Reduced native state stability in crowded cellular environment due to protein-protein interactions

BEMM-GEN: A Toolkit for Generating a Biomolecular Environment-Mimicking Model for Molecular Dynamics Simulation

Understanding the influence of the cellular environment on protein conformations is crucial for elucidating protein functions within living cells. In studies using molecular dynamics (MD) simulation, carbon nanotubes and hydrophobic cages have been widely used to emulate the cellular environment inside specific large biomolecules such as ribosome tunnels and chaperones. However, recent studies suggest that these uniform hydrophobic models may not adequately capture the environmental effects inside each biomolecule. Based on these facts, it is necessary to generate spherical and cylindrical models with varied chemical properties corresponding to the components within target biomolecules. We developed a biomolecular environment-mimicking model generator (BEMM-GEN) that generates spherical and cylindrical models with user-specified chemical properties and allows the integration of arbitrary protein conformations into the generated models. BEMM-GEN provides model and protein complex structures, along with the corresponding parameter files for MD simulation (AMBER and GROMACS), and users immediately run their MD simulation based on the generated input files. BEMM-GEN can be freely downloaded and installed via a Python package manager (pip install BEMM-gen). The source code files and a user manual for operation are provided on GitHub (https://github.com/y4suda/BEMM-GEN).

Ribosome Tunnel Environment Drives the Formation of α-Helix during Cotranslational Folding

Protein conformations in cells are not solely determined by amino acid sequences; they also depend on cellular environments. For instance, the ribosome tunnel induces its specific α-helix formation during cotranslational folding. Owing to the link between these temporally α-helix and biological functions, the mechanism of α-helix formation inside the ribosome tunnel has been previously explored. Consequently, the conformational restrictions of the tunnel were considered one of the driving forces of α-helix formation. Conversely, the ribosomal tunnel environment, including its chemical properties, appears to influence the α-helix formation. However, a comprehensive analysis of the ribosome tunnel environment's impact on the α-helix formation has not been conducted yet due to challenges in experimentally controlling it. Therefore, as a new computational approach, we proposed a ribosome environment-mimicking model (REMM) based on the radius and components of the experimentally determined ribosome tunnel structures. Using REMM, we assessed the impact of the ribosome tunnel environment on α-helix formation. Herein, we employed carbon nanotubes (CNT) as a reference model alongside REMM because CNT reproduce conformational restrictions rather than the ribosome tunnel environment. Quantitatively, the ability to reproduce the α-helix of nascent peptides in the experimental structure was compared between the CNT and REMM using enhanced all-atom molecular dynamics simulations. Consequently, the REMM more accurately reproduced the α-helix of the nascent peptides than the CNT, highlighting the significance of the ribosome tunnel environment in α-helix formation. Additionally, we analyzed the properties of the peptide inside each model to reveal the mechanism of ribosome tunnel-specific α-helix formation. Consequently, we revealed that the chemical diversities of the tunnel are essential for the formation of backbone-to-backbone hydrogen bonds in the peptides. In conclusion, the ribosome tunnel environment, with the diverse chemical properties, drives its specific α-helix formation. By proposing REMM, we newly provide the technical basis for investigating the protein conformations in various cellular environments.

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.

Bridging Soft Interaction and Excluded Volume in Crowded Milieu through Subtle Protein Dynamics

The impact of macromolecular crowding on biological macromolecules has been elucidated through the excluded volume phenomenon and soft interactions. However, it has often been difficult to provide a clear demarcation between the two regions. Here, using temperature-dependent dynamics (local and global) of the multidomain protein human serum albumin (HSA) in the presence of commonly used synthetic crowders (Dextran 40, PEG 8, Ficoll 70, and Dextran 70), we have shown the presence of a transition that serves as a bridge between the soft and hard regimes. The bridging region is independent of the crowder identity and displays no apparent correlation with the critical overlap concentration of the polymeric crowding agents. Moreover, the dynamics of domains I and II and the protein gating motion respond differently, thereby bringing to the fore the asymmetry underlying the crowder influence on HSA. In addition, solvent-coupled and decoupled protein motions indicate the heterogeneity of the dynamic landscape in the crowded milieu. We also propose an intriguing correlation between protein stability and dynamics, with increased global stability being accompanied by eased local domain motion.

Differential local ordering of mixed crowders determines effective size and stability of ss-DNA capped gold nanoparticle

Understanding the influence of a crowded intracellular environment on the structure and solvation of DNA functionalized gold nanoparticles (ss-DNA AuNP) is necessary for designing applications in nanomedicine. In this study, the effect of single (Gly, Ser, Lys) and mixture of amino acids (Gly+Ser, Gly+Lys, Ser+Lys) at crowded concentrations is examined on the structure of the ss-DNA AuNP using molecular dynamics simulations. Using the structural estimators such as pair correlation functions and ligand shell positional fluctuations, the solvation entropy is estimated. Combining the AuNP-solvent interaction energy with the solvation entropy estimates, the free energy of solvation of the AuNP in crowded solutions is computed. The solvation entropy favours the solvation free energy which becomes more favourable for larger effective size of AuNP in crowded solutions relative to that in water. The effective size of AuNP depends on the different propensity of the crowders to adsorb on Au surface, with the smallest crowder (Gly) having the highest propensity inducing the least effective AuNP size as compared to other single crowder solutions. In mixed crowded solutions of amino acids of variable size and chemistry, distinctive local adsorption of the crowders on the gold surface is observed that controls the additive or non-additive crowding effects which govern an increase (in Gly+Ser) or decrease (in Gly+Lys) in nanoparticle effective size respectively. The results shed light into the fundamental understanding of the influence of intracellular crowding on structure of ss-DNA AuNP and plausible employability of crowding as a tool to design programmable self-assembly of functionalized nanoparticles.

Induced Circular Dichroism Analysis of Thermally Induced Conformational Changes on Protein Binding Sites Under a Crowding Environment

Protein-ligand interactions in crowded cellular environments play a crucial role in biological functions. The crowded environment can perturb the overall protein structure and local conformation, thereby influencing the binding pathway of protein-ligand reactions within the cellular milieu. Therefore, a detailed understanding of the local conformation is crucial for elucidating the intricacies of protein-ligand interactions in crowded cellular environments. In this study, we investigated the feasibility of induced circular dichroism (ICD) using 8-anilinonaphthalene-1-sulfonic acid (ANS) for local conformational analysis at the binding site in a crowding environment. Bovine serum albumin (BSA) concentration-dependent measurements were performed to assess the feasibility of ANS-ICD for analyzing protein interior binding sites. The results showed distinct changes in the ANS-ICD spectra of BSA solutions, indicating their potential for analyzing the internal conformation of proteins. Moreover, temperature-dependent measurements were performed in dilute and crowding environments, revealing distinct denaturation pathways of BSA binding sites. Principal component analysis of ANS-ICD spectral changes revealed lower temperature pre-denaturation in the crowded solution than that in the diluted solution, suggesting destabilization of binding sites owing to self-crowding repulsive interactions. The established ANS-ICD method can provide valuable conformational insights into protein-ligand interactions in crowded cellular environments.

Glycosylation and Crowded Membrane Effects on Influenza Neuraminidase Stability and Dynamics

All protein simulations are conducted with varying degrees of simplification, oftentimes with unknown ramifications about how these simplifications affect the interpretability of the results. In this work, we investigated how protein glycosylation and lateral crowding effects modulate an array of properties characterizing the stability and dynamics of influenza neuraminidase. We constructed three systems: (1) glycosylated neuraminidase in a whole virion (i.e., crowded membrane) environment, (2) glycosylated neuraminidase in its own lipid bilayer, and (3) unglycosylated neuraminidase in its own lipid bilayer. We saw that glycans tend to stabilize the protein structure and reduce its conformational flexibility while restricting the solvent movement. Conversely, a crowded membrane environment encouraged exploration of the free energy landscape and a large-scale conformational change, while making the protein structure more compact. Understanding these effects informs what factors one must consider in attempting to recapture the desired level of physical accuracy.

Glycosylation and Crowded Membrane Effects on Influenza Neuraminidase Stability and Dynamics

All protein simulations are conducted with varying degrees of simplifications, oftentimes with unknown ramifications on how these simplifications affect the interpretability of the results. In this work we investigated how protein glycosylation and lateral crowding effects modulate an array of properties characterizing the stability and dynamics of influenza neuraminidase. We constructed three systems: 1) Glycosylated neuraminidase in a whole virion (i.e. crowded membrane) environment 2) Glycosylated neuraminidase in its own lipid bilayer 3) Unglycosylated neuraminidase in its own lipid bilayer. We saw that glycans tend to stabilize the protein structure and reduce its conformational flexibility while restricting solvent movement. Conversely, a crowded membrane environment encouraged exploration of the free energy landscape and a large scale conformational change while making the protein structure more compact. Understanding these effects informs what factors one must consider while attempting to recapture the desired level of physical accuracy.

Ethylene glycol energetically disfavours oligomerization of pseudoisocyanine dyestuffs at crowded concentrations

The intriguing role of the intracellular crowded environment in regulating protein aggregation remains elusive. The convolution of several factors such as the protein sequence-dependence, crowder's shape and size and diverse intermolecular interactions makes it complex to identify systematic trends. One of the ways to simplify the problem is to study a synthetic model for self-assembling proteins. In this study, we examine the aggregation behaviour of the cationic pseudoisocyanine chloride (PIC) dyestuff which is known to self-assemble and form fibril-like J-aggregates in aqueous solutions, similar to those formed by amyloid-forming proteins. Prior experimental studies have shown that polyethylene glycol impedes and Ficoll-400 promotes the self-assembly of PIC dyes. To achieve molecular insights, we examine the effect of crowding by ethylene glycol on the solvation thermodynamics of oligomerization of dyes into H-type and J-type oligomers using extensive molecular dynamics simulations. The binding free energy calculations show that the formation of J-oligomers is more favourable than that of H-oligomers in water. The stability of H- and J- tetramers and pentamers decreases in crowded solutions. The formation of oligomers is supported by the favourable change in dye-solvent interaction energy in both pure water and aqueous ethylene glycol solution although it is opposed by the reduced dye-solvent entropy. Ethylene glycol, as a molecular crowder, disfavours the H- as well as J-oligomerization via preferential binding to the dye oligomers. An unfavourable change in dye-crowder and dye-dye interaction energy on dye association makes the H-oligomer formation less favourable in crowded solution than in pure water solution. In the case of J-oligomers, however, the unfavourable change in dye-crowder interaction energy primarily contributes to making total dye-solvent energy unfavourable. The results are supported by isothermal titration calorimetry measurements where the binding of ethylene glycol to PIC molecules is found to be endothermic. The results provide an emerging view that a crowded environment can disfavour self-assembly of PIC dyes by interactions with the oligomeric states. The findings have implications in understanding the role of a crowded environment in shaping the free energy landscapes of proteins.

Acceleration of generalized replica exchange with solute tempering simulations of large biological systems on massively parallel supercomputer

Generalized replica exchange with solute tempering (gREST) is one of the enhanced sampling algorithms for proteins or other systems with rugged energy landscapes. Unlike the replica-exchange molecular dynamics (REMD) method, solvent temperatures are the same in all replicas, while solute temperatures are different and are exchanged frequently between replicas for exploring various solute structures. Here, we apply the gREST scheme to large biological systems containing over one million atoms using a large number of processors in a supercomputer. First, communication time on a multi-dimensional torus network is reduced by matching each replica to MPI processors optimally. This is applicable not only to gREST but also to other multi-copy algorithms. Second, energy evaluations, which are necessary for the multistate bennet acceptance ratio (MBAR) method for free energy estimations, are performed on-the-fly during the gREST simulations. Using these two advanced schemes, we observed 57.72 ns/day performance in 128-replica gREST calculations with 1.5 million atoms system using 16,384 nodes in Fugaku. These schemes implemented in the latest version of GENESIS software could open new possibilities to answer unresolved questions on large biomolecular complex systems with slow conformational dynamics.

Molecular Basis for Actin Polymerization Kinetics Modulated by Solution Crowding

Actin polymerization drives cell movement and provides cells with structural integrity. Intracellular environments contain high concentrations of solutes, including organic compounds, macromolecules, and proteins. Macromolecular crowding has been shown to affect actin filament stability and bulk polymerization kinetics. However, the molecular mechanisms behind how crowding influences individual actin filament assembly are not well understood. In this study, we investigated how crowding modulates filament assembly kinetics using total internal reflection fluorescence (TIRF) microscopy imaging and pyrene fluorescence assays. The elongation rates of individual actin filaments analyzed from TIRF imaging depended on the type of crowding agent (polyethylene glycol, bovine serum albumin, and sucrose) as well as their concentrations. Further, we utilized all-atom molecular dynamics (MD) simulations to evaluate the effects of crowding molecules on the diffusion of actin monomers during filament assembly. Taken together, our data suggest that solution crowding can regulate actin assembly kinetics at the molecular level.

Varying molecular interactions explain aspects of crowder-dependent enzyme function of a viral protease

Biochemical processes in cells, including enzyme-catalyzed reactions, occur in crowded conditions with various background macromolecules occupying up to 40% of cytoplasm's volume. Viral enzymes in the host cell also encounter such crowded conditions as they often function at the endoplasmic reticulum membranes. We focus on an enzyme encoded by the hepatitis C virus, the NS3/4A protease, which is crucial for viral replication. We have previously found experimentally that synthetic crowders, polyethylene glycol (PEG) and branched polysucrose (Ficoll), differently affect the kinetic parameters of peptide hydrolysis catalyzed by NS3/4A. To gain understanding of the reasons for such behavior, we perform atomistic molecular dynamics simulations of NS3/4A in the presence of either PEG or Ficoll crowders and with and without the peptide substrates. We find that both crowder types make nanosecond long contacts with the protease and slow down its diffusion. However, they also affect the enzyme structural dynamics; crowders induce functionally relevant helical structures in the disordered parts of the protease cofactor, NS4A, with the PEG effect being more pronounced. Overall, PEG interactions with NS3/4A are slightly stronger but Ficoll forms more hydrogen bonds with NS3. The crowders also interact with substrates; we find that the substrate diffusion is reduced much more in the presence of PEG than Ficoll. However, contrary to NS3, the substrate interacts more strongly with Ficoll than with PEG crowders, with the substrate diffusion being similar to crowder diffusion. Importantly, crowders also affect the substrate-enzyme interactions. We observe that both PEG and Ficoll enhance the presence of substrates near the active site, especially near catalytic H57 but Ficoll crowders increase substrate binding more than PEG molecules.

GB1 Dimerization in Crowders: A Multiple Resolution Approach

In-cell protein-protein association, which is crucial in enzyme catalysis and polymerization, occurs in an environment that is highly heterogeneous and crowded. The crowder molecules exclude the reactant molecules from occupying certain regions of the cell, resulting in changes in the reaction thermodynamics and kinetics. Recent studies, both experiment and simulations, revealed that the nature of the interaction between crowder and protein species, in particular the soft interactions, plays an important role in crowder induced effects on protein association. To this end, from a simulation perspective, it is important to decipher the level of structural resolution in a protein-crowder model that can faithfully capture the influence of crowding on protein association. Here, we investigate the dimerization of model system GB1 in the presence of lysozyme crowders at two structural resolutions. The lower resolution model assumes both protein and crowder species as spherical beads, similar to the analytical scaled particle theory model, whereas the higher resolution model retains residue specific structural details for protein and crowder species. From the higher resolution model, it is found that GB1 dimer formation is destabilized in the presence of lysozyme crowders, and the destabilization is more for the side-by-side dimer compared to the domain-swapped dimer, in qualitative agreement with experimental findings. However, the low resolution CG model predicts stabilization of the dimers in the presence of the lysozyme crowder, similar to the SPT model. Our results indicate a nontrivial role of the choice of model resolution in computer simulation studies investigating crowder induced effects.

Activation of L-lactate oxidase by the formation of enzyme assemblies through liquid-liquid phase separation

The assembly state of enzymes is gaining interest as a mechanism for regulating the function of enzymes in living cells. One of the current topics in enzymology is the relationship between enzyme activity and the assembly state due to liquid-liquid phase separation. In this study, we demonstrated enzyme activation via the formation of enzyme assemblies using L-lactate oxidase (LOX). LOX formed hundreds of nanometer-scale assemblies with poly-L-lysine (PLL). In the presence of ammonium sulfate, the LOX-PLL clusters formed micrometer-scale liquid droplets. The enzyme activities of LOX in clusters and droplets were one order of magnitude higher than those in the dispersed state, owing to a decrease in K_M and an increase in k_cat. Moreover, the clusters exhibited a higher activation effect than the droplets. In addition, the conformation of LOX changed in the clusters, resulting in increased enzyme activation. Understanding enzyme activation and assembly states provides important information regarding enzyme function in living cells, in addition to biotechnology applications.

Biomolecular Condensates Regulate Enzymatic Activity under a Crowded Milieu: Synchronization of Liquid-Liquid Phase Separation and Enzymatic Transformation

Cellular crowding plays a key role in regulating the enzymatic reactivity in physiological conditions, which is challenging to realize in the dilute phase. Enzymes drive a wide range of complex metabolic reactions with high efficiency and selectivity under extremely heterogeneous and crowded cellular environments. However, the molecular interpretation behind the enhanced enzymatic reactivity under a crowded milieu is poorly understood. Herein, using the horseradish peroxidase (HRP) and glucose oxidase (GOx) cascade pair, we demonstrate for the first time that macromolecular crowding induces liquid-liquid phase separation (LLPS) via the formation of liquid-like condensates/droplets and thereby increases the intrinsic catalytic efficiencies of HRP and GOx. Both these enzymes undergo crowding induced homotypic LLPS via enthalpically driven multivalent electrostatic as well as hydrophobic interactions. Using a set of kinetic and microscopic experiments, we show that precise synchronization of spontaneous LLPS and enzymatic transformations is key to realize the enhanced enzymatic activity under the crowded environments. Our findings reveal an unprecedented enhancement (91- to 205-fold) in the catalytic efficiency (k_cat/K_m) of HRP at pH 4.0 within the droplet phase relative to that in the bulk aqueous phase in the presence of different crowders. In addition, we have shown that other enzymes also undergo spontaneous LLPS under macromolecular crowding, signifying the generality of this phenomenon under the crowded environments. More importantly, coalescence driven highly regulated GOx/HRP cascade reactions within the fused droplets have been demonstrated with enhanced activity and specificity under the crowded environments. The present discovery highlights the active role of membraneless condensates in regulating the enzymatic efficacy for complex metabolic reactions under the crowded cellular environments and may find significant importance in the field of biocatalysis.

Connecting the Dots: Macromolecular Crowding and Protein Aggregation

Proteins are one of the dynamic macromolecules that play a significant role in many physiologically important processes to sustain life on the earth. Proteins need to be properly folded into their active conformation to perform their function. Alteration in the protein folding process may lead to the formation of misfolded conformers. Accumulation of these misfolded conformers can result in the formation of protein aggregates which are attributed to many human pathological conditions including neurodegeneration, cataract, neuromuscular disorders, and diabetes. Living cells naturally have heterogeneous crowding environments with different concentrations of various biomolecules. Macromolecular crowding condition has been found to alter the protein conformation. Here in this review, we tried to show the relation between macromolecular crowding, protein aggregation, and its consequences.

Physiological models to study the effect of molecular crowding on multi-drug bound proteins: insights from SARS-CoV-2 main protease

Molecular Dynamics simulations are often used in drug design. However, such simulations do not account for the physiological environment of the receptor; hence overlook its impact on biomolecular interactions. To address this lacuna, we identified three objectives to pursue - develop models of physiological environment, study a drug-receptor complex in such environments, and identify methods to analyze these complicated simulations. Two novel physiological models were developed and studied. The first, called 'm10', comprises of 10 of the most abundant cytoplasmic metabolites at physiological concentrations. The second, called 'phy', supplements m10 with an additional crowder protein to elicit macromolecular crowding effect. The main protease (M^pro) of SARS-CoV-2, being essential for viral replication, is an attractive drug target for COVID-19. Hence, we chose M^pro docked with multiple drugs as our model drug-receptor system. With a plethora of compounds, physiological systems can be exceedingly large and complex. A novel Spark-based software (SparkTraj) was developed to rapidly analyze non-specific contacts and water interactions. Our study shows that crowding enhances the difference in the dynamics of apo- vs drug-bound complexes. Metabolites, at times as a cluster, were seen interacting with the protease, drugs, and binding sites in drug-free receptor. Except one that crawled to an adjacent pocket in phy, the drugs remained in their respective pockets in all simulations. Given these observations, we hope that the models and approach presented here would help the optimization, evaluation, and selection of potential drugs. Generic biomolecular dynamics could also benefit from such models and tools.Communicated by Ramaswamy H. Sarma.

Water Stress-Driven Changes in Bacterial Cell Surface Properties

Increased drought intensity and frequency exposes soil bacteria to prolonged water stress. While numerous studies reported on behavioral and physiological mechanisms of bacterial adaptation to water stress, changes in bacterial cell surface properties during adaptation are not well researched. We studied adaptive changes in cell surface hydrophobicity (CSH) after exposure to osmotic (NaCl) and matric stress (polyethylene glycol 8000 [PEG 8000]) for six typical soil bacteria (Bacillus subtilis, Arthrobacter chlorophenolicus, Pseudomonas fluorescens, Novosphingobium aromaticivorans, Rhodococcus erythropolis, and Mycobacterium pallens) covering a wide range of cell surface properties. Additional physicochemical parameters (surface chemical composition, surface charge, cell size and stiffness) of B. subtilis and P. fluorescens were analyzed to understand their possible contribution to CSH development. Changes in CSH caused by osmotic and matric stress depend on strain and stress type. CSH of B. subtilis and P. fluorescens increased with stress intensity, R. erythropolis and M. pallens exhibited a generally high but constant contact angle, while the response of A. chlorophenolicus and N. aromaticivorans depended on growth conditions and stress type. Osmotically driven changes in CSH of B. subtilis and P. fluorescens are accompanied by increasing surface N/C ratio, suggesting an increase in protein concentration within the cell wall. Cell envelope proteins thus presumably control bacterial CSH in two ways: (i) by increases in the relative density of surface proteins due to efflux of cytoplasmic water and subsequent cell shrinkage, and (ii) by destabilization of cell wall proteins, resulting in conformational changes which render the surface more hydrophobic. IMPORTANCE Changes in precipitation frequency, intensity, and temporal distribution are projected to result in increased frequency and intensity of droughts and heavy rainfall events. Prolonged droughts can promote the development of soil water repellency (SWR); this impacts the infiltration and distribution of water in the soil profile, exposing soil microorganisms to water stress. Exposure to water stress has recently been reported to result in increased cell surface hydrophobicity. However, the mechanism of this development is poorly understood. This study investigates the changes in the physicochemical properties of bacterial cell surfaces under water stress as a possible mechanism of increased surface hydrophobicity. Our results improve understanding of the microbial response to water stress in terms of surface properties, the variations in stress response depending on cell wall composition, and its contribution to the development of SWR.

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.

Evaluation of Weak Interactions of Proteins and Organic Cations with DNA Duplex Structures

Molecular interactions and reactions in living cells occur with high background concentrations of organic compounds including proteins. Uncharged water-soluble polymers are commonly used cosolutes in studies on molecular crowding, and most studies argue about the effects of intracellular crowding based on results obtained using polymer cosolutes. Further investigations using protein crowders and organic cations are important in understanding the effects of cellular environments on nucleic acids with negatively charged surfaces. We assessed the effects of using model globular proteins, serum proteins, histone proteins, structurally flexible polypeptides, di- and polyamines, and uncharged polymers. Thermal stability analysis of DNA oligonucleotide structures revealed that unlike conventional polymer cosolutes, basic globular proteins (lysozyme and cytochrome c) at high concentrations stabilized long internal and bulge loop structures but not fully matched duplexes. The selective stabilization of long loop structures suggests preferential binding to unpaired nucleotides in loops through weak electrostatic interactions. Furthermore, the ability of the proteins to stabilize the loop structures was enhanced under macromolecular crowding conditions. Remarkably, the effects of basic proteins on the stability of fully matched duplexes were dissimilar to those of basic amino-acid-rich polypeptides and polyamines. This study provides new insights into the interaction of nucleic acid structures with organic cations.

Crowding-induced protein destabilization in the absence of soft attractions

It is generally assumed that volume exclusion by macromolecular crowders universally stabilizes the native states of proteins and destabilization suggests soft attractions between crowders and protein. Here we show that proteins can be destabilized even by crowders that are purely repulsive. With a coarse-grained sequence-based model, we study the folding thermodynamics of two sequences with different native folds, a helical hairpin and a β-barrel, in a range of crowder volume fractions, φ_c. We find that the native state, N, remains structurally unchanged under crowded conditions, while the size of the unfolded state, U, decreases monotonically with φ_c. Hence, for all φ_c>0, U is entropically disfavored relative to N. This entropy-centric view holds for the helical hairpin protein, which is stabilized under all crowded conditions as quantified by changes in either the folding midpoint temperature, T_m, or the free energy of folding. We find, however, that the β-barrel protein is destabilized under low-T, low-φ_c conditions. This destabilization can be understood from two characteristics of its folding: 1) a relatively compact U at T<T_m, such that U is only weakly disfavored entropically by the crowders; and 2) a transient, compact, and relatively low-energy nonnative state that has a maximum population of only a few percent at φ_c=0, but increasing monotonically with φ_c. Overall, protein destabilization driven by hard-core effects appears possible when a compaction of U leads to even a modest population of compact nonnative states that are energetically competitive with N.

Macromolecular Crowding-Induced Unusual Liquid-Liquid Phase Separation of Human Serum Albumin via Soft Protein-Protein Interactions

Macromolecular crowding has a profound impact on the conformational dynamics and intermolecular interactions of biological macromolecules. In this context, the role of inert synthetic crowders in the protein-protein interactions of globular proteins is poorly understood. Here, using native human serum albumin (HSA) under physiological conditions, we show that macromolecular crowding induces liquid-liquid phase separation (LLPS) via liquid-like membrane-less droplet formation in a concentration- and time-dependent manner. Circular dichroism measurements reveal significant alteration in the secondary structure of HSA inside the droplet during aging. In contrast, at a high protein concentration, a liquid-to-solid-like phase transition has been observed upon maturation. Our findings reveal that the LLPS of HSA is mainly driven by enthalpically controlled intermolecular protein-protein interactions via hydrophobic contacts involving aromatic and/or nonaromatic residues. Moreover, modulation of LLPS of HSA has been demonstrated upon denaturation and ligand binding. This study highlights the importance of soft protein-protein interactions of globular proteins in a crowded cellular environment in driving the LLPS.

Influence of Nonspecific Interactions between Proteins and In Vivo Cytoplasmic Crowders in Facilitated Diffusion of Proteins: Theoretical Insights

The binding of proteins to their respective specific sites on the DNA through facilitated diffusion serves as the initial step of various important biological processes. While this search process has been thoroughly investigated via in vitro studies, the cellular environment is complex and may interfere with the protein's search dynamics. The cytosol is heavily crowded, which can potentially modify the search by nonspecifically interacting with the protein that has been mostly overlooked. In this work, we probe the target search dynamics in the presence of explicit crowding agents that have an affinity toward the protein. We theoretically investigate the role of such protein-crowder associations in the target search process using a discrete-state stochastic framework that allows for the analytical description of dynamic properties. It is found that stronger nonspecific associations between the crowder and proteins can accelerate the facilitated diffusion of proteins in comparison with a purely inert, rather weakly interacting cellular environment. This effect depends on how strong these associations are, the spatial positions of the target with respect to the crowders, and the size of the crowded region. Our theoretical results are also tested with Monte Carlo computer simulations. Our predictions are in qualitative agreement with existing experimental observations and computational studies.

Protein assembly and crowding simulations

Proteins encounter frequent molecular interactions in biological environments. Computer simulations have become an increasingly important tool in providing mechanistic insights into how such interactions in vivo relate to their biological function. The review here focuses on simulations describing protein assembly and molecular crowding effects as two important aspects that are distinguished mainly by how specific and long-lived protein contacts are. On the topic of crowding, recent simulations have provided new insights into how crowding affects protein folding and stability, modulates enzyme activity, and affects diffusive properties. Recent studies of assembly processes focus on assembly pathways, especially for virus capsids, amyloid aggregation pathways, and the role of multivalent interactions leading to phase separation. Also, discussed are technical challenges in achieving increasingly realistic simulations of interactions in cellular environments.

Computational Models for the Study of Protein Aggregation

Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.

Crowding affects structural dynamics and contributes to membrane association of the NS3/4A complex

Using molecular dynamics simulations, we describe how crowded environments affect the internal dynamics and diffusion of the hepatitis C virus proteases NS3/4A. This protease plays a key role in viral replication and is successfully used as a target for antiviral treatment. The NS3 enzyme requires a peptide cofactor, called NS4A, with its central part interacting with the NS3 β-sheet, and flexible, protruding terminal tails that are unstructured in water solution. The simulations describe the enzyme and water molecules at atomistic resolution, whereas crowders are modeled via either all-atom or coarse-grained models to emphasize different aspects of crowding. Crowders reflect the polyethylene glycol (PEG) molecules used in the experiments to mimic the crowded surrounding. A bead-shell model of folded coarse-grained PEG molecules considers mainly the excluded volume effect, whereas all-atom PEG models afford more protein-like crowder interactions. Circular dichroism spectroscopy experiments of the NS4A N-terminal tail show that a helical structure is formed in the presence of PEG crowders. The simulations suggest that crowding may assist in the formation of an NS4A helical fragment, positioned exactly where a transmembrane helix would fold upon the NS4A contact with the membrane. In addition, partially interactive PEGs help the NS4A N-tail to detach from the protease surface, thus enabling the process of helix insertion and potentially helping the virus establish a replication machinery needed to produce new viruses. Results point to an active role of crowding in assisting structural changes in disordered protein fragments that are necessary for their biological function.

Macromolecular crowding effects on electrostatic binding affinity: Fundamental insights from theoretical, idealized models

The crowded cellular environment can affect biomolecular binding energetics, with specific effects depending on the properties of the binding partners and the local environment. Often, crowding effects on binding are studied on particular complexes, which provide system-specific insights but may not provide comprehensive trends or a generalized framework to better understand how crowding affects energetics involved in molecular recognition. Here, we use theoretical, idealized molecules whose physical properties can be systematically varied along with samplings of crowder placements to understand how electrostatic binding energetics are altered through crowding and how these effects depend on the charge distribution, shape, and size of the binding partners or crowders. We focus on electrostatic binding energetics using a continuum electrostatic framework to understand effects due to depletion of a polar, aqueous solvent in a crowded environment. We find that crowding effects can depend predictably on a system's charge distribution, with coupling between the crowder size and the geometry of the partners' binding interface in determining crowder effects. We also explore the effect of crowder charge on binding interactions as a function of the monopoles of the system components. Finally, we find that modeling crowding via a lowered solvent dielectric constant cannot account for certain electrostatic crowding effects due to the finite size, shape, or placement of system components. This study, which comprehensively examines solvent depletion effects due to crowding, complements work focusing on other crowding aspects to help build a holistic understanding of environmental impacts on molecular recognition.

Crowding effects on water-mediated hydrophobic interactions

Understanding the fundamental forces such as hydrophobic interactions in a crowded intracellular environment is necessary to comprehensively decipher the mechanisms of protein folding and biomolecular self-assemblies. The widely accepted entropic depletion view of crowding effects primarily attributes biomolecular compaction to the solvent excluded volume effects exerted by the "inert" crowders, neglecting their soft interactions with the biomolecule. In this study, we examine the effects of chemical nature and soft attractive energy of crowders on the water-mediated hydrophobic interaction between two non-polar neopentane solutes using molecular dynamics simulations. The crowded environment is modeled using dipeptides composed of polar and non-polar amino acids of varying sizes. The results show that amongst the non-polar crowders, Leu₂ strengthens the hydrophobic interactions significantly, whereas the polar and small-sized non-polar crowders do not show significant strengthening. Distinct underlying thermodynamic driving forces are illustrated where the small-sized crowders drive hydrophobic interaction via a classic entropic depletion effect and the bulky crowders strengthen it by preferential interaction with the solute. A crossover from energy-stabilized solvent-separated pair to entropy-stabilized contact pair state is observed in the case of bulky non-polar (Leu₂) and polar (Lys₂) crowders. The influence of solute-crowder energy in affecting the dehydration energy penalty is found to be crucial for determining the neopentane association. The findings demonstrate that along with the entropic (size) effects, the energetic effects also play a crucial role in determining hydrophobic association. The results can be extended and have implications in understanding the impact of protein crowding with varying chemistry in modulating the protein free energy landscapes.

Reduced efficacy of a Src kinase inhibitor in crowded protein solution

The inside of a cell is highly crowded with proteins and other biomolecules. How proteins express their specific functions together with many off-target proteins in crowded cellular environments is largely unknown. Here, we investigate an inhibitor binding with c-Src kinase using atomistic molecular dynamics (MD) simulations in dilute as well as crowded protein solution. The populations of the inhibitor, 4-amino-5-(4-methylphenyl)-7-(t-butyl)pyrazolo[3,4-d]pyrimidine (PP1), in bulk solution and on the surface of c-Src kinase are reduced as the concentration of crowder bovine serum albumins (BSAs) increases. This observation is consistent with the reduced PP1 inhibitor efficacy in experimental c-Src kinase assays in addition with BSAs. The crowded environment changes the major binding pathway of PP1 toward c-Src kinase compared to that in dilute solution. This change is explained based on the population shift mechanism of local conformations near the inhibitor binding site in c-Src kinase.

Soluble State of Villin Headpiece Protein as a Tool in the Assessment of MD Force Fields

Protein self-assembly plays an important role in cellular processes. Whereas molecular dynamics (MD) represents a powerful tool in studying assembly mechanisms, its predictions depend on the accuracy of underlying force fields, which are known to overly promote protein assembly. We here examine villin headpiece domain, HP36, which remains soluble at concentrations amenable to MD studies. The experimental characterization of soluble HP36 at concentrations of 0.05 to 1 mM reveals concentration-independent 90% monomeric and 10% dimeric populations. Extensive all-atom MD simulations at two protein concentrations, 0.9 and 8.5 mM, probe the HP36 dimer population, stability, and kinetics of dimer formation within two MD force fields, Amber ff14SB and CHARMM36m. MD results demonstrate that whereas CHARMM36m captures experimental HP36 monomer populations at the lower concentration, both force fields overly promote HP36 association at the higher concentration. Moreover, contacts stabilizing HP36 dimers are force-field-dependent. CHARMM36m produces consistently higher HP36 monomer populations, lower association rates, and weaker dependence of these quantities on the protein concentration than Amber ff14SB. Nonetheless, the highest monomer populations and dissociation constants are observed when the TIP3P water model in Amber ff14SB is replaced by TIP4P/2005, showcasing the critical role of the water model in addressing the protein solubility problem in MD.

Modeling protein association from homogeneous to mixed environments: A reaction-diffusion dynamics approach

Protein-protein association in vivo occur in a crowded and complex environment. Theoretical models based on hard-core repulsion predict stabilization of the product under crowded conditions. Soft interactions, on the contrary, can either stabilize or destabilize the product formation. Here we modeled protein association in presence of crowders of varying size, shape, interaction potential and used different mixing parameters for constituent crowders to study the influence on the association reaction. It was found that size is a more dominant factor in crowder-induced stabilization than the shape. Furthermore, in a mixture of crowders having different sizes but identical interaction potential, the change of free energy is additive of the free energy changes produced by individual crowders. However, the free energy change is not additive if two crowders of same size interact via different interaction potentials. These findings provide a systematic understanding of crowding influences in heterogeneous medium.

Specific Interactions and Environment Flexibility Tune Protein Stability under Extreme Crowding

Macromolecular crowding influences protein mobility and stability in vivo. A precise description of the crowding effect on protein thermal stability requires the estimate of the combined effects of excluded volume, specific protein-environment interactions, as well as the thermal response of the crowders. Here, we explore an ideal model system, the lysozyme protein in powder state, to dissect the factors controlling the melting of the protein under extreme crowding. By deploying state-of-the art molecular simulations, supported by calorimetric experiments, we assess the role of the environment flexibility and of intermolecular electrostatic interactions. In particular, we show that the temperature-dependent flexibility of the macromolecular crowders, along with specific interactions, significantly alleviates the stabilizing contributions of the static volume effect.

Pesticide interactions induce alterations in secondary structure of malate dehydrogenase to cause destability and cytotoxicity

Environmental exposure to pesticides increases the risk of neurotoxicity and neurodegenerative diseases. The mechanism of pesticide-induced toxicity is attributed to the increased reactive oxygen species, mitochondrial dysfunction, inhibition of key cellular enzymes and accelerated pathogenic protein aggregation. The structural basis of pesticide-protein interaction is limited to pathogenic proteins such as α-synuclein, Tau and amyloid-beta. However, the effect of pesticides on metabolic proteins is still unexplored. Here, we used rotenone and chlorpyrifos to understand the interaction of these pesticides with a metabolic protein, malate dehydrogenase (MDH) and the consequent pesticide-induced cytotoxicity. We found that rotenone and chlorpyrifos strongly bind to MDH, interferes with protein folding and triggers alteration in its secondary structure. Both pesticides showed high binding affinities for MDH as observed by NMR and LCMS. Rotenone and chlorpyrifos induced structural alterations during MDH refolding resulting in the formation of cytotoxic conformers that generated oxidative stress and reduced cell viability. Our findings suggest that pesticides, in general, interact with proteins resulting in the formation of cytotoxic conformers that may have implications in neurotoxicity and neurodegenerative diseases.

Stability enhancement in a mAb and Fab coformulation

Multiple therapeutic proteins can be combined into a single dose for synergistic targeting to multiple sites of action. Such proteins would be mixed in dose-specific ratios to provide the correct potency for each component, and yet the formulations must also preserve their activity and keep degradation to a minimum. Mixing different therapeutic proteins could adversely affect their stability, and reduce the shelf life of each individual component, making the control of such products very challenging. In this study, a therapeutic monoclonal antibody and a related Fab fragment, were combined to investigate the impact of coformulation on their degradation kinetics. Under mildly destabilizing conditions, these proteins were found to protect each other from degradation. The protective effect appeared to originate from the interaction of Fab and IgG1 in small soluble oligomers, or through the rapid coalescence of pre-existing monomeric IgG1 nuclei into a dead-end aggregate, rather than through macromolecular crowding or diffusion-limitations.

Small crowder interactions can drive hydrophobic polymer collapse as well as unfolding

Biomolecules evolve and function in the intracellular crowded environment that is densely packed with macromolecules. Yet, a microscopic understanding of the effects of such an environment on the conformational preferences of biomolecules remains elusive. While prior investigations have attributed crowding effects mainly to the excluded volume (size) effects of the crowders, very little is known about the effects exerted due to their chemical interactions. In this study, crowding effects of tri-alanine peptides on the collapse equilibria of generic hydrophobic polymer are investigated using molecular dynamics simulations. The role of weak, non-specific, attractive polymer-crowder interactions in modulating the polymer collapse equilibria is examined. The results highlight that crowding effects can lead to polymer compaction as well as unfolding depending on the strength of polymer-crowder interaction energy. Strongly interacting crowders weaken hydrophobic collapse (or unfold the polymer) at high volume fractions and induce polymer collapse only under dilute conditions. Weakly interacting crowders induce polymer collapse at all crowder concentrations. Interestingly, the thermodynamic driving forces for polymer collapse are remarkably different in the two cases. Strongly and weakly interacting crowders induce collapse by preferential adsorption and preferential depletion respectively. The findings provide new insights into the possible effects of interplay of intermolecular interactions in a crowded environment. The results have implications in understanding the impact of crowding in altering free energy landscapes of proteins.

Unraveling Dynamic Transitions in Time-Resolved Biomolecular Motions by A Dressed Diffusion Model

Recent experimental data reveal the complexity of diffusion dynamics beyond the scope of classical Brownian dynamics. The particles exhibit diverse diffusive motions from the anomalous toward classical diffusion over a wide range of temporal scales. Here a dressed diffusion model is developed to account for non-Brownian phenomena. By coupling the particle dynamics with a local field, the dressed diffusion model generalizes the Langevin equation through coupled damping kernels and generates the salient feature of time-dependent diffusion dynamics reported in the experimental measurements of biomolecules. The dressed diffusion model provides one quantitative aspect for future endeavors in this rapid-growing field.

Understanding biochemical processes in the presence of sub-diffusive behavior of biomolecules in solution and living cells

In order to maintain cellular function, biomolecules like protein, DNA, and RNAs have to diffuse to the target spaces within the cell. Changes in the cytosolic microenvironment or in the nucleus during the fulfillment of these cellular processes affect their mobility, folding, and stability thereby impacting the transient or stable interactions with their adjacent neighbors in the organized and dynamic cellular interior. Using classical Brownian motion to elucidate the diffusion behavior of these biomolecules is hard considering their complex nature. The understanding of biomolecular diffusion inside cells still remains elusive due to the lack of a proper model that can be extrapolated to these cases. In this review, we have comprehensively addressed the progresses in this field, laying emphasis on the different aspects of anomalous diffusion in the different biochemical reactions in cell interior. These experiment-based models help to explain the diffusion behavior of biomolecules in the cytosolic and nuclear microenvironment. Moreover, since understanding of biochemical reactions within living cellular system is our main focus, we coupled the experimental observations with the concept of sub-diffusion from in vitro to in vivo condition. We believe that the pairing between the understanding of complex behavior and structure-function paradigm of biological molecules would take us forward by one step in order to solve the puzzle around diseases caused by cellular dysfunction.

Clustering and dynamics of crowded proteins near membranes and their influence on membrane bending

Atomistic molecular dynamics simulations of concentrated protein solutions in the presence of a phospholipid bilayer are presented to gain insights into the dynamics and interactions at the cytosol-membrane interface. The main finding is that proteins that are not known to specifically interact with membranes are preferentially excluded from the membrane, leaving a depletion zone near the membrane surface. As a consequence, effective protein concentrations increase, leading to increased protein contacts and clustering, whereas protein diffusion becomes faster near the membrane for proteins that do occasionally enter the depletion zone. Since protein-membrane contacts are infrequent and short-lived in this study, the structure of the lipid bilayer remains largely unaffected by the crowded protein solution, but when proteins do contact lipid head groups, small but statistically significant local membrane curvature is induced, on average.

Whole-Cell Models and Simulations in Molecular Detail

Comprehensive data about the composition and structure of cellular components have enabled the construction of quantitative whole-cell models. While kinetic network-type models have been established, it is also becoming possible to build physical, molecular-level models of cellular environments. This review outlines challenges in constructing and simulating such models and discusses near- and long-term opportunities for developing physical whole-cell models that can connect molecular structure with biological function.

Modeling Crowded Environment in Molecular Simulations

Biomolecules perform their various functions in living cells, namely in an environment that is crowded by many macromolecules. Thus, simulating the dynamics and interactions of biomolecules should take into account not only water and ions but also other binding partners, metabolites, lipids and macromolecules found in cells. In the last decade, research on how to model macromolecular crowders around proteins in order to simulate their dynamics in models of cellular environments has gained a lot of attention. In this mini-review we focus on the models of crowding agents that have been used in computer modeling studies of proteins and peptides, especially via molecular dynamics simulations.

Proteins are Solitary! Pathways of Protein Folding and Aggregation in Protein Mixtures

We present a computational and experimental study on the folding and aggregation in solutions of multiple protein mixtures at different concentrations. We show how in protein mixtures each component is capable of maintaining its folded state at densities greater than the one at which they would precipitate in single-species solutions. We demonstrate the generality of our observation over many different proteins using computer simulations capable of fully characterizing the cross-aggregation phase diagram of all the mixtures. Dynamic light scattering experiments were performed to evaluate the aggregation of two proteins, bovine serum albumin (BSA) and consensus tetratricopeptide repeat (CTPR), in solutions of one or both proteins. The experiments confirm our hypothesis and the simulations. These findings elucidate critical aspects of the cross-regulation of expression and aggregation of proteins exerted by the cell and on the evolutionary selection of folding and non-aggregating protein sequences, paving the way for new experimental tests.

Reduced density profile of small particles near a large particle: Results of an integral equation theory with an accurate bridge function and a Monte Carlo simulation

Solute-solvent reduced density profiles of hard-sphere fluids were calculated by using several integral equation theories for liquids. The traditional closures, Percus-Yevick (PY) and the hypernetted-chain (HNC) closures, as well as the theories with bridge functions, Verlet, Duh-Henderson, and Kinoshita (named MHNC), were used for the calculation. In this paper, a one-solute hard-sphere was immersed in a one-component hard-sphere solvent and various size ratios were examined. The profiles between the solute and solvent particles were compared with those calculated by Monte Carlo simulations. The profiles given by the integral equations with the bridge functions were much more accurate than those calculated by conventional integral equation theories, such as the Ornstein-Zernike (OZ) equation with the PY closure. The accuracy of the MHNC-OZ theory was maintained even when the particle size ratio of solute to solvent was 50. For example, the contact values were 5.7 (Monte Carlo), 5.6 (MHNC), 7.8 (HNC), and 4.5 (PY), and the first minimum values were 0.48 (Monte Carlo), 0.46 (MHNC), 0.54 (HNC), and 0.40 (PY) when the packing fraction of the hard-sphere solvent was 0.38 and the size ratio was 50. The asymptotic decay and the oscillation period for MHNC-OZ were also very accurate, although those given by the HNC-OZ theory were somewhat faster than those obtained by Monte Carlo simulations.

A Molecular Sensor Reveals Differences in Macromolecular Crowding between the Cytoplasm and Nucleoplasm

We describe a molecular sensor that reports, using fluorescence resonance energy transfer (FRET), on the degree of macromolecular crowding in different cellular compartments. The oligonucleotide-based sensor is sensitive to changes in the volume fraction of macromolecules over a wide range in vitro and, when introduced in cells, rapidly distributes and shows a striking contrast between the cytosol and the nucleus. This contrast can be modulated by osmotic stress or by using a number of drugs that alter chromatin organization within the nucleus. These findings suggest that the sensor can be used as a tool to probe chromosome organization. Further, our finding that the cell maintains different degrees of macromolecular crowding in the cytoplasm and nucleoplasm has implications on molecular mechanisms since crowding can alter protein conformations, binding rates, reaction kinetics, and therefore protein function.

Structural and energetic evolution of fibrinogen toward to the betablocker interactions

We present a computational analysis coupled with experimental studies, focusing on the binding-interaction between beta-adrenoreceptor blocking agents (acebutolol and propranolol) with fibrinogen protein (E-region). Herein, computational modeling on structural validation and flexibility properties of fibrinogen E-region showed that the E-region interacting residues, which form the funnel-shaped hydrophobic cavity for ligand-binding, can be efficiently modeled. The obtained free energy of binding (FEB) values for the docking complexes, namely acebutolol/fibrinogen E-region and propranolol/fibrinogen E-region, were very close and amounted to - 6.9 kcal/mol and - 6.8 kcal/mol, respectively. They were supported by a high binding-accuracy (R.M.S.D < 2 Å) for the best crystallographic binding-poses in both cases. In this regard, we identify a docking-mechanism of interaction for the propranolol and acebutolol mainly based on non-covalent hydrophobic contacts with the fibrinogen E-region binding-site. Besides, the beta-adrenoreceptor blocking agents are able to induce local perturbations affecting particularly the fibrinogen E-region allosteric residues linked to significant changes in the inter-residue communication and flexibility properties of residue network. In this sense, we show that the key biophysical parameters like frequency and collectivity degree may be compromised in different ways by the interaction with acebutolol and propranolol. Isothermal titration calorimetry, zeta potential and small angle X-ray scattering (SAXS) measurements were performed to complete and corroborate computational analysis. The combined experimental results point out that acebutolol acts to a lesser extent to fibrinogen structure than propranolol.