Inside of a cell is highly crowded with a large number of macromolecules together with solvents and metabolites. How variable interactions within dense cellular environments may affect the structure and dynamics, and ultimately function is one of the most fundamental questions in life science. By integrating data from a variety of sources, we constructed full atomistic model of the cytoplasm of bacteria (Mycoplasma genitalium) with all of the molecular components, i.e., proteins, RNA, metabolites, ions, and solvent, that are mapped on the complete biochemical pathways (see figure). The volume of the system is (100 nm)<sup>3</sup>, which greatly exceeds that of typical molecular dynamics (MD) simulations, covering about 10% of the volume of an entire cell. Using this model, we performed MD simulation with the highly parallelized MD program GENESIS on the super computer K. The simulations provided information of dynamics, stability, and interactions of biomolecules in cell. Native protein structures were either stabilized or destabilized relative to dilute solutions as a result of not just the excluded volume effect but also electrostatic interactions with ions and charged metabolites. The diffusion of macromolecules was influenced significantly upon the magnitude of local crowding and slowed down as a function of their size. Metabolite dynamics and interactions with proteins in the crowded environment differed from dilute environments with a significant 2D surface diffusion component and competitive interactions with surrounding macromolecules. Finally, functionally correlated weak protein-protein interactions between enzymes involved in the glycolysis pathway was suggested. This work presents a first step towards physically, chemically, and biologically realistic in silico cell models that connect molecular with cellular biology and opens the door to a new era of cellular-scale rational drug design applications.

Dynamics, stability, and interactions of biomolecules in bacterial cytoplasm: Microscopic understanding with atomistic simulation

251st National Meeting (2016)

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