Macromolecular Crowding: Biochemical, Biophysical, and Physiological Consequences

Abstract

Measurements of biochemical rates and equilibria are conventionally carried out under relatively idealized conditions selected to minimize effects of nonspecific interactions between the constituents of the reaction unit (i.e. the reactants, products, and transition-state complexes) and other species that do not ~lirectly participate in the reaction under study. Concentration-dependent apparent rate or equilibrium constants are then extrapolated to the limit of infinite dilution in order to extract intrinsic quantities reflecting the properties of isolated reactant and product molecules in an idealized bath of solvent. Biological media differ from the idealized solvent bath in two important ways. First, a biological medium is likely to contain a high total concentration of nominally soluble macromolecules. Sometimes a single species at a high concentration predominates, such as hemoglobin within red cells (~350 g/liter) (see 3). More commonly, a medium may contain variety of macromolecular species, none of which taken individually may be present at high concentration, but which taken collectively occupy a substantial fraction of the total volume of the medium [e.g. ~ 340 g/liter

Regulation of kinase activity by diffusion and feedback

“…2 we analyze the dependence of the stable steady state K( ) on the diffusion parameter (1) large diffusion (small α) speeds translocation of active kinase, so they have a larger chance to remain phosphorylated until they reach the cell center, Major simplification of our study is that it does not account for macromolecular crowding and presence of diffusion obstacles within the cell (organelle, cellular structures). The macromolecular crowding may have non-trivial effect on molecular association in the cell, possibly increasing its rate by limiting the volume in which molecules are free to diffuse (see Minton 2001 andZimmerman andMinton 1993). …”

Electrochemical structure of the crowded cytoplasm

“…These proposals include the effect of crowding on interactions of macromolecules in the cytoplasm [7][8][9][10][11], possible cytoplasmic 'phase separations' [12], the entropically driven order arising from high concentrations of particles [13,14], the concept of the 'metabolon' and of 'metabolite channeling' [15][16][17][18], the concept of 'hyperstructures' [19] and the current advent of modular and network cell biology [20][21][22]. Another view on the origin of cytoplasmic order stems from the 'dissipative structures' of Prigogine's order out of chaos theory [23].…”

Modeling Transcriptional Control in Gene Networks—Methods, Recent Results, and Future Directions

“…For example, binding coefficients between macromolecules can often be measured in vitro by a variety of methods [e.g., changes in fluorescence of labeled oligonucleotides upon binding of a transcription factor (Richards et al, 1996)], although corrections may then have to be estimated for macromolecular crowding in vivo because such crowding tends in general to strongly promote macromolecular association and oligomerization (Zimmerman and Minton, 1993). More difficult to obtain are rate constants appropriate for in vivo reactions.…”