significant. The ability to relate η to short-range attraction from SAXS measurements at high concentrations and to theoretical characterization of electrostatic patches on the 3D surface is not only of fundamental interest but also of practical value for mAb discovery, processing, formulation, and subcutaneous delivery.

Optimized OPEP Force Field for Simulation of Crowded Protein Solutions

Macromolecular crowding has profound effects on the mobility of proteins, with strong implications on the rates of intracellular processes. To describe the dynamics of crowded environments, detailed molecular models are needed, capturing the structures and interactions arising in the crowded system. In this work, we present OPEPv7, which is a coarse-grained force field at amino-acid resolution, suited for rigid-body simulations of the structure and dynamics of crowded solutions formed by globular proteins. Using the OPEP protein model as a starting point, we have refined the intermolecular interactions to match the experimentally observed dynamical slowdown caused by crowding. The resulting force field successfully reproduces the diffusion slowdown in homogeneous and heterogeneous protein solutions at different crowding conditions. Coupled with the lattice Boltzmann technique, it allows the study of dynamical phenomena in protein assemblies and opens the way for the in silico rheology of protein solutions.

Controlling the assembly of soy β-conglycinin to fabricate heat-stable particles for high protein liquid systems

BACKGROUND

Recently, there is a growing interest in developing protein-fortified liquid systems, which are formulated to provide special nutrient combinations to those with special dietary needs. The fabrication of heat-stable protein for protein-fortified liquid systems relies heavily on precise control of the edible protein-building process.

RESULTS

Results suggested that heat-stable 7S protein particles (7SPPs) could be obtained by preheating at 100 °C for an extended time, whereas 7S proteins with better gelling properties were discovered after preheating at lower temperatures. According to the findings of the protein conformational and morphological characterization, the 7SPPs showed rather stable tertiary and secondary structures as well as size distributions, which might be responsible for their heat stability. Additionally, during the reheating test, suspensions of 7SPPs showed no signs of gelation and had a low viscosity even though the protein content was as high as 120 mg mL^-1 . However, 7S proteins with improved gelling properties were found to show rising aggregate size, higher susceptibility and larger conformational structure changing rates upon reheating treatment.

CONCLUSION

Soy β-conglycinin (7S) proteins with tunable heat stability were successfully prepared by preheating 10 mg mL^-1 protein dispersions at various temperatures (80-120 °C) and durations (15-120 min). These findings provide fundamental insights for developing 7S-based protein-fortified systems. © 2023 Society of Chemical Industry.

Evaluation and Screening of Biopharmaceuticals using Multi-Angle Dynamic Light Scattering

Biopharmaceuticals are large, complex and labile therapeutic molecules prone to instability due to various factors during manufacturing. To ensure their safety, quality and efficacy, a wide range of critical quality attributes (CQAs) such as product concentration, aggregation, particle size, purity and turbidity have to be met. Size exclusion chromatography (SEC) is the gold standard to measure protein aggregation and degradation. However, other techniques such as dynamic light scattering (DLS) are employed in tandem to measure the particle size distribution (PSD) and polydispersity of biopharmaceutical formulations. In this study, the application of multi-angle dynamic light scattering (MADLS) was evaluated for the determination of particle size, particle concentration and aggregation in 3 different protein modalities, namely bovine serum albumin (BSA) and two biopharmaceuticals including a monoclonal antibody (mAb) and an enzyme. The obtained calibration curve (R² > 0.95) for the particle number concentration of the 3 proteins and the observed correlation between MADLS and SEC (R² = 0.9938) for the analysis of aggregation in the enzyme can be employed as a 3-in-1 approach to assessing particle size, concentration and aggregation for the screening and development of products while also reducing the number of samples and experiments required for analysis prior to other orthogonal tests.

Conformational Changes and Drivers of Monoclonal Antibody Liquid-Liquid Phase Separation

Liquid-liquid phase separation is a phenomenon within biology whereby proteins can separate into dense and more dilute phases with distinct properties. Three antibodies that undergo liquid-liquid phase separation were characterized in the protein-rich and protein-poor phases. In comparison to the protein-poor phase, the protein-rich phase demonstrates more blue-shift tryptophan emissions and red-shifted amide I absorbances. Large changes involving conformational isomerization around disulfide bonds were observed using Raman spectroscopy. Amide I and protein fluorescence differences between the phases persisted to temperatures above the critical temperature but ceased at the temperature at which aggregation occurred. In addition, large changes occurred in the structural organization of water molecules within the protein-rich phase for all three antibodies. It is hypothesized that as the proteins have the same chemical potential in both phases, the protein viscosity is higher in the protein-rich phase resulting in slowed diffusion dependent protein aggregation in this phase. For all three antibodies we performed accelerated stability studies and found that the protein-rich phase aggregated at the same rate or slower than the protein-poor phase.

AF4 and PEG Precipitation as Predictive Assays for Antibody Self-Association

Monoclonal antibodies (mAbs) are often formulated as high-protein-concentration solutions, which in some cases can exhibit physical stability issues such as high viscosity and opalescence. To ensure that mAb-based drugs can meet their manufacturing, stability, and delivery requirements, it is advantageous to screen for and select mAbs during discovery that are not prone to such behaviors. It has been recently shown that both these macroscopic properties can be predicted to a certain extent from the diffusion interaction parameter (k_D), which is a measure of self-association under dilute conditions.¹ However, k_D can be challenging to measure at the early stage of discovery, where a relatively large amount of a high-purity material, which is required by traditional methods, is often not available. In this study, we demonstrate asymmetric field-flow fractionation (AF4) as a tool to measure self-association and therefore identify antibodies with problematic issues at high concentrations. The principle lies on the ability to concentrate the sample close to the membrane during the injection mode, which can reach formulation-relevant concentrations (>100 mg/mL).² By analyzing a well-characterized library of commercial antibodies, we show that the measured retention time of the antibodies allows us to pinpoint molecules that exhibit issues at high concentrations. Remarkably, our AF4 assay requires very little (30 μg) sample under dilute conditions and does not need extensive sample purification. Furthermore, we show that a polyethylene glycol (PEG) precipitation assay provides results consistent with AF4 and moreover can further differentiate molecules with issues of opalescence or high viscosity. Overall, our results delineate a two-step strategy for the identification of problematic variants at high concentrations, with AF4 for early developability screening, followed by a PEG assay to validate the problematic molecules and further discriminate between opalescence or high-viscosity issues. This two-step antibody selection strategy enables us to select antibodies early in the discovery process, which are compatible with high-concentration formulations.

Vitreous Humor: Composition, Characteristics and Implication on Intravitreal Drug Delivery

Purpose: Intravitreal administration of drug molecules is one of the most common routes for treating posterior segment eye diseases. However, the properties of vitreous humour changes with the time. A number of ocular complications such as liquefaction of the vitreous humour, solidification of the vitreous humour in the central vitreous cavity and detachment of the limiting membrane due to the shrinking of vitreous humour are some of the factors that can drastically affect the efficacy of therapeutics delivered via intravitreal route. Although significant research has been conducted for studying the properties of vitreous humour and its changes during the ageing process, there have been limited work to understand the effect of these changes on therapeutic efficacy of intravitreal drug delivery systems. Therefore, in this review we discussed both the coomposition and characteristics of the vitreous humour, and their subsequent influence on intravitreal drug delivery.Methods: Articles were searched on Scopus, PubMed and Web of Science up to March 2022.Results: In this review, we discussed the biological composition and biomechanical properties of vitreous humour, methods to study the properties of vitreous humour and the changes in these properties and their relevance in ocular drug delivery field, with the aim to provide a useful insight into these aspects which can aid the process of development of novel intravitreal drug delivery systems.Conclusions: The composition and characteristics of the vitreous humour, and how these change during natural aging processes, directly influence intravitreal drug delivery. This review therefore highlights the importance of understanding the properties of the vitreous and identifies the need to achieve greater understanding of how changing properties of the vitreous affect the therapeutic efficacy of drugs administered for the treatment of posterior eye diseases.

Diffusive Dynamics of Bacterial Proteome as a Proxy of Cell Death

Temperature variations have a big impact on bacterial metabolism and death, yet an exhaustive molecular picture of these processes is still missing. For instance, whether thermal death is determined by the deterioration of the whole or a specific part of the proteome is hotly debated. Here, by monitoring the proteome dynamics of E. coli, we clearly show that only a minor fraction of the proteome unfolds at the cell death. First, we prove that the dynamical state of the E. coli proteome is an excellent proxy for temperature-dependent bacterial metabolism and death. The proteome diffusive dynamics peaks at about the bacterial optimal growth temperature, then a dramatic dynamical slowdown is observed that starts just below the cell's death temperature. Next, we show that this slowdown is caused by the unfolding of just a small fraction of proteins that establish an entangling interprotein network, dominated by hydrophobic interactions, across the cytoplasm. Finally, the deduced progress of the proteome unfolding and its diffusive dynamics are both key to correctly reproduce the E. coli growth rate.

A brief history of visualizing membrane systems in molecular dynamics simulations

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

Effects of External Perturbations on Protein Systems: A Microscopic View

Protein folding can be viewed as the origami engineering of biology resulting from the long process of evolution. Even decades after its recognition, research efforts worldwide focus on demystifying molecular factors that underlie protein structure-function relationships; this is particularly relevant in the era of proteopathic disease. A complex co-occurrence of different physicochemical factors such as temperature, pressure, solvent, cosolvent, macromolecular crowding, confinement, and mutations that represent realistic biological environments are known to modulate the folding process and protein stability in unique ways. In the current review, we have contextually summarized the substantial efforts in unveiling individual effects of these perturbative factors, with major attention toward bottom-up approaches. Moreover, we briefly present some of the biotechnological applications of the insights derived from these studies over various applications including pharmaceuticals, biofuels, cryopreservation, and novel materials. Finally, we conclude by summarizing the challenges in studying the combined effects of multifactorial perturbations in protein folding and refer to complementary advances in experiment and computational techniques that lend insights to the emergent challenges.

A mechanistic model of cross-bridge migration in RBC aggregation and disaggregation

Red blood cells (RBCs) clump together under low flow conditions in a process called RBC aggregation, which can alter RBC perfusion in a microvascular network. As elevated RBC aggregation is commonly associated with cardiovascular and inflammatory diseases, a better understanding of aggregation is essential. Unlike RBC aggregation in polymer solutions which can be well explained by polymer depletion theory, plasma-mediated RBC aggregation has features that best match explanations with cross-bridging mechanisms. Previous studies have demonstrated the dominant role of fibrinogen (Fg) in promoting aggregate formation and recent cell-force spectroscopy (CFS) experiments on interacting RBC doublets in plasma have reported an inverse relationship between disaggregation force and the adhesive contact area between RBCs. This has led investigators to revisit the hypothesis of inter-RBC cross-bridging which involves cross-bridge migration under interfacial tension during the forced disaggregation of RBC aggregates. In this study, we developed the cross-bridge migration model (CBMM) in plasma that mechanistically represents the migrating cross-bridge hypothesis. Transport of mobile Fg cross-bridges (mFg) was calculated using a convection-diffusion transport equation with our novel introduction of convective cross-bridge drift that arises due to intercellular friction. By parametrically transforming the diffusivity of mFg in the CBMM, we were able to match experimental observations of both RBC doublet formation kinematics and RBC doublet disaggregation forces under optical tweezers tension. We found that non-specific cross-bridging promotes spontaneous growth of adhesion area between RBC doublets whereas specific cross-bridging tends to prevent adhesion area growth. Our CBMM was also able to correlate Fg concentration shifts from healthy population blood plasma to SLE (lupus) condition blood plasma with the observed increase in doublet disaggregation forces for the RBC doublets in SLE plasma.

Characterizing Transient Protein-Protein Interactions by Trp-Cys Quenching and Computer Simulations

Transient protein-protein interactions occur frequently under the crowded conditions encountered in biological environments. Tryptophan-cysteine quenching is introduced as an experimental approach with minimal labeling for characterizing such interactions between proteins due to its sensitivity to nano- to microsecond dynamics on subnanometer length scales. The experiments are paired with computational modeling at different resolutions including fully atomistic molecular dynamics simulations for interpretation of the experimental observables and to gain molecular-level insights. This approach is applied to model systems, villin variants and the drkN SH3 domain, in the presence of protein G crowders. It is demonstrated that Trp-Cys quenching experiments can differentiate between overall attractive and repulsive interactions between different proteins, and they can discern variations in interaction preferences at different protein surface locations. The close integration between experiment and simulations also provides an opportunity to evaluate different molecular force fields for the simulation of concentrated protein solutions.

Brownian dynamics simulations of hard rods in external fields and with contact interactions

We propose a simulation method for Brownian dynamics of hard rods in one dimension for arbitrary continuous external force fields. It is an event-driven procedure based on the fragmentation and mergers of clusters formed by particles in contact. It allows one to treat particle interactions in addition to the hard-sphere exclusion as long as the corresponding interaction forces are continuous functions of the particle coordinates. We furthermore develop a treatment of sticky hard spheres as described by Baxter's contact interaction potential.

Biomimetic Bacteriophage-Like Particles Formed from Probiotic Extracts and NO Donors for Eradicating Multidrug-Resistant Staphylococcus aureus

Effectively clearing multidrug-resistant bacteria through nonantibiotic treatments is crucial for the recovery of infected tissues in favorable biological environments. Herein, a thermally responsive donor of cell-messenger nitric oxide (NO) is combined with extracts of food-grade Lactobacillus casei to form biomimetic phage-like microparticles with a tailspike structure. These particles can invade bacterial membranes and release NO to disrupt nitrogen and respiratory metabolisms, which initiates the programmed death of multidrug-resistant Staphylococcus aureus (MRSA) for inducing lysis, like the bacterial virus. Experiments suggest that these microparticles can also weaken bacterial toxicity and provide favorable conditions for cell proliferation because of the continuously released NO. By encapsulating these microparticles into graphene-oxide-doped polymers, a dual-mode antibacterial hydrogel (DMAH) can be constructed. In vivo results reveal that the DMAH achieves a long-time sterilization of MRSA with 99.84 ± 0.13% antibacterial rate in the dark because of the phage-like performance of the biomimetic microparticles. In its other antibacterial mode, DMAH subjected to 20 min of near-infrared irradiation release NO, which, together with the photothermal effect, synergistically damages bacterial cell membranes to achieve very fast disinfection (97.13 ± 0.41% bactericidal rate). This multifunctional hydrogel can also significantly accelerate wound healing due to the phage-like particles.

Diffusion of small molecule drugs is affected by surface interactions and crowder proteins

Crowded environments are known to affect the diffusion of macromolecules, but their effects on the diffusion of small molecules are largely uncharacterized. We investigate how three protein crowders, bovine serum albumin (BSA), hen egg-white lysozyme, and myoglobin, influence the diffusion rates and interactions of four small molecules: fluorescein, and three drugs, doxorubicin, glycogen synthase kinase-3 inhibitor SB216763, and quinacrine. Using Line-FRAP measurements, Brownian dynamics simulations, and molecular docking, we find that the diffusion rates of the small molecules are highly affected by self-aggregation, interactions with the proteins, and surface adsorption. The diffusion of fluorescein is decreased because of its interactions with the protein crowders and their surface adsorption. Protein crowders increase the diffusion rates of doxorubicin and SB216763 by reducing surface interactions and self-aggregation, respectively. Quinacrine diffusion was not affected by protein crowders. The mechanistic insights gained here may assist in optimization of compounds for higher mobility in complex macromolecular environments.

Docking-based long timescale simulation of cell-size protein systems at atomic resolution

Computational methodologies are increasingly addressing modeling of the whole cell at the molecular level. Proteins and their interactions are the key component of cellular processes. Techniques for modeling protein interactions, thus far, have included protein docking and molecular simulation. The latter approaches account for the dynamics of the interactions but are relatively slow, if carried out at all-atom resolution, or are significantly coarse grained. Protein docking algorithms are far more efficient in sampling spatial coordinates. However, they do not account for the kinetics of the association (i.e., they do not involve the time coordinate). Our proof-of-concept study bridges the two modeling approaches, developing an approach that can reach unprecedented simulation timescales at all-atom resolution. The global intermolecular energy landscape of a large system of proteins was mapped by the pairwise fast Fourier transform docking and sampled in space and time by Monte Carlo simulations. The simulation protocol was parametrized on existing data and validated on a number of observations from experiments and molecular dynamics simulations. The simulation protocol performed consistently across very different systems of proteins at different protein concentrations. It recapitulated data on the previously observed protein diffusion rates and aggregation. The speed of calculation allows reaching second-long trajectories of protein systems that approach the size of the cells, at atomic resolution.

Cell-Size Space Regulates the Behavior of Confined Polymers: From Nano- and Micromaterials Science to Biology

Polymer micromaterials in a liquid or gel phase covered with a surfactant membrane are widely used materials in pharmaceuticals, cosmetics, and foods. In particular, cell-sized micromaterials of biopolymer solutions covered with a lipid membrane have been studied as artificial cells to understand cells from a physicochemical perspective. The characteristics and phase transitions of polymers confined to a microscopic space often differ from those in bulk systems. The effect that causes this difference is referred to as the cell-size space effect (CSE), but the specific physicochemical factors remain unclear. This study introduces the analysis of CSE on molecular diffusion, nanostructure transition, and phase separation and presents their main factors, i.e., short- and long-range interactions with the membrane surface and small volume (finite element nature). This serves as a guide for determining the dominant factors of CSE. Furthermore, we also introduce other factors of CSE such as spatial closure and the relationships among space size, the characteristic length of periodicity, the structure size, and many others produced by biomolecular assemblies through the analysis of protein reaction-diffusion systems and biochemical reactions.

Resolving molecular diffusion and aggregation of antibody proteins with megahertz X-ray free-electron laser pulses

X-ray free-electron lasers (XFELs) with megahertz repetition rate can provide novel insights into structural dynamics of biological macromolecule solutions. However, very high dose rates can lead to beam-induced dynamics and structural changes due to radiation damage. Here, we probe the dynamics of dense antibody protein (Ig-PEG) solutions using megahertz X-ray photon correlation spectroscopy (MHz-XPCS) at the European XFEL. By varying the total dose and dose rate, we identify a regime for measuring the motion of proteins in their first coordination shell, quantify XFEL-induced effects such as driven motion, and map out the extent of agglomeration dynamics. The results indicate that for average dose rates below 1.06 kGy μs^-1 in a time window up to 10 μs, it is possible to capture the protein dynamics before the onset of beam induced aggregation. We refer to this approach as correlation before aggregation and demonstrate that MHz-XPCS bridges an important spatio-temporal gap in measurement techniques for biological samples.

Modified Protein-Water Interactions in CHARMM36m for Thermodynamics and Kinetics of Proteins in Dilute and Crowded Solutions

Proper balance between protein-protein and protein-water interactions is vital for atomistic molecular dynamics (MD) simulations of globular proteins as well as intrinsically disordered proteins (IDPs). The overestimation of protein-protein interactions tends to make IDPs more compact than those in experiments. Likewise, multiple proteins in crowded solutions are aggregated with each other too strongly. To optimize the balance, Lennard-Jones (LJ) interactions between protein and water are often increased about 10% (with a scaling parameter, λ = 1.1) from the existing force fields. Here, we explore the optimal scaling parameter of protein-water LJ interactions for CHARMM36m in conjunction with the modified TIP3P water model, by performing enhanced sampling MD simulations of several peptides in dilute solutions and conventional MD simulations of globular proteins in dilute and crowded solutions. In our simulations, 10% increase of protein-water LJ interaction for the CHARMM36m cannot maintain stability of a small helical peptide, (AAQAA)₃ in a dilute solution and only a small modification of protein-water LJ interaction up to the 3% increase (λ = 1.03) is allowed. The modified protein-water interactions are applicable to other peptides and globular proteins in dilute solutions without changing thermodynamic properties from the original CHARMM36m. However, it has a great impact on the diffusive properties of proteins in crowded solutions, avoiding the formation of too sticky protein-protein interactions.