Binding by TRBP-dsRBD2 Does Not Induce Bending of Double-Stranded RNA

Inherent conformational plasticity in dsRBDs enables interaction with topologically distinct RNAs

Many double-stranded RNA-binding domains (dsRBDs) interact with topologically distinct dsRNAs in biological pathways pivotal to viral replication, cancer causation, neurodegeneration, and so on. We hypothesized that the adaptability of dsRBDs is essential to target different dsRNA substrates. A model dsRBD and a few dsRNAs, slightly different in shape from each other, were used to test the systematic shape dependence of RNA on the dsRBD-binding using nuclear magnetic resonance (NMR) spectroscopy and molecular modeling. NMR-based titrations showed a distinct binding pattern for the dsRBD with the topologically distinct dsRNAs. The line broadening upon RNA binding was observed to cluster in the residues lying in close proximity, thereby suggesting an RNA-induced conformational exchange in the dsRBD. Further, while the intrinsic microsecond dynamics observed in the apo-dsRBD were found to quench upon binding with the dsRNA, the microsecond dynamics got induced at residues spatially proximal to quench sites upon binding with the dsRNA. This apparent relay of conformational exchange suggests the significance of intrinsic dynamics to help adapt the dsRBD to target various dsRNA-shapes. The conformational pool visualized in MD simulations for the apo-dsRBD reported here has also been observed to sample the conformations seen previously for various dsRBDs in apo- and in dsRNA-bound state structures, further suggesting the conformational adaptability of the dsRBDs. These investigations provide a dynamic basis for the substrate promiscuity for dsRBD proteins.

Role of salt-bridging interactions in recognition of viral RNA by arginine-rich peptides

Interactions between RNA molecules and proteins are critical to many cellular processes and are implicated in various diseases. The RNA-peptide complexes are good model systems to probe the recognition mechanism of RNA by proteins. In this work, we report studies on the binding-unbinding process of a helical peptide from a viral RNA element using nonequilibrium molecular dynamics simulations. We explored the existence of various dissociation pathways with distinct free-energy profiles that reveal metastable states and distinct barriers to peptide dissociation. We also report the free-energy differences for each of the four pathways to be 96.47 ± 12.63, 96.1 ± 10.95, 91.83 ± 9.81, and 92 ± 11.32 kcal/mol. Based on the free-energy analysis, we further propose the preferred pathway and the mechanism of peptide dissociation. The preferred pathway is characterized by the formation of sequential hydrogen-bonding and salt-bridging interactions between several key arginine amino acids and the viral RNA nucleotides. Specifically, we identified one arginine amino acid (R8) of the peptide to play a significant role in the recognition mechanism of the peptide by the viral RNA molecule.

An account of solvent accessibility in protein-RNA recognition

Protein–RNA recognition often induces conformational changes in binding partners. Consequently, the solvent accessible surface area (SASA) buried in contact estimated from the co-crystal structures may differ from that calculated using their unbound forms. To evaluate the change in accessibility upon binding, we compare SASA of 126 protein-RNA complexes between bound and unbound forms. We observe, in majority of cases the interface of both the binding partners gain accessibility upon binding, which is often associated with either large domain movements or secondary structural transitions in RNA-binding proteins (RBPs), and binding-induced conformational changes in RNAs. At the non-interface region, majority of RNAs lose accessibility upon binding, however, no such preference is observed for RBPs. Side chains of RBPs have major contribution in change in accessibility. In case of flexible binding, we find a moderate correlation between the binding free energy and change in accessibility at the interface. Finally, we introduce a parameter, the ratio of gain to loss of accessibility upon binding, which can be used to identify the native solution among the flexible docking models. Our findings provide fundamental insights into the relationship between flexibility and solvent accessibility, and advance our understanding on binding induced folding in protein-RNA recognition.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.