The astonishing diversity in folding patterns of RNA threedimensional (3D) structures is crafted by myriads of noncovalent contacts, of which base pairing and stacking are the most prominent. A systematic and comprehensive classification and annotation of these interactions is necessary for a molecular-level understanding of their roles. However, unlike in the case of base pairing, where a widely accepted nomenclature and classification scheme exists in the public domain, currently available classification schemes for base−base stacking need major enhancements to comprehensively capture the necessary features underlying the rich stacking diversity in RNA. Here, we extend the previous stacking classification based on nucleobase interacting faces by introducing a structurally intuitive geometry-cum topology-based scheme. Specifically, a stack is first classified in terms of the geometry described by the relative orientation of the glycosidic bonds, which generates eight basic stacking geometric families for heterodimeric stacks and six of those for homodimeric stacks. Further annotation in terms of the identity of the bases and the region of involvement of purines (five-membered, six-membered, or both rings) leads to the enumeration of 384 distinct RNA base stacks. Based on our classification scheme, we present an algorithm for automated identification of stacks in RNA crystal structures and analyze the stacking context in selected RNA structures. Overall, the work described here is expected to greatly facilitate the structure-based RNA research.
Nucleobase π−π stacking is one of the crucial organizing interactions within three-dimensional (3D) RNA architectures. Characterizing the structural variability of these contacts in RNA crystal structures will help delineate their subtleties and their role in determining function. This analysis of different stacking geometries found in RNA X-ray crystal structures is the largest such survey to date; coupled with quantum-mechanical calculations on typical representatives of each possible stacking arrangement, we determined the distribution of stacking interaction energies. A total of 1,735,481 stacking contacts, spanning 359 of the 384 theoretically possible distinct stacking geometries, were identified. Our analysis reveals preferential occurrences of specific consecutive stacking arrangements in certain regions of RNA architectures. Quantum chemical calculations suggest that 88 of the 359 contacts possess intrinsically stable stacking geometries, whereas the remaining stacks require the RNA backbone or surrounding macromolecular environment to force their formation and maintain their stability. Our systematic analysis of π−π stacks in RNA highlights trends in the occurrence and localization of these noncovalent interactions and may help better understand the structural intricacies of functional RNA-based molecular architectures.
Identification and characterization of base-multiplets, which are essentially mediated by base-pairing interactions, can provide insights into the diversity in the structure and dynamics of complex functional RNAs, and thus facilitate hypothesis driven biological research. The necessary nomenclature scheme, an extension of the geometric classification scheme for base-pairs by Leontis and Westhof, is however available only for base-triplets. In the absence of information on topology, this scheme is not applicable to quartets and higher order multiplets. Here we propose a topology-based classification scheme which, in conjunction with a graph-based algorithm, can be used for the automated identification and characterization of higher order base-multiplets in RNA structures. Here, the RNA structure is represented as a graph, where nodes represent nucleotides and edges represent base-pairing connectivity. Sets of connected components (of n nodes) within these graphs constitute subgraphs representing multiplets of "n" nucleotides. The different topological variants of the RNA multiplets thus correspond to different nonisomorphic forms of these subgraphs. To annotate RNA base-multiplets unambiguously, we propose a set of topology-based nomenclature rules for quartets, which are extendable to higher multiplets. We also demonstrate the utility of our approach toward the identification and annotation of higher order RNA multiplets, by investigating the occurrence contexts of selected examples in order to gain insights regarding their probable functional roles. Downloaded from 2. Then three terminal bases (nodes having degree = 1) are numbered according to alphabetical order.
Understanding the frequency and structural context of discrete noncovalent interactions between nucleotides is of pivotal significance in establishing the rules that govern RNA structure and dynamics. Although T-shaped contacts (i.e., perpendicular stacking contacts) between aromatic amino acids and nucleobases at the nucleic acid–protein interface have recently garnered attention, the analogous contacts within the nucleic acid structures have not been discussed. In this work, we have developed an automated method for identifying and unambiguously classifying T-shaped interactions between nucleobases. Using this method, we identified a total of 3262 instances of T-shaped (perpendicular stacking) contacts between two nucleobases in an array of RNA structures from an up-to-date dataset of high-resolution crystal structures deposited in the Protein Databank. These analyses add to the understanding of the physicochemical forces that are responsible for structure and dynamics of RNA.
With wide ranging diversity in their geometries, binding strengths and chemical properties, noncanonical base pairs are equipped to intricately regulate and control the structural dynamics of RNA molecules. Protonation of nucleobases adds to the diversity. Compared to the unprotonated scenario, on one hand they open up new alternatives for base pairing interactions (Class I) while on the other, they modulate the geometry and stability of existing base pairing interactions (Class II). In both cases, compensation of the energetic cost associated with nucleobase protonation at physiological pH, can be understood in terms of protonation induced restructuring of charge distribution. This not only leads to modifications in existing base-base interactions but often also leads to additional stabilizing interactions, resulting in the formation of protonated base triples. Here we report our detailed quantum chemical studies, in conjunction with structural bioinformatics based analysis of RNA crystal and NMR structure datasets, probing into the contribution of such protonated triples in the structural dynamics of RNA. Our studies revealed more than 55 varieties of protonated triples in RNA, some of which occur recurrently within conserved structural motifs present in rRNAs, tRNAs and in other synthetic RNAs. Our studies suggest that high occurrence frequencies are associated with protonated triples which satisfy the specific structural requirements of conserved motifs where they occur. For example, protonated triples with flexible geometries are involved in the formation of tertiary contacts between different distant motifs. Stabilization of protonated base pairs, through the induction of additional energetically cooperative interactions, appears to be another factor. These results provide significant insights into the sequence-structure-function relationships in RNA.
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