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Macromolecular crowding

Macromolecular crowding is a biophysical phenomenon characterized by the high volume occupancy of macromolecules—such as proteins, nucleic acids, and polysaccharides—within cellular environments, typically filling 5–40% of the available space and creating excluded volume effects that alter the effective concentrations and behaviors of other biomolecules.^[1] This crowding arises from the dense intracellular milieu, where total macromolecular concentrations often reach 200–400 g/L, fundamentally influencing the thermodynamics and kinetics of biological processes. In living cells, macromolecular crowding reduces the diffusion coefficients of molecules, shifting from normal Brownian motion to anomalous diffusion due to steric hindrance and entanglement, which can slow transport by up to 10-fold compared to dilute solutions.^[2] It also stabilizes compact protein conformations by favoring folded states through excluded volume interactions, thereby enhancing folding rates under physiological conditions.^[3] Furthermore, crowding promotes the association of proteins and protein-nucleic acid complexes by increasing their effective local concentrations, which accelerates binding events and enzymatic reactions essential for cellular function.^[4] The concept of macromolecular crowding has evolved from early polymer physics theories, such as the Flory-Huggins model in the 1940s, to modern biophysical studies recognizing its role in phenomena like phase separation and amyloid formation.^[5] First quantified in bacterial cytoplasm in the 1990s,^[6] it underscores the limitations of in vitro experiments conducted in dilute buffers and highlights the need for crowding-mimicking agents, like polyethylene glycol, in research to replicate in vivo conditions. Overall, macromolecular crowding is a key determinant of cellular physiology, affecting everything from metabolic efficiency to stress responses.^[7]

Fundamentals

Definition and Overview

Macromolecular crowding refers to the biophysical phenomenon arising from the high intracellular concentrations of macromolecules (such as proteins and nucleic acids) and cellular structures (such as organelles), which occupy a substantial portion of the available space and thereby restrict the diffusion and interactions of other molecules. In typical cellular environments, these occupy 20-30% of the cytoplasmic volume, creating a densely packed milieu that deviates markedly from the dilute conditions of most in vitro experiments.^[8] For instance, in the cytosol of Escherichia coli, the total macromolecular concentration reaches 300-400 g/L, corresponding to a volume fraction φ of approximately 0.3-0.4.^[9] The concept of macromolecular crowding emerged in the 1970s from foundational work in polymer physics, notably A.G. Ogston's 1970 analysis of excluded volume effects in porous media analogous to cellular interiors.^[9] It was further advanced by researchers including Donald J. Winzor, whose studies on thermodynamic nonideality in macromolecular solutions in the late 1970s and 1980s highlighted the implications beyond mere dilution.^[10] The term "macromolecular crowding" was formally coined by Allen P. Minton in 1981 to encapsulate the pervasive influence of volume exclusion on biochemical equilibria and rates.^[11] In contrast to the low-concentration, dilute solutions prevalent in laboratory settings—where water fully solvates molecules without significant steric hindrance—cellular crowding creates an environment where water remains the dominant solvent but is effectively excluded from the substantial volume occupied by inert crowders.^[12] This volume fraction φ, typically 0.2-0.4 in eukaryotic and prokaryotic cytoplasms, serves as a key quantitative descriptor of crowding intensity and underscores its role in mimicking physiological conditions.^[9]

Physical Principles

Macromolecular crowding arises primarily from the excluded volume effect, whereby crowder molecules occupy a significant portion of the available space, thereby reducing the effective volume accessible to other macromolecules. In the hard-sphere model, which treats crowders and target molecules as impenetrable spheres, the accessible volume for the center of a target molecule of radius r in a solution containing crowders of radius r_c is given by V_\text{eff} = V_\text{total} (1 - \phi), where \phi represents the volume fraction occupied by the crowders. This reduction in available space leads to steric repulsions that are nonspecific and entropically driven, without requiring direct chemical interactions between the molecules involved.^[9] The thermodynamic consequences of this excluded volume are profound, as crowding elevates the chemical potential of macromolecules and their effective concentrations within the available space. The excess chemical potential due to crowding can be approximated as \Delta \mu = RT \ln \left( \frac{1}{1 - \phi} \right), reflecting the increased thermodynamic activity equivalent to concentrating the macromolecule by a factor of $1/(1 - \phi). This shift favors more compact conformations for flexible macromolecules, such as proteins or nucleic acids, as they minimize their own excluded volume and thereby lower the overall free energy of the system. For instance, unfolded polypeptide chains experience a strong drive toward folding to reduce their spatial footprint in crowded environments.^[9] At the entropic level, crowding induces indirect attractions between macromolecules known as depletion forces, originating from osmotic pressure imbalances around the surfaces of the macromolecules. Small crowder molecules are excluded from a thin layer surrounding larger macromolecules, creating an osmotic gradient that effectively pushes the larger particles together when their depletion zones overlap; this process is purely entropic, with no enthalpic contribution from specific binding. These forces enhance association rates and stabilities of macromolecular complexes without altering the intrinsic binding affinities. The seminal description of such depletion attractions traces back to colloidal systems but applies directly to biological crowding scenarios. In terms of transport properties, macromolecular crowding impedes diffusion through both steric obstruction and increased viscosity. For macromolecules navigating entangled crowder networks, polymer physics models like the reptation theory predict significant reductions in the diffusion coefficient due to constraints from reduced effective pore size or tube diameter in the crowded medium. This highlights how even moderate volume fractions significantly slow diffusive processes, impacting reaction kinetics in cellular environments.^[13]

Mechanisms

Causes in Biological Systems

In biological systems, macromolecular crowding arises primarily from the high concentrations of large biomolecules and supramolecular structures that occupy substantial portions of cellular volume. Proteins represent the most abundant crowders in the cytoplasm, with total concentrations typically ranging from 200 to 300 g/L in eukaryotic cells and up to 300–400 g/L in prokaryotes such as Escherichia coli, where they account for the majority of the excluded volume.^[14] RNA and DNA contribute significantly in specific compartments; for instance, RNA concentrations reach 75–150 g/L in bacterial cytoplasm, while in the eukaryotic nucleus, chromatin and associated nucleic acids can achieve up to 100–400 g/L, exacerbating local crowding.^[14]^[15] Other crowders include polysaccharides in the extracellular matrix or periplasmic spaces, lipids forming membrane bilayers that enclose crowded domains, and large organelles such as ribosomes, which occupy 20–30% of the cytoplasmic volume in prokaryotes.^[12]^[16] Crowding levels exhibit considerable variability across cell types and compartments due to differences in macromolecular composition and spatial organization. In prokaryotes like E. coli, the overall volume fraction (φ) occupied by macromolecules approaches 0.3, reflecting a densely packed cytoplasm optimized for rapid growth.^[8] Eukaryotic cytoplasm generally has a lower φ of approximately 0.2, but compartmentalization leads to higher local densities; for example, the mitochondrial matrix maintains elevated crowding from proteins and metabolites, while the nucleus experiences even greater occlusion from chromatin, pushing φ toward 0.3 or higher in subnuclear regions.^[17]^[18] This variability underscores how evolutionary divergence in cellular architecture—from compact bacterial envelopes to compartmentalized eukaryotic designs—influences the distribution of crowders. The degree of crowding is not static but fluctuates dynamically in response to physiological states, modulating the effective volume available for biomolecules. During active metabolism or protein synthesis, transient increases in crowder concentrations can elevate φ by 10–20%, as seen in rapidly dividing cells where ribosomal biogenesis ramps up.^[19] Cell cycle progression further drives variations; for instance, in budding yeast, crowding intensifies at the bud neck during cytokinesis due to localized accumulation of cytoskeletal and synthetic machinery.^[20] Stress responses, such as hyperosmotic shock or nutrient limitation, also alter crowding by prompting osmotic adjustments that concentrate or dilute intracellular solutes, with osmotic stress alone capable of raising cytoplasmic φ by up to 15% in bacteria.^[21] From an evolutionary perspective, macromolecular crowding has been an intrinsic feature of life since its origins, facilitating efficient molecular packing within the confined volumes of primordial protocells, viruses, and modern organelles. In viruses, such as HIV-1, the capsid interior mimics extreme crowding with protein and nucleic acid concentrations exceeding 300 g/L, enabling compact genome storage and assembly without expansive cellular machinery.^[22] This principle extends to organelles like mitochondria, where matrix crowding—analogous to bacterial ancestors—supports metabolic efficiency in submicrometer spaces, highlighting crowding's role in enabling the evolution of compartmentalized, high-density biochemistry across scales from viral particles to eukaryotic cells.^[23]

Effects on Biomolecular Behavior

Macromolecular crowding significantly influences the kinetics of biomolecular processes by impeding molecular motion and altering reaction pathways. The diffusion coefficient of biomolecules typically decreases by 2- to 10-fold in crowded environments, such as the cytoplasm, due to excluded volume effects and increased frictional drag from surrounding macromolecules. This reduction is more pronounced for larger molecules, leading to slower transport and longer times for random encounters. For bimolecular association reactions, crowding can decrease rates by factors of 2- to 10-fold, particularly with large crowder molecules that limit reactant diffusion, though the exact magnitude depends on reaction probability and crowder size.^[24] In contrast, intramolecular processes, such as loop formation or refolding steps, often experience enhanced on-rates because crowding increases the effective local concentration and promotes recollisions within the same molecule.^[25] Thermodynamically, crowding shifts equilibria toward more compact or associated states through depletion attractions, which arise from the reduced available volume for crowders when biomolecules interact. This can increase binding affinities for protein-protein interactions by 10- to 100-fold, favoring dimerization or complex formation over dissociation.^[26] Such shifts are entropically driven, as the release of excluded volume upon association allows crowders greater configurational freedom, effectively stabilizing bound conformations. Beyond simple hard-core repulsions, soft interactions—including electrostatic, hydrophobic, and van der Waals forces—between crowders and biomolecules amplify these effects, often leading to altered solvation shells and enhanced attractions. These interactions can promote liquid-liquid phase separation by strengthening transient protein-protein contacts, resulting in biomolecular condensates with distinct internal dynamics. Hydrophobic effects, in particular, may reorganize water networks around proteins, further modulating stability and association.^[27] In cellular contexts, these kinetic and thermodynamic alterations manifest in broader physiological impacts, such as increased cytoplasmic viscosity—typically 10- to 100-fold higher than pure water—which hinders small molecule transport and diffusion across the cell. Enzymatic turnover rates are similarly affected, with reduced substrate access often lowering overall activity, though some enzymes benefit from crowding-induced conformational sampling that accelerates catalysis.^[28]

Biological Importance

Roles in Cellular Processes

Macromolecular crowding in the nucleus enhances the binding affinity of transcription factors to DNA by shifting protein-DNA equilibria toward the bound state, thereby promoting more efficient gene expression. This effect is particularly evident in the crowded nuclear environment, where high concentrations of macromolecules stabilize transcription factor interactions and facilitate chromatin compaction, reducing the search time for target sites and increasing transcriptional output. For instance, crowding strengthens the association of repressors like CI in phage lambda systems, amplifying regulatory control over gene networks.^[29]^[30]^[31] In metabolic pathways and signaling cascades, macromolecular crowding promotes enzyme channeling, where intermediates are directly passed between sequential enzymes, minimizing diffusion distances and enhancing reaction efficiency. This is crucial for processes like glycolysis and reduces the loss of labile metabolites in the cytoplasm. Crowding also amplifies signal transduction in pathways such as the MAPK cascade by stabilizing kinase-phosphatase complexes and increasing the sensitivity of phosphorylation events, allowing for rapid and robust cellular responses to stimuli. These effects collectively lower effective diffusion times for signaling molecules, enabling faster propagation of signals within the congested cellular milieu.^[32]^[33] Crowding further facilitates liquid-liquid phase separation (LLPS), driving the formation of membraneless organelles that organize cellular functions without lipid membranes. In the nucleus, this supports nucleoli assembly for ribosomal biogenesis, while in the cytoplasm, it aids P-body formation, where repressed mRNAs are sequestered for storage, decay, or translational reactivation. By promoting multivalent interactions among RNA-binding proteins and nucleic acids, crowding enhances the concentration of components within these condensates, streamlining mRNA processing and quality control.^[34]^[35]^[36] Recent studies from 2023 to 2025 highlight crowding's role in maintaining osmotic balance in eukaryotic cells by modulating macromolecular concentrations to counteract volume changes and prevent osmotic stress. These insights underscore crowding as an adaptive regulator of cellular homeostasis, integrating physical constraints with biochemical performance.^[37]^[38]^[39]

Implications for Diseases

Macromolecular crowding significantly contributes to the pathogenesis of neurodegenerative diseases by accelerating the aggregation of misfolded proteins into amyloid fibrils. In Alzheimer's disease, crowding within cellular condensates promotes the primary nucleation of amyloid-β (Aβ) peptides, enhancing fibril formation rates by orders of magnitude depending on local concentrations and crowders like polyethylene glycol.^[40] Similarly, for Parkinson's disease, crowding agents such as Ficoll accelerate α-synuclein amyloid fiber growth, with overall reaction rates increasing at least 10-fold through boosted primary nucleation and elongation steps.^[41] In tauopathies, molecular crowding synergizes with RNA to induce liquid-liquid phase separation of tau protein, fostering pathological aggregation in condensates that deviate from physiological microtubule binding.^[42] In hemoglobinopathies like sickle cell disease, elevated macromolecular crowding exacerbates the polymerization of deoxygenated sickle hemoglobin (HbS), reducing its solubility and promoting fiber formation that distorts red blood cells. Non-polymerizing crowders, such as fetal hemoglobin (HbF), inadvertently intensify this effect by increasing overall hemoglobin density without incorporating into polymers, thereby limiting HbF's therapeutic potential in mixed HbS/HbF scenarios.^[43] The tumor microenvironment in cancer features heightened macromolecular crowding due to extracellular matrix degradation and elevated biomolecule concentrations, which increases fluid viscosity and profoundly influences disease progression. This crowding enhances cancer cell migration speeds in confined spaces through actin network remodeling and protrusive motility shifts, facilitating invasion and metastasis in models like breast and osteosarcoma cells.^[44] Additionally, it impedes drug diffusion by raising hydraulic resistance, contributing to chemotherapy resistance, while altering cell adhesion dynamics to promote metastatic dissemination.^[44] Recent studies from 2023 to 2025 underscore gaps in bioengineered tissues and cell therapies where neglecting macromolecular crowding leads to suboptimal extracellular matrix deposition and inaccurate disease modeling, resulting in failed clinical translations for applications like vascular grafts and anti-fibrotic screens.^[45] Emerging links also connect crowding-induced osmotic imbalances to metabolic disorders, where cellular volume dysregulation amplifies protein misfolding and signaling disruptions in conditions like diabetes.^[46] Macromolecular crowding also plays a role in viral infections, where viruses exploit crowded cellular environments to enhance assembly and replication efficiency, as seen in SARS-CoV-2 capsid formation within condensates, contributing to pathogenesis and immune evasion as of 2024.^[5]

Investigation Methods

Experimental Approaches

Experimental approaches to macromolecular crowding primarily involve in vitro reconstitution using inert crowding agents to mimic the high volume occupancy (φ ≈ 0.2–0.4) typical of cellular environments, where macromolecules occupy 20–40% of the available space. Synthetic polymers such as polyethylene glycol (PEG) at concentrations of 5–20% w/v, Ficoll, and dextran are commonly employed as neutral crowders to induce volume exclusion effects without specific interactions, allowing controlled simulation of crowding on biomolecular processes. These agents, particularly PEG and dextran, have been extensively characterized for their ability to replicate entropic crowding while minimizing enthalpic perturbations, as demonstrated in studies of protein-polymer interactions. Seminal work by Minton established the foundational use of such crowders to quantify excluded volume impacts on equilibria and rates.^[47]^[48] In vivo methods focus on direct observation within living cells to capture native crowding heterogeneity. Fluorescence correlation spectroscopy (FCS) measures diffusion coefficients and association kinetics of fluorescently labeled probes, revealing subdiffusive behavior due to crowding in crowded cellular milieus like the cytoplasm. Recent advances include synchrotron-based small-angle X-ray scattering (SAXS), which enables real-time probing of macromolecular dynamics under crowding conditions; for instance, SAXS has quantified enhanced RNA structure stability in crowded solutions, highlighting crowding's role in thermodynamic robustness.^[49] These techniques complement each other by providing ensemble-averaged structural insights from SAXS and single-molecule mobility data from FCS. Advanced imaging techniques visualize local variations in crowding at nanoscale resolutions. Super-resolution microscopy, such as stimulated emission depletion (STED), resolves highly curved membrane structures and macromolecular distributions in crowded synthetic vesicles, uncovering spatial heterogeneities not accessible by diffraction-limited methods. Crowding-sensitive probes, including genetically encoded GFP variants like mEGFP, utilize fluorescence anisotropy or FRET to report interfacial or cytoplasmic crowding levels in real time, with sensitivity to osmotic shifts and stress-induced changes. Recent developments as of 2025 include FRET-based sensors for membrane interfacial crowding and nanopore-based detection of protein translocation under crowding, enhancing dynamic monitoring capabilities.^[50]^[51]^[52]^[53] These probes facilitate dynamic monitoring without disrupting native environments. Quantification of crowding effects relies on osmotic pressure measurements and volume exclusion assays to assess effective excluded volumes and interaction strengths. Osmotic pressure parameterizes crowding by quantifying the compressive forces on macromolecules, as applied to subcellular compartments to estimate φ from ion and polymer contributions. Volume exclusion assays, often involving sedimentation equilibrium or phase separation analysis, evaluate how crowders restrict accessible space, with mixed agents like PEG and Ficoll amplifying effects beyond single-component systems. Challenges persist in fully replicating soft, non-sterically specific interactions inherent to cellular crowders, due to microenvironmental variability and potential artifacts from labeling or synthetic mimics.

Theoretical Models

Theoretical models of macromolecular crowding provide mathematical and computational frameworks to predict how excluded volume effects and intermolecular interactions influence biomolecular behavior in dense environments, extending basic physical principles to quantitative simulations and predictions. These models are essential for interpreting experimental observations and forecasting crowding impacts on processes like protein folding and association, often treating crowders as inert obstacles or incorporating more realistic interactions. Seminal approaches began with simplified assumptions of hard-sphere exclusions, evolving to include softer potentials and advanced simulations that capture cellular heterogeneity. Hard-sphere models form the foundation of crowding theory by approximating macromolecules as impenetrable spheres, where crowding induces effective attractions via depletion forces. The Asakura-Oosawa theory, introduced in 1958, quantifies these depletion attractions between larger particles (e.g., proteins) mediated by smaller crowders, arising from osmotic pressure imbalances in the excluded volume overlap region. For two spheres of radius R in a solution of crowders with diameter \sigma and volume fraction \phi, the depletion potential is approximated by

V \approx -\frac{3}{2} kT \left( \frac{2R}{\sigma} \right)^2 \phi,

where k is Boltzmann's constant and T is temperature (valid for large R \gg \sigma); this predicts short-range attractions that promote aggregation or compaction without direct binding.^[54] Scaled particle theory extends these ideas to non-ideal solutions by calculating the work required to insert a test particle into a crowded fluid, accounting for cavity formation costs and predicting activity coefficients that enhance association equilibria. This approach has been applied to estimate crowding-induced stabilization of protein dimers, showing how shape and size mismatches amplify excluded volume effects. To address limitations of hard-sphere approximations, soft potential extensions incorporate additional interactions such as electrostatics and hydrophobicity, treating crowders as deformable with finite-range potentials. Recent reviews highlight how these models integrate charge distributions to modulate binding affinities, where crowders can either screen or enhance electrostatic attractions depending on ionic strength, and hydrophobic effects drive preferential exclusion of water to stabilize compact states. For instance, polymer crowders with soft repulsive potentials predict altered phase behaviors in cellular mimics, bridging ideal solution theories with real biomolecular dynamics. These developments, summarized in analyses from 2022 to 2024, emphasize the role of non-spherical crowder geometries in amplifying crowding beyond simple volume exclusion. Computational simulations complement analytical models by enabling dynamic predictions in complex systems. Molecular dynamics (MD) simulations using coarse-grained representations of crowders—such as spherical obstacles or simplified polymers—reproduce depletion forces and diffusion slowdowns observed in vitro, allowing studies of protein conformational changes under varying crowder densities. Recent advances incorporate machine learning to accelerate these simulations, generating accurate coarse-grained potentials for large-scale cellular models that include thousands of macromolecules, as demonstrated in 2024 frameworks that reduce computational costs while preserving thermodynamic accuracy. These ML-enhanced MD approaches facilitate modeling of crowding in whole-cell environments, predicting spatiotemporal heterogeneities in biomolecular interactions. Despite progress, theoretical models face challenges in capturing the full complexity of intracellular crowding. Dynamic aspects, such as crowder fluctuations and binding-unbinding events, remain difficult to parameterize accurately, leading to overestimations of stability in static approximations. Heterogeneous crowder compositions—mixing proteins, RNAs, and metabolites—introduce variabilities that current models struggle to resolve without excessive computational demands, resulting in gaps in predicting liquid-liquid phase separations or multivalent interactions. Ongoing efforts focus on hybrid analytical-simulation methods to bridge these limitations, but validation against in vivo data highlights the need for more adaptive frameworks.

Key Applications

Protein Folding and Stability

Macromolecular crowding significantly influences protein folding kinetics by favoring the formation of compact states through excluded volume effects, which reduces the entropy of unfolded ensembles and compels the polypeptide chain toward the native conformation. Experimental studies on hen egg white lysozyme have shown that crowding agents like dextran and Ficoll accelerate the fast phase of oxidative refolding by 2- to 5-fold but slow the slow phase, leading to an overall decrease in yield due to aggregation, while enhancing the efficiency of intermediate state transitions.^[55] This compaction of the energy landscape under crowding conditions minimizes the search space for folding pathways, leading to faster overall kinetics for many globular proteins, though the effect can vary with protein size and crowder type. Crowding also shifts the thermodynamic stability of proteins toward the folded state, often increasing the melting temperature (T_m) by approximately 5–15°C for globular proteins such as ubiquitin and actin in the presence of crowders like polyethylene glycol (PEG) or dextran at physiological volume fractions (φ ≈ 0.1–0.3). This stabilization arises from both hard-core repulsions, which entropically favor compact conformations, and soft chemical interactions that can contribute enthalpically. Scaled particle theory predicts modest but physiologically relevant stabilization for typical cellular crowding levels (φ ≈ 0.2–0.3), on the order of 1–5 kJ/mol.^[56]^[57]^[9] In addition to promoting proper folding, macromolecular crowding elevates the risk of misfolding and aggregation by increasing effective protein concentrations and altering conformational dynamics, which can accelerate the nucleation phase of amyloid formation by 10- to 50-fold for proteins like α-synuclein and β2-microglobulin. Recent 2024 studies using neutron scattering and molecular dynamics simulations have revealed that crowding induces slowdowns in rotational and conformational dynamics, with diffusion coefficients decreasing by up to 10-fold and loop motions restricted on microsecond timescales, thereby trapping partially unfolded states and facilitating off-pathway aggregation. These effects highlight crowding's dual role in stabilizing native folds while heightening aggregation propensity under cellular stress.^[58] In cellular contexts, chaperone-assisted folding mitigates these aggregation risks within the crowded cytosol, where proteins like Hsp70 and GroEL/ES facilitate refolding by shielding hydrophobic regions and preventing intermolecular associations, as evidenced by proteome-wide mapping in E. coli showing enhanced refolding efficiency for over 20% of cytosolic proteins under crowding-mimicking conditions.^[59] This natural mechanism inspires in vitro refolding optimizations using crowding agents like Ficoll or PEG to mimic cytosolic conditions and improve yields of recombinant proteins.

Nucleic Acid Interactions

Macromolecular crowding significantly influences DNA structure by promoting compaction through mechanisms such as the coil-globule transition, where extended DNA coils collapse into more compact globules under high crowder concentrations.^[31] This transition is induced by crowders like polyethylene glycol (PEG), with collapse observed at volume fractions (φ) greater than 0.1, leading to a 2-3 fold reduction in the radius of gyration for single DNA molecules.^[60] For instance, in experiments using PEG at 18-30% (w/w), the critical force required for decompaction decreases from approximately 0.6 pN to 0.1 pN, highlighting the entropic drive toward compactness via excluded volume effects akin to depletion forces.^[31] Crowding enhances protein-DNA interactions critical for processes like replication and gene regulation. It increases binding affinity for transcription factors and nucleoid-associated proteins, with bovine serum albumin (BSA) as a crowder elevating local concentrations of proteins like HU by over 4-fold, thereby stabilizing associations.^[31] This effect facilitates DNA looping, as seen with H-NS proteins, where crowding at φ = 0.13-0.22 promotes cooperative bridging and loop formation, essential for regulatory enhancer-promoter contacts.^[31] On RNA, macromolecular crowding stabilizes secondary structures through the excluded volume effect, favoring compact folded states over extended unfolded ones.^[61] For example, 20% PEG reduces the radius of gyration of unfolded RNA from 76 Å to 64 Å and shifts the folding midpoint to lower Mg²⁺ concentrations (0.21 mM vs. 0.7 mM without crowder), decreasing the free energy barrier by about 5.8 k_B T.^[61] Crowding also impacts translation by limiting ribosome function; the slow diffusion of bulky tRNA complexes in crowded cytoplasm caps translation speed at 20-23 amino acids per second, imposing a physical constraint on cellular growth rates.^[62] Recent studies from 2024-2025 reveal advanced roles of soft interactions in heterogeneous crowded environments, where crowders like PEG suppress DNA strand separation under mechanical stress, altering extension and favoring plectoneme formation even in negatively supercoiled DNA at 0.8 pN tension.^[63] These soft, non-specific interactions modulate supercoiling dynamics, bridging in vitro observations to in vivo conditions as outlined in a 2023 review.^[31] In viral genomes, crowding reinforces capsid mechanics, as in brome mosaic virus, where it prestresses the shell against disassembly by reducing entropic fluctuations, with implications for infection in cellular milieus.^[64]

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Macromolecular crowding (MMC) refers to the presence of a high density of macromolecules such as proteins, nucleic acids, polysaccharides, and lipids in ...
[43]
Macromolecular Crowding: a Hidden Link Between Cell Volume and ...
Aug 6, 2025 · High density of intracellular macromolecules creates a special condition known as macromolecular crowding (MC).
[44]
https://www.nature.com/articles/s41586-022-05394-6
[45]
https://www.sciencedirect.com/science/article/pii/S2590006425003321
[46]
https://www.researchgate.net/publication/348755023_Macromolecular_Crowding_a_Hidden_Link_Between_Cell_Volume_and_Everything_Else
[47]
Super-Resolution Imaging of Highly Curved Membrane Structures in ...
Molecular crowding is an inherent feature of cell interiors. Synthetic cells as provided by giant unilamellar vesicles (GUVs) encapsulating macromolecules ...<|separator|>
[48]
Exploring the role of macromolecular crowding and TNFR1 in cell ...
Sep 19, 2024 · ... Minton, 1981 ... (2015) Macromolecular crowding gives rise to microviscosity, anomalous diffusion and accelerated actin polymerization.
[49]
Probing macromolecular crowding at the lipid membrane interface ...
Here, we developed a genetically‐encoded fluorescence‐based sensor for probing the macromolecular crowding at the membrane interfaces.
[50]
Macromolecular crowding perturbs protein refolding kinetics
This prediction has led to the suggestion that crowding could alter the free energy landscape of protein folding processes significantly (Minton, 2000b).
[51]
https://elifesciences.org/articles/92719
[52]
Molecular Crowding Effects on Protein Stability - DESPA - 2006
May 12, 2006 · Crowding increases usually the value of the melting temperature of a protein. ... ΔTm, for the melting temperatures of these biomolecules in situ.
[53]
Macromolecular crowding effects on protein dynamics - ScienceDirect
This article discusses how protein translational, rotational, conformational, and solvation dynamics change under crowded conditions
[54]
A proteome-wide map of chaperone-assisted protein refolding in a ...
The cytosolic environment and its complement of chaperones play critical roles in granting many proteins safe passage to their native states; however, it is ...
[55]
Resolving chaperone-assisted protein folding on the ribosome at the ...
Jul 10, 2024 · Protein folding in vivo begins during synthesis on the ribosome and is modulated by molecular chaperones that engage the nascent polypeptide.
[56]
Error | Proceedings of the National Academy of Sciences
**Summary:**
[57]
Molecular crowding stabilizes folded RNA structure by the excluded ...
It follows, therefore, that a reduction of water activity due to molecular crowding will de-stabilize RNA secondary structure, but will stabilize tertiary ...
[58]
Molecular crowding limits translation and cell growth - PNAS
Sep 30, 2013 · We show that the slow diffusion of the bulky tRNA complexes in the crowded cytoplasm imposes a physical limit on the speed of translation, which ultimately ...
[59]
https://www.pnas.org/doi/10.1073/pnas.2210536119
[60]
https://www.pnas.org/doi/10.1073/pnas.0807764106