Crowding revisited: Open questions and future perspectives

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.

Molecular Crowding: The History and Development of a Scientific Paradigm

It is now generally accepted that macromolecules do not act in isolation but "live" in a crowded environment, that is, an environment populated by numerous different molecules. The field of molecular crowding has its origins in the far 80s but became accepted only by the end of the 90s. In the present issue, we discuss various aspects that are influenced by crowding and need to consider its effects. This Review is meant as an introduction to the theme and an analysis of the evolution of the crowding concept through time from colloidal and polymer physics to a more biological perspective. We introduce themes that will be more thoroughly treated in other Reviews of the present issue. In our intentions, each Review may stand by itself, but the complete collection has the aspiration to provide different but complementary perspectives to propose a more holistic view of molecular crowding.

Two-photon excited-state dynamics of mEGFP-linker-mScarlet-I crowding biosensor in controlled environments

Macromolecular crowding affects many cellular processes such as diffusion, biochemical reaction kinetics, protein-protein interactions, and protein folding. Mapping the heterogeneous, dynamic crowding in living cells or tissues requires genetically encoded, site-specific, crowding sensors that are compatible with quantitative, noninvasive fluorescence micro-spectroscopy. Here, we carried out time-resolved 2P-fluorescence measurements of a new mEGFP-linker-mScarlet-I macromolecular crowding construct (GE2.3) to characterize its environmental sensitivity in biomimetic crowded solutions (Ficoll-70, 0-300 g L-1) via Förster resonance energy transfer (FRET) analysis. The 2P-fluorescence lifetime of the donor (mEGFP) was measured under magic-angle polarization, in the presence (intact) and absence (enzymatically cleaved) of the acceptor (mScarlet-I), as a function of the Ficoll-70 concentration. The FRET efficiency was used to quantify the sensitivity of GE2.3 to macromolecular crowding and to determine the environmental dependence of the mEGFP-mScarlet-I distance. We also carried out time-resolved 2P-fluorescence depolarization anisotropy to examine both macromolecular crowding and linker flexibility effects on GE2.3 rotational dynamics within the context of the Stokes-Einstein model as compared with theoretical predictions based on its molecular weight. These time-resolved 2P-fluorescence depolarization measurements and conformational population analyses of GE2.3 were also used to estimate the free energy gain upon the structural collapse in crowded environment. Our results further the development of a rational engineering design for bioenvironmental sensors without the interference of cellular autofluorescence. Additionally, these results in well-defined environments will inform our future in vivo studies of genetically encoded GE2.3 towards the mapping of the crowded intracellular environment under different physiological conditions.

Conformational entropy in molecular recognition of intrinsically disordered proteins

Broad conformational ensembles make intrinsically disordered proteins or regions entropically intriguing. Although methodologically challenging and understudied, emerging studies into their changes in conformational entropy (ΔS°conf) upon complex formation have provided both quantitative and qualitative insight. Recent work based on thermodynamics from isothermal titration calorimetry and NMR spectroscopy uncovers an expanded repertoire of regulatory mechanisms, where ΔS°conf plays roles in partner selection, state behavior, functional buffering, allosteric regulation, and drug design. We highlight these mechanisms to display the large entropic reservoir of IDPs for the regulation of molecular communication. We call upon the field to make efforts to contribute to this insight as more studies are needed for forwarding mechanistic decoding of intrinsically disordered proteins and their complexes.

Insights into In Vivo Environmental Effects on Quantitative Biochemistry in Single Cells

Biomacromolecules exist and function in a crowded and spatially confined intracellular milieu. Single-cell analysis has been an essential tool for deciphering the molecular mechanisms of cell biology and cellular heterogeneity. However, a sound understanding of in vivo environmental effects on single-cell quantification has not been well established. In this study, via cell mimicking with giant unilamellar vesicles and single-cell analysis by an approach called plasmonic immunosandwich assay (PISA) that we developed previously, we investigated the effects of two in vivo environmental factors, i.e., molecular crowding and spatial confinement, on quantitative biochemistry in the cytoplasm of single cells. We find that molecular crowding greatly affects the biomolecular interactions and immunorecognition-based detection while the effect of spatial confinement in cell-sized space is negligible. Without considering the effect of molecular crowding, the results by PISA were found to be apparently under-quantitated, being only 29.5-50.0% of those by the calibration curve considering the effect of molecular crowding. We further demonstrated that the use of a calibration curve established with standard solutions containing 20% (wt) polyethylene glycol 6000 can well offset the effect of intracellular crowding and thereby provide a simple but accurate calibration for the PISA measurement. Thus, this study not only sheds light on how intracellular environmental factors influence biomolecular interactions and immunorecognition-based single-cell quantification but also provides a simple but effective strategy to make the single-cell analysis more accurate.

Macromolecular Crowding Is Surprisingly Unable to Deform the Structure of a Model Biomolecular Condensate

The crowded interior of a living cell makes performing experiments on simpler in vitro systems attractive. Although these reveal interesting phenomena, their biological relevance can be questionable. A topical example is the phase separation of intrinsically disordered proteins into biomolecular condensates, which is proposed to underlie the membrane-less compartmentalization of many cellular functions. How a cell reliably controls biochemical reactions in compartments open to the compositionally-varying cytoplasm is an important question for understanding cellular homeostasis. Computer simulations are often used to study the phase behavior of model biomolecular condensates, but the number of relevant parameters increases as the number of protein components increases. It is unfeasible to exhaustively simulate such models for all parameter combinations, although interesting phenomena are almost certainly hidden in their high-dimensional parameter space. Here, we have studied the phase behavior of a model biomolecular condensate in the presence of a polymeric crowding agent. We used a novel compute framework to execute dozens of simultaneous simulations spanning the protein/crowder concentration space. We then combined the results into a graphical representation for human interpretation, which provided an efficient way to search the model's high-dimensional parameter space. We found that steric repulsion from the crowder drives a near-critical system across the phase boundary, but the molecular arrangement within the resulting biomolecular condensate is rather insensitive to the crowder concentration and molecular weight. We propose that a cell may use the local cytoplasmic concentration to assist the formation of biomolecular condensates, while relying on the dense phase to reliably provide a stable, structured, fluid milieu for cellular biochemistry despite being open to its changing environment.

Increased mesoscale diffusivity in response to acute glucose starvation

Macromolecular crowding is an important parameter that impacts multiple biological processes. Passive microrheology using single particle tracking is a powerful means of studying macromolecular crowding. Here we monitored the diffusivity of self-assembling fluorescent nanoparticles (μNS) in response to acute glucose starvation. mRNP diffusivity was reduced upon glucose starvation as previously reported. In contrast, we observed increased diffusivity of μNS particles. Our results suggest that, upon glucose starvation, mRNP granule diffusivity may be reduced due to changes in physical interactions, while global crowding in the cytoplasm may be reduced.

Increased mesoscale diffusivity in response to acute glucose starvation

Macromolecular crowding is an important property of cells that impacts multiple biological processes. Passive microrheology using single particle tracking is a powerful means of studying macromolecular crowding. Here we monitored the diffusivity of self-assembling fluorescent nanoparticles (μNS) and mRNPs ( GFA1 -PP7) in response to acute glucose starvation. mRNP diffusivity was reduced upon glucose starvation as previously reported. By contrast, we observed increased diffusivity of μNS particles. Our results suggest that, upon glucose starvation, mRNP granule diffusivity may be reduced due to increased physical interactions, whereas macromolecular crowding in the cytoplasm may be globally reduced.