The increasing interest in RNA nanotechnology and the demonstrated feasibility of using RNA nanoparticles as therapeutics have prompted the need for imaging systems with nanometer-scale resolution for RNA studies. Phi29 dimeric pRNAs can serve as building blocks in assembly into the hexameric ring of the nanomotors, as modules of RNA nanoparciles, and as vehicles for specific delivery of therapeutics to cancers or viral infected cells. The understanding of the 3D structure of this novel RNA dimeric particle is fundamentally and practically important. Although a 3D model of pRNA dimer has been proposed based on biochemical analysis, no distance measurements or X-ray diffraction data have been reported. Here we evaluated the application of our customized single-molecule dual-viewing system for distance measurement within pRNA dimers using single-molecule Fluorescence Resonance Energy Transfer (smFRET). Ten pRNA monomers labeled with single donor or acceptor fluorophores at various locations were constructed and eight dimers were assembled. smFRET signals were detected for six dimers. The tethered arm sizes of the fluorophores were estimated empirically from dual-labeled RNA/DNA standards. The distances between donor and acceptor were calculated and used as distance parameters to assess and refine the previously reported 3D model of the pRNA dimer. Distances between nucleotides in pRNA dimers were found to be different from those of the dimers bound to procapsid, suggesting a conformational change of the pRNA dimer upon binding to the procapsid.

Molecular dynamics (MD) is a widely used technique for computer simulation of complex systems, modelled at the atomic or some coarse‐grained level. In this article, basic concepts pertaining to MD simulations are systematically introduced and related to the underlying models of physical systems. The principles of the atomic force fields, representation of the environment, the time evolution of the system, as well as the derivation of kinetic and thermodynamic properties of interest from MD trajectories are discussed. Applications of MD to biological systems are illustrated by examples of large scale studies on protein structure and dynamics, protein–protein interactions, and drug design. Limitations and several recent extensions of classical MD, including Replica Exchange and Steered MD, are discussed in the context of applications to biological systems as well. Related simulation protocols, including Monte Carlo and free energy methods, are summarized, highlighting complementarity and common principles of these molecular simulation approaches. Key Concepts Computer simulations can be used to facilitate and complement experimental studies of biomolecular systems. Empirical force fields describe interatomic interactions in the system and enable efficient computation of forces in MD simulations. MD is routinely used to study biological macromolecules and their environment. A physical quantity can be measured using MD simulations by taking an arithmetic average over instantaneous values of that quantity obtained from MD trajectories. Other simulation methods, such as Monte Carlo, enhanced sampling and free energy methods, are often being used in conjunction with MD and its extensions. Slow processes can be studied computing the relative free energies of different states. MD and related methods can be applied to systems comprising millions of atoms, providing unique insights into complex biological systems.

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Fluorescence microscopy of cortical slices, yielding ready access to all six layers of cortex, has proven to be a powerful technique in neurophysiology, however it lacks the context of in vivo experiments. In vivo microscopy, pri-