The ribosome structure controls and directs mRNA entry, translocation and exit dynamics

Simulating activity of the bacterial ribosome

Computational modeling studies that investigate activity of the bacterial ribosome were reviewed. Computational approaches became possible with the availability of three-dimensional atomic resolution structures of the ribosomal subunits. However, due to the enormous size of the system, theoretical efforts to study the ribosome are few and challenging. For example, to extend the simulation timescales to biologically relevant ones, often, reduced models that require tedious parameterizations need to be applied. To that end, modeling of the ribosome focused on its internal dynamics, electrostatic properties, inhibition by antibiotics, polypeptide folding in the ribosome tunnel and assembly mechanisms driving the formation of the small ribosomal subunit.

Defining coarse-grained representations of large biomolecules and biomolecular complexes from elastic network models

Coarse-grained (CG) models of large biomolecular complexes enable simulations of these systems over long timescales that are not accessible for atomistic molecular dynamics (MD) simulations. A systematic methodology, called essential dynamics coarse-graining (ED-CG), has been developed for defining coarse-grained sites in a large biomolecule. The method variationally determines the CG sites so that key dynamic domains in the protein are preserved in the CG representation. The original ED-CG method relies on a principal component analysis (PCA) of a MD trajectory. However, for many large proteins and multi-protein complexes such an analysis may not converge or even be possible. This work develops a new ED-CG scheme using an elastic network model (ENM) of the protein structure. In this procedure, the low-frequency normal modes obtained by ENM are used to define dynamic domains and to define the CG representation accordingly. The method is then applied to several proteins, such as the HIV-1 CA protein dimer, ATP-bound G-actin, and the Arp2/3 complex. Numerical results show that ED-CG with ENM (ENM-ED-CG) is much faster than ED-CG with PCA because no MD is necessary. The ENM-ED-CG models also capture functional essential dynamics of the proteins almost as well as those using full MD with PCA. Therefore, the ENM-ED-CG method may be better suited to coarse-grain a very large biomolecule or biomolecular complex that is too computationally expensive to be simulated by conventional MD, or when a high resolution atomic structure is not even available.