Coarse-Grained Models of RNA Nanotubes for Large Time Scale Studies in Biomedical Applications

Abstract

<jats:p>In order to describe the physical properties of large time scale biological systems, coarse-grained models play an increasingly important role. In this paper we develop Coarse-Grained (CG) models for RNA nanotubes and then, by using Molecular Dynamics (MD) simulation, we study their physical properties. Our exemplifications include RNA nanotubes of 40 nm long, equivalent to 10 RNA nanorings connected in series. The developed methodology is based on a coarse-grained representation of RNA nanotubes, where each coarse bead represents a group of atoms. By decreasing computation cost, this allows us to make computations feasible for realistic structures of interest. In particular, for the developed coarse-grained models with three bead approximations, we calculate the histograms for the bond angles and the dihedral angles. From the dihedral angle histograms, we analyze the characteristics of the links used to build the nanotubes. Furthermore, we also calculate the bead distances along the chains of RNA strands in the nanoclusters. The variations in these features with the size of the nanotube are discussed in detail. Finally, we present the results on the calculation of the root mean square deviations for a developed RNA nanotube to demonstrate the equilibration of the systems for drug delivery and other biomedical applications such as medical imaging and tissue engineering.</jats:p>

Coupled Multiphysics Modelling of Sensors for Chemical, Biomedical, and Environmental Applications with Focus on Smart Materials and Low-Dimensional Nanostructures

“…Finally, we mention efficient coarse-graining models [ 199 , 200 , 201 , 202 , 203 , 204 ] that have been developed for nucleic-acid-based nanostructures discussed in detail in Section 5.2 .…”

“…Moreover, there are also a number of proposals for hybrid nanostructures where various design and screening strategies can lead to a myriad of RNA-DNA hybrid nanostructures that can be used as programmable platforms for applications in sensing, molecular recognition, protein interaction, and catalyst research [ 253 ]. Given the capabilities of nonlinear responses of such nucleic acid biosensors over a wide dynamic range, refined modelling techniques such as those based on MD simulations are required along with the development of efficient coarse-grained procedures [ 199 , 200 , 201 , 202 , 203 , 204 , 254 ]. In this way, properties of associated nucleic acid nanostructures such as RNA nanotubes have been studied in detail, including their behavior in fluids.…”