Computer simulations of the bacterial cytoplasm

Abstract

Ever since the pioneering work of Minton, it has been recognized that the highly crowded interior of biological cells has the potential to cause dramatic changes to both the kinetics and thermodynamics of protein folding and association events relative to behavior that might be observed in dilute solution conditions. One very productive way to explore the effects of crowding on protein behavior has been to use macromolecular crowding agents that exclude volume without otherwise strongly interacting with the protein under study. An alternative, complementary approach to understanding the potential differences between behavior in vivo and in vitro is to develop simulation models that explicitly attempt to model intracellular environments at the molecular scale, and that thereby can be used to directly monitor biophysical behavior in conditions that accurately mimic those encountered in vivo. It is with studies of this type that the present review will be concerned. We review in detail four published studies that have attempted to simulate the structure and dynamics of the bacterial cytoplasm and that have each explored different biophysical aspects of the cellular interior. While each of these studies has yielded important new insights, there are important questions that remain to be resolved in terms of determining the relative contributions made by energetic and hydrodynamic interactions to the diffusive behavior of macromolecules and to the thermodynamics of protein folding and associations in vivo. Some possible new directions for future generation simulation models of the cytoplasm are outlined.

Thermodynamics of protein destabilization in live cells

“…The answer to how protein behavior in vitro translates to in vivo conditions (13,44,59) seems now to be gradually unfolding. Although general confinement and excludedvolume effects must contribute, the rule of the game is in the molecular details: In-cell stability depends not only on the protein sequence itself, but also on how it interacts with its specific intracellular environment.…”

The effect of macromolecular crowding on mobility of biomolecules, association kinetics, and gene expression in living cells

“…Therefore, at the beginning of the review, we give a short introduction to our own contribution to this field of research i.e., motion of probes in synthetic complex liquids. The material presented in this paper does not overlap significantly with many informative reviews written in the last few years that concern theoretical and in vitro experimental contributions to protein mobility [21][22][23][24], protein folding [8,10,23], and protein-protein interactions [10,11,24].…”

Krylov subspace methods for computing hydrodynamic interactions in Brownian dynamics simulations

“…37,38 On the other hand, the understanding of their role in biological reactions is limited. 2,9,[24][25][26] The main reason for this is the high complexity of biological systems. As is often the case, computational approaches that can simulate large systems for long time scales are very desirable.…”

“…[24][25][26] Therefore, testing a model with attractive interactions is quite important. Here, we examine a simple chain model that collapses to a compact conformation.…”